62
Small Scale Polygeneration System for Hotels in Costa Rica David Vargas Masis
Small Scale Polygeneration System
for Hotels in Costa Rica
David Vargas Masis
-2-
Master of Science Thesis EGI 2020: MJ232X
Small Scale Polygeneration System for
Hotels in Costa Rica
David Vargas Masis
Approved
2020-09-04
Examiner
Dr. Anders Malmquist
Supervisor
Moritz Wegener
Commissioner
Contact person
-3-
Acknowledgements
I would like to thank my family for the amazing support during all my studies, especially during the last two
years in order to conclude my master studies. I would like to give a special thanks to my parents for always
pushing me to be better and giving me all the help, I needed to succeed. Their guidance has made me the
person I am today and without them nothing would have been possible, so this is for you.
To my brother, Leo, and my partner, Heidi, thanks for always being there for me during this time. Including
moments in which I was giving up or down, you always helped me to move forward and push me to give
my best. Being away from home was not easy, but with your help Heidi it was possible to enjoy and finish
this master’s studies.
Thank you to my examiner Dr. Anders Malmquist for his expertise during this thesis study. A special thanks
to my supervisor Moritz Wegener for his constant advice and contribution to this study. Thank you for your
time and guidance.
In general, thanks to all the people that helped and supported me through this journey.
Pura vida,
David Vargas Masis
Abstract
In a world where energy consumption increases every year and the current system harms the environment,
new technologies are necessary to cope with such intensive energy demands worldwide. In such an era,
polygeneration systems are an innovative and sustainable solution for that problem. Polygeneration systems
can simultaneously produce electricity, heating, cooling, hot water, potable water, and other services in
smaller, more flexible, and more efficient ways. Small-scale polygeneration systems can also help with the
decentralization of energy generation and with promoting the use of more renewable energy sources in the
power generation sector.
In this study, a polygeneration system is proposed for an ecohotel in the Guanacaste region of Costa Rica.
The ecohotel demand as well as the availability of local renewable energy resources were studied to size the
components of the system correctly. The small-scale polygeneration system consists of a biomass gasifier
and an internal combustion engine as prime mover, as well as PV panels, batteries, a biomass boiler, an
absorption chiller, and a membrane distillation system. The outputs obtained from the system and to be
used in the hotel are electricity, cooling, hot water, and potable water. The results obtained were positive
from an economic and environmental perspective when compared to the national grid electricity system.
The economic savings are of $410,268 per the system lifetime of 25 years, which represents a 27% margin
difference. As for the emissions, 14.4 tons of CO2 are saved every year from going into the atmosphere
which represents a 38% yearly reduction.
The results shown in this study reflect that the polygeneration systems are of great interest in order to shift
to a more sustainable and efficient energy system. This study can be replicated by other hotels in Costa Rica
taking into consideration the natural resources present in the local surroundings and adjusting the system
to those resources available.
-5-
Sammanfattning
I en värld där energiförbrukningen ökar varje år och det nuvarande systemet skadar miljön, är ny teknik
nödvändig för att klara sådana intensiva energibehov över hela världen. I en sådan tid är
polygenerationssystem en innovativ och hållbar lösning för det problemet. Polygenerationssystem kan
samtidigt producera el, värme, kylning, varmt vatten, dricksvatten och andra tjänster på mindre, mer flexibla
och effektivare sätt. Småskaliga polygenerationssystem kan också hjälpa till att decentralisera
energiproduktionen och främja användningen av mer förnybara energikällor inom kraftproduktionssektorn.
I denna studie föreslås ett polygenerationssystem för ett ekohotel i Guanacaste-regionen i Costa Rica.
Ekohotelbehovet och tillgängligheten för lokala förnybara energikällor studerades för att dimensionera
systemkomponenterna korrekt. Det småskaliga polygenerationssystemet består av en biomassaförgasare och
en förbränningsmotor, liksom PV-paneler, batterier, en biobränslepanna, en absorptionskylare och ett
membrandestillationssystem. Energiflödena från systemet, vilka ska användas på hotellet är el, kylning,
varmt vatten och dricksvatten. Resultaten är positiva ur ett ekonomiskt och miljömässigt perspektiv jämfört
med det nationella elnätet. De ekonomiska besparingarna uppgår till 410 268 USD under en systemlivslängd
på 25 år, vilket motsvarar en marginalskillnad på 27%. När det gäller utsläppen sparas 14,4 ton koldioxid
varje år från att nå atmosfären, vilket motsvarar en minskning på 38% per år.
Resultaten som visas i denna studie återspeglar att polygenerationssystemen är av stort intresse för att övergå
till ett mer hållbart och effektivt energisystem. Denna studie kan replikeras för andra hotell i Costa Rica med
beaktande av de naturresurser som finns i de lokala omgivningarna och med anpassning av systemet till de
tillgängliga resurserna.
-6-
Table of Contents
Acknowledgements ....................................................................................................................................................... 3
Abstract ........................................................................................................................................................................... 4
Sammanfattning ............................................................................................................................................................. 5
1 Introduction ........................................................................................................................................................10
1.1 Polygeneration Systems ............................................................................................................................11
1.2 Ecotourism in Costa Rica ........................................................................................................................12
1.3 Goals and Objectives................................................................................................................................12
2 Methodology .......................................................................................................................................................13
2.1 System Boundaries and Limitations .......................................................................................................13
2.2 Literature Review ......................................................................................................................................13
2.3 Research Approach ...................................................................................................................................14
2.4 Results and Discussion .............................................................................................................................14
2.5 Sustainability ..............................................................................................................................................14
3 State of the Art ...................................................................................................................................................17
3.1 Decentralization of Energy......................................................................................................................17
3.2 Explanation of Polygeneration Systems, CHP and CCHP ................................................................19
3.3 Studies of Small Scale Polygeneration Systems ....................................................................................21
3.4 Feasibility of Sustainable projects in Costa Rica ..................................................................................23
4 Case Study: Design of Polygeneration System ..............................................................................................27
4.1 HOMER Pro Software.............................................................................................................................27
4.2 Resources in the Region and Ambient Conditions..............................................................................28
4.2.1 Weather conditions ..........................................................................................................................29
4.2.2 Wind resources .................................................................................................................................29
4.2.3 Solar resources ..................................................................................................................................29
4.2.4 Biomass availability ..........................................................................................................................30
4.3 System Boundaries and Assumptions of Case Study ..........................................................................31
4.4 Data Acquisition of Electric and Cooling Demand ............................................................................32
4.5 Proposed System .......................................................................................................................................36
4.6 Description of System Components ......................................................................................................37
4.7 Load Control of the System ....................................................................................................................38
5 Results and Sustainability Assessment ............................................................................................................39
5.1 Simulation Results .....................................................................................................................................39
5.2 Sensitivity Analysis ....................................................................................................................................41
5.3 Environmental Impacts............................................................................................................................45
5.4 Social Impacts ............................................................................................................................................46
5.5 Economic Impacts ....................................................................................................................................47
-7-
5.6 Impact of the System on a Country Level ............................................................................................48
6 Conclusions and Future Research ...................................................................................................................50
Bibliography .................................................................................................................................................................51
Appendix A- HOMER configurations and results ................................................................................................59
Table of Figures
Figure 1. IEA Installed power generation capacity by source in the Stated Policies Scenario, 2000-2040, IEA,
Paris. (IEA, 2019) ........................................................................................................................................................10
Figure 2. Electricity generation share in Costa Rica 2019 (CENCE, 2019) .......................................................11
Figure 3. Thesis plan schematic ................................................................................................................................14
Figure 4. IEA, General Electricity Consumption. (IEA,2020) ............................................................................15
Figure 5. IEA, Electricity Consumption by sector. (IEA, 2020) .........................................................................15
Figure 6. IRENA, Renewable Energy Patents Evolution. (IRENA, 2020). ......................................................16
Figure 7. IRENA, Electricity Generation of different Renewable Energy sources Worldwide. (IRENA,
2020). .............................................................................................................................................................................17
Figure 8. Energy flow of CCHP (last image) and normal system (first three images) (Wu & Wang, 2006) 19
Figure 9. Schematic CCHP system technologies (Moussawi et al. 2016) ...........................................................20
Figure 10. System schematic of a polygeneration system in the Mediterranean region in Spain (Rubio-Maya
et al. 2011) .....................................................................................................................................................................21
Figure 11. Cost comparison of services supplied by the proposed PP's systems versus services in the market
(Villaroel-Schneider et al. 2020) ................................................................................................................................22
Figure 12. Comparison of NPC, capital investment and CO2 emissions for all four cases (Wegener et al.
2019). .............................................................................................................................................................................23
Figure 13. Carbon cycle in a hydropower reservoir (IHA, 2020) ........................................................................24
Figure 14.GHG emissions intensity (g CO2 -eq/kWh) by climate region (IHA, 2018) ..................................25
Figure 15. Price of electricity for commercial and business in Costa Rica (ICE, 2020) ..................................25
Figure 16. Comparison of commercial and industrial electricity prices in Latin America (Osinergmin, 2018)
........................................................................................................................................................................................26
Figure 17. Comprehensive framework of HOMER optimization procedure (Bahramra et al. 2016)...........27
Figure 18. Location of hotel for the case study (Google Maps, 2020) ...............................................................28
Figure 19. Wind speed in Costa Rica (Global Wind Atlas, 2020) ........................................................................29
Figure 20. Solar irradiance in Costa Rica (European Commission PVGIS, 2020) ...........................................30
Figure 21. Monthly electrical demand for the hotel in 2019 ................................................................................32
Figure 22. Electrical hourly data for the full year in 2019 .....................................................................................33
Figure 23. Demand profile for March 2019 ............................................................................................................34
Figure 24. Demand profile for October 2019 ........................................................................................................34
Figure 25. Energy demand of the hotel in March ..................................................................................................35
Figure 26. Energy demand of the hotel in October...............................................................................................35
Figure 27. Demand data for the hotel in the case study .......................................................................................36
Figure 28. System schematic ......................................................................................................................................36
Figure 29. Economic results ......................................................................................................................................39
Figure 30. Yearly CO2 emissions for both cases ....................................................................................................40
Figure 31. Cost of Electricity for both cases...........................................................................................................40
Figure 32. Detailed cash flow for proposed system ...............................................................................................41
Figure 33. Economic comparison of all configurations ........................................................................................42
Figure 34. Yearly CO2 emissions for all systems ...................................................................................................43
-8-
Figure 35. Cost of Electricity for all systems ..........................................................................................................44
Figure 36. Cost per month comparison with the COVID-19 pandemic situation ...........................................44
Figure 37. Sustainable Development Goals (UN, 2020) .......................................................................................46
Figure 38. Location selection for case study in HOMER pro .............................................................................59
Figure 39. System Schematic of Proposed System in HOMER Pro ..................................................................59
Figure 40. NPC calculated by HOMER Pro for Proposed System ....................................................................59
Figure 41. System Schematic of Grid Case in HOMER Pro ...............................................................................60
Figure 42. NPC calculated by HOMER Pro for Grid Case .................................................................................60
Figure 43. System Schematic of Grid Case with Covid-19 prices in HOMER Pro .........................................60
Figure 44. NPC calculated by HOMER Pro for Grid Case with Covid-19 prices ...........................................60
Figure 45. System Schematic of Only Biomass Case in HOMER Pro ...............................................................60
Figure 46. NPC calculated by HOMER Pro for Only Biomass Case ................................................................61
Figure 47. System Schematic of Only PV Case in HOMER Pro ........................................................................61
Figure 48. NPC calculated by HOMER Pro for Only PV Case ..........................................................................61
Figure 49. System Schematic of System with Wind Turbines Case in HOMER Pro ......................................61
Figure 50. NPC calculated by HOMER Pro for System with Wind Turbines Case ........................................62
Table of Tables
Table 1. Summary of benefits and drawbacks of DES (Alanne & Saari, 2006). ...............................................18
Table 2. Annual Potential for biomass gasification in Chorotega region ...........................................................31
Table 3. Price of bagasse per hectare .......................................................................................................................31
Table 4. Price of bagasse per ton ..............................................................................................................................32
Table 5. Water demand estimation for the hotel ....................................................................................................35
Table 6. Summary of system component costs and characteristics ....................................................................38
Table 7. Proposed system component sizes............................................................................................................39
Table 8. Electricity generation ...................................................................................................................................41
Table 9. Different configurations component sizes ..............................................................................................42
Table 10. Results of proposed system for Guanacaste region .............................................................................48
Table 11. Results of proposed system at a country level ......................................................................................48
-9-
Abbreviations
AB: Auxiliary Boiler
A/C: Air Conditioning
AC: Alternate Current
AbsC: Absorption Chiller
BG: Biomass Gasification System
COE: Cost of Energy
CHP: Combine Heat and Power
CCHP: Combine Cooling, Heating and Power
CCHPW: Combine Cooling, Heat, Power and
Water
CRF: Capital Recovery Factor
CST: Certification for Sustainable Tourism
Program
DC: Direct Current
DES: Distributed Energy System
DG: Distributed Generation
DH: District Heating
DEH: Domestic Electrical Heater
DEWH: Domestic Electrical Water Heater
ELC: Electric Load Control
FEL: Follow Electric Load
FTL: Follow Thermal Load
GHG: Greenhouse Gas Emissions
HOMER Hybrid Optimization Model for
Multiple Energy Resources
HX: Heat Exchanger
IFMT: Internally Fired Microturbine
ICE: Internal Combustion Engine
LCA: Life Cycle Assessment
LCOE: Levelized Cost of Energy
LHV: Low Heating Value
MD: Membrane Distillation
NPC: Net Present Cost
O&M: Operation and Maintenance
PES: Primary Energy Sources
PP: Polygeneration Plants
PV: Photovoltaics (solar)
RE: Renewable Energy
RES: Renewable Energy Sources
RO: Reverse Osmosis
SD: Sustainable Development
SDG: Sustainable Development Goals
SG: Smart Grid
TES: Thermal Energy Storage
TLC: Thermal Load Control
ZEB: Zero Energy Building
-10-
1 Introduction
Our generation has a challenge in the coming years: to slow down, or better yet, stop the deterioration of
our planet. In 2015, the Paris Agreement was signed by many global leaders promising to keep Earth’s
temperature increase well below 2ºC to slow down the effects of climate change; however not enough
changes have been made in order to make that happen. In the 2019 World Energy Outlook report by the
International Energy Agency, current scenarios are compared to sustainable development scenarios and it
shows that a lot of changes need to take place in order to keep the temperature rise under control (IEA,
2019).
