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ABSTRACT
Nowadays there is a great interest for the use of microturbines as sources of
distributed generation, particularly in areas where demand is both electricity and heat. In
these areas microturbines reach very high efficiency rates.
Microturbines can operate both stand-alone and grid connected. The second one
of the mentioned possibilities is which deserves a much deeper study, to analyse the
interaction of the microturbine with the distribution network it is connected to.
This project deals with the theory, modeling, simulation, mathematical analyses
and analysis of load following behavior of a micro turbine (MT) as a distributed energy
resource (DER).
In this project a dynamic model of a microturbine is developed with
Matlab/Simulink/Sim power systems. The model has been included The model has been
mathematical verified and several dynamic simulations have been performed to study the
response to step changes in the power control references. Also, the performance of the
microturbine to faults in the network has been analyzed.
Index Terms:
Distributed energy resources (DERs), load following Performance, micro turbine
(MT), recuperator, speed control, Synchronous generator (SG), Dynamic model.
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
INTRODUCTION
DISTRIBUTED energy resources (DERs) are a variety of small-scale, modular
distributed generation (DG) technologies that can be combined with energy management
and storage systems. DERs have received significant attention as a means to improve the
performance and reliability of electrical power system. They can provide low-cost energy
and increase energy efficiency through combined heat and power (CHP) mode of
operation. Moreover, their application can also reduce transmission and distribution
(T&D) losses, relieve T&D assets, reduce constraints, and improve overall power quality
and reliability. Literature review shows that there is extensive thrust on the application of
MT for DG. Research areas include simulation, offline/real-time studies, and
development of inverter interfaces for MT applications. Peirs et al. Report the
development of a single-stage axial flow MT for power generation. Nichols and Loving
highlight the facilities of MT technology through relevant test results.Suter reports the
development of an active filter for MT operations.Jurado and Saenz describe an adaptive
control mechanism of a hybrid power system with fuel cell and MT.Gaonkar and
coworkers demonstrate a simulation model developed from the dynamics of each part of
the MT and discuss its operation in islanded and grid-connected modes
Most MT’s use a permanent-magnet synchronous generator (PMSG) or
asynchronous generator for power generation. The system model in considers
bidirectional power flow between the grid and MT system using PMSG.PMSG is also
used in and the operation of MT is considered in islanded connected mode. However,
very little is reported on development and load following performance analysis of MT
models with a synchronous generator (SG) in islanded connected mode. This area needs
to be extensively investigated to resolve the technical issues for integrated operation of an
MT with the utility grid.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
In this project, we describe the modeling and simulation of an MT–generator
(MTG) system consisting of an MT coupled with an SG followed by its load
following performance analysis. We have analyzed the performance in islanded
connected mode. Simulation is done in MATLAB–Simulink platform. Simulation results
have been compared with other existing results as well as typical real MT data. The
proposed model is also suitable for studying the dynamic behavior of the MTG system
connected with other types of DG in micro grid and grid applications.
1.1 Background
Nowadays, the need of energy production to be used for either industrial or
several transportations is in great demand. The type of power generation has become the
major concern because of its widespread need. For the concern of recent time needs, the
suitable power generation type is one which achieves a relatively better efficiency, low
in cost, and satisfied the demanding criteria.
For those needs the gas turbine system is the answer. Gas turbines are internal
combustion engines that they use a rotating shaft or rotor instead of "reciprocating" in
cylinders. It has the advantages of small dimensions, light weight, easy to be serviced
(resulting to low maintenance cost), and most of all it can produce more power (relative
to the power produced-to-weight ratio) and faster speed spin. They became practical sixty
years ago; today gas turbines are one of the keystone technologies of the civilization.
Because of its critical role, it is understandable that innovation to a step further
is needed. In a field where the major role needed and development costs both 2 are the
major concerns, it was thought to build the smallest possible gas turbine, and to explore
whether the device could be made into smaller size. The microturbine is actually the
scale-down of the large ordinary gas turbine system.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
This is what gave birth to this project – since the advantages of gas turbines are
already known compare to the others, in this thesis, I have simulated gas based
microturbine and analyzed its performance for different loads. The behavior of torque and
speed for slow dynamic conditions is care fully examined. Also I have connected the MT
generator to low voltage and high voltage grids. Analysis is made for voltages and currents
at different points in the networks in the event of faults.
1.3. Objective of Study
The objective of this study to simulated gas based microturbine and analyzed its
performance for different loads. The behavior of torque and speed for slow dynamic
conditions is care fully examined. Also I have connected the MT generator to low voltage
grid with and with out fault. Analysis is made for voltages and currents in the networks in
the event of faults.
1.4 Outline of Report
This project is divided into ten chapters.
Chapter 1 presents the Introduction, the background of the study, which gave
birth to this project. It also covers the objective of study, and this project’s outline report.
Chapter 2 describes the literature review of the project.
Chapter 3 describes the Generally, the term Distributed or Distributed Generation
refers to any electric power production technology that is integrated within distribution
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
systems, close to the point of use. Distributed generators are connected to the high
voltage or low voltage grid
Chapter 4 discussed a number of micro turbines generators have recently been
announced as currently commercially available for sale to customers, such as end
users, utilities, and energy service providers. Manufacturers and others are reporting
certain performance capabilities of the turbines; however, no consistent third-party
independent testing as been done to confirm or discredit such performance claims
Chapter 5 discussed a gas turbine is a rotating engine that extracts energy from a
flow of combustion gases that result from the ignition of compressed air and a fuel
(either a gas or liquid, most commonly natural gas). It has an upstream compressor
module coupled to a downstream turbine module, and a combustion chamber(s)
module in between.
On chapter 6 discussed a Micro turbines are small high-speed gas turbines. The
three main components of a micro turbine are compressor, combustor, and the turbine.
The compressor is used to pressurize the air before entering the combustor. Injected fuel
is mixed with the compressed air in the combustor and the mixture is ignited.
Mechanical energy is produced when the hot combustion gases flow and expand
through the turbine. The turbine drives a synchronous generator.
On chapter 7 discussed the microturbine model description. Usually, an MT
consists of turbine, synchronous machine, power electronics, recuperator, control and
communication. And also discussed mt, controller, turbine model and parameters of all
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
models used in this project.
On chapter 8 discussed the simulation model for MT model and Simulation
Results of Islanded mode and connected to fault.
On chapter 9 discussed the Mathematical analysis of micro turbine.
In this project, modeling and simulation of MT coupled with SG are performed
and reported. Its load following performance is thoroughly tested and validated for
different operating conditions, with and without speed controllers. The model has been
simulated working in grid connected mode and different operation conditions have been
analysed (Step change, fault,…). The simulation results have showed that the
microturbine works properly connected to a low voltage distribution grid.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
LITERATURE REVIEW
Nowadays there is a great interest for the use of microturbines as sources of
distributed generation, particularly in areas where demand is both electricity and heat.
This project deals with the theory, modeling, simulation, and analysis of load following
behavior of a micro turbine (MT) as a distributed energy resource (DER). In these areas
microturbines reach very high efficiency rates. Also, the performance of the microturbine
to faults in the network has been analysed. In this project a dynamic model of a
microturbine is developed with Matlab/Simulink/Sim power systems.
A Development of models for analyzing the load-following performance of
microturbines and fuel cells, Y. Zhu, K. Tomsovic, [1] presents Deregulation has begun
to allow for the provision of various ancillary services, such as load-following. This
paper presents simplified slow dynamic models for microturbines and fuel cells. Their
stand-alone dynamic performances are analyzed and evaluated. A distribution system
embedded with a microturbine plant and an integrated fuel cell power plant is used as an
example. The control strategy and load-following service in this distribution system are
simulated. It is illustrated that microturbines and fuel cells are capable of providing load-
following service, significantly enhancing their economic value. a simplified slow
dynamic model of a split-shaft microturbines is developed.
A Dynamic model of microturbine generation system for grid connected/islanding
operation, D. N. Gaonkar, R. N. Patel, and G. N. Pillai. [2] presents the performance of
microturbine generation systems their efficient modeling is required. This paper presents
a dynamic model of a MTG system, suitable for grid connection/islanding operation. The
presented model allows the bidirectional power flow between grid and MTG system. The
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
components of the system are built from the dynamics of each part with their
interconnections. At first the mathematical modeling of the microturbine along with the
control systems is given and following that the detailed simulation model of the MTG
system is developed using MATLAB's SimPowerSystems library. The simulation results
demonstrate that the established model provides a useful tool suitable to study and to
perform accurate analysis of most electrical phenomena that occur when a micro turbine
is connected to the grid or is operated in islanded mode. The simulation results show that
the developed model of the MTG system has the ability to adjust the supply as per the
power requirements of the load within MTG's rating.
