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Oviedo, 27 February 2014
Paolo Michele Sonvilla
Minerva Consulting & Communication
Ahorros energéticos obtenidos con el EnRima DSS
An Integrated Approach to Optimal Energy
Operations in Buildings
P. Rocha1 M. Groissböck2 A. Siddiqui1,3 M. Stadler2
1University College London
2Center for Energy and Innovative Technologies
3Stockholm University
e-nova 2013 Conference,
15 November 2013
Background
EU policy objectives for year 2020 include:• ↓ greenhouse gas emissions by ≥ 20% below 1990 levels• ↑ contribution of renewable resources to EU energy consumption
to 20%• ↓ primary energy use by 20% relative to projections
=⇒ energy efficiency ofexisting buildingsmust be improved
Background
Multiple objectives & combinations of resource-load pairs=⇒ operational optimisation model (Hobbs, 1995)
Decision Support Schema
Lower-Level Operational Module1
• Determines operation of heating, ventilation & cooling systems given:
• thermodynamics of conventional heating & HVAC systems• building’s physics• external temperatures & solar gains• internal loads
• Range for zone temperature =⇒ endogenous space heat & coolingdemand
1Groissböck et al. (2013), Liang et al. (2012)
Upper-Level Operational Module
• Determines sourcing of energy & operation of installed equipment
• Upper-level constraints:• Energy balance equation:
EnergyPurchased − EnergySold + EnergyOutput − EnergyInput +EnergyFromStorage − EnergyToStorage = Demand
• Technology capacity limits
• Energy trading limits
• Energy storage constraints
• King and Morgan (2007), Marnay et al. (2008), Stadler et al. (2012),Pruitt et al. (2013)
Integrated Operational OptimisationModel
minimise Energy trading costs + technology operation costs
subject to Upper-level constraints:Energy balanceTechnology capacity limitsEnergy trading limitsStorage constraints
Lower-level constraints:Zone temperature update & boundsEnergy flows & operational constraints for radiatorsEnergy flows & operational constraints for HVAC systems
Numerical Examples• Two test sites:
• Centro de Adultos La Arboleya (Siero, Spain), from FundaciónAsturiana de Atención y Protección a Personas conDiscapacidades y/o Dependencias (FASAD)
• Fachhochschule Burgenland’s Pinkafeld campus (Pinkafeld,
Austria)
• Typical winter day, hourly decision intervals
• Cases:• FMT: Fixed mean temperature• OPT: Optimisation
Operating Scenarios for FASAD
• Scenario 1 (Baseline):• Conventional heating and natural ventilation• 1293.3 kW and 232.6 kW natural gas-fired boilers, 5.5 kWe CHP
unit• Exogenous daily end-use electricity demand of 691 kWhe and
domestic hot water demand of 1592 kWh• Flat energy tariff rates: 0.14 e/kWhe for electricity purchases, 0.05e/kWh for natural gas purchases
• Electricity feed-in tariff (FiT) of 0.18 e/kWhe
• Scenario 2: Revocation of FiT
• Scenario 3: Regulation imposes that zone temperature ≤ 21◦C
• Scenario 4: Installation of a 7.58 kW solar thermal system
FASAD’s ResultsScenarios 1, 2 and 4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
FMT
Time (h)
Tem
pera
ture
(o C)
Estimated Zone Temperature = Required Zone TemperatureExternal Temperature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
1012141618202224262830
OPT
Time (h)
Tem
pera
ture
(o C)
Lower Limit TemperatureOptimal Zone TemperatureUpper Limit TemperatureExternal Temperature
FASAD’s Results
FMT OPTSpace Heat Cost CO2 Space Heat Cost CO2
Demand Emissions Demand Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 1,2,4 700 42 154 494 30 108-29% -29% -30%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