Figure 1. IEA Installed power generation capacity by source in the Stated Policies Scenario, 2000-2040, IEA, Paris. (IEA, 2019)
One of the most important tasks is to shift from fossil fuels to renewable energy systems. As seen in Figure
1, the projections are promising for renewable energy sources in the Stated Policies Scenario. This scenario
provides a detailed sense of the direction in which existing policy frameworks and today’s policy ambitions
would take the energy sector until 2040. It used to be called the New Policies Scenario, but the name was
changed in 2019 to iterate that it considers only specific policy initiatives that have already been announced
(IEA, 2019). Even though the share of renewable energies such as solar PV, hydro and wind would increase
very rapidly under this Stated Polices Scenario; coal and gas would still be a big part of the energy generation
in the coming years, thus causing significant amounts of greenhouse gas (GHG) emissions, accelerating the
deterioration of our planet. For the necessary energy transition to happen more rapidly, governments need
to make law enforcements accelerate the shift towards energy generation by renewables and focus on energy
efficiency and the decentralization of energy (Solomon, 2011).
An important aspect in the energy transition towards a more sustainable world is the decentralization of
energy. Nowadays, the energy infrastructure is mostly centralized to electrify homes, heat houses, connect
producers and consumers, and transport energy across countries. All this energy related infrastructure, in
addition to roads, on average amounts to 70% of countries’ GDP (Goldthau, 2014). One challenge is to
-11-
decentralize this energy production by using renewable energy systems and smart grids as the new era of
energy infrastructure. Decentralized systems offer numerous advantages over centralized ones: reduced
costs for transmission systems, energy efficiency gains, lower grid loss, higher resilience due to more reliance
on distributed generation (DG) from small scale providers and larger share of renewables in the local energy
mix (Sims et.al, 2007).
For these reasons, this thesis focuses on the decentralization of energy using small scale polygeneration
system. The polygeneration concept combines different energy sources as input and produces several energy
services as output, within one enclosed system, in a lucrative, sustainable, and efficient way. Specifically, this
study concentrates on the hotel sector in Costa Rica and how it can be powered by renewable sources. Costa
Rica is a small country in Central America that has ample natural resources. As a result, the country produces
most of its energy from renewable sources, however a large portion of that share comes from hydropower,
as the mix is not very diversified.
Figure 2. Electricity generation share in Costa Rica 2019 (CENCE, 2019)
As seen in Figure 2, hydropower represents 69.2% of the total energy production share, wind energy
accounts for 15.8% and the remaining energy sources such as biomass, solar and geothermal only represent
15% of the total share (CENCE, 2019). This graph indicates that there are other resources available in the
country which are not being exploited to their full potential. Those resources can be utilized to produce
electricity in small scale polygeneration systems as decentralized systems for hotels in Costa Rica. The
following sections will introduce polygeneration systems, elaborate on the impact of ecotourism on Costa
Rica’s economy, and outline the goals and purpose of this study.
1.1 Polygeneration Systems
The polygeneration concept combines different energy sources as input and produces several energy
services as output, within one enclosed system, in a lucrative, sustainable, and efficient way. With one output,
or energy service of the system, for example electricity, the concept is simply called generation. With two
outputs it is called cogeneration (CHP) and with three outputs it is called trigeneration (CCHP). In this
thesis, Polygeneration is defined as a system providing more than three energy services. The purpose of
polygeneration is energy efficiency optimization of the system. The benefits of polygeneration systems are
lower GHG emissions and improved energy efficiency by, for example, using residual heat for heating
purposes. The systems not only provide more flexibility but are also more complex, and thus, are more
complicated to create (Wegener & Malmquist, 2018).
-12-
In general, typical outputs of polygeneration systems are energy services such as: electricity, heat, cooling,
and purified water. The inputs of polygeneration systems vary depending on the different resources found
in the regions and where they will be developed. However, the objective is to use renewable sources such
as solar, wind, biomass, hydropower and geothermal to produce a system that generates low emissions. To
produce heat, a combustion system is needed, which can be fueled by biomass, for example. Normally,
electricity is the primary service and heat is a secondary output. This excess heat can be utilized for additional
energy services such as heating, water purification, or even for cooling systems using an absorption chiller
(AbsC). Also, it is important to emphasize that to accommodate the electricity demand, which varies
throughout the course of a day, a combination of energy systems and storage systems is essential.
1.2 Ecotourism in Costa Rica
Ecotourism is defined as responsible travel to natural areas that conserves the environment, sustains the
well-being of the local people, and involves interpretation and education (Hearne, 2001). Costa Rica is a
developing country, in which 25% of the total territory is protected as natural reserves and parks, and it is
estimated that 5% of the world’s total biodiversity can be found within its borders (ICT, 2020). Because of
Costa Rica’s abundant nature and biodiversity, many tourists visit the country to explore nature and be close
to its flora and fauna, which is one aspect of ecotourism. The tourist that visit the country contribute to the
development of the communities in areas around nature reserves and the entire economy. Tourism
represents 8.2% of the GDP of Costa Rica and this translates to 8.8% of overall employment in the country.
This represents an economic income of $3,832,000 in 2018 (ICT, 2019).
As one can see, tourism accounts for a large part of the economy in Costa Rica, and thus the focus of this
thesis is to create a small scale polygeneration systems for the hotel sector in order to help the tourism sector
advance in a more sustainable way by using decentralized renewable systems. Many hotels in Costa Rica use
sustainable practices to reduce their impact on nature on the surrounding areas. Another way to make hotels
more sustainable is to produce their own electricity from renewable sources. Depending on the hotel’s
location, different sources could be used, such as: wind, solar, biomass, hydropower, geothermal and
hydrogen. In doing so, the energy production would have lower GHG emissions, and the impact on nature
would be less, as the systems would be small, thus decreasing the disturbance to the flora and fauna in the
region.
1.3 Goals and Objectives
In this thesis study, the aim is to analyze the resources that are present in the western coast of Costa Rica
and understand how these resources can be combined into a polygeneration system to obtain electricity,
cooling, potable water, and heated water. The polygeneration system will be developed for a sustainable
hotel in Costa Rica, as polygeneration systems can be an opportunity for hotels to produce their own energy
in a renewable way which produces low emissions. This could in turn attract more tourists and help to
protect flora and fauna in these regions, which is important for the growth and development of the
ecotourism sector of the country.
Further, the system which will be developed in this study can be replicated for other hotels in the west coast
region of Costa Rica as the available resources would be similar. In order to design an effective small scale
polygeneration system, some factors need to be taken into consideration such as a proper system sizing,
control strategy and power management operation. This study takes those factors in consideration in the
designing process of the system to then compare the system results from an environmental, financial, and
social perspective.
-13-
2 Methodology
In this section, the research approach adopted in this study is explained and analyzed. The research method
used in this study is a quantitative approach that combines descriptive and experimental research. The study
is based on a thorough literature review to explain the manner in which electricity is being produced
nowadays and how it is affecting the environment. Based on the literature review, the problem is identified
and a solution in the form of a decentralized system is proposed. Finally, the new system is compared to the
current centralized system to draw conclusions about the feasibility and benefits of the proposed system. In
order to perform this quantitative research, some processes need to be considered to achieve the objectives
as proposed before. The following sections explain those processes which are system boundaries, limitations
of the study, literature review, the research approach, and the results and discussions.
2.1 System Boundaries and Limitations
In this thesis, a case study is analyzed, so the system boundaries are constrained to the energy input and
output of the system. The boundary starts at the analysis of the demand data to cover the required energy
load and finishes at the energy produced in the system. The data utilized in this study is real data that was
provided by an energy consumer – in this case a hotel in Costa Rica – for a full calendar year. That data is
then used to design a system that meets the energy demand through the system’s output. would be to add a
thermally driven membrane distillation unit that can be used to purify water. Is important to also mention
that in this thesis, the focus is on a small-scale system, the systems are classified based on the capacities of
the prime mover. Small-scale systems have been defined as systems with a capacity of 20kW-1MW (Maraver
et al. 2013). Other boundaries of the study are that only renewable energy resources are considered, the
system is developed specifically for a region in Costa Rica, only small-scale system is designed, and it is
specifically designed for the hotel sector.
In the power system analyzed, it is necessary to consider some limitations in the process. The polygeneration
system is designed taking into consideration three main factors: the users, the electricity demand, and the
thermal demand. Due to the context of this study – a hotel – it should be noted that the users of energy are
not constant or consistent over the entire time period during which the data was gathered. Users fluctuated
constantly throughout the time period represented, and their usage behaviors undoubtedly varied, which
can affect the demand data. This is different, for example, than if this study took place in an apartment
building, where the users would be more constant for a substantial period of time. This factor affects the
electricity and thermal demand data, in turn affecting the entire system, which needs to adapt to that dynamic
behavior. Another limitation of the data collection for the case study is that in Costa Rica, there is no
distinction between the thermal and electrical loads on the energy bill. The energy bill presents one number
for total energy usage, without distinction if that energy was used for electrical, heating, or cooling purposes.
This means that some assumptions were necessary to obtain data for the cooling, water purification, and
hot water demand in the hotel. Finally, another limitation in this study relates to the components of the
system. The software used in the study, HOMER Pro, has data about each component that is used in the
calculation. Thus, some criteria cannot be changed easily.
2.2 Literature Review
The literature review starts with a very general perspective of the world energy outlook and the path that
needs to be followed in order to decrease GHG emissions and accelerate the energy transition. The focus
then shifts to sustainability, and how the decentralization of energy and the use of renewable sources can
help to achieve that energy transition from a general perspective. Then, a literature survey about
polygeneration systems and its advantages are detailed. Another important part of the literature review is
the survey about all the aspects described before, but in the specific location of the study, Costa Rica, and
-14-
how small scale polygeneration systems can make a difference in that country. After explaining the situation
from a general perspective, a more detailed review is done about each component of the system proposed.
A study is presented about the characteristics of small scale polygeneration systems and how they can be
integrated into the energy system in a sustainable and feasible way. Finally, a review on how the system will
be able to function with regards to the operational strategy and the control of the system is analyzed.
2.3 Research Approach
The first and very crucial part of the research approach for this study is the data collection, which is the
base to be able to design and scale the polygeneration system accurately. In order to collect the data, contact
was made with a hotel representative in Costa Rica, thus obtaining real demand data for a full calendar year
was possible. As mentioned before, since the data obtained only included electrical and was not divided into
the thermal usage by the hotel, some research was performed in order to obtain a percentage of the energy
that is used by hotels for cooling and water heating. This allowed for an estimate of the thermal load in the
case study to be made. After reliable data is gathered, the design process can be done to properly configure
the system with the different components. This is a crucial step in the case study, since the system
configuration is responsible for the output results and thus, the final outcome of the project. To finalize the
proper system configuration, some research regarding the best control strategy for the proposed system
need to be performed, to ensure the system covers the electric and thermal demand. Finally, a sustainability
analysis is performed to compare the system proposed in the case study with the centralized national grid
system currently used by the hotel.
2.4 Results and Discussion
The results of this case study are achieved when the system can fulfill the thermal and electrical demand of
the hotel. To obtain substantial results, the demand data for full calendar year was collected, and the system
will be designed and tested using HOMER Pro Software in order to have techno-economic results
depending on the different technologies used, and to be able to compare configurations. For a better
explanation of the system variations, a discussion regarding daily energy behaviors will be conducted. By
doing so, the results can give better insight on how much energy is used for electrical purposes and thermal
purposes depending on the time of the day and systems used. Also, the results will be compared considering
the different seasons of the year as to ensure comparable data. An expected outcome of this study is that a
sustainable and reliable model that can be replicated by other hotels will be developed. The proposed system
will be compared to the currently used systems from a sustainability, environmental, financial, and social
perspective. Finally, some recommendations can be made regarding the future implementation of a system
such as the one proposed for hotels in Costa Rica and how that can be beneficial for both the country and
the individual users.
Figure 3. Thesis plan schematic
2.5 Sustainability
Sustainability means an equitable distribution of limited resources and opportunities in the context of the
economy, society, and the environment. It aims at the well-being of everyone – now and in the future –
admitting that needs in the future can be vastly different than what we could possibly imagine now (Alanne
& Saari, 2006). However, in the last decades resources have been exploited in an irresponsible manner, due
-15-
to the objective of establishing more powerful economies. Developed countries decided to excessively burn
fossil fuels to produce cheap energy in order to power their economies. Historically, economic development
has been strongly correlated with increasing energy use and the increase of greenhouse gas (GHG) emissions
(Sathaye et al. 2011). However, in the last decade, many countries have broken that correlation which means
that counties can continue to develop their economies without damaging the planet (EEA, 2012). Also, in
some developing countries, the demand for energy is growing rapidly in order to catch up with other
economies, and it is important that this energy production is done in a more sustainable manner through
renewable energies and more efficient systems.
Figure 4. IEA, General Electricity Consumption. (IEA,2020)
As seen in Figure 4, the electricity consumption worldwide has been increasing steadily, and in the last 20
years the demand has doubled. The energy demand is expected to continue growing in the coming years, so
some measures will need to take place to allow for less polluting growth. In order to achieve a sustainable
energy system, a transition away from energy sources with high greenhouse emissions is required. Several
energy resources are available to meet our needs, and technology pathways for making this transition exist
(Benson & Orr, 2008).
Figure 5. IEA, Electricity Consumption by sector. (IEA, 2020)
From Figure 5 it can be deducted that the sector which consumes most electricity is consistently the industry
sector, nearly twice as much as the second most consuming sector, which is residential. However, part of
-16-
both residential and commercial, the building sector accounts for about 35% of total energy consumption
in the world (Wang, et. al, 2015). In order to respond to the rapid growth in the electricity consumption,
more sustainable electricity production needs to take the lead in transitioning to more efficient systems.