A Modeling and Performance Analysis of a Microturbine as a Distributed Energy
Resource, A. K. Saha, [3] presents modeling, simulation, and analysis of load following
behavior of a microturbine (MT) as a distributed energy resource (DER). The MTG
model also incorporates a speed controller for maintaining constant speed at variable
loads. Performance is studied both with and without the speed controller. The paper also
compares the simulation results with already reported results and with real life load
following data for a typical islanded MT of similar rating. modeling and simulation of
MT coupled with SG are performed and reported for both islanded and gridconnected
modes of operation. The results are compared with already reported results and with
typical real life load following data for a similar system in islanded mode. This model is
quite useful for studying the dynamic performances of MTs in microgrid and hybrid
power system environment.
A Novel Power Conversion System for Distributed Energy Resources, R. Esmaili
et, al., [4] presents a novel approach to developing a power conversion system (PCS) for
Distributed Energy Resources (DER). Many DER require the use of a PCS to develop
useable electricity from an energy source. The paper discusses various aspects of the
design including inverter topology, power, control and power supply circuit designs,
switching and protection equipment and thermal considerations. Experimental and
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
analytical results indicate that losses associated with a three-level inverter topology are
compatible with design concepts. Immersing the power circuit in transformer oil can
dissipate the heat generated by a three-level inverter, when utilizing a heat sink designed
by Heat Technology Inc. to optimize heat transfer.
A Modeling and Simulation of the Electric Part of a Grid Connected Micro
Turbine, O. Fethi, L.-A. Dessaint, [5] presents a simulation model of the electric part of a
grid connected micro turbine (MT). The simulation results obtained with the model using
Sim Power Systems software were compared with experimental results obtained with a
Capstone 30 kW micro turbine. The simulation results demonstrate that the established
model provides a useful tool suitable to study and to perform accurate analysis of most
electrical phenomenon that occurs when a micro turbine is connected to the grid. The
model has been validated through several experiments preformed on a 30 kW Capstone
unit. The simulation results obtained for utility voltage unbalances as well as for utility
voltage distortions show the usefulness of the model and its accuracy.
An Assessment of Microturbine Generators, D. K. Nichols and Kevin P. Loving,
[6] discusses microturbine technology , those facilities and present test results.
Microturbine generators hold promise to efficiently meet energy demand while lowering
associated environmental impact. As with any new technology, application of the
technology will occur only after thorough assessment and demonstration , To accomplish
that assessment test facilities have heen developed to assess performance, system
compatibility , and efiiciency and emission issues.
Adaptive Control of a Fuel Cell-Microturbine Hybrid Power Plant, Francisco
Jurado, and José Ramón Saenz, [7] presents The composition of natural gas may vary
significantly, and load power varies randomly. Traditional control design approaches
consider a fixed operating point in the hope that the resulting controller is robust enough
to stabilize the system for different operating conditions. An adaptive minimum variance
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
controller is developed in this paper. Conventional control depends on the mathematical
model of the plant being controlled. This paper develops the control system with an
adaptive minimum variance controller and based on the simulation study, the resulting
controller is robust enough to stabilize the system for different disturbances affecting the
plant (load power variation) or a change in the plant model parameters (gas composition).
Dynamic Performance of a Microturbine Connected to a Low Voltage Network,
E. Torres1 et,al., [8] presents a dynamic model of a microturbine is developed with
Matlab/Simulink/Simpowersystems. The model has been included within a low voltage
network model and several dynamic simulations have been performed to study the
response to step changes in the power control references. The model has been simulated
working in grid connected mode and different operation conditions have been analysed
(Step change, fault,…). The simulation results have showed that the microturbine works
properly connected to a low voltage distribution grid. Next developments in this field will
be the improvement and optimization of the microturbine model as well as the analysis of
multiple operation conditions, mainly related to different fault situations and the
definition of the settings of protection relays.
A Simulink-Based Microturbine Model for Distributed Generation Studies,
Sreedhar R. Guda, C. Wang, [9] presents the modeling and simulation of a microturbine
generation system suitable for isolated as well as grid-connected operation. The system
comprises of a permanent magnet synchronous generator driven by a microturbine.
Simulation studies have been carried out in MATLAB/Simulink under different load
conditions. The modeling of a single-shaft microturbine generation system suitable for
power management in DG applications is presented in this paper. Simulation results show
that the developed model has the ability to meet the requirements of the load, maintaining
prescribed values of voltage and frequency with the help of the power electronic controls.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Modeling and Performance Analysis of a Microturbine as a Distributed Energy
Resource, A. K. Saha, [10] presents modeling, simulation, and analysis of load following
behavior of a microturbine (MT) as a distributed energy resource (DER). The MTG
model also incorporates a speed controller for maintaining constant speed at variable
loads. Performance is studied both with and without the speed controller. The paper also
compares the simulation results with already reported results and with real life load
following data for a typical islanded MT of similar rating. The results are compared with
already reported results and with typical real life load following data for a similar system
in islanded mode. This model is quite useful for studying the dynamic performances of
MTs in microgrid and hybrid power system environment.
An Educational Guide to Extract the Parameters of Heavy Duty Gas Turbines
Model in Dynamic Studies Based on Operational Data, Mohammad Reza Bank Tavakoli
et, al., [11] presents of Rowen’s model for heavy duty gas turbines in dynamic studies are
estimated by use of available operational and performance data. The way of obtaining the
parameters and sole physical laws are explained to some extents to make it useful for
students of electrical engineering and trainers who are involved in dynamic studies. The
paper provides background knowledge for the students who want to know more about the
building blocks of HDGT dynamic model. Among a lot of parameters and data which are
provided by manufacturer, the useful and most straight forward ones for deriving the
model parameters are used here which can be invoked in any similar case.
Pwm inverters in decentralized generation systems: characterization of the
dynamic behavior under utility fault conditions, S. Nguefeu et,al., [12] presents the
concept of dispersed generation and its impact on the utility distribution network,
focusing on four energy sources : solar energy, fuel cells, wind power and micro turbines.
Specific models for each type of source as well as coupling interfaces are developed.
Finally, an example of the utilization of the models is given : it shows the simulation
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
results obtained in the micro turbine case for a few faults occurring on the utility low
voltage grid.
In this thesis, I have simulated gas based microturbine and analyzed its performance
for different loads. The behavior of torque and speed for slow dynamic conditions is care
fully examined. Also I have connected the MT generator to low voltage grid. Analysis is
made for voltages and currents at different points in the networks in the event of faults.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
DISTRIBUTED ENERGY RESOURCES (DER)
3.1Distributed Generation Background
Generally, the term Distributed or Distributed Generation refers to any electric
power production technology that is integrated within distribution systems, close to the
point of use. Distributed generators are connected to the medium or low voltage grid.
They are not centrally planned and they are typically smaller than 30 MWe (DTI 2001).
The concept of DG contrasts with the traditional centralised power generation concept,
where the electricity is generated in large power stations and is transmitted to the end
users through transmission and distributions lines (see figure 1.1). While central power
systems remain critical to the global energy supply, their flexibility to adjust to changing
energy needs is limited. Central power is composed of large capital-intensive plants and a
transmission and distribution (T&D) grid to disperse electricity. A distributed electricity
system is one in which small and micro generators are connected directly to factories,
offices, and households and to lower voltage distribution networks. Electricity not
demanded by the directly connected customers is fed into the active distribution network
to meet demand elsewhere. Electricity storage systems may be utilised to store any excess
generation.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Figure 3-1. An electric power system
Large power stations and large-scale renewable, e.g. offshore wind remain
connected to the high voltage transmission network providing national back up and
ensure quality of supply. Again, storage may be utilised to accommodate the variable
output of some forms of generation. Such a distributed electricity system is represented in
figure 1-2 below.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Figure 3-2. A Distributed Electricity System
The non-traditional operating model of DG has drawn strong interest
because of its potential to cost effectively increase system capacity while meeting the
industry restructuring objective of market driven, customer-oriented solutions. These
distributed generation systems, capable of operating on a broad range of gas fuels, offer
clean, efficient, reliable, and flexible on-site power alternatives. This emerging portfolio
of distributed generation options being offered by energy service companies and
independent power producers is changing the way customers view energy.