10
20
30
40
50
60
70
80
90
100Space Heat Demand
Time (h)
Spac
e He
at D
eman
d (k
Wh)
FMTOPT
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8Natural Ventilation
Time (h)
Natu
ral V
entila
tion
(m3 /s
)
FMTOPT
FASAD’s Results
FMT OPTSpace Heat Cost CO2 Space Heat Cost CO2
Demand Emissions Demand Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 3 558 34 123 474 29 104-15% -15% -15%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
FMT
Time (h)
Tem
pera
ture
(o C)
Estimated Zone Temperature = Required Zone TemperatureExternal Temperature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
1012141618202224262830
OPT
Time (h)
Tem
pera
ture
(o C)
Lower Limit TemperatureOptimal Zone TemperatureUpper Limit TemperatureExternal Temperature
FASAD’s Results
FMT OPTPrimary Cost CO2 Primary Cost CO2Energy Emissions Energy Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 1 4071.0 213.7 809.9 3847.9 202.0 764.9-5.5% -5.5% -5.5%
Scen. 2 3798.8 218.0 757.3 3576.1 206.4 712.3-5.9% -5.3% -6%
Scen. 3 3917.3 205.6 778.9 3827.2 200.9 760.7-2.3% -2.3% -2.3%
Scen. 4 4019.6 211.0 799.5 3796.6 199.3 754.5-5.5% -5.5% -5.6%
Operating Scenarios for Pinkafeld
• Scenario 1 (Baseline):• Heating and HVAC systems• 1.28 kWp PV system• Exogenous daily end-use electricity demand of 543 kWhe
• Flat energy tariff rates: 0.15 e/kWhe for electricity purchases, 0.08e/kWhe for electricity sales, 0.08 e/kWh for district heat purchases
• Scenario 2: Installation of a 100 kWp PV system & availability of anelectricity FiT (0.18 e/kWhe)
• Scenario 3: Change to a time-of-use (TOU) electricity purchasing tariff(0.16 e/kWhe at 7:00-14:00 and 17:00-20:00, 0.15 e/kWhe at14:00-17:00, 0.14 e/kWhe otherwise)
• Scenario 4: Installation of a 75 kW solar thermal system
Pinkafeld’s Results
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
FMT
Time (h)
Tem
pera
ture
(o C)
Estimated Zone Temperature = Required Zone TemperatureExternal Temperature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
OPT
Time (h)
Tem
pera
ture
(o C)
Lower Limit TemperatureOptimal Zone Temperature, Scenarios 1−3Optimal Zone Temperature, Scenario 4Upper Limit Temperature
Pinkafeld’s ResultsFMT OPT
Space HVAC Cost CO2 Space HVAC Cost CO2Heat Elec. Emis- Heat Elec. Emis-
Demand Demand sions Demand Demand sions(kWh) (kWhe) (e) (kg) (kWh) (kWhe) (e) (kg)
Scen. 1–3 696 5.73 55.9 20.9 629 3.64 50.5 18.9-10% -37% -10% -10%
Scen. 4 696 5.73 53.7 20.1 644 3.91 48.8 18.2-7.5% -38% -9% -9%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
10
20
30
40
50
60
70
80
90
100Space Heat Demand
Time (h)
Spac
e He
at D
eman
d (k
Wh)
FMTOPT, Scenarios 1−3OPT, Scenario 4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
0.5
1
1.5
2
2.5
3HVAC Ventilation
Time (h)
HVAC
Ven
tilatio
n (m
3 /s)
FMTOPT, Scenarios 1−3OPT, Scenario 4
Pinkafeld’s Results
FMT OPTPrimary Cost CO2 Primary Cost CO2Energy Emissions Energy Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 1 1987.5 137.9 29.5 1851.2 132.2 27.5-6.9% -4.1% -6.8%
Scen. 2 1989.4 113.0 29.6 1853.1 107.3 27.5-6.9% -5.1% -7.1%
Scen. 3 1987.5 139.4 29.5 1851.2 133.7 27.5-6.9% -4.1% -6.8%
Scen. 4 1933.3 135.7 28.7 1808.8 130.5 26.9-6.5% -3.9% -6.3%
Summary
• Short-term building energy management model consisting ofupper- and lower-level operational modules
• Evaluated using data from two EU test sites and plausible futureoperating scenarios
• 10-30% ↓ space heat demand and associated CO2 emissions
• 5-7% ↓ overall primary energy consumption
• Reflects load-shifting behaviour
• Future work:
• Multi-criteria objective function
• Further policy insights