Buildings have great potential for energy saving and emission reduction, as it has been predicted that 25%
of the CO2 emission reduction in 2030 will come from the building sector (Brandoni & Renzi, 2015). To
achieve that reduction in GHG emissions, more energy efficient technologies need to be used, but there is
also an opportunity to increase energy generation from renewable sources and decentralize the energy
production. In Figure 6, an exponential increase in the number of patents for new technologies in the energy
sector is shown. With a heavy emphasis on solar PV and wind energy technologies leading the way in the
coming years towards more sustainable electricity generation.
Figure 6. IRENA, Renewable Energy Patents Evolution. (IRENA, 2020).
Energy sustainability is of great importance to the overall sustainability of humanity. Given the pervasiveness
of energy use, it is important for economic development and the improvement of living standards, and its
impact on the environment (Rosen, 2009).
-17-
3 State of the Art
3.1 Decentralization of Energy
Decentralized energy generation means that energy conversion units are situated close to energy consumers,
and thus, large power plants are substituted for smaller ones. A distributed energy system (DES) is an
efficient, reliable, and environmentally friendly alternative to the traditional energy system (Alanne, 2006).
An important detail about decentralized energy generation is that the transmission losses are very small
because energy is generated closer to the consumers, so there is no large transmission infrastructure and the
losses are reduced. The decentralization of energy production is an opportunity for renewable energy
sources to be implemented in some areas were electricity and thermal energy are needed by local users (Wu
& Wang, 2006). Renewable energies are becoming cost competitive very quickly and have the advantage
that they can be deployed in some areas where building a large energy facility is not feasible. As Aichmayer
et al. (2014) state, worldwide growth in electrical demand is mainly due to new customers in rural areas,
which often lack access to a conventional electricity network. As Figure 7 illustrates, renewable energy
technologies have been growing at a rapid pace in recent years and have been becoming more cost effective
in combination with the DES concept.
Figure 7. IRENA, Electricity Generation of different Renewable Energy sources Worldwide. (IRENA, 2020).
In Figure 7, it can be observed that the electricity capacity from renewable energy sources has doubled in
the last decade, with hydropower still being the main source of renewable electricity globally. As expected,
the two technologies with the largest impact on the total generation are wind energy and solar PV, but it is
also important to mention that biomass still accounts for a sizeable portion of this renewable production.
Another advantage that a DES can offer is that it can be adapted depending on the resources present in a
specific location. The combination of Renewable Energy Systems (RES) such as solar PV, wind, and
biomass could achieve a total fulfillment of the demand for electricity, cooling, and heating energy.
The energy sector is evolving rapidly and undergoing a disruptive transformation fueled by decentralized
renewable electricity generation. Since 2012, renewable generating capacity has exceeded that of non-
Hydropower (mix plants)
Wind Onshore
Wind Offshore
-18-
renewables by a widening margin. Similarly, renewable energies have had a positive impact on the provision
of electricity access. Out of the people who have gained access since 2000, 27% have been reached through
on-grid renewables, and 3% through minigrid and off-grid renewables (IEA, 2017). That shift into more
RES and decentralization can be challenging for the systematic transformation of the energy sector.
Maintaining business as usual in the energy sector will not allow for the mobilization of renewable energy
to its full potential. Comprehensive regulatory, legal, and financial frameworks will need to enable a
decentralized and proactive citizen-oriented organization of the energy sector with high shares of renewable
energy (UN, 2018). The RE technologies have evolved so successfully in the last decade that the
technological advantages are clear. One major challenge now lies in the regulatory and legal sector. A
significant task for governments around the world is to set clear regulations for the implementation of RES
and DES at full capacity. The World Bank estimates that only 40% of countries have a grid code that
includes variability of renewable energy (RE), 36% of countries have transmission pricing rules for RE, 14%
of countries have plant forecast rules for RE generation, and only 8% of countries have power exchange
rules for balancing areas, which is an important consideration for feasibility of grid-connected RE projects
(World Bank, 2017). Those numbers need to increase rapidly so that the RES and DES can be deployed
quickly and easily in the years to come. Renewable energy technologies in DES offer the opportunity to
contribute to a number of important sustainable development goals: (1) social and economic development;
(2) energy access; (3) energy security; (4) climate change mitigation and the reduction of environmental and
health impacts (Sathaye et al. 2011).
Table 1. Summary of benefits and drawbacks of DES (Alanne & Saari, 2006).
Table 1 summarizes the benefits and the drawbacks of DES. It can be argued based on this table that the
benefits are greater than the drawbacks in each sector of sustainability, which is a good sign for a vast
implementation of DES worldwide.
-19-
3.2 Explanation of Polygeneration Systems, CHP and CCHP
As mentioned before, a polygeneration system has been defined as a system with more than three energy
services as outputs. These could be electricity, heating, cooling, and water purification, for example. A well-
designed polygeneration system maximizes the utilization of the energy consumed (Buonomano et al. 2014).
However, polygeneration is still a very new term in the energy sector, while combined heat and power (CHP)
and combined cooling, heat, and power (CCHP) are terms that have a longer history in the energy sector.
These concepts became of strong interest in the energy sector because the efficiencies can increase when
more than one product is obtained from the same system. As Moussawi et al. (2016) mentioned, electricity,
heating and cooling are the three main components constituting the tripod of energy consumption in
residential, commercial, and public buildings around the world. So, it makes sense to obtain all those
products from the same system, which is why the CHP and CCHP systems began to be implemented around
the world. These types of systems started to be deployed and gained more interest at the beginning of this
millennium. The IEA reported that in 2007, CHP systems produced approximately 9% of global power
generation (Cho et al. 2014). CHP systems have also been estimated to be responsible for 15% reduction of
greenhouse gas emissions between 1990-2005 (IEA, 2008). Those findings paved the way for the
introduction of CCHP and polygeneration systems in the coming years. Figure 9 shows how the efficiencies
of these systems increased tremendously, comparing a CCHP to a “normal system” to produce heating,
cooling, and electricity.
Figure 8. Energy flow of CCHP (last image) and normal system (first three images) (Wu & Wang, 2006)
Figure 8 shows that in order to produce electricity, heating, and cooling from different systems, a total fuel
input of 148 units is needed and it has a total energy loss of 90 units. However, in the CCHP system, to
-20-
obtain the same output only 100 units of fuel are needed, and the energy losses are reduced to only 19 units.
This makes the CCHP far more efficient compared to systems that work independently, which is one of the
main goals of polygeneration systems.
It is important to mention that polygeneration systems can be powered by both fossil fuels and renewable
energies, in this thesis the focus is on the implementation of RES. As Rong & Su (2017) emphasize,
polygeneration offers a potential to fulfill the ambitious target of zero energy buildings (ZEB), because the
interdependence of different energy products can be utilized as an advantage and provide flexibility. Thus,
they can accommodate more renewable energy sources in the system. The integration of renewables into
polygeneration systems is very useful in terms of efficiencies as well, as Yousefi et al. (2017) concluded.
Using an optimal CCHP system integrated with PV panels leads to a 40.8% reduction of energy costs, 38.7%
reduction of the primary energy consumption and 72% reduction in emissions. The use of renewable
technologies is of great interest for polygeneration systems, but in order to produce electricity, a prime
mover is needed. That is where the use of biomass as a fuel becomes beneficial for these systems, as it can
be used in a variety of prime movers: Stirling engines reciprocating engines, steam turbines, fuel cells and
gas turbines (Maraver et al. 2013). In addition, biomass combustion is a carbon-free process as the resulting
CO2 would be previously captured by the plants being combusted, and will be recaptured by future plants
(IEA, 2007).
Figure 9. Schematic CCHP system technologies (Moussawi et al. 2016)
Figure 9 presents a schematic of a CCHP system technology. In this example, the electricity production is
presented only by prime movers and not RES. However, the use of RES can be a main part of the
polygeneration systems. Hybridizing renewable energy technologies with CCHP systems based on
conventional energy sources has come into the spotlight, because the two kinds of technologies can be used
in a complementary way (Yang & Zhai, 2019).
As Rong & Su (2017) mentioned, current challenges of small-scale polygeneration systems are:
1. First, it is not easy for a small-scale polygeneration plant to operate as efficiently as a large-scale one
when considering only the electric output.
2. Second, the plant is always required to stay on for more time to supply heat and power.
-21-
3. Finally, small-scale systems have big upfront investment while the payback time is not short.
In spite of the challenges of small-scale polygeneration systems, the benefits could outweigh the drawbacks.
It is true that they are less efficient than large scale systems when only the electrical output is measured, but
that is the reason why is a polygeneration plant has multiple outputs, so the efficiency can be increased to
higher levels. To overcome the significant upfront investment and payback time, governments need to
create new policies and regulations to make these systems more cost competitive as a way to attract more
investors to change to these type of generation systems, which have reduced GHG emissions.
3.3 Studies of Small Scale Polygeneration Systems
As previously mentioned, polygeneration systems are a recent concept in the energy sector. Many studies
have been done to determine the benefits that polygeneration systems have in comparison to CHP, CCHP
and traditional ways of serving electricity, heating, and cooling. For example, a study performed by
Baghernejad et al. (2016) in a controlled environment with an ambient temperature of 21° Celsius and a
solar irradiation of 800 W/m2 showed that a biomass-solar polygeneration system has an electrical efficiency
of 57.6%, but when the overall efficiency of the system is considered (accounting for heating and cooling)
a maximum efficiency of 96.7% is achieved, and the system CO2 emissions decrease by 33.2%. Similarly,
Wu & Wang (2006) determined that efficiency in polygeneration systems, ranging from 70-90%, improves
dramatically when compared to centralized power plants which only have a fuel utilization of 30-45%.
There are several studies of small-scale polygeneration systems performed by Katsaprakakis &
Voumvoulakis (2018), Karellas & Braimakis (2016), Chua et al. (2014), Calise et al. (2016) and the European
Union with the Concerto Programme (2014). However, most of these projects were done on islands and
communities in Europe. This section focuses on three specific small-scale polygeneration cases to consider
projects that are similar to the case study in this thesis. Two of them are systems developed for hotels and
the other is an example of a polygeneration system in a similar climate condition.
First, a look at a polygeneration system for a hotel in the Mediterranean region of Spain is considered. In
this system, the prime mover is fuelled by biogas produced by biomass, and a solar collector system is also
used. The outputs are electricity, heating, cooling, and purified water from a desalination system, as seen in
Figure 10.
Figure 10. System schematic of a polygeneration system in the Mediterranean region in Spain (Rubio-Maya et al. 2011)1
Unfortunately, in this case study, the efficiencies of the system were not identified. However, a comparison
was made with a natural gas system to obtain the emissions saved per year, and the results show that
1 SGAS = Biomass Gasification System, AXB= Auxiliary Boiler, PM = Prime Mover, DHW= Domestic Hot Water, SCS= Solar Collector System, TAT= Thermally Activated Technologies, CMPC= Compression Chiller, DES= Desalination Technologies.
-22-
polygeneration systems have huge benefits considering environmental aspects. In this study, the biomass-
solar polygeneration system avoided 3,114 tons per year of GHG emissions when compared to the natural
gas system (Rubio-Maya et al. 2011).
Another small-scale polygeneration system that is of great interest is a dairy farm of 30 associate families in
Bolivia that was studied by Villaroel-Schneider et al. (2020). For the polygeneration system, the outputs are
electricity, refrigeration, biogas, and fertilizer production. The polygeneration plant (PP) was studied for two
configurations: one with an internally fired microturbine (IFMT) and another with an internal combustion
engine (ICE). The production of biogas to power the prime movers is done by an anaerobic biogas digester
fed with cow dung and water. In this case study, the production of the outputs is more than the demand
needed by the dairy farm so some of the excess products can be sold on the market. Figure 11 shows the
cost comparison of biogas, electricity, and cooling for the two polygeneration systems proposed and the
prices of the services in the Bolivian market.
Figure 11. Cost comparison of services supplied by the proposed PP's systems versus services in the market (Villaroel-Schneider et al. 2020)
The cost of biogas is significantly cheaper for both PP in comparison with the market prices. For electricity,
the cost is cheaper when produced by the Internal Combustion Engine (ICE) in comparison with both the
IFMT and the market prices. And lastly, for the cooling prices, the market subsidized prize is cheaper than
both PP, but the ICE is cheaper than IFMT. The authors of the study concluded that for an implementation
of a polygeneration plant in the dairy farm, the most promising option is the ICE, as the investment cost is
low, it has high electric efficiency, it requires less subsidies to be competitive in the market and the payback
time period is shorter (Villaroel-Schneider et al. 2020). This case study shows that besides common outputs
like electricity, other services can be provided by polygeneration systems, as in this case with the fertilizer.
Finally, a polygeneration system study was performed for a hotel in the Andaman Islands in India by
Wegener et al. (2019). In this study, four different cases were investigated in detail: a base case with a diesel
based grid system of the island and a local diesel generator as backup; a second case with a diesel generator,
PV panels and batteries; a third case consisting of an off-grid system with a syngas engine, PV panels and
batteries; and a fourth case with a similar configuration to the third case, but with the addition of a
absorption chiller (AC) and a boiler. The results of the electrical efficiencies of the different cases are 33.1%
for the first case, 35% for the second case, 24.1% for the third case and only 22.7% for the fourth case.
However, when the whole system including the thermal efficiency is considered, the mean total efficiency
of the polygeneration system in case 4 is of 80.6%. The energetic efficiencies are a very important aspect
when an energy system is being designed, but also economic factors and environmental factors need to be
-23-
taken into consideration. Figure 12 illustrates a comparison of the net present cost (NPC), the capital
investment and the CO2 emissions for the four different cases.
Figure 12. Comparison of NPC, capital investment and CO2 emissions for all four cases (Wegener et al. 2019).
For the NPC, the fourth case is the best option in comparison to the other three cases and the difference
from the base case is significant. On the other hand, the capital investment is very low for the first case as
the only system component is the back-up diesel generator, while in the other three cases the upfront
investment is high because a new system would need to be deployed. Lastly, the comparison of the CO2
emissions shows how beneficial a fossil-fuel-free system can be to the environment. As the authors state,
this study indicates enormous ecological and economic potential of biomass-based solutions compared to
conventional systems, leading to savings of more than $578,000 over a period of 20 years, a payback period
of less than 4 years and saving 365 tons of CO2 per year (Wegener et al. 2019).