Both options require significant investments of time and money to increase
capacity. Distributed generation complements central power by providing in many cases
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
a relatively low capital cost response to incremental increases in power demand, avoiding
T&D capacity upgrades by where it is most needed, and having the flexibility to put
power back into the grid at user sites. Significant technological advances through
decades of intensive research have yielded major improvements in the economic,
operational, and environmental performance of small, modular gas-fuelled power
generation options. Forecasts predict a total 520GW from newly installed DG around the
globe by 2030.
3.2 Advantages of DER:
DERs have received significant attention as a means to improve the
performance and reliability of electrical power system. They can provide low-cost energy
and increase energy efficiency through combined heat and power (CHP) mode of
operation. Moreover, their application can also reduce transmission and distribution (T&D)
losses, relieve T&D assets, reduce constraints, and improve overall power quality and
reliability.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 3.3 distributed energy resources
3.2 Small Distributed Generation Technologies:
Recent DER technologies include micro turbine (MT), fuel cells, photovoltaic,
wind energy, Solar Thermal, Small Reciprocating Engines etc. Under the current electric
utility restructuring and public environmental policy, there is ample scope for large-
scale integration of DERs into utility grid distribution system .
Micro turbines:
Micro turbines are composed of a generator and small gas turbine
mounted on a single shaft. The turbine technology is based on a refinement of automotive
turbo chargers and military engines. Micro turbines rotate at high speeds, some at nearly
100,000 rpm. A permanent magnet generator spinning at this high shaft speed produces
the power in the form of high-frequency AC, which is converted to DC and then to
standard 60-Hz AC using an inverter. Most micro turbines are fueled by natural gas but
can also use liquid fuels such as diesel or jet fuel. These units currently range in size from
30 to about 100 kW; larger units are under development. Most micro turbines also have a
recuperator to recycle some exhaust heat back to the combustor. A micro turbine with
recuperator typically has 20-30 percent efficiency. Utilization of waste heat can increase
overall system efficiency (electricity and heat) to 70- 80 percent. Because the combustion
process is closely controlled and relies on relatively clean burning fuels, micro turbines
typically produce few emissions
Fuel Cells:
A number of fuel cell technologies are either under development or
currently being used to generate power. The attraction of fuel cells is their potential for
highly efficient conversion to electrical power (35 to 55 percent without heat recovery).
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
The only technology in general use today is the phosphoric acid fuel cell, which is
available in the 200-kW size range. This fuel cell operates at about 40 percent conversion
efficiency. Because this device operates at 400 degrees F, waste heat is available as
steam, which boosts the overall fuel conversion efficiency. A number of other fuel cell
technologies are being developed. For the power industry, these include: proton exchange
membrane (low-temperature, hydrogen fueled), molten carbonate (high- temperature),
and solid oxide (high-temperature).
Photovoltaic Cells:
Photovoltaic (PV) devices have been in existence for many years since
their early use in the U.S. space program. They rely on sunlight to produce DC voltage at
cell terminals. The amounts of voltage and current that PV cells can produce depend on
the intensity of sunlight and the design of the cell. PV systems use cell arrays that are
either fixed or track the sun to capture additional energy. Because solar energy is a
diffuse resource, it takes a large area of PV cells to produce significant power. At a
typical cell conversion efficiency of 10 percent, about 10 m2 of panels are needed to
provide a peak power of 1 kW. To reduce the number of costly PV devices used, mirrors
or lenses can be used to concentrate sunlight on to the cells. This increases the PV cell
output but requires tracking devices to insure that the array is aligned with the sun.
Solar Thermal:
Although there are a number of large-scale (several-megawatt) generation
technologies in the solar thermal field, the main technology for small-scale generation is
the sterling dish. This technology is being tested in the 10- to 25-kW range. In this
system, light is concentrated on a small receiver by a sun-tracking array of mirrors. The
heat collected by the receiver is transferred to the hot end of a sterling engine. The
sterling engine uses working fluid in a closed cycle to push pistons and generate shaft
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
rotation. In a sterling dish, shaft rotation is used to spin an induction generator that is
connected to the electric grid.
Wind:
Wind generation has been commercially available for many years. The main push
has been in large wind farms where wind turbines from 700 kW to 1.5 MW are available
and in use. Several smaller wind turbines (<250 kW) are available for use in MicroGrids.
These machines typically use an induction generator driven by a rotor with blades. As is
true for the solar options, the wind generators’ power output is determined by the
availability of their energy source. When the turbine is operating in stand-alone mode,
any power requirement in excess of the wind energy available must be supplied by
storage systems or other generation.
Small Reciprocating Engines:
Reciprocating engines that run on various fuels are available in small sizes and
up to several megawatts. Currently available engines are typically intended for stand-
alone or back-up use. These engines, especially the larger ones, have good efficiencies
(30 to 40 percent). They operate in stand-alone applications like scaled-down generation
plants with synchronous generators capable of controlling voltage and frequency. Waste
heat from these units can help boost overall system efficiencies.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
MICRO TURBINE GENERATOR
A number of micro turbines generators have recently been announced as currently
commercially available for sale to customers, such as end users, utilities, and energy
service providers. Manufacturers and others are reporting certain performance
capabilities of the turbines; however, no consistent third-party independent testing as
been done to confirm or discredit such performance claims.
4.1 Overview
There are several manufacturers of Micro turbine generators (MTGs) announcing
their products as currently commercially available. Their potential customers are end-
users, utilities, and energy service providers. The chart shows some of the MTG
Manufacturers and current MTG operating features. To be competitive with existing
technology, most MTG manufacturers rely on enhanced reliability and lower
maintenance costs. MTG manufacturers expect to achieve greater reliability and lower
costs by using fewer moving parts and lower manufacturing costs. Manufacturers thus
expect economy of manufacturing of microturbines to replace economics of scale for
central plants. For MTGs to be competitive in the marketplace, minimum customers’
expectations are:
_ 40,000 hour “wheel life”
_ Heat rate of 12,000 to 16,000 BTU/kWh
_ Good part load performance
_ Emissions < 9ppm
_ Noise < 70 dB
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
_ Cheap and easy installation and maintenance
There is a tremendous potential market for MTGs if the MTG manufacturers can
make their products competitive with the other forms of energy available at the meter.
Using turbo-charger technology, the cost of producing an MTG can become lower and
lower -- depending on the manufacturer’s expertise in economy of manufacturing.
This is especially true if the manufacturer can use a casting process versus a
machined process. The MTG manufacturers realize that with an adequate volume of
sales, relying on low cost economics of manufacturing, MTGs have a stronger potential
to compete well at the meter with large central power plants. Additionally, on site power
maybe able to pick off other markets within niches to provide for future product
development. MTGs are intended to provide the energy industry with dispersed power
generation assets that may be located close to the loads they serve. For utilities, interest in
MTGs is based on deferred central power plant construction, deferred distribution line
upgrades, and improved reliability. End use customers may view MTGs as an alternative
to other small generators, an environmentally acceptable power generation device, and a
reliability improvement mechanism. There is speculation that MTGs may be an integral
part of the future utility infrastructure. In such as speculation, numerous, small generators
are scattered throughout a utility's traditional distribution network working in parallel
with central power plants. Some believe this will emulate what personal computers and
local area networks did by working in parallel to mainframes. MTG manufacturers and
others are reporting certain performance capabilities of the turbines; however, no
consistent, independent, third party independent testing has been done to confirm or
discredit such performance claims. However, MTGs will only be considered if they
perform acceptably and meet customers’ requirements for power quality, reliability,
availability, environmental considerations, cost effectiveness, usability and system
efficiency. As a part of the overall testing program, MTGs are purchased, installed,
operated and tested to assess their performance. Data was collected electronically and
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
manually. Ultimately results, as applicable for each unit, include the following
performance measures:
_ Starts/stops
_ Overall unit efficiency
_ Net power output
_ Operability
_ Emissions level monitoring
_ Power quality monitoring
_ Endurance testing
4.2 Technical Backgrounds:
MTGs are small, high-speed power plants that usually include the turbine,
compressor, generator, and power electronics to deliver the power to the grid. These
small power plants typically operate on natural gas. Future units may have the potential
to use lower energy fuels such as gas produced from landfill or digester gas.
Figure 4.1. MTG Components
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
MTGs have a high-speed gas turbine engine driving an integral electrical generator that
produces 20-100 kW power while operating at a high speed, generally in the range of
50,000-120,000 rpm. Electric power is produced in the 10,000s of Hz, converted to high
voltage DC, and then inverted back to 60 Hz, 480 VAC by an inverter. Most of MTG
engine designs typically have one or several power producing sections, which include the
turbine, compressor, and generator on a single shaft. During engine operation, engine air
is drawn into the unit and passes through the recuperator where temperature is increased
by hot exhaust gas. The air flows into the combustor where it is mixed with fuel, ignited
and burned. The ignitor is used only during startup, and then the flame is self-sustaining.
The combusted gas passes through the turbine nozzle and turbine wheel, converting
thermal energy of the hot expanding gases to rotating mechanical energy of the turbine.
The turbine drives the compressor and generator. The gas exhausting from the turbine is
directed back through the recuperator, and then out the stack.
4.3 MTG Testing Program
This MTG test program is expected to provide valuable insight, both qualitative
and quantitative, into the installation, performance and maintenance requirements of units
presently available to the market. Test results are based on actual operating conditions at
the test site in
Irvine, California. In addition to the results and experiences derived from installing and
operating these units, performance data are collected to trend and profile operating
characteristics via a Data Acquisition System and manually.
4.3.1 Data Acquisition System (DAS)
The Data Acquisition System (DAS) installed at the MTG test site provides
interval sampling of MTGs in operation. Raw data is collected in 5-minute intervals from
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
various measurement sensors that feed a datalogger with either pulse or analog signals.
The raw data is collected nightly, and processed once a month. Each MTG is retrofitted
with sensors at various locations. Additionally, environmental parameters are collected
for the entire site. Data parameters collected are described in Table4.1.
Table 4.1. MTG DAS Monitoring Parameters
Parameter Instrument
Electrical Energy
Produced3-phase electrical meter
with pulse output module
Fuel Consumed (Gas
Flow)
Gas flow meter
Water Flow* Water flow meter
Fuel Temperature RTD
Boiler Air
Temperature – Inlet
and Outlet*
Thermocouple
Relative Humidity Solid State IC
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Gas Pressure Pressure transducer
Ambient Temperature Temperature Probe
Water Temperature –
Inlet and Outlet*Resistance Thermal
Detector (RTD)
Power Quality
Snapshots
BMI 7100 and BMI
8010 power quality
meters
4.3.2 Test Procedures
To fully evaluate the MTGs, a series of tests were developed. Testing of MTGs is
categorized into three phases:
_ Installation and Startup
_ Operation and Maintenance
_ Performance
4.3.3 Installation and Startup
Each MTG delivered to the test site is inspected and noted to include operating
instructions, repair parts or a recommended spare parts list, consumable supplies, trouble-
shooting and maintenance procedures/guides, and a drawings and diagrams to sufficient
to support maintenance Once installed, the MTGs start and stop capabilities are tested.
Units are expected to withstand the wear of daily starts and stops. Operators at the test
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
site manually shut down the units several times per month. At other times, the units shut
down (e.g. loss of grid) and/or were manually restarted.
Figure4. 2. Bowman MTGs Bowman 60 kW rated MTG (left) and a Bowman 35 kW
rated MTG (right) are shown installed at test location.
4.4. Machine Performance Test Criteria
4.4.1 Endurance
For the test program, MTGs will be operated for as long as practicable at nominal
load. Daily operating parameters: fuel flow, ambient air pressure, temperature and
humidity, energy (kWh), operating temperatures and pressures will be recorded. Critical
MTG parameters will be recorded with the intent of correlating degradation with factors
other than wear and tear.
4.4.2 Transient Response
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
MTGs should be able to respond adequately to load changes. Units that are not
capable of isolated bus operation will operate in parallel with the system grid. Changes in
system load will be picked up by the grid and not by MTG units. Load changes on these
MTG units will be accomplished by manually setting load using the control system.
4.4.3 Harmonic Distortion
The power output will be measured with a BMI or equivalent recorder, which will
measure total harmonic distortion (THD). The BMI will also be used to determine the
power factor of the fully loaded unit during the endurance test. The measured power
factor will be used to verify that the package achieves rated output when connected to the
utility grid.
4.4.4 Noise Measurement
Ambient noise levels will be measured using a handheld noise meter. Each unit
will be operated independently to acquire the noise measurements during operations.
4.4.5 Emissions Measurement
For each MTG type tested, one certified test will be conducted to determine
compliance with South Coast Air Quality Management District Rule 2005 for NOx
emissions. Additionally, periodic measurements with available handheld equipment
would be made to determine trends and any condition of degradation that may occur with
operating hours.
4.4.6 Peak Load Gross and Net
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Peak load gross and net measurements will be taken with a BMI meter or
equivalent recorder that measures power. For units without compressors, or compressors
that are externally powered, the net output must be determined by subtracting the external
power requirements to sustain MTG operation. Results of this test will yield performance
characteristics such as efficiency, heat rate, fuel consumption and operating hours.
Comparisons will be made to manufacturer specifications.
Figure 4.3.Capstone 28 kW MTG
If current technology proves itself; the next hurdles are those of specific
application such as power quality, standby power, and peak shaving. Advancing
technology that proves itself in specific applications will grow in value by offering
customers new options.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
GAS TURBINE
5.1 Gas Turbine
A gas turbine is a rotating engine that extracts energy from a flow of combustion
gases that result from the ignition of compressed air and a fuel (either a gas or liquid, most
commonly natural gas). It has an upstream compressor module coupled to a
downstream turbine module, and a combustion chamber(s) module in between.
Energy is added to the gas stream in the combustor, where air is mixed with
fuel and ignited. Combustion increases the temperature, velocity, and volume of the
gas flow. This is directed through a nozzle over the turbine’s blades, spinning the
turbine and powering the compressor. Energy is extracted in the form of shaft power,
compressed air, and thrust, in any combination, and used to power aircraft, trains,
ships, generators, and even tanks.
5.2 Types of Gas Turbine
There are different types of gas turbines. Some of them are named below:
1. Aero derivatives and jet engines
2. Amateur gas turbines
3. Industrial gas turbines for electrical generation
4. Radial gas turbines
5. Scale jet engines
6. Micro turbines
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
The focus of this project is the modeling of micro turbine.
5.3 Gas Turbine Cycle
The simplest gas turbine follows the Brayton cycle (Figure 1.1). In a
closed cycle (i.e., the working fluid is not released to the atmosphere), air is
compressed isentropically, combustion occurs at constant pressure, and expansion
over the turbine occurs isentropically back to the starting pressure. As with all
heat engine cycles, higher combustion temperature (the common idustry reference
is turbine inlet temperature) means greater efficiency. The limiting factor is the
ability of the steel, ceramic, or other materials that make up the engine to withstand
heat and pressure. Considerable design/manufacturing engineering goes into keeping
the turbine parts cool. Most turbines also try to recover exhaust heat, which
otherwise is wasted energy. Recuperators are heat exchangers that pass exhaust
heat to the compressed air, prior to combustion. Combined-cycle designs pass
waste heat to steam turbine systems, and combined heat and power (i.e.,
cogeneration) uses waste heat for hot water production. Mechanically, gas turbines
can be considerably less complex than internal combustion piston engines.
Simple turbines might have one moving part: the shaft/compressor/
turbine/alternator-rotor assembly, not counting the fuel system. More sophisticated
turbines may have multiple shafts (spools), hundreds of turbine blades, movable
stator blades, and a vast system of complex piping, combustors, and heat
exchangers.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Figure 5.1- Idealized Brayton Cycle
The largest gas turbines operate at 3000 (50 hertz [Hz], European and Asian power
supply) or 3600 (60 Hz, U.S. power supply) RPM to match the AC power grid.
They require their own building and several more to house support and auxiliary
equipment, such as cooling towers. Smaller turbines, with fewer compressor/turbine
stages, spin faster. Jet engines operate around 10,000 RPM and micro turbines around
100,000 RPM. Thrust bearings and journal bearings are a critical part of the design.
Traditionally, they have been hydrodynamic oil bearings or oil- cooled ball
bearings.
5.4 Advantages of Gas Turbine
1. Very high power-to-weight ratio, compared to reciprocating engines.
2. Smaller than most reciprocating engines of the same power rating.
3. Moves in one direction only, with far less vibration than a reciprocating engine.
4. Fewer moving parts than reciprocating engines.
5. Low operating pressures.
6. High operation speeds.
7. Low lubricating oil cost and consumption.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
MICROTURBINE
6.1 Definition:
Micro turbines are small high-speed gas turbines. The three main components of
a micro turbine are compressor, combustor, and the turbine. The compressor is used to
pressurize the air before entering the combustor. Injected fuel is mixed with the
compressed air in the combustor and the mixture is ignited. Mechanical energy is
produced when the hot combustion gases flow and expand through the turbine. The
turbine drives a synchronous generator. A portion of power produced in the turbine is
utilized for driving the air compressor while the rest is converted to electric power in the
generator.