There are not many polygeneration studies in the hotel sector, which gives reason for the case study in this
thesis to be a valuable resource for future polygeneration systems in this sector. As the United Nations
World Tourism Organization (2020) states, the hotel sector is one of the tourism industry’s largest drivers
of employment and economic revenue, but at the same time, it is one of the most energy intensive. In fact,
hotels, and other types of accommodation account for up to 5% of global CO2 emitted by the tourism
sector. For that reason, the decentralization of power and use of thermal energy for heating, cooling, and
water purification (CCHPW) could contribute to the improvement of sustainability in tourism, which is a
crucial economic sector, but very insensitive in its energy and water consumption (Rubio-Maya et al. 2011).
3.4 Feasibility of Sustainable projects in Costa Rica
In this section, some characteristics that make this country feasible for a renewable polygeneration system
are presented. Costa Rica has established a world-renowned green trademark and eco-tourism industry by
protecting its abundant biodiversity and developing renewable energy sources (OECD, 2018). As previously
mentioned, Costa Rica is very keen on the continual growth of eco-tourism as the country’s GDP depends
heavily on tourism. To continue on this path, the Ministry of Tourism has an ecolodge branding that they
give to certain hotels and lodges that meet some defined requirements. An ecolodge has the following
attributes: it is located in a natural area, it is small (usually with less than 30 rooms), it employs systems that
protect the environment from pollution and degradation, and it uses energy saving tactics, such as renewable
energy technologies (Worldwide Ecolodges, 2017). The current ecolodge branding in Costa Rica is
represented by the country’s certification for sustainable tourism program (CST). There are approximately
300 establishments managing their operations under the CST in Costa Rica (Mic & Eagles, 2019). Since
-24-
ecotourism is of great importance in the country, this thesis aims to be developed in a hotel that has ecolodge
characteristics and thus, it is apparent that the hotel would be interested in a polygeneration system powered
by RES.
Another important parameter that should be mentioned is the natural resources that the country has, which
could be exploited in an environmentally friendly way to produce renewable energy. Costa Rica is situated
close to the equator, which means that it has 12h of daily solar irradiation all year around. Further, the
country also has seven active volcanoes that can be utilized for geothermal energy production, it is
surrounded by two oceans in its coasts, it has large portions of its land designated to the agriculture industry,
which generates biomass, and it has a very diverse geographical structure, with mountains and rivers, making
it ideal for hydropower. However, despite all the different natural resources that the country has, the mix of
energy generation is very poor, as seen in previous Figure 2.
Solar energy capacity for Costa Rica will be studied in a later chapter, but it is important to mention that the
country is situated in a zone with some of the highest solar capacities in the world (Ram et al. 2019). That
means that solar PV has potential to be exploited further in the country. For that reason, the case study in
this thesis focuses on the opportunity to design a polygeneration system to be powered by solar and biomass.
The share of renewable energy in the generation mix in Costa Rica is one of the highest in the world. As
Ebeling (2020) mentions, in the realm of electricity production, currently around 95% of generation comes
from renewable energy sources, and a 100% goal is set for 2030. However, as previously mentioned most
of that renewable energy is obtained from hydropower. Hydropower plants are, currently a key electricity
generator worldwide, especially in tropical countries. With a share of 16% in the world power generation
and reaching 56% of the supply of electrical energy demand in Central and South America (TSP, 2018), this
source has always been considered a clean way of generating energy. Despite being a renewable energy
source, it has been discovered that it is not operated without Greenhouse Gas emissions (GHG).
Figure 13. Carbon cycle in a hydropower reservoir (IHA, 2020)
Large reservoirs produce CO2 and CH4 when microorganisms present in the water decompose organic
matter that is trapped in the flooding area, as explained in Figure 13. The GHG emissions emitted by a
hydropower plant in tropical areas are notably higher than in other regions, due to the higher temperatures
and higher irradiation, two factors directly linked to an increase in CO2 equivalent emissions. The
International Hydropower Association (IHA, 2018), establishes that hydropower reservoirs have a median
life cycle carbon equivalent intensity of 18.5 g CO2 -eq/kWh., in comparison with other sources as coal that
has a carbon equivalent intensity of 820 g CO2 -eq/kWh or gas that has 490 g CO2 -eq/kWh, hydro is a
positive source. But if compare to nuclear that produces 12 g CO2 -eq/kWh or wind and solar PV that have
0 g CO2 -eq/kWh (taking into consideration only generation, not the whole LCA cycle) then the pollution
created by hydropower is significant. Also, as seen in Figure 14, for hydropower plants in tropical areas that
average increases and can be deducted to be around 40 g CO2 -eq/kWh.
-25-
Figure 14.GHG emissions intensity (g CO2 -eq/kWh) by climate region (IHA, 2018)
This means that despite the electricity generation mix being almost 100% renewable in Costa Rica, there are
some GHG emissions produced by large hydropower plants that need to be considered. This is a main
reason why this thesis project focuses the attention on other renewable energies such as solar, wind and
biomass to help diversify the generation mix in Costa Rica and decrease the percentage of energy produced
by hydropower.
Another important factor that contributes to the feasibility of a polygeneration project for hotels in Costa
Rica is the high price of electricity in the country. The monthly cost of electricity for commercial and
business starts at $0.23 per kWh when the usage is between 0-3,000 kWh and $0.14 per kWh when the usage
exceeds 3,000 kWh.
Figure 15. Price of electricity for commercial and business in Costa Rica (ICE, 2020)
In Figure 15, the prices of electricity in Costa Rica are in colones (the local currency of Costa Rica). However,
the prices have been changed to USD for ease of interpretation (1 USD equals 576 colones). Moreover,
Costa Rica has exceedingly high cost of electricity in comparison to other Latin American countries, as seen
in Figure 16. The country ranks fourth in Latin America for commercial and industrial electricity prices. It
can be noted that the price of electricity in Costa Rica doubles the price of electricity in countries like Mexico
and Argentina. The high electricity prices in Costa Rica are another reason the implementation of stand-
alone polygeneration systems for hotels is relevant.
-26-
Figure 16. Comparison of commercial and industrial electricity prices in Latin America (Osinergmin, 2018)
All the factors mentioned in this section: importance of ecotourism, diversification of generation mix, GHG
produced by hydropower plants and the high prices of electricity in Costa Rica are clear signals that the
opportunity for DES such as renewable polygeneration systems in Costa Rica are very feasible and relevant.
That is the main reason for the development of this study: to give a solution that can help the country be
more environmentally friendly and more cost competitive for the users.
-27-
4 Case Study: Design of Polygeneration System
4.1 HOMER Pro Software
For the simulation of the case study, a software often used by researchers for microgrids will be utilized.
Hybrid Optimization Model for Multiple Energy Resources (HOMER) software was originally developed
by the National Renewable Energy Laboratory (NREL). This software allows the user to design and
optimize distributed energy generation projects, and to evaluate their cost effectiveness and technical
implementation (HOMER, 2020). To run the techno-economic optimization simulation HOMER requires
six types of input data, which are: meteorological data, load profile, equipment characteristics, search space,
economic and technical data (Bahramara et al. 2016). These input data can be introduced by the user or it
can be obtained in the software interface. The meteorological data in HOMER is obtained from the NASA
surface meteorology and solar energy database, and the equipment characteristics can be obtained from the
software database. Figure 17 provides a visualization of the optimization process carried out by HOMER.
Figure 17. Comprehensive framework of HOMER optimization procedure (Bahramra et al. 2016)
Using the input data and some uncertainty parameters, the optimization simulation runs several iterations
of different component sizes for an entire year, and it finds the best Net Present Cost (NPC) solution for
the studied case (see equation (1) and (2)). The best solution is the one with the most competitive NPC,
however other results such as initial capital cost, operation cost, renewable fraction, cost of energy (COE)
(see equation (3)) and emissions produced are calculated for each iteration simulated by HOMER. This
-28-
allows the user to compare different simulation solutions and choose the best solution for the case
depending on the user’s preferences.
The net present cost (NPC) of a component is the present value of all costs of installing and operating the
component over the project timeline, minus the present value of all revenues that it earns over the project
lifetime. HOMER calculates the NPC of each component of the system and of the entire system (HOMER,
2020). The equations used by HOMER to calculate the NPC are as follows:
𝑁𝑃𝐶 = 𝐶𝑎𝑛𝑛,𝑡𝑜𝑡𝑎𝑙
𝐶𝑅𝐹 (𝑖,𝑅𝑝𝑟𝑜𝑗) (1)
𝐶𝑅𝐹 (𝑖, 𝑅𝑝𝑟𝑜𝑗) =𝑖(1+𝑖)𝑅
𝑖(1+𝑖)𝑅−1 (2)
𝐶𝑎𝑛𝑛,𝑡𝑜𝑡𝑎𝑙 is the total annualized costs and CRF is the capital recovery factor. The lifetime of the project is
represented by R, and i represents the interest rate for the project.
Another important parameter for system evaluation is the levelized cost of energy (COE). HOMER (2020)
defines COE as the average cost per kWh of useful electrical energy produced by the system. The equation
used by HOMER to calculate the COE is as follows:
𝐶𝑂𝐸 = 𝐶𝑎𝑛𝑛,𝑡𝑜𝑡𝑎𝑙−(𝐶𝑏𝑜𝑖𝑙𝑒𝑟)(𝐻𝑠𝑒𝑟𝑣𝑒𝑑)
𝐸𝑠𝑒𝑟𝑣𝑒𝑑 (3)
𝐶𝑎𝑛𝑛,𝑡𝑜𝑡𝑎𝑙 is the total annualized costs, 𝐶𝑏𝑜𝑖𝑙𝑒𝑟 is the boiler marginal cost, 𝐻𝑠𝑒𝑟𝑣𝑒𝑑 is the total thermal load
served, and 𝐸𝑠𝑒𝑟𝑣𝑒𝑑 is the total electrical load served.
HOMER is an effective tool for research due to the ease of use of the platform and the multiple results
obtained for each simulation, making it convenient for comparison and analysis of how different parameters
influence the results.
4.2 Resources in the Region and Ambient Conditions
The building chosen for the case study is a hotel in the Guanacaste province of Costa Rica. The province
of Guanacaste has a total extension of 10,140 km2, which is 20% of the total territory of Costa Rica (MAG,
2018). The hotel in the case study is in the Nicoya area of the province, in northwest Costa Rica, as seen in
Figure 18.
Figure 18. Location of hotel for the case study (Google Maps, 2020)
-29-
4.2.1 Weather conditions
The region of study has tropical, dry, and hot weather, with the dry season from December to May and the
rainy season from June to November. The maximum mean annual temperature is 33º Celsius and the
minimum mean annual temperature is 22º Celsius, with an annual average of 27.5º Celsius. The mean annual
precipitation at the region averages 1,652.7 mm. The driest months are January with 3.9 mm, February with
12.0 mm, and March with 5.2 mm of precipitation (IMN, 2018).
4.2.2 Wind resources
Costa Rica is mountainous in the center of the country and flattens along the coasts. This creates a wind
passage through the middle of the country while on the coasts the wind resources are not as strong. This is
caused by the country`s shape and the fact that the northern neighbor Nicaragua, is more extensive in terrain
which creates an effect that slows down much of the incoming wind.
Figure 19. Wind speed in Costa Rica (Global Wind Atlas, 2020)
As seen in Figure 19, the highest wind speed occurs in the middle of the country and in the area of study the average wind speed is only 5 m/s. These conditions are still suitable for installation of wind turbines but are not ideal as the wind is not strong enough to yield high energy outputs.
4.2.3 Solar resources
Costa Rica is situated at only 9.75º North of the equator, with a zone of high solar irradiance. As shown in
Figure 20, the highest solar irradiance in the country occurs in the west pacific, where the hotel of study is
located.
The yearly solar irradiance in the specific location of study is of 2,048.93 kWh/m2 (5.61 kWh/m2/day), with
the highest radiance values being measured during the dry season from December to May with a monthly
average of 200 kWh/m2, and during the rainy season the monthly average is of 150 kWh/m2 (European
Commission PVGIS, 2020). The solar resource availability makes the case study site an ideal site for solar
PV utilization.
-30-
Figure 20. Solar irradiance in Costa Rica (European Commission PVGIS, 2020)
4.2.4 Biomass availability
The main use of the land in the region is for agriculture and cattle raising. As mentioned by the Ministry of
Agriculture (MAG, 2018), the land that is not used for residential or commercial purposes, is used as 70.47%
for agriculture of grains, fruits, vegetables, and flowers; 22.58% for cattle raising and 6.95% for protected
areas and parks.
The agriculture sector uses a total of 85,418 hectares for growing vegetables and fruits such as: rice, onions,
peppers, beans, corn, watermelon, tomatoes, avocados, coffee, sugarcane, mangoes, oranges, and other
crops. The two main crops in the region are rice and sugar cane, with an estimated 28.46% and 41.85% of
the total land use for agriculture in the region respectively (MAG, 2018). This information indicates that
biomass is present in the region and could be used as a resource for power generation.
This case study focuses on the use of biomass from the two main crops in the region. The most harvested
crop in the region is sugar cane with a total of 35,754 hectares used. The annual production of sugarcane in
the region is 60 tons per year per hectare (MAG, 2007). This means that the total annual production of
sugarcane is 2,145,240 tons. Of the sugarcane, 69% is used in the production of sugar, 10% is considered
waste and 30% is bagasse which is a byproduct that can be used for the generation of syngas for electricity.
Using this information as a reference, the total biomass obtained from sugarcane in the region is 643,572
tons per year. Sugarcane bagasse has a Lower Heating Value (LHV) of 7,980 MJ/ton (Shukla & Kumar,
2017).
Rice is the second most harvested crop in the region with 24,313 hectares of land used. As mentioned by
the Food and Agriculture Organization of the United Nations (FAO, 2004) the yield of rice is 5.5 tons per
year per hectare in Latin America. This adds up to 133,721 tons per year of rice harvested every year in the
region. In the harvest of rice, rice straw represents 29% of the total harvest and rice husk represents a 20%
of the total harvest, rice straw has an LHV of 10,460 MJ/ton and rice husk as an LHV of 12,550 MJ/ton
(Singal et al. 2007).