The outputs of the MTs range typically from around 25 to 300 kW. Performance
improvement techniques incorporated in MTs include recuperation, low NOx emission
technologies, and the use of advanced materials, such as ceramic for the hot section parts.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
MTs are available as single-shaft or split-shaft units. Single-shaft unit is a high-speed
synchronous machine with the compressor and turbine mounted on the same shaft. For
these machines, the turbine speed ranges from 50 000 to 120 000 r/min. On the contrary,
the split-shaft design uses a power turbine rotating at 3000 r/min and a conventional
generator connected via a gearbox for speed multiplication. Unlike traditional backup
generators, MTs are designed to operate for extended periods of time and require little
maintenance. They can supply a customer’s base-load requirements or can be used for
standby, peak shaving, and cogeneration applications.
Fig 6.1 micro turbine
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
The micro turbine took in place because of the emerging need of innovation to
the existing large gas turbine power plant, especially for the application of remote and
limited area to be placed. In 1994, when a MIT turbine engineer named Alan Epstein
found himself sitting in a jury pool and started to think about what it would take to build
the smallest possible jet engine. Then conclusion made that in theory the device could be
shrunk a lot. The idea was then started to make realization for a humungous application
to appear. By attaching a micro generator to the turbine, essentially creating a tiny power
plant, the combination would act like a battery, making power of twenty to fifty times or
even more to the rate of anything could be get on batteries (because there is much more
energy per ounce in burning hydrocarbons than in the electrochemical that usually goes
in batteries). For example: Current Li-ion batteries have energy densities up to 0.5 MJ/kg,
but fuel offers a much higher energy density of about 45 MJ/kg. It gives the insatiable
appetite to our needs for batteries; the micro turbine project suddenly became very
interesting. For comparison micro turbines are operated at lower pressure ratios (3 to 4)
than larger gas turbines (10 to 15). Micro turbine usually implemented the recuperated
system, which function is as the air-to-air heat exchanger (regenerator). The heat
collected from the turbine exhaust gas temperature. In a recuperated system, pressure
ratio is in direct proportion to temperature spread between inlet and exhaust. This allows
heat (from exhaust) to be introduced to the recuperator, increasing net cycle efficiency to
as much as 30%. Unrecuperated micro turbines average to 17% net cycle efficiency. So it
is clear that the non-recuperated cycle micro turbine configuration would have difficulty
competing on an operating cost basis unless coupled with some form of waste heat
recovery.
Micro turbine costs include the heat engine assembly itself, the recuperator, and
the generator. On the other hand, micro turbine engine accessory and control costs tend to
remain nearly constant, i.e., independent of size. Engine control costs also do not follow
scalar relationships, since control dynamic relationships (apart from inertial effects) are
relatively independent of size. Typical micro turbine system cost percentages are of the
order:
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
• Power head 25%
• Recuperator 30%
• Electronics 25%
• Generator 5%
• Accessories 5%
• Package 10%
Micro turbine efficiency and electrical (and thermal) output are basically
functions of peak cycle temperature (turbine inlet temperature, TIT), recuperator inlet
temperature (i.e., turbine exhaust gas temperature, EGT), compressor pressure ratio, and
component efficiencies and size effects (recuperator effectiveness, turbine isentropic
efficiency, compressor isentropic efficiency) . The TIT is essentially determined by the
limits of turbine rotor alloy stress rupture and low cycle fatigue strengths, duty cycle, and
rotor cooling options. Likewise, the recuperator inlet temperature, i.e., EGT, is also
determined by recuperator matrix material life limitations. The pressure ratio is dictated
by the compressor type and material.
6.2 single-shaft configuration:
Single shaft design typically employs metallic radial turbo machinery
components. They operate using one stage of compression and one turbine stage attached
in one shaft. The shaft connects the compressor, the turbine, and the unit generator
(figure 2.2). Those components thus have the same rotational speed. The air flowing into
the compressor, essential to the mass flow through the engine depends on the power
turbine condition; the turbine delivers more torque as it spins faster.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 6.2 single shaft configuration
The main advantage of using single-shaft configuration with a PMSG or
asynchronous generator is that it is simpler in design. Moreover, there is no need for
a gear reducer as power electronics rectifier–inverter is used to supply standard
voltage/frequency power to the load A bidirectional inverter can be used to facilitate
power flow from electric grid to drive the generator at the start-up. The system is also
small and light. The disadvantage of the method is that the power electronics system
causes some conversion loss. Also, the complex conversion system is not robust enough.
Moreover, the disadvantages of using high-speed PMSG are thermal stress,
demagnetization phenomena, centrifugal forces, rotor losses because of fringing effects,
high cost, etc. Rare earth permanent magnets are more expensive than the electrical steel
used in electromagnets. They also need to be contained using additional supporting rings.
PMSG requires special machining operations. Handling of recharged permanent magnets
is generally difficult in production shops. These requirements increase the cost of labor
for PMSG. The PMSG produces raw ac power with unregulated voltage. Depending upon
the changes in load and speed, the voltage variation can be wide. When an internal failure
36
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
occurs in a PMSG, the failed winding will continue to draw energy until the generator is
stopped. For high-speed generators, this may lead to a long-enough duration during
which further damage to electrical and mechanical components may occur. It could
also lead to safety hazards for the operating personnel. Zhu and Tomsovic used
an induction generator with GAST model. Though induction generators are cheaper and
robust, their speed is load-dependent and they have to be interfaced to the grid
only through expensive power converter systems. For induction generators, self-
excitation capacitance is of great concern. The output voltage and frequency vary with
the self-excitation capacitance when all other parameters are constant. The value of this
capacitance should lie between a minimum and a maximum limit depending upon the
combination of load, rotor speed, and magnetizing reactance. If this capacitance value is
not chosen properly, the machine fails to self-excite.
6.3 Split-shaft configuration:
Split-shaft micro turbines follow an industrial equipment design philosophy.
They are built to meet utility grade reliability and durability standards while producing
electricity as efficiently as central generation and distribution technologies currently in
use. Split-shaft micro turbines are designed exclusively for rugged, industrial quality
stationary applications; they fit right in on the plant floor or utility room and include no
design compromises inherited from vehicle or aerospace ancestries. Like single-shaft
micro turbine engines, two-shaft designs typically employ metallic radial Like single-
shaft micro turbine engines, two-shaft designs typically employ metallic radial turbo
machinery components. They use strengthened turbocharger components featuring
pressurized lube-oil systems consistent with industrial best practice. They operate at
relatively low pressure ratios in the 3:1 range using one stage of compression and two
turbine stages. The first turbine (the gasifier turbine) drives the compressor and the
second free-power turbine drives the load generator.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 6.3 Split-shaft configuration
Split-shaft configuration is more suitable for machine drive applications because
it does not require an inverter to convert the frequency of the ac power. The main
advantage of coupling an SG with a split-shaft MT is that it eliminates the use of
the rectifier and power converter. In this case, the generator is connected to the turbine
via a gearbox to generate standard 50/60 Hz power. These generators are robust and less
costly as compared to PMSG, and all other problems with high-speed PMSG are
eliminated. The use of power electronic interfaces for power conversion introduces
harmonics in the system to reduce the output power quality. These harmonics are
eliminated if SG is used with a gearbox. Also, there are less chances of failure as the
gearbox is much robust as compared to complex power electronics devices. However, the
main drawback of a gearbox is that it requires maintenance along with its supporting
lubricating system. The dimension and weight of the system increase with respect to the
single-shaft configuration. Some manufacturing companies like Ingersoll Rand Energy
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Systems, Ballard, Bowman, and Elliott are using synchronous machines with their MT
for both stand-alone and grid-connected operations
6.4 Synchronous Machine:
Model the dynamics of a three-phase round-rotor or salient-pole synchronous
machine.
The Synchronous Machine block operates in generator or motor modes. The
operating mode is dictated by the sign of the mechanical power (positive for generator
mode, negative for motor mode). The electrical part of the machine is represented by a
sixth-order state-space model and the mechanical part is the same as in the Simplified
Synchronous Machine block.
The model takes into account the dynamics of the stator, field, and damper windings.
The equivalent circuit of the model is represented in the rotor reference frame (qd frame).