To calculate the amount of syngas that can be produced from biomass, it is important to consider the
efficiency of the biomass gasifier. As mentioned by Mathieu & Dubuisson (2002) the efficiency of the
gasifier can vary depending on the air temperature, the amount of oxygen in the combustion process and
-31-
the operating pressure. Considering these parameters, the efficiency of the gasifier usually ranges between
65% and 80%. For the calculation in this study, a gasifier efficiency of 75% as calculated by Meyer &
Mamphweli (2010) will be assumed. Table 2 shows the energy that could be obtained from the biomass
present in the region.
Type of Biomass LHV
(MJ/ton)
Biomass available
per year (ton)
Syngas mass
available per year
(ton)
Syngas energy
available for
combustion per
year (MWh/year)1
Sugarcane Bagasse 7,980 643,572 482,679 1,070,021.05
Rice Husk 12,550 26,744 20,058 69,930.01
Rice Straw 10,460 38,779 29,084 84,512.86
Total --- 709,095 531,821 1,224,463.92
1Conversion from MJ to MWh is 0.0002778
Table 2. Annual Potential for biomass gasification in Chorotega region
The weather and ambient conditions in the Chorotega region, where the hotel of the case study is situated,
make these three resources very important in the development of the system. Hydro resources were also
considered for the case study, but the hotel regional water flow is not steep enough and the precipitation is
not high enough during six months of the year, so hydro resources are neglected.
4.3 System Boundaries and Assumptions of Case Study
As previously mentioned, some assumptions had to be made in order to have a more accurate demand data
for the different systems. For the air conditioning system, the demand data was calculated based on the A/C
units in the hotel and the power ratio of the units. For the domestic hot water (DHW) demand data, an
assumption based on a constant usage for the quantity of people in the hotel was used to calculate how
much thermal power is needed to heat up water. Similarly, the energy usage of the MD system was calculated
based on the amount of water needed per person in the hotel, as explained in Table 5.
It was assumed that the residual biomass waste is currently not being used for any purpose and hence a part
of the waste can be used for syngas production. An assumption was made to calculate the price of the
biomass waste. It is important to mention that in this region, biomass energy is not commercially traded,
but some large agricultural plants use sugarcane bagasse to power their own electricity plants (El Viejo,
2020). To estimate the price for the biomass that would be used in this case study, a document by the
Ministry of Agriculture in Costa Rica (2007) was considered. Using the values in that document, a price for
the bagasse produce in a hectare was calculated in Table 3.
Table 3. Price of bagasse per hectare
In the table above, the price was calculated per hectare. As mentioned previously, in one hectare, 18 tons
of bagasse are produced, so the price per ton can be calculated, as shown in Table 4. To the cost of the
Cost type ($/hectare)
Labor work 45
Equipment, water,
fertilizer, and electricity
155
Marginal 40% 80
Total Cost 280
-32-
bagasse the transportation cost must be added. After some research for transportation costs in the
Guanacaste region, it has been concluded that a truck with a capacity to carry two tons of bagasse charge
$60 per trip, which means that the transportation cost per ton of bagasse is $30.
Table 4. Price of bagasse per ton
Including all costs, it has been estimated that for the case study, a ton of sugarcane bagasse has a value of
$45.55, this cost is included in the HOMER simulation to have an accurate COE for later comparison.
Also, some assumptions needed to be made for the selection of the system components. For the production
of syngas, a down draft gasifier was selected due to its proven technology maturity with agricultural biomass,
with an efficiency of 75% (Meyer, 2015). An ICE was selected as prime mover due to the maturity of the
technology, the high efficiency at small sizes, and higher tolerance to contaminants than turbines, which is
especially useful for small-scale biomass applications (Stanek et al. 2015). The ICE electrical efficiency is
around 30%, but due to the 2:1 heat to power ratio the overall efficiency can be increased to 90% when
utilizing recovered heat for energy service purposes (Mertzis et al. 2014). Another assumption that has been
made is the efficiency of the absorption chiller to covert the residual heat into cooling power. The absorption
chiller in this case study is set to have an efficiency of 60% (Matjanov, 2020).
4.4 Data Acquisition of Electric and Cooling Demand
The hotel considered for the case study has 26 rooms for double occupancy, a pool, and a restaurant. As
seen in Figure 21, the hotel has its highest occupancy from November to April, with March being the month
with the highest occupancy. The hotel has a lower demand from May to October, with October showing
the lowest occupancy month.
Figure 21. Monthly electrical demand for the hotel in 2019
Cost type ($/ton)
Production cost 15.55
Transportation cost 30
Final cost 45.55
-33-
This data correlates with the dry and rainy season, respectively, and data provided by the tourism institute
of Costa Rica (Instituto Costarricense de Turismo), where March has the highest occupancy per month at
82.8% and October has the lowest occupancy per month at only 47.3% (ICT, 2019).
The hotel provided the demand data for the year 2019 for use in this case study. The hotel systems for air
conditioning (A/C) and domestic hot water (DHW) are run electrically. The electric demand data includes
these systems as well as a pump to extract water from an underground well, the system for the functioning
of the pool, and the electrical appliances that are used in the hotel rooms (ceiling fans and power outlets)
and in the restaurant (stoves, ceiling fans, microwaves, refrigerators, freezers, TVs, etc.).
The hotel provided data based on monthly electrical usage, therefore it was necessary to generate hourly
demand data based on reference studies (Wegener et al. 2019; Smith et al. 2020). The data in Figure 22,
presents all 8760 hourly values of electricity demand from the first hour of the year in January to the last
hour in December for the year 2019. The blue bars represent hourly electric demand data, which fluctuate
depending on the occupancy of the hotel. The red line shows an hourly average, which correlates to the
monthly data previously showed in Figure 21.
Figure 22. Electrical hourly data for the full year in 2019
In this case study, the A/C and the DHW outputs are going to be obtained from a heat recovery system
using a biomass genset and a boiler. To obtain the demand data for these two systems from the provided
electrical data some assumptions were made. It was investigated that in the hotel a total of 30 A/C units
with an output power of 1.4 kW are used. This means that if the occupancy of the hotel was 100% then the
A/C will consume 42 kWh/hour and if the hotel was 50% then only 24 kWh/hour of electrical output will
be needed. As for the DHW it was identified that assuming a constant production of 20 l/occupant/day
for 75 persons the hot water demand will use 4.39 kW at full occupancy (Aichmayer et al. 2014).
As shown in Figure 21, March is the month with the highest electricity consumption in the hotel. The profile
fluctuates during the day, with the breakfast, lunch, and dinner time showing peaks in demand. This is due
to the fact that tourists are usually in the hotel during those times of the day. The highest demand occurs at
night due to the intensity of the lights and appliances in use. The DHW profile is mostly used during the
day with a constant profile, while at night the usage of DHW is almost null. As for A/C, the electricity
demand does not vary much during the day as people like to keep the room cool. At night, the A/C profile
decreases a bit as well as in the afternoon when there are less people in the hotel.
-34-
Figure 23. Demand profile for March 2019
In Figure 24, the demand profile for the lowest month of the year is presented. The variations during daily
use does not change much, but the intensity is decreased due to the low occupancy of the hotel for all energy
service appliances.
Figure 24. Demand profile for October 2019
As for the demand of fresh water in the hotel, currently an electrically driven reverse osmosis (RO) system
is used to purify the water, which is pumped up from the well. In the proposed system the RO system will
be substituted by a membrane distillation (MD) system, which utilizes thermal energy to purify water. To
calculate the amount of heat needed in the system, first a calculation of the freshwater demand is needed.
In a study by Howard and Bartran (2003) it was calculated that the demand for freshwater is 20 liters/person.
However, the freshwater demand of the hotel will fluctuate depending on the occupancy. To ensure the
fulfillment of freshwater demand in the hotel, a demand of freshwater for 100% occupancy of the hotel is
assumed.
-35-
Number of People Water demand per
capita (l/person/day)
Total water demand
(l/day)
Total water demand
(m3/day)2
52 20 1040 1.04
2Coversion from liter to m3 is .001
Table 5. Water demand estimation for the hotel
As mentioned before, the MD system utilizes thermal energy to purify the water. Ullah et al. (2008),
calculated that the thermal energy required by a MD system is 100 kWh/m3. This means that for the hotel
in this case study, the total heat energy required to power the system is 104 kWh per day. This thermal
demand for the MD system fluctuates during the day to account for the hours that more purified water is
needed.
To account for the MD system as well as the DHW and A/C systems to be driven by thermal energy, the
demand data for the hotel varies. For the case study, there are two demand loads: one electrical demand and
one thermal demand. Figure 25 and Figure 26 present the demand loads for March and October respectively.
Figure 25. Energy demand of the hotel in March
Figure 26. Energy demand of the hotel in October
For the case study, the total energy demand of the hotel is separated by the thermal and electrical demand as shown in Figure 27. While the electrical demand is still higher than the thermal demand in each month, the thermal demand is significant.
-36-
Figure 27. Demand data for the hotel in the case study
It is important to also mention that, for this case study, the COE from the grid was determined from the
electricity bills of the hotel, as explained in Figure 15, the electricity price for hotels in Costa Rica has a fixed
price for the first 3,000 kWh and after that, the rate is lower. This means that the COE changes monthly
depending on the usage, for the hotel in the case study the highest COE is in the month of October where
the occupation is the lowest with a price of $0.22/kWh and the lowest in March when the occupancy is the
most, with a price of $0.17/kWh. For the year 2019, the average monthly COE is $0.197kWh, this is the
value used in the HOMER simulation.
4.5 Proposed System
The proposed polygeneration system consists of photovoltaic panels, a biomass gasifier to power an ICE,
a battery bank to store excess energy, a biomass boiler to help with heating and potable water production,
an absorption chiller to generate cooling form heating and a membrane distillation unit to purify water. The
system design is shown in Figure 28.
Figure 28. System schematic
-37-
As seen in the system schematic above, the biomass is fed into the gasifier to produce syngas to be used to
fuel the ICE. The ICE and the PV panels produce electrical energy to cover the electrical load. The electrical
load in the hotel operates with alternate current (AC), but the solar PV panels produce direct current (DC)
electricity. So, the electricity produced by the PV panels in DC is stored in the battery bank, and when it is
needed to cover the electrical demand, a converter converts the current from DC to AC. For the AC system,
the residual heat from the ICE is converted into cooling power by the absorption chiller. The residual heat
is also used to heat up the water to produce DHW in the hotel and using a membrane distillation system
the heat is used to produce clean water. To help in the production of thermal energy in case of an energy
shortage, a boiler is added as part of the system. The boiler is relatively inexpensive, powered by biomass,
and it operates only when needed so it is more an auxiliary part of the system. It is also important to mention
that the boiler is added to the system party due to the modelling limitation in HOMER to account for
thermal energy.
4.6 Description of System Components
This chapter provides a summary of all the components in the proposed system. It also presents the
characteristics of all the components, their capital costs, and the operation and maintenance (O&M) costs.
For the prices, scientific and commercial sources have been used for each component, as well as the prices
suggested by HOMER Pro. The estimated prices are conservative, in order to account for shipping and
engineering costs.
Component Capital & Replacement
Cost
O&M Cost Characteristics
ICE + Down-draft
gasifier
1,060 $/kW
(Bhattacharjee &
Dey, 2014)
0.1 $/operating h
(Sigarchian et al.
2015)
Lifetime: 15,000 h
(Bhattacharjee & Dey, 2014)
Gasifier efficiency: 75%
(Meyer, 2015)
Engine max. el. efficiency:
30%
Engine max. efficiency with
heat recovery: 90%
(Mertzis et al. 2014)
PV panels 1,000 $/kW
(Ossenbrink et al.
2012)
25 $/kW/year
(Yoo et al. 2014)
Lifetime: 25 years
Derating factor: 80%
Max Efficiency: 15%
(Wegener et al. 2019)
Batteries 1,500 $/kWh
(Wegener et al.
2019)
30 $/year/battery
(Wegener et al.
2019)
Lead Acid type
Minimum lifetime: 7 years
Lifetime Throughput: 10,973
kWh
(Wegener et al. 2019)
-38-
Converter 750 $/kW
(Sigarchian et al.
2015)
10 $/kW/year
(Wegener et al.
2019)
Lifetime: 20 years
Inverter efficiency: 90%
Rectifier efficiency: 90%
(Sigarchian et al. 2015)
Boiler 700 $/kW
(HOMER database,
2020)
Negligible Boiler efficiency: 85%
(HOMER database, 2020)
Absorption Chiller 50 $/ kW
(Coronado et al.
2011)
.005 $/kWh
(Coronado et al.
2011)
Heat recovery rate: 70%
COP: 0.6
(Wegener et al. 2019)
Membrane
Distillation
1,080 $/m3
(Perves et al. 2016)
0.2 $/m3
(Perves et al. 2016)
Direct Contact Membrane
Distillation
Lifetime: 25 years
Power ratio: 100 kWh/m3
(Ullah et al. 2008)
CCHP measures 15,000 $/per system
(Wegener et al.
2019)
.013 $/kWh
(Coronado et al.
2011)
Capital cost including piping,
engineering, and shipment
Lifetime: 25 years
Table 6. Summary of system component costs and characteristics
4.7 Load Control of the System
For the polygeneration system optimization, an adequate load control is needed. There are different load
control strategies: follow electric load (FEL), thermal load (FTL), or a combination of both (Das & Al-
Abdeli, 2017). In this case study, the electrical load demand of the hotel is slightly higher than the thermal
load demand, and the heat to power ratio of the ICE prime mover is 2:1. So, for this hotel, it has been
concluded that a FEL control ensures that the electricity load is fulfilled, while the thermal energy demand
is fulfilled simultaneously due to the heat to power ratio.
-39-
5 Results and Sustainability Assessment
5.1 Simulation Results
The proposed system schematic is shown in Figure 28 and the system component sizes are displayed in
Table 7. The results obtained by HOMER show that the proposed system’s ICE has a configuration that is
10 times larger than the PV system, this is because biomass is used the majority of time and the PV system
for peak hours during the daytime.