All rotor parameters and electrical quantities are viewed from the stator. They are
identified by primed variables. The subscripts used are defined as follows:
d,q: d and q axis quantity
R,s: Rotor and stator quantity
l,m: Leakage and magnetizing inductance
f,k: Field and damper winding quantity
The electrical model of the machine is
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Note that this model assumes currents flowing into the stator windings. The measured
stator currents returned by the Synchronous Machine block (Ia, Ib, Ic, Id, Iq) are the
currents flowing out of the machine.
6.5 Necessity of Micro Turbine:
Under the current electric utility restructuring and public environmental policy,
there is ample scope for large-scale integration of DERs into utility grid
distribution system . Nowadays, there is growing interest in deploying MTs in DG
application, because of their quick start capability and easy controllability useful for
efficient peak shaving.
6.6 SPECIFICATIONS:
The current generation MTs have the following specifications.
1) Size: relatively smaller in size as compared to other DERs.
2) High efficiency: fuel-to-electricity conversion can reach the range of 25%–30%.
However, if the waste heat recovery is used for CHP applications, energy efficiency
levels are greater than 80%.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
3) Environmental superiority: NOx emissions are lower than 7 ppm for natural gas
machines in practical operating ranges.
4) Durability: designed for 11 000 h of operation between major overhauls with a service
life of at least 45 000 h.
5) Economy of operation: system costs lower than $500/kW. Cost of electricity is
competitive with alternatives including grid power for market applications.
6) Fuel flexibility: capable of using alternative fuels like natural gas, diesel, ethanol,
landfill gas, and/or other biomass-derived liquids and gases.
7) Noise level: reduced noise and vibrations.
8) Installation: simpler installation.
MODEL DESCRIPTION
7.1 MICROTURBINE MODEL
Usually, an MT consists of the following parts as listed next
1) Turbine: High-speed single-shaft or split-shaft gas turbines.
2) Alternator: In single-shaft units, the alternator is directly coupled to the turbine. The
rotor is either two-pole or four-pole permanent design. The stator is of conventional
copper wound design. In split-shaft units, a conventional induction machine or
synchronous machine is mounted on the turbine through the gearbox.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
3) Power electronics: In single-shaft machines, the high- frequency (1500–4000 Hz) ac
voltage generated by the alternator is converted to standard power frequency voltage
through the power electronic interfaces. However, in the split-shaft design, these are not
required due to the presence of the gearbox.
4) Recuperator: The recuperator recovers the waste heat to improve the energy efficiency
of the MT. It transfers heat from the exhaust gas to the discharge air before it enters the
combustor. This reduces the amount of fuel needed to raise the discharge air temperature
to that required value.
5) Control and communication: Control and communication systems include the entire
turbine control mechanism, Inverter interface, start-up electronics, instrumentation and
signal conditioning, data logging, and diagnostics and user control communications.
Fig. 7.1.MT model.
In this I focused their attention on slow dynamic performance of the system and not on
the transient behaviors. MT
Modeling is based on the following assumptions.
1) System operation under normal conditions: This paper considers normal operating
conditions of the system. Hence, start-up and shut down of MT along with fast
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
dynamics (faults, loss of power, etc.) are omitted from the model as they do not
affect the operating conditions under normal load. The we would like to work in future
for developing an advanced MT model to include the aforesaid fast dynamics.
2) Omission of the recuperator model: The electromechanical behavior of MT is of main
interest, and hence, the recuperator model is not included as it is only a heat exchanger to
raise engine efficiency. Also, due to the recuperator’s very slow response time, it has
little influence in the timescale of dynamic simulations.
3) Omission of temperature and acceleration control models: The temperature and
acceleration controls have no impact on the normal operating conditions. Temperature
control acts as an upper output power limit. At normal operating conditions, the turbine
temperature remains steady, and hence, it is omitted from the model. Acceleration control
is used primarily during turbine start-up to limit the rate of the rotor acceleration prior to
reaching operating speed. If the operating speed of the system is closer to its rated speed,
the acceleration control is of no significance in the modeling. However, without the
temperature control block, the model does not represent turbine operations accurately
at higher load levels when the control is to be done based on exhaust gas temperature
rather than machine speed to prevent the damage of the turbine blades. Besides, if a load
rejection occurs, the speed accelerates at a higher rate than the normal as the acceleration
control block is omitted. The nonlinearities appearing due to this could not be taken care
of. In this respect, the we would include these blocks in the advanced MT model.
4) Omission of governor model: The governor model is omitted as the MT does not use
any governor. Instead, a speed controller is incorporated in the model to keep the speed
constant. The simplified MT model is shown in Fig 3.1
7.2 CONTROLLER MODEL
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
As the main emphasis is on active power control, therefore the entire control system
is simplified as an active power proportional–integral (PI) control function.
The controlled active power is applied to the turbine. Active power control is represented
as a conventional PI controller, as illustrated in fig 7.2
Fig. 7.2 Controller model.
The controller model variables are:
Pin active power control variable applied to the input of MT;
Pde m actual load demand;
Pre f preset power reference;
Kp proportional gain of PI controller;
Ki integral gain of PI controller.
As MTs work on the similar principle as gas turbines, their dynamic models are
evolved from the concept of gas turbine dynamics. Gaonkar and Patel used an MT model
that consists of fuel control, turbine dynamics, temperature control, speed governor,
and acceleration control blocks. Speed control acts when there is a difference between the
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
reference speed and rotor speed. It is the primary method of speed control when the
turbine is operating under part-load conditions. Temperature control sets the upper
limit of the output power. Acceleration control is used primarily during turbine start-up to
limit the rate of the rotor acceleration prior to reaching operating speed. Gaonkar et al.
also used the same model but excluded the temperature and acceleration control blocks as
they have no impact in normal operating conditions. Recuperator was not included in the
both the models as only electromechanical behavior was of interest. The model used in
consists of transfer function representing fuel system with actuator, turbine, and
compressor dynamics along with heat recovery exchanger. Zhu and Tomsovic sed GAST
model for simulation of a split-shaft MT system. The single-shaft MT model in consists
of turbine, PMSG, rectifier, and inverter with their dynamics and interconnections.
7.3 TURBINE MODEL
The turbine or prime mover model for GAST model consists of two fuel systems
and a temperature control feedback. However, the temperature control feedback has
been eliminated in this project.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 7.3 Block diagram of prime-moverlturbine model
The prime mover model in Fig. 7.3 shows that there are two fuel system lag time
constants to represent the turbine of the GAST model as a prime mover. The first fuel
system lag time constant, Tfl characterizes the k e l valve position time constant. Whilst
the second fuel system lag time constant, Tn describes the fuel injection before being
burned in order to produce hot gas at high pressure and high velocity that go through the
turbine blades for spinning.
The model also includes the limiter due to the fact that there is a maximum and
minimum limit of fuel to be injected in the combustion chamber. This will affect the
mechanical power output from the turbine in terms of its maximum and minimum limit.
The input of the turbine model is the change in valve position from nominal
value, APVa,,,. The turbine model takes into account the turbine damping to obtain the
mechanical power output performance of the turbine. Thus, mechanical power output
from the prime mover is expressed by:
(7.1)
The MT does not use any speed regulator. In this project, we have used the widely
accepted GAST turbine model, as shown in Fig. 3.3 for representing the dynamic
behavior of a gas turbine. The advantages of GAST model are that it is simple and
follows typical modeling guidelines.
The following swing equation describes the machine speed and power relationship of the
GAST model:
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
(7.1)
It is a Western System Coordinating Council (WSCC) compliant model that can
directly be used in specific commercial simulation programs. The model does not
represent turbine operations accurately at higher load levels when the control is to be
done based on exhaust gas temperature rather than machine speed to prevent the damage
of the turbine blades. Hence, the model cannot provide adequate representation of the
temperature control loop. The GAST model also does not account for the nonlinearities
that play a major role in over speed conditions following a sudden load rejection.
Moreover, the model parameters could not be adjusted accurately to reproduce the
hunting phenomena around the final settling frequency.
Fig 7.4 Turbine model.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
The alternator coupled to the MT is modeled as a standard MATLAB–Simulink
synchronous machine block.
The parameters used for simulation of the MT, the alternator are based on work
reported by Zhu and Tomsovic and are illustrated in Tables 7.1 and 7.2 respectively.
7.4 Synchronous Machine:
Model the dynamics of a three-phase round-rotor or simplified synchronous
machine.The Simplified Synchronous Machine block models both the electrical and
mechanical characteristics of a simple synchronous machine. The electrical system for
each phase consists of a voltage source in series with an RL impedance, which
implements the internal impedance of the machine. The value of R can be zero but the
value of L must be positive.