Component Optimal Configuration
ICE 100 kW
PV 10 kW
Batteries 46 kWh
Converter 10.7 kW
Table 7. Proposed system component sizes
The results obtained by HOMER for the proposed system configuration are compared to usage of electricity
from the grid over a period of 25 years. As previously mentioned, HOMER displays the best solution
according to the NPC. For the grid case simulation only the price of electricity and the total demand of the
hotel were used as input into the simulation. The price of the electricity from the grid was calculated based
on the information in section 4.4. No cost was added for grid connection since the hotel is already connected
to the grid. After simulating the proposed system case (Figure 28) and the grid system in HOMER, the
results are presented in Figure 29.
Figure 29. Economic results
It can be seen that between the two cases, the grid case is more expensive than the proposed system. The
NPC for the grid case is of $1,522,000 and the NPC for the proposed case is of $1,111,732, which means
that there is a difference of $410,268 which represents a 27% margin in the 25-year period. As expected,
since there is no connection to the grid needed, the initial investment for the proposed system is higher.
This is also true for the O&M costs, as the proposed system components need to be maintained for proper
functioning of the system, and for the grid case there is no O&M cost to the client.
-40-
Another important parameter is the GHG emissions. Based on the information of Section 3.5, which
presents the GHG emissions by hydropower, the grid CO2 emissions in Costa Rica are calculated to be 61
g CO2/kWh (ElectricityMap, 2020). As mentioned in the previous chapters, the electricity mix of Costa Rica
consists already of a considerably high renewable energy mix. As for the proposed system, it has been
calculated using an LCA analysis (IPPC Biomass, 2020) that biomass gasification ICE emits 45 g CO2/kWh.
A comparison can be seen in Figure 30. From an environmental standpoint, the proposed system is
significantly better as it produces 38% less emissions than the grid.
Figure 30. Yearly CO2 emissions for both cases
Figure 31 presents a comparison of the system COE in the case of the proposed system where there is also
thermal energy produced only the electric energy is taken into consideration. The COE is lower for the grid
case than for the proposed system, but this is only taking into consideration the electric energy produced,
not the thermal energy produced in the proposed system.
Figure 31. Cost of Electricity for both cases
As shown in Table 8, the proposed system would generate most of the electrical energy using the ICE, while
the PV panels would support the electrical power generation mostly during daytime peak hours. The total
biomass used by the ICE in the system to generate energy is 167 tons per year.
-41-
Component Production (kWh/year) Percentage
ICE 348,812 89.7%
PV 40,020 10.3%
Total 388, 832 100%
Table 8. Electricity generation
The 2:1 power to heat ratio of the ICE makes it possible that almost all of the thermal power is obtained
from the ICE and then used in the absorption chiller for A/C, for DHW, and in the membrane distillation
system for potable water. Most of the cost occurs due to ICE replacements, but the batteries and the MD
system also inflict costs due to their replacement requirements. Despite the reasonably low price, the
biomass fuel still represents an important part of the costs in the system. Considering some conservative
assumptions, the proposed system is economically better than the reference grid system. The detailed cash
flow of the proposed system is shown in Figure 32.
Figure 32. Detailed cash flow for proposed system
5.2 Sensitivity Analysis
The proposed system for the case study was designed considering the availability of resources in the
Guanacaste region and its feasibility to cover the hotel demand in an efficient and economically viable way.
However, in this section, three other systems are proposed to compare to the proposed system and the grid
case. All systems schematic and results are shown in Appendix A, and the component sizes are shown in
Table 9. The three systems are:
• Case 1: using only biomass via a gas engine and batteries
• Case 2: using only solar PV and batteries
• Case 3: similar to the proposed system, but also using wind turbines to generate electrical power.
-42-
Case 1: Only Biomass
Component Optimal Configuration
ICE 120 kW
Batteries 201 kWh
Converter 46.7 kW
Case 2: Only PV
Component Optimal Configuration
PV 1,168 kW
Batteries 1,264 kWh
Converter 160 kW
Case 3: Wind
enhancement
Component Optimal Configuration
ICE 50 kW
PV 10 kW
Wind Turbines 192 kW
Batteries 1,026 kWh
Converter 133 kW
Table 9. Different configurations component sizes
These systems were designed for cases where the availability of different resources would be more limited
than assumed. If it were not possible to obtain biomass during a given time in the region, then a system
consisting of only PV panels could show major advantages over a system using only biomass. Similarly, a
system may be composed of only biomass units without PV panels, because, for example, in the case that
the ceiling structure was not strong enough for a PV panels system or in the event that the location would
be too shaded. Lastly, a system with the same components as the proposed system but adding wind turbines
to use the wind resource in the region was designed. In Figure 33, an economic comparison consisting of
initial investment, NPC and O&M is shown for all of the systems previously described.
Figure 33. Economic comparison of all configurations
-43-
As seen in the figure above, the PV-only system and the proposed system + wind turbines system are
economically unreasonable. These two systems have an NPC of more than $5,000,000 difference with the
proposed system. The PV-only system has a very significant initial investment, which is due to the need of
more batteries. This exposes the benefit of having more than one generation system. The case 3 system also
requires a large initial investment, because wind turbines are comparatively expensive, and the relative energy
output is not high enough. Wind energy is usually used in larger energy systems and also the site of the hotel
is not a in a favorable wind resource area as explained in Figure 19. For the biomass-only system, comparing
the NPC with the proposed system the difference is $800,000 during the 25-year period. This shows how
beneficial the PV panels are, as they help with the production of energy during daytime peak hours. In
addition, the difficulty with a biomass-only system is that even though at the moment the biomass availability
is considered as sufficient, in the coming years if the biomass supply would decrease, the price of the biomass
might fluctuate and could make the system economically unfeasible. In conclusion, from an economic and
technical perspective, the proposed system appears to be the most favorable one.
In Figure 34, a comparison of CO2 emissions is shown, where the same data as for Section 5.1 was
considered. The calculated proposed system’s CO2 emission is based on an LCA analysis (IPPC, 2020) for
biomass and the proposed system emissions based on the grid emissions. The graph shows that any
proposed system is better than the national grid electricity as the electricity from the grid generates 37.74
tons of CO2 per year for the hotel in the case study. The case 3 system has the lowest yearly CO2 emissions,
but then the proposed system is second with 10% more emissions. So, even though the proposed system is
not the best case, it still shows an emissions reductions potential of approx. 50% in comparison with the
grid.
Figure 34. Yearly CO2 emissions for all systems
In Figure 35, a COE comparison is made to give another perspective from the economic view. As expected,
the COE is more expensive in all of the new systems proposed. The COE is the highest for the case 2 PV-
only system as it requires a lot of capital investment for batteries and solar panels. The case 3 system also
has a very high COE as the price of turbines is high and the number of batteries needed is considerable
high as well. The biomass-only system has a more competitive COE than the two alternative proposed cases
but is still higher in comparison with the proposed system and the grid COE, again due to the amount of
batteries needed. As mentioned before, the grid case has a lower COE, but the COE of the proposed system
is only $0.01 higher, making the proposed system very competitive according to COE even though for this
comparison HOMER does not consider the thermal energy produced.
-44-
Figure 35. Cost of Electricity for all systems
Another possible case is a decrease in the electricity price from the grid. Currently, the world is facing a
global health crisis and national economies have been negatively impacted worldwide. Costa Rica is no
exception to this pandemic and the country’s economy is currently suffering. To help citizens, the National
Energy Agency has reduced the electricity price in Costa Rica since April of 2020. Based on the information
by ICE (2020), due to the COVID 19 situation the price of electricity for hotels and commercial buildings
in Costa Rica has been decreased to $0.17/kWh from $0.23/kWh (Figure 15). For the pre-COVID 19
electricity price in Costa Rica the 0-3,000 kWh cost $0.23 and then after the 3,000 kWh the cost is
approximately $0.14, as for the COVID- 19 cost is always $0.17/kWh. This means that if the grid system is
calculated with this COE, the NPC is decreased to $1,360,000. In Figure 36, a comparison of the cost for
electricity for each month of the case study is done using the COE pre and post pandemic.
Figure 36. Cost per month comparison with the COVID-19 pandemic situation
-45-
This means that the COVID 19 situation would have decreased the price of electricity in every month of
the case study except the month of March as shown in the figure above. The month of March is higher for
the COVID 19 prices because the use after 3,000 kWh is significant, so the price is reduced, but with the
COVID 19 prices for electricity, the amount of electricity used is not considered in the price to pay. The
decrease in electricity price would have been such that the NPC of the grid case system is decreased by
$162,000 which represents about a 10% decrease. However, even taking into consideration the price
decrease for electricity in Costa Rica, the proposed system is still more economically feasible for this case
study with a difference in NPC of -$250,000 over the grid case affected by COVID 19 situation.
Another situation that could affect the systems price would be if electricity could be sold back to the grid.
Currently in Costa Rica, only about 15% of total energy produced by a system can be sold to the grid, but
this law is currently under revision (MINAE, 2020) to potentially offer a higher allowed percentage to be
sold back to the grid. This would make it conceivable to install a bigger system and sell more electricity to
the grid. This could be an interesting future study for the hotel after the new law has been published.
5.3 Environmental Impacts
This section represents an environmental perspective of the benefits that the proposed small-scale
polygeneration system provides. Those benefits are reducing GHG emissions and allocating those
emissions, which helps to change the way energy is produced in the country from large power plants that
damage ecosystems, to a more sustainable small-scale system that utilizes waste to produce energy. Those
changes encourage the shift to a more environmentally friendly way to generate energy in the country.
In Figure 34, a comparison between all the proposed systems and the grid CO2 emissions was shown. From
this, it can be concluded that the proposed systems show less CO2 emissions than the grid electricity.
However, it is not just the GHG emissions that need to be taken into consideration for an environmental
analysis. Large power plants produce vast GHG emissions in a small area, contaminating the surrounding
air. This is an advantage that small scale polygeneration systems have over larger power plants, as the GHG
emissions generated by small scale systems distribute the contamination in small amounts to different areas
(Aldrich et al. 2011). This means that instead of damaging a small area where a large power plant is present,
multiple small-scale generating plants in different areas with a lower amount of GHG emissions help the
ecosystem’s surroundings to deal with that GHG emissions in a more tolerable way and prevent it from
damaging a specific location.
Another environmental drawback that is specific to this study is the negative impact that large hydropower
plants have on surrounding ecosystems. In Costa Rica, hydropower accounts for almost 70% (Figure 2) of
the electricity production and besides being considered a renewable energy source and having lower GHG
emissions, the hydropower plants have a significant environmental impact on the immediate surroundings.
In order to build hydropower plants, vast areas are flooded to create reservoirs. Such areas are usually
occupied by people, often indigenous tribes that live around rivers with favorable conditions for food,
irrigation for agriculture and transportation. To build large water reservoirs, these individuals are frequently
displaced from their territories, often without giving consent. It is estimated that displacement worldwide
due to hydropower plants reaches almost 80 million people, and a significant part of this displacement
occurs in Latin America, Africa, and Asia (VanCleef, 2016). Another negative impact that large hydropower
plants have is on ecosystems, as rivers are transformed which damages the river’s natural ecosystem. Fish
environments are transformed completely, causing some species to be disconnected from their original
habitat. Additionally, the areas flooded are so vast and, in some areas, there is so little water movement that
the invasion of weeds and the growth of mosquitoes and other insects is facilitated. Thus, an unsustainable
ecosystem for original species living around those waters is created (Abbasi, 2011). In this context, it should
be noted that the largest hydropower plant in the country was recently completed in Costa Rica, Reventazon,
which required flooding of an area of over 700 hectares (ICE, 2020). This new hydropower plant can create
40% of the country’s electricity demand, but during the building of the plant, a significant amount of
-46-
environmental issues such as the aforementioned displacement and changes of the ecosystem occurred.
Small scale polygeneration plants such as the one proposed in this thesis report provide an example of how
electricity can be generated without damaging the environment on such an enormous scale.
In this report, the use of biomass as an energy input is explained. Biomass can be of great use in the case
study region, as it can not only diversify the energy generation, but also when using biomass waste to
produce energy, the unnecessary generation of GHG emissions by burning down the biomass waste is
avoided (Larios, 2010). In the Chorotega region, a lot of sugarcane bagasse is produced as a byproduct of
sugarcane. This bagasse is considered waste, and since there is not a convenient way of disposing this waste,
farmers burn the bagasse. This is an issue that could be tackled by the proposed system, as instead of burning
the bagasse in open fields, it could be utilized in the generation of energy in small scale systems. This would
be beneficial for the environment and also for the farmers, as it provides a more useful way to dispose of
the byproduct waste.
5.4 Social Impacts
The United Nations (UN) have established the Sustainable Development Goals (SDGs) to ensure action is
taken in developing areas to prevent worsening the climate crisis (UN, 2020). For the social impacts that
the proposed system in this thesis report have, the SDGs are used to explain how the system achieves some
of the goals for a more sustainable future in the region.
Figure 37. Sustainable Development Goals (UN, 2020)
Some of the SDGs in Figure 37, such as clean water and sanitation, affordable and clean energy, responsible
consumption and production, climate action, life below water and life on land are already tackled by the
proposed system and explained in the Section 5.3 on the environmental impacts.
However, in this section, the focus is more on the SDGs that have a more social connotation and how the
proposed system can help this region to reach those SDGs. In the Chorotega region, the percentage of
-47-
poverty reaches 23% of the population (ENAHO, 2017). The creation of small scale polygeneration systems
such as the one proposed can help to tackle unemployment in the region as it would require labor to collect
the bagasse and transport it to the plant site. This can create jobs and impact the first two SDGs. The
creation of jobs can also encourage economic growth opportunities in the region and allow for more decent
working conditions for individuals in the Chorotega region.
Additionally, the creation of small scale polygeneration systems in the region can address another SGD:
sustainable cities and communities. This proposed system is designed for a hotel, but this system could also
be implemented for small communities in the region. The importance of the design of this system is that is
based on locally available resources so it can be duplicated for other buildings around the community. This
includes not only hotels but also government buildings, restaurants, commercial buildings, and even small
organized communities, and would help with the management of agricultural waste and the development
of more sustainable communities.
The proposed small scale polygeneration system can create jobs, improve the life of the people in the region
and play a part in the reduction of poverty, but this is only possible if the local government helps to
responsibly exploit the resources in the region.
5.5 Economic Impacts
From an economic perspective it was already determined that the proposed system is more viable for the
hotel than buying electricity from the grid. In the span of 25 years, the hotel could save $410,268 which
represents a 27% margin compared to buying electricity from the grid. However, this is not the only
economic benefit that the hotel could realize. The proposed system was designed to fulfill the requirement
of the hotel consumption, but the system could be increase in size to generate more energy and sell it back
to the grid, generating revenue. In a previous section, it was mentioned that the current law in Costa Rica
allows the prosumer to sell back 15% of the total energy produced (MINAE, 2020), but this law is currently
under revision and that percentage could increase. For a hotel with the infrastructure to increase the size of
the PV system and to add more gasifiers and ICE, this could mean a way to generate an extra revenue stream
and take advantage of the vast resources in the region. Also, it is important to mention that by producing
its own energy from renewable sources the hotel would be seen as a sustainable and ecological friendly hotel,
which could attract more tourists.
The proposed system impacts not only the hotel, but also the surrounding agricultural sector. This could
create an extra revenue stream by selling the biomass “waste” to the client to use in the generation of energy
services. As mentioned in the environmental section, currently, the sugarcane bagasse is burned in the open
field, but that bagasse could be sold instead. As calculated in Table 3, farmers could sell the sugarcane
bagasse produced in one hectare of land for $280. Also, another industry in the region that could benefit
from the proposed system is the transportation sector, as each trip to carry a ton of sugarcane bagasse costs
approximately $30. This means that the proposed system could elevate the economy of the region and create
new revenue streams for the hotel, the agricultural sector, and the transportation sector of the Chorotega
region.
As mentioned in the previous section, some SGDs can be tackled by the proposed system, and from an
economic perspective, an SDG that is achieved is decent working conditions and economic growth. In a
region that relies heavily on tourism and agriculture, adding an extra revenue stream that could benefit the
people in the region to activate the economy and generate jobs is a significant way of helping. Also, the
SDGs mentioned in the previous sector to improve the life of individuals from a social perspective would
only be possible if the economic impact is significant enough to help achieve those SDGs. The proposed
system not only improves the hotel’s economic standing, but more importantly the region’s economy and
at the same time, it also has a positive impact on the social aspects and the environment of the Chorotega
region.
-48-
5.6 Impact of the System on a Country Level
As previously mention, the proposed system shows the environmental, social, and economic improvements
for the hotel and the region in general. In this section, a brief analysis of how the proposed system could
influence a change in the country is presented. Costa Rica has abundant natural resources that have not
been fully exploited to generate electricity responsibly. Most of the energy generation is centralized and
there is not a clear regulation for DES.
The system was proposed for a hotel in the Guanacaste region, taking into consideration the natural
resources available in that area. According to the Ministry of Tourism there are 835 hotels in the Guanacaste
region (ICT, 2019), with an average room quantity of 16 rooms per hotel. If hypothetically, the proposed
system in this study can be replicated in all the hotels of the region, the economic and environmental impacts
would be as shown in Table 10.
Number of
hotels
Economic Impact per
hotel ($)
Environmental Impact per
hotel (tons CO2 /year
saved)
Biomass
consumption (tons)
835 $410,268 14.4 166
Results $342,573,780 12,024 138,610
Table 10. Results of proposed system for Guanacaste region
As one can see, the economic savings that the hotel owners would have in a period of 25 years by generating
their own electricity would amount to more than 340 million USD. And the environmental benefit that
saving 12,024 tons of CO2 every year is of great interest too. It is clear that implementing the proposed
system in all the hotels of the region is a great task. However, the natural resources in the region are
sufficient. If each system uses the same amount of biomass to generate energy as the proposed system, then
166 tons of biomass per year per system for 835 hotels, there are 138, 610 tons of biomass per year needed.
As mentioned in a previous section, more than 600,000 tons of biomass are available in this region annually
(MAG, 2018). So, the resources are available to implement the proposed system in all hotels, but it is also
difficult, as some hotels might not have the economic resources to make the investment to build their own
system.
Using the same calculation approach to estimate the impact of deploying similar polygeneration systems on
a country level for the 3,741 hotels in Costa Rica (ICT,2019), the results shown in Table 11 are presented.
Number of
hotels
Economic Impact per
hotel ($)
Environmental Impact per
hotel (tons CO2 /year
saved)
Biomass
consumption (tons)
3,741 $410,268 14.4 166
Results $1,534,812,588 53,870.4 621,006
Table 11. Results of proposed system at a country level
However, it should be reiterated that these results are very optimistic and idealistic, and assumptions need
to be made to obtain these results. The natural resources available in other regions of the country were not
established, so this result is assuming that similar resources are available in the entire country to build a
similar system as the one proposed in this study. With those simple assumptions it can be determined that
the economic and environmental benefits could be very positive and can represent an important benefit for
-49-
the country. Even if the proposed system could not be replicated for all the hotels, if only a small percentage
of the hotels in the country could make that change, then a significant amount of money and tons of CO2
can be saved every year.
-50-
6 Conclusions and Future Research
The goal of this case study was to propose a renewable polygeneration system that could satisfy the energy
demand of a hotel in the Guanacaste region of Costa Rica. In order to propose a system, historical demand
data, scientific literature, and the availability of natural resources in the region were investigated to propose
a realistic system that could be implemented in the hotel. Then, the proposed system was compared to the
national grid system to show the benefits and drawbacks that the system has over the grid. To further study
the benefits of the proposed system, three more cases with different system structures based on different
renewable energy sources were compared and the proposed system proved to be significantly better than
the alternative systems.
The results showed that a biomass-based, solar assisted polygeneration system outperforms the reference
case. The economic benefit has a margin of 27% over the national grid system, with savings of $410,268
during the system lifetime of 25 years. Also, the environmental benefits are vast with savings of 14.4 tons
of CO2 per year in comparison to the national grid, which represents 38% less GHG emissions. This study
indicates huge potential benefits from an economic and environmental perspective for one specific hotel.
However, a study of how the system could be applied to similar hotels in the region and in the whole country
revealed enormous potential.
This study also shows that even in a country like Costa Rica, where approximately 98% (ICE, 2020) of
electricity comes from renewable sources, some flaws can be found in the electricity system, and a more
beneficial system can be proposed using more local renewable energy resources. This study can be used by
the hotel sector as a preliminary study to shift towards a more decentralized energy system structure in the
country that could bring benefits to the many stakeholders involved. This study also aims to show that
polygeneration systems can be a great way to utilize energy more efficiently, as less input is needed to
generate more energy services, thus improving the current energy system.
Future studies of this topic including more precise calculation at a country level, utilization of different
natural resources, and other technologies for the system are advised. The proposed system is one small step
into a more efficient and decentralized energy generation system in Costa Rica, and the results from an
economic, social, and environmental perspective are shown to be of great interest to change the energy
sector in the country.
-51-
Bibliography
Abbasi, T. & Abbasi, S. (2011). Small hydro and the environmental implications of its extensive utilization.
Renewable and Sustainable Energy Reviews, 15, pp. 2134-2143
Aichmayer, L., Spelling, J., Laumert, B. (2014). Small Scale Hybrid Solar Power Plants for Polygeneration in
Rural Areas. Energy Procedia 57, pp.1536-1545.
Alanne, K., & Saari, A. (2006). Distributed energy generation and sustainable development. Renewable and
Sustainable Energy Reviews, 10, pp. 539-558
Aldrich, R., Llauro, F., Puig, J., Mutje, P. & Pelach, M. (2011). Allocation of GHG emissions in CHP
systems: a new proposal considering inefficiencies in the system. Journal of Cleaner Production, 19, pp.
1072-1079
Bahramara, S., Parsa, M. & Haghifam, M.R. (2016). Optimal planning of hybrid renewable energy systems
using HOMER: A review. Renewable and Sustainable Energy Reviews, 62, pp. 609-620
Baghernejad, A., Yaghoubi, M., & Jafarpur, K. (2016). Exergoeconomic comparison of three novel
trigeneration systems using SOFC, biomass and solar energies. Applied Thermal Engineering, 104, pp.
534-555
Benson, S., & Orr, F. (2008). Sustainability and Energy Conversions. MRS Bulletin, 33(4), 297-302.
doi:10.1557/mrs2008.257
Bhattacharjee, S. & Dey, A. (2014). Techno-economic performance evaluation of grid integrated PV-
biomass hybrid power generation for rice mill. Sustainable Energy Technologies and Assessments, 7, pp.
6–16
Brandoni, C. & Renzi, M. (2015). Optimal sizing of hybrid solar micro-CHP systems for the household
sector. Applied Thermal Engineering, 75, pp. 896–907
Buonomano, A., Calise, F., Ferruzzi, G., & Vanoli, L. (2014). A novel renewable polygeneration system for
hospital buildings: Design, simulation, and thermo-economic optimization. Applied Thermal
Engineering, 67, pp. 43-60
Calise, F., Cipollina, A., d’Accadia, D.M., Piacentino, A. (2016). A novel renewable polygeneration system
for a small Mediterranean volcanic island for the combined production of energy and water:
Dynamic simulation and economic assessment. Applied Energy, 135, pp. 675–693
Cho, H., Smith, A., & Mago, P. (2014). Combined cooling, heating, and power: A review of performance
improvement and optimization. Applied Energy, 136, pp. 168-185
Chua, K.J., Yang, W.M., Er, S.S., & Ho, C.A. (2014). Sustainable energy systems for a remote island
community. Applied Energy, 113, pp. 1752–1763
-52-
Coronado, C., Yoshioka, J., Silveira, J. (2011). Electricity, hot water, and cold water production from
biomass. Energetic and economic analysis of the compact system of cogeneration run with wood
gas from a small downdraft gasifier. Renewable Energy, 36, pp. 1861–1868
Das, B. & Al-Abdeli, Y. (2017). Optimization of stand-alone hybrid CHP systems meeting electric and
heating loads. Energy Conversion and Management, 153, pp. 391-408
Ebeling, F. (2020). Assessing the macroeconomic effects of sustainable energy transitions in Costa Rica and
Chile: a multisectoral balance-of-payments-constrained growth approach. The Regulation and Policy of
Latin American Energy Transitions, 3, pp. 39-58. Doi: https://doi.org/10.1016/B978-0-12-819521-
5.00003-6
EEA. (2012). Available online: https://www.eea.europa.eu/data-and-maps/figures/greenhouse-gas-
emissions-intensity-per-gdp-for-eu-15-and-eu-27-and-their-member-states [Accessed 20 May 2020]
Electricity Map Org. (2020). Available online: https://www.electricitymap.org/zone/CR [Accessed 2
August 2020]
ENAHO. (2017). Encuesta Nacional de Hogares, INEC Costa Rica. Available online:
https://www.inec.cr/encuestas/encuesta-nacional-de-
hogares?keys=pobreza&at=All&prd=All&field_anio_documento_value%5Bvalue%5D%5Bdate
%5D= [Accessed 10 August 2020]
El Viejo Azucarera. (2020). Available online: http://www.azucareraelviejo.com/es/energia-electrica
[Accessed 11 July 2020]
European Commission. (2014). Energy Solutions for Smart Cities and Communities. Concerto Programme.
Stuttgart, Germany
European Commission. (2020). Photovoltaic Geographical Information System, Available online:
https://re.jrc.ec.europa.eu/pvg_tools/en/tools.html [Accessed 18 June 2020]
Food and Agriculture Organization of the United Nations, FAO. (2004). Rice and narrowing the yield gap,
FAO, Rome: http://www.fao.org/rice2004/en/f-sheet/factsheet5.pdf
Global Wind Atlas (2020). Wind resources around the world, Available online:
https://globalwindatlas.info/ [Accessed 18 June 2020]
Google Maps. (2020). Location of Costa Rica, Available online:
https://www.google.es/maps/@9.9625688,-85.7087741,12.56z [Accessed 17 June 2020]
Goldthau, A. (2014). Rethinking the governance of energy infrastructure: Scale, decentralization, and
polycentrism. Energy Research and Social Science, 1, pp. 134-140.
-53-
Hearne, R., Salinas, Z. (2001). The use of choice experiments in the analysis of tourist preferences for
ecotourism development in Costa Rica. Journal of Environmental Management, 65, pp. 153-163.
doi:10.1006/jema.2001.054
HOMER. (2020). HOMER Energy, Available online: https://www.homerenergy.com/index.html
[Accessed 16 June 2020]
Howard, G. & Bartran, J. (2003). Domestic Water Quantity, Service, Level and Health. World Health
Organization.