The Simplified Synchronous Machine block implements the mechanical system
described by
Where
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Although the parameters can be entered in either SI units or per unit in the dialog
box, the internal calculations are done in per unit. The following block diagram illustrates
how the mechanical part of the model is implemented. Notice that the model computes a
deviation with respect to the speed of operation, and not the absolute speed itself
These expressions represent, in summary, the electrical component of the model
implemented in Matlab/Simulink[MathWorks,2007]. The mechanical equations,
significantly simpler than previous ones, are represented by:
MODEL PARAMETERS
7.1 MT PARAMETERS
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
7.2 ALTERNATOR PARAMETERS
7.2 THREE-PHASE SOURCE PARAMETERS
Parameter Value
Phase to phase voltage 440
Frequency 60hz
3-phase short-circuit level
at base voltage
3.73e3
Base voltage 440
x/r ratio 5
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
SIMULATION AND RESULTS
8.1 ISLANDED MODE
Following cases have been simulated in MATLAB–Simulink environment. Total
simulation time for this case is 120s.The output powers and loads are expressed as per
units with 3.73 kw and the rated line voltage is 440V. the parameters of this microturbine
modal are listed in above table.
2
Tm
1
Pm
1
3.0s+1
Transfer Fcn3
1
0.1s+1
Transfer Fcn2
1
10s+1
Transfer Fcn1
1
sTransfer Fcn
Saturation
min
MinMax
1.0
Gain3
-K-
Gain2
1
Gain1
0.1
Gain
Divide
1.2Constant2
2
Wr
1
Pref
51
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 8(A) Turbine MATLAB–Simulink model.
Fig 8(B) MICROTURBINE MATLAB–Simulink model.
Case 1:
In this case, the islanded MTG system is running with a load of 3.73 kW (1 p.u.)
applied to the generator bus up to t = 120 s. The load on the MTG system is shown in
Fig. 8.1, Fig 8.2 shows the mechanical power output of MT. It is observed that MT power
output takes about 55 s to match the load demand. Which shows that the MTG system
takes almost the same time to reach the new steady-state speed at the constant load. The
electrical power output of the generator is shown in Fig. 8.4 .It is seen to closely follow
change in load demand.
52
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 8.1 Load on the MT (Islanded mode).
Fig. 8.2 Mechanical power output of MT.
53
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 8.4 Generator electrical power output (Islanded mode).
Case 2:
In this case there is a step increase of the power demand from 0.7 p.u.(2.6 kW) to
1 p.u. (3.73 kW) as shows in figure 8.5. Figure 8.7 shows the dynamic response of the
mechanical power, Pm, and the total three-phase electrical power output, Pe Figure 8.8
shows .
54
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 8.5 Load on the MT (Islanded mode).
Fig. 8.6 Mechanical power output of MT.
55
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 8.7 Generator electrical power output (Islanded mode).
Case 3:
In this case there is a step decreasing of the power demand from 0.7 p.u. (2.6 kW)
to 0.4 p.u.(1.5 kW) as shows in figure 8.8. Figure 8.9 shows the dynamic response of the
mechanical power, Pm, and the total three-phase electrical power output, Pe Figure 8.10
shows .
56
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 8.8 Load on the MT (Islanded mode).
Fig. 8.9 Mechanical power output of MT.
57
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 8.10 Generator electrical power output (Islanded mode).
Simulation results analysis
From simulation results, the following points are observed:
The initial response time for the step change is around 10 sec; this delay mainly
due to the turbine response time.
The oscillations in Pm and Pe is significant with a time period around 20 sec; this
is mainly due to the small inertia and damping of the Micro Turbine.
A Micro Turbine is the most suitable micro source for dealing with the load
changing in the micro grid.
This microturbine model appears suitable for the time scale to be used in our
dynamic simulation.
58
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Case 4: MICROTURBINE WITH OUT FAULT
Following cases have been simulated in MATLAB–Simulink environment. Total
simulation time for this case is 120s.The output powers and loads are expressed as per
units with 3.73 kw and the rated line voltage is 440V.
Fig 8.11 MICROTURBINE WITH OUT FAULT MATLAB–Simulink model.
In this case, the islanded MTG system is running with a load of 3.73 kW (1 p.u.)
applied to the generator bus up to t = 120 s. The load on the MTG system is shown in
59
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 8.11, Fig 8.12 shows the mechanical power output of MT. It is observed that MT
power output takes about 55 s to match the load demand. Which shows that the MTG
system takes almost the same time to reach the new steady-state speed at the constant
load. The electrical power output of the generator is shown in Fig. 8.13 .It is seen to
closely follow change in load demand. The voltage and current output wave forms as
shown in fig 8.14&8.15.
Fig. 8.11 Load on the MT .
60
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 8.12 Mechanical power output of MT.
Fig 8.13 Generator electrical power output .
61
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 8.14 Generator voltage output
Fig 8.15 Generator current output
62
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Case 5: MICROTURBINE WITH FAULT
Following cases have been simulated in MATLAB–Simulink environment. Total
simulation time for this case is 120s.The output powers and loads are expressed as per
units with 3.73 kw and the rated line voltage is 440V.
Fig 8.16 MICROTURBINE WITH FAULT MATLAB–Simulink model.
63
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
In this case, the islanded MTG system is running with a load of 3.73 kW (1 p.u.)
applied to the generator bus up to t = 120 s and connected with a three phase fault. This
fault of duration of 60 to 90 s of duration of run time. The load on the MTG system is
shown in Fig. 8.17, Fig 8.18 shows the mechanical power output of MT. The electrical
power output of the generator is shown in Fig. 8.19 .It is seen to closely follow change in
load demand. The voltage and current output wave forms as shown in fig 8.20&8.21.
Fig. 8.17 Load on the MT
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig. 8.18 Mechanical power output of MT.
Fig 8.19 Generator electrical power output
65
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Fig 8.20 Generator voltage output
Fig 8.21 Generator current output
66
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Simulation results analysis
From simulation results, the following points are observed:
The initial response time for the step change is around 10 sec; this delay mainly
due to the turbine response time.
The oscillation in Pm and Pe is significant with a time period around 20 sec; this
is mainly due to the small inertia and damping of the Micro Turbine.
A Micro Turbine is the most suitable micro source for dealing with the load
following in the micro grid.
When fault period of 60 to 100 sec of duration the power is decreased, when fault
period is over again power will reaches its original values. These are observed
from the above wave forms.
When fault occurs voltage becomes zero and current will be increased as shone in
the wave forms.
67
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
This microturbine model appears suitable for the time scale to be used in our
dynamic simulation
MATHEMATICAL ANALYSIS
Introduction
Gas turbine plants are used for isolated and standalone operations. They are
mainly used in oil fields, desert areas, off shore installations and bio gas plants.
An effective control strategy is required to keep the system stable under
disturbance. The Transfer function model of heavy duty gas turbine has been developed
by Rowen [37] based upon his field experience and the tests he conducted in the gas
turbine plants. This model has been used in many works such as, the dynamic analysis of
combined cycle plant [38], twin shaft gas turbine model [39], and combustion turbine
model [40] and even in micro turbine power generation [41]. The transfer function
simplification has been validated [42]. After tuning the parameters, the response of the
gas turbine plant shows steady state error.
To improve the transient and steady state response, PID controller is required.
Mathematical Model of Micro Turbine :
The Transfer function model developed by Rowen [1] with the following
implifications is considered for the simulation of the response of an isolated micro
turbine.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
2
Tm
1
Pm
1
3.0s+1
Transfer Fcn3
1
0.1s+1
Transfer Fcn2
1
10s+1
Transfer Fcn1
1
sTransfer Fcn
Saturation
min
MinMax
1.0
Gain3
-K-
Gain2
1
Gain1
0.1
Gain
Divide
1.2Constant2
2
Wr
1
Pref
i. If the frequency variation is not greater than [+ or -]1%, the acceleration control will become inactive. It can be eliminated.
ii. The turbine output is predominantly controlled by the set point so the need for temperature control is significantly diminished, thereby allowing elimination of temperature control.
iii. The multiplier used in the transfer function can be neglected for small speed variations
The simplified block diagram of micro turbine is shown
A unit step load disturbance has been given to the gas turbine using MATLAB
Simulink and the response is obtained.
The response shows that there is a steady state error. An appropriate secondary
controller has to be included to improve both the steady state and transient response.