ICE. (2020). Tarifas Electricas, CNFL. Available online:
https://www.grupoice.com/wps/portal/ICE/Electricidad/servicios-elect/servicios-
empresariales [Accessed 27 March 2020]
ICE. (2020). Tarifas Electricas Actualizadas por situación Covid-19, CNFL. Available online:
https://www.grupoice.com/wps/wcm/connect/669c79e9-84c9-4682-b63b-
136238ebc7e2/Tarifas+actuales.pdf?MOD=AJPERES [Accessed 20 July 2020]
ICT. (2020). Instituto Costarricense de Turismo, Available online: https://www.ict.go.cr/es/noticias-
destacadas-2/1358-industria-tur%C3%ADstica-aporta-6,3-del-pib-a-la-econom%C3%ADa-de-
costa-rica.html [Accessed 10 April 2020]
ICT. (2019). Instituto Costarricense de Turismo, Available online: https://www.ict.go.cr/es/documentos-
institucionales/estad%C3%ADsticas/cifras-tur%C3%ADsticas/establecimientos-de-hospedaje-
bccr/927-2016-2019/file.html [Accessed 22 June 2020]
ICT. (2019). Instituto Costarricense de Turismo, Available online: https://www.ict.go.cr/es/documentos-
institucionales/estad%C3%ADsticas/cifras-tur%C3%ADsticas/oferta-de-hospedaje/1592-
cuadros-oferta-hospedaje-2019/file.html [Accessed 14 August 2020]
IEA. (2007). Biomass for Power Generation and CHP, IEA, Paris: https://www.iea.org/reports/biomass-
for-power-generation-and-chp
IEA. (2008). Combined heat and power: evaluating the benefits of greater global investment. IEA, Paris:
https://webstore.iea.org/combined-heat-and-power
IEA. (2017). Energy Access Outlook 2017, IEA, Paris: https://www.iea.org/reports/energy-access-
outlook-2017
IEA. (2019). World Energy Outlook 2019, IEA, Paris: https://www.iea.org/reports/world-energy-outlook-
2019
IHA. (2018). Hydropower Status Report, IHA, London:
https://www.hydropower.org/sites/default/files/publications/docs/iha_2018_hydropower_stat
us_report_4.pdf
-54-
IMN. (2018). Instituto Metereologico Nacional, Available online:
https://www.imn.ac.cr/documents/10179/20911/Uso+agr%C3%ADcola+de+pronostico+basa
do+en+ENOS/d27eb44c-96a5-4fae-8cdb-cb517f210739?version=1.0 [Accessed 17June 2020]
Instituto Costarricense de Electricidad, CENCE. (2019). Annual Energy Outlook 2019, ICE, San Jose:
https://apps.grupoice.com/CenceWeb/CenceDescargaArchivos.jsf?init=true&categoria=3&codi
goTipoArchivo=3008
Instituto Costarricense de Electricidad, CENCE. (2020). Monthly Energy Outlook March 2020, ICE, San
Jose:https://apps.grupoice.com/CenceWeb/CenceDescargaArchivos.jsf?init=true&categoria=3&
codigoTipoArchivo=3007
Intergovernmental Panel on Climate Change, IPPC. (2020). Renewable Energy Sources and Climate Change
Mitigation Chapter 2: Biomass. Available online: https://www.ipcc.ch/report/renewable-energy-
sources-and-climate-change-mitigation/bioenergy/ [Accessed 2 August 2020]
Intergovernmental Panel on Climate Change, IPPC. (2020). Renewable Energy Sources and Climate Change
Mitigation Chapter 5: Hydropower. Available online: https://www.ipcc.ch/report/renewable-
energy-sources-and-climate-change-mitigation/hydropower/ [Accessed 2 August 2020]
IRENA. (2020). Available online: https://www.irena.org/Statistics/View-Data-by-Topic/Innovation-and-
Technology/Patents-Evolution [Accessed 9 May 2020]
IRENA. (2020). Available online: https://www.irena.org/Statistics/View-Data-by-Topic/Capacity-and-
Generation/Statistics-Time-Series [Accessed 10 May 2020]
Karellas, S., Braimakis, K. (2016). Energy-exergy analysis and economic investigation of a cogeneration and
trigeneration ORC-VCC hybrid system utilizing biomass fuel and solar power. Energy Conversion and
Management, 107, pp. 103-113
Katsaprakakis, D. & Voumvoulakis, M. (2018). A hybrid power plant towards 100% energy autonomy for
the island of Sifnos, Greece. Energy, 161, pp. 680-698
Larios, G. (2010). La quema de la caña de azúcar en Guanacaste, impacto ambiental. Universidad de Costa
Rica. Available online: http://iij.ucr.ac.cr/wp-content/uploads/bsk-pdf-manager/2017/06/La-
Quema-de-la-Ca%C3%B1a-de-Az%C3%BAcar-en-Guanacaste-Impacto-Ambiental.pdf
[Accessed 7 August 2020]
MAG. (2018). Ministerio de Agricultura y Ganaderia, Desarrollo Region Chorotega, Available online:
http://www.mag.go.cr/regiones/chorotega/REGION-CHOROTEGA.pdf [Accessed 17 June
2020]
MAG. (2007). Ministerio de Agricultura y Ganaderia, Agrocadena de la caña de azúcar para la producción
de dulce, Available online: http://www.mag.go.cr/bibliotecavirtual/E70-10273.pdf [Accessed 13
July 2020]
-55-
Malmquist, A. (2018). Lecture 1: Polygeneration Concept, A General Overview, Power point presentation,
KTH, Retrieved 15 April 2020
Maraver, D., Sin, A., Royo, J., & Sebastian, F. (2013). Assessment of CCHP systems based on biomass
combustion for small-scale applications through a review of the technology and analysis of energy
efficiency parameters. Applied Energy, 102, pp. 1303-1313
Mathieu, P. & Dubuisson, R. (2002). Performance analysis of a biomass gasifier. Energy Conversion and
Management, 43, pp. 1921-1299
Matjanov, E. (2020). Gas turbine efficiency enhancement using absorption chiller. Case study for Tashkent
CHP. Energy, 192, 116625
Mertzis, D., Mitsakis, P., Tsiakmakis, S. Manara, P., Zabaniotou, A. & Samaras, Z. (2014). Performance
analysis of a small-scale combined heat and power system using agricultural biomass residues: The
SMARt-CHP demonstration project. Energy, 64, pp. 367-374
Meyer, E. & Mamphweli, N. (2010). Evaluation of the conversion efficiency of the 180 Nm3/h Johansson
Biomass Gasifier. International Journal of Energy and Environment, 1, pp.113-120
Mic, M. & Eagles, P. (2019). Cooperative branding for mid-range ecolodges: Costa Rica case study. Journal
of Outdoor Recreation and Tourism, 25, 113-121. Doi: https://doi.org/10.1016/j.jort.2017.12.001
MINAE. (2020). Ministerio de Ambiente y Energía, decreto 39220. Available online:
http://www.pgrweb.go.cr/scij/Busqueda/Normativa/Normas/nrm_texto_completo.aspx?param
1=NRTC&nValor1=1&nValor2=80310&nValor3=101897&strTipM=TC [Accessed 22 July 2020]
Moussawi, H., Fardoun, F., & Louahlia-Gualous, H. (2016). Review of Trigeneration Technologies: Design
evaluation, optimization, decision making and selection approach. Energy Conversion and Management,
120, pp. 157-196
OECD. (2018). OECD Economic Surveys: Costa Rica 2018. OECD, Paris:
http://www.oecd.org/economy/surveys/Costa-Rica-2018-OECD-economic-survey-
overview.pdf
OSINERGMIN. (2018). Available online: https://observatorio.osinergmin.gob.pe/tarifas-electricas-
industriales-comerciales-latinoamerica
Ossenbrink, H., Jäger-Waldau, A., Huld, T. & Taylor, N. (2012). New Opportunities for PV Systems. In
Proceedings of the 27th European Photovoltaic Solar Energy Conference and Exhibition,
Frankfurt, Germany
Perves, M., Bahar, R. & Ariff, T. (2016). Low Energy and Low-Cost Freshwater Production by Membrane
Distillation. Proceedings of the 2016 International Conference on Industrial Engineering and
Operations Management. Kuala Lumpur, Malaysia
-56-
Ram, M., Bogdanov, D., Aghahosseini, A., Gulagi, A., Oyewo, A.S., Child, M., Caldera, U., Sadovskaia, K.,
Farfan, J., Barbosa, LSNS., Fasihi, M., Khalili, S., Dalheimer, B., Gruber, G., Traber, T., De Caluwe,
F., Fell, H.-J., Breyer, C. (2019). Global Energy System based on 100% Renewable Energy – Power,
Heat, Transport and Desalination Sectors. Study by Lappeenranta University of Technology and
Energy Watch Group, Berlin.
Rubio-Maya, C., Uche-Marcuello, J., Martinez-Gracia, A. & Bayod-Rujula, A. (2011). Design optimization
of a polygeneration plant fueled by natural gas and renewable energy sources. Applied Energy, 88,
pp. 449-457
Rong, A., & Su, Y. (2017). Polygeneration system in buildings: A survey on optimization approaches. Energy
and Buildings, 151, pp. 439-454
Rosen, M. (2009). Energy Sustainability: A Pragmatic Approach and Illustrations. Sustainability Journal, 1, pp.
55-80. doi:10.3390/su1010055
Rubio-Maya, C., Uche-Marcuello, J., & Martinez-Gracia, A. (2011). Sequential optimization of a
polygeneration plant. Energy Conversion and Management, 52, pp. 2861-2869
Rubio-Maya, C., Uche-Marcuello, J., Martinez-Gracia, A. & Bayod-Rujula, A. (2011). Design optimization
of a polygeneration plant fuelled by natural gas and renewable energy sources. Applied Energy, 88,
pp. 449-457
Sathaye, J., Lucon O., Rahman, A., Christensen, J., Denton, F., Fujino, J., Heath, G., Kadner, S., Mirza, M.,
Rudnick, H., Schlaepfer, A., Shmakin, A. (2011). Renewable Energy in the Context of Sustainable
Development. In IPCC Special Report on Renewable Energy Sources and Climate Change
Mitigation, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA
Shukla, A. & Kumar, S. (2017). A comparative study of Sugarcane Bagasse gasification and Direct
Combustion. International Journal of Applied Engineering Research, 12, pp.14739-14745
Sigarchian, S., Paleta, R., Malmquist, A. & Pina, A. (2015). Feasibility study of using a biogas engine as
backup in a decentralized hybrid (PV/wind/battery) power generation system—Case study Kenya.
Energy, 90, pp. 1830–1841
Sims, R., Schock R., Adegbululgbe, A., Fenhann, J., Konstantinaviciute I. (2007). Energy supply. In Climate
Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of
the Intergovernmental Panel on Climate Change, 252-322. Cambridge University Press.
https://doi.org/10.1017/CBO9780511546013.008
Singal, S.K. & Singh, R.P. (2007). Rural electrification of remote island by renewable energy sources.
Renewable Energy, 32, pp. 2491-2501
Smith, S., Tolstorebrov, I. & Hafner, A. (2020). Integrated CO2 system with HVAC and hot water for hotels:
Field measurements and performance evaluation. International Journal of Refrigeration, 116, pp. 59-69
-57-
Solomon, B. & Krishna, Ka. (2011). The coming sustainable energy transition: History, strategies, and
outlook. Energy Policy, 39, pp. 7422-7431
Stanek, W., Gazda, W., & Kostowski, W. (2015). Thermo-ecological assessment of CCHP plant supported
with renewable energy. Energy, 92, 279-289
TSP. (2018). Breakdown of Electricity Generation by Energy Source. Available online: http://www.tsp-
data-portal.org/Breakdown-of-Electricity-Generation-by-Energy-Source#tspQvChart [Accessed
21 May 2020]
Ullah, R., Khraisheh, M., Esteves, R., McLeskey, J., AlGhouti, M., Gad-el-Hak, M & Vhaedi, H. Energy
efficiency of direct contact membrane distillation. Desalination, 433, pp. 56-67
UNWTO. (2020). United Nation World Tourism Organization, Available Online:
https://www.unwto.org/hotel-energy-solution [Accessed 30 April 2020]
United Nations. (2018). Policy Brief #24 Energy Sector Transformation: Decentralized Renewable Energy
for Universal Energy Access, Germany:
https://sustainabledevelopment.un.org/content/documents/17589PB24.pdf
United Nations. (2020). Sustainable Development Goals Report. Available online:
https://www.un.org/sustainabledevelopment/progress-report/ [Accessed 08 August 2020]
VanCleef, Ali. (2016). Hydropower Development and Involuntary Displacement: Toward a Global
Solution. Indiana Journal of Global Legal Studies, 23, article 15
Villaroel-Schneider, J., Mainali, B., Marti-Herrero, J., Malmquist, A., Martin, A. & Alejo, L. (2020). Biogas
based polygeneration plant options utilizing dairy farm waste: A Bolivian case. Sustainable Energy
Technologies and Assessments, 37, 100571
Visit Costa Rica. (2020). Available online: https://www.visitcostarica.com/en/costa-rica/things-to-
do/ecoturism/national-parks [Accessed 10 April 2020]
Wang, J., Yang, Y., Mao, T., Sui, J., & Jin, H. (2015). Life cycle assessment (LCA) optimization of solar-
assisted hybrid CCHP system. Applied Energy, 146, pp. 38–52
Wegener, Moritz., Isalgue, A., Malmquist, A. & Martin, A. (2019). Analysis of a Bio-Solar CCHP System for
the Andaman Islands, India-A Case Study. Energies, 12, 1113. doi:10.3390/en12061113
World Bank. (2017). Regulatory indicators for sustainable energy: a global scorecard for policymakers,
Washington, D.C.: https://www.icsu.org/cms/2017/05/SDGs-Guide-to-Interactions.pdf
Worldwide Ecolodges. (2017). Ecolodge Types and Definitions, Available online:
http://worldwideecolodges.com/wp/ecolodge-exp-2 [Accessed 2 May 2020]
Wu, D.W., & Wang, R.Z. (2006). Combined cooling, heating, and power: A review. Progress in Energy and
Combustion Science, 32, pp. 459-495
-58-
Yang, G., & Zhai, X. (2019). Optimal design and performance analysis of solar hybrid CCHP system
considering influence of building type and climate conditions. Energy, 174, pp. 647-663
Yoo, K., Park, E., Kim, H., Ohm, J., Yang, T., Kim, K., Chang, H. & del Pobil, A. (2014) Optimized
Renewable and Sustainable Electricity Generation Systems for Ulleungdo Island in South Korea.
Sustainability, 6, pp.7883–7893
Yousefi, H., Ghodusinejad, M., & Noorollahi, Y. (2017). GA/AHP-based optimal design of a hybrid CCHP
system considering economy, energy, and emission. Energy and Buildings, 138, pp. 309-317
-59-
Appendix A- HOMER configurations and results
Figure 38. Location selection for case study in HOMER pro
Figure 39. System Schematic of Proposed System in HOMER Pro
Figure 40. NPC calculated by HOMER Pro for Proposed System
-60-
Figure 41. System Schematic of Grid Case in HOMER Pro
Figure 42. NPC calculated by HOMER Pro for Grid Case
Figure 43. System Schematic of Grid Case with Covid-19 prices in HOMER Pro
Figure 44. NPC calculated by HOMER Pro for Grid Case with Covid-19 prices
Figure 45. System Schematic of Only Biomass Case in HOMER Pro
-61-
Figure 46. NPC calculated by HOMER Pro for Only Biomass Case
Figure 47. System Schematic of Only PV Case in HOMER Pro
Figure 48. NPC calculated by HOMER Pro for Only PV Case
Figure 49. System Schematic of System with Wind Turbines Case in HOMER Pro
-62-
Figure 50. NPC calculated by HOMER Pro for System with Wind Turbines Case