69
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Let the PID controller be implemented as
PID Controller:
Proportional--Integral--Derivative (PID) controllers are widely used in many
control applications because of their simplicity and robustness [10]. It is well known that
if the control law employs integral control, the system has no steady state error. However,
it increases the type of the system by one. Therefore the response with integral control is
slow during the transient period. In the absence of the integral control, the gain of the
closed loop system can be increased significantly thereby improving the transient
response. Similarly the closed loop system stability can be improved by the differential
control, and therefore PID controller will improve the static and dynamic accuracy.
PID controller consists of Proportional Action, Integral Action and Derivative
action. It is commonly refer to Ziegler-Nichols PID tuning parameters.PID controllers
algorithm are mostly used in feedback loops. PID controllers can be implemented in
many forms. It can be implemented as a stand-alone controller or as part of Direct Digital
Control (DDC) package or even Distributed Control System (DCS). The latter is a
hierarchical distributed process control system which is widely used in process plants
such as pharceumatical or oil refining industries.
It is interesting to note that more than half of the industrial controllers in use today utilize
PID or modified PID control schemes. Below is a simple diagram illustrating the
schematic of the PID controller. Such set up is known as non-interacting form or parallel
form.
70
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Figure 11.1. Schematic of The PID Controller – Non-Interacting Form
PID Controller
In proportional control,
Pterm = KP X Error
It uses proportion of the system error to control the system. In this action an offset is
introduced in the system.
In Integral control,
It is proportional to the amount of error in the system. In this action, the I-action will
introduce a lag in the system. This will eliminate the offset that was introduced earlier on
by the P-action.
In Derivative control,
It is proportional to the rate of change of the error. In this action, the D-action will
introduce a lead in the system. This will eliminate the lag in the system that was
introduced by the I-action earlier on.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
3.3 Continuous PID
The three controllers when combined together can be represented by the following
transfer function.
This can be illustrated below in the following block diagram
Figure11.2. Block diagram of Continuous PID Controller.
What the PID controller does is basically is to act on the variable to be
manipulated through a proper combination of the three control actions that is the P
control action, I control action and D control action. The P action is the control action
that is proportional to the actuating error signal, which is the difference between the input
and the feedback signal. The I action is the control action which is proportional to the
integral of the actuating error signal. Finally the D action is the control action which is
proportional to the derivative of the actuating error signal. With the integration of all the
three actions, the continuous PID can be realized.
This type of controller is widely used in industries all over the world. In fact a lot
of research, studies and application have been discovered in the recent years.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Optimizing Of PID Controller
For the system under study, Zieger-Nichols tuning rule based on critical gain Ker
and critical period Per will be used. In this method, the integral time Ti will be set to
infinity and the derivative time Td to zero. This is used to get the initial PID setting of the
system. This PID setting will then be further optimized using the “steepest descent
gradient method”.
In this method, only the proportional control action will be used. The Kp will be
increase to a critical value Ker at which the system output will exhibit sustained
oscillations. In this method, if the system output does not exhibit the sustained
oscillations hence this method does not apply.
it will be shown that the inefficiency of designing PID controller using the
classical method. This design will be further improved by the optimization method such
as “steepest descent gradient method” as mentioned earlier.
Designing PID Parameters
From the response below, the system under study is indeed oscillatory and hence
the Z-N tuning rule based on critical gain Ker and critical period Per can be applied.
73
1
1
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
Figure 11.3. Illustration of Sustained Oscillation with Period Per.
The transfer function of the PID controller is
Gc(s) = Kp(1 + Ti S + T ds )
In this project there was only PI controller so there was no D block in the controller, so
the block diagram is
Figure 11.4. Schematic of The PI Controller – Non-Interacting Form
The transfer function of the PI controller is
Gc(s) = Kp(1 + Ti S )
The objective is to achieve a unit-step response curve of the designed system that exhibits
a maximum overshoot of 25 %. If the maximum overshoot is excessive says about greater
than 40%, fine tuning should be done to reduce it to less than 25%.
74
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
The system under study above has a following block diagram
Figure 10.4. Block Diagram Of Controller And Plant.
Since the Ti = ∞ and Td = 0, this can be reduced to the transfer function of
The value of Kp that makes the system marginally stable so that sustained oscillation
occurs can be obtained by using the Routh’s stability citerion. Sincethe characteristic
equation for the closed-loop system is
S2 + 10.1s + 1 + K p = 0
75
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
From the Routh’s Stability Criterion, the value of Kp that makes the system marginally
stable can be determined.
The table below illustrates the Routh array.
s² 1 1
s¹ 10.1 Kp
sº 10.1-Kp/10.1 0
Table11.1. Routh Array
By observing the coefficient of the first column, the sustained oscillation will occur
if Kp=10.1.
Hence the critical gain Ker is
Ker = 10.1
Thus with Kp set equal to Ker, the characteristic equation becomes
S2 + 10.1s + 11.1 = 0
The frequency of the sustained oscillation can be determined by substituting the s terms
with jω term. Hence the new equation becomes
( jω )² + 10.1ω ) + 11.1=0
This can be simplified to
11.1 ( jω – 1)² + jω ( jω – 1 ) = 0
From the above simplification, the sustained oscillation can be reduced to
ω² = 1
Or
76
1
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
ω = √1
The period of the sustained oscillation can be calculated as
Per = 2π/√1
= 2.8099
The transfer function of the PID controller with all the parameters is given as
Gc(s) = Kp(1 + Ti S )
From the above transfer function, we can see that the PID controller has pole at the origin
and double zero at s = -1.4235. The block diagram of the control system with PID
controller is as follows.
Figure 11.5. Illustrated the Close Loop Transfer Function.
Using the MATLAB function, the following system can be easily calculated. The
above system can be reduced to single block by using the following MATLAB function.
Below is the Matlab codes that will calculate the two blocks in series
% calculation of series system response using matlab
num1=[0 1.08 1];
77
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
den1=[0 1.08 0];
num2=[0 0 1];
den2=[1 10.1 1];
[num,den]=series(num1,den1,num2,den2);
printsys(num,den)
This will gives the following answer
num/den =
1.08 s + 1
------------------------------
1.08 s^3 + 10.908 s^2 + 1.08 s
Hence the above block diagram is reduced to
Figure 11.6. Simplified System.
Using another MATLAB function, the overall function with its feedback can be
calculated as follow
% calculation of feedback system response using matlab
78
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
num1=[0 0 1.08 1];
den1=[1.08 10.908 1.08 0];
num2=[0 0 0 0 1];
den2=[0 0 0 0 1];
[num,den]=feedback(num1,den1,num2,den2);
printsys(num,den)
Hence the above block diagram is reduced to
This will result to
num/den =
1.08 s + 1
----------------------------------
1.08 s^3 + 10.908 s^2 + 2.16 s + 1
Therefore the overall close loop system response of
The unit step response of this system can be obtained with MATLAB.
79
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
%MATLAB script of the Designed PID Controller System.
num=[0 0 1.08 1];
den=[1.08 10.908 2.16 1];
step(num,den);
grid;
title('Unit Step Response of The Design System');
The unit step response is
0 10 20 30 40 50 600
0.2
0.4
0.6
0.8
1
1.2
1.4Unit Step Response of The Design System
Time (sec)
Am
plit
ude
Figure 11.7. Unit Step Response Of The Designed System
The figure above is the system response of the designed system. From the above response
it is obvious that the system can be further improved
Justification
80
DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
From simulation and mathematical results, the following points are observed:
The initial response time for the step change is around 10 sec; this delay mainly
due to the turbine response time.
The oscillations in Pm and Pe is significant with a time period around 20 sec; this
is mainly due to the small inertia and damping of the Micro Turbine.
This microturbine model appears suitable for the time scale to be used in our
dynamic simulation.
CONCLUSION
In this project, modeling, simulation and mathematical analysis of MT coupled
with SG are performed and reported. Its load following performance is thoroughly tested
and validated for different operating conditions, with and without speed controllers. It has
been observed that the MTG system can be effectively used to supply fixed and time-
varying load demands. This model is quite useful for studying the dynamic performance.
A microturbine simplified model has been developed by using Matlab/ Simulink/
Sim power systems software. The model has been mathematically analysis and different
operation conditions have been analyzed (Step change, fault,…). The simulation results
have showed that the microturbine works properly connected to a low voltage distribution
grid. Next developments in this field will be the improvement and optimization of the
microturbine model as well as the analysis of multiple operation conditions, mainly
related to different fault situations and the definition of the settings of protection relays.
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DYNAMIC PERFORMANCE ANALYSIS OF A MICROTURBINE BASED DISTRIBUTED ENERGY RESOURCE
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