辅导案例-W1274-162
Project No.W1274-162



Optimal operation of combined cooling heat and
power (CCHP) systems in future energy networks




Submitted by: Chen Yumin
Matriculation Number: N1600040F


Supervisor: Xu Yan

School of Electrical & Electronic Engineering
A final year project report presented to the Nanyang Technological University
in partial fulfilment of the requirements of the degree of
Bachelor of Engineering
2017
Project No.W1274-162
Abstract
With the rapid development of energy internet, distributed energy resources and
energy storage technology, the relationship between cooling, heat and power energy is
getting closer and closer. It is evitable that combined cooling, heat and power energy
(CCHP) system being widely used in the future. To optimize the operation of CCHP
system, this study established a model of CCHP-based microgrid, considering energy
storage, operation characteristics of different units and time-of-use electricity prices.
Optimization methods based on PSO algorithm and Lingo software were used to
minimize the total operational costs of microgrid in the scheduling period. Besides,
comparison and discussion were made on three separate scheduling modes of microgrid
in order to find the best and most cost-saving mode. The results of calculation indicate
that the model established in this paper could effectively reduce the operational costs.
Hoping that the outcome of this paper could serve as a reference for future studies on
CCHP system-based microgrid.

KEY WORDS: microgrid; combined cooling, heat and power energy system(CCHP);;
economic dispatch; energy storage; particle swarm optimization algorithm


Project No.W1274-162
Acknowledgements
First of all, I would like to acknowledge my parents. Without their understanding
and support, I could not have an opportunity to do my final year project in Nanyang
Technological University, a first-class and world-renowned university. It is their
encouragement that inspires me to strive forward.
I would wish also to express gratitude to my project supervisor, Associate
Professor Xu Yan for helping me get started this project by giving me some guidance
and valuable suggestions.
Besides, another person who deserves greatly to be acknowledged is Dr.Li
zhengmao. He shared much of his experience and knowledge in this area to me. I have
learnt a lot on optimization problems and Lingo programming techniques from him. I
could not have come this far without his continuous encouragement and useful advice.
Finally, I would like to express my thanks to all my friends for giving me
considerable comfort and supporting me through the hard times.






Project No.W1274-162
Acronyms
CCHP combined cooling, heat and power
MT micro turbine
FC fuel cell
WT wind turbine
PV photovoltaic cell
EB electric boiler
ES electric energy storage
HS thermal storage


Symbols
∆ scheduling unit time (1hour)
,() maintenance costs of wind turbine at time slot t
,() maintenance costs of photovoltaic cell at time slot t
() wind power output at time slot t
() photovoltaic power output at time slot t
() exhaust heat of micro turbine at time slot t
() electric power of micro turbine at time slot t
() generating efficiency of micro turbine at time slot t
Project No.W1274-162
−ℎ() the quantity of heat produced by absorption chiller at time slot t
loss rate of heat dissipation
ℎ coefficient of performance of absorption chiller
ℎ recovery rate of absorption chiller
() fuel costs of micro turbines at time slot t
low calorific value of natural gas
() heat power of electric boiler at time slot t
() electric power of electric boiler at time slot t
efficiency of electricity transforming to heat for electric boiler
() energy storage capacity at time slot t
self-discharge rate of energy storage
ℎ() charging power of energy storage
() discharging power of energy storage
charging/ discharging efficiency of energy storage
the total capacity of energy storage
the maximum value of state of charge (SOC) for energy storage
the minimum value of state of charge (SOC) for energy storage
, maximum value of discharging power of energy storage
, minimum value of discharging power of energy storage
() thermal storage capacity at time slot t
heat losing rate of thermal storage
ℎ() heat absorbing power of thermal storage
Project No.W1274-162
() heat releasing power of thermal storage
ℎ heat absorbing/releasing efficiency of thermal storage
the total costs
() fuel costs
() interaction costs
() maintenance costs
() start-up costs
() heat selling benefits
() the interactive power at time slot t
() sale price of exchanged electricity at time slot t
() purchase price of exchanged electricity at time slot
unit maintenance costs of the ith unit
() output power of the ith unit at time slot t
() operational state of the jth controllable generator
,
the start-up and shut-down costs per time of the jth controllable generator
ℎ unit heat purchase price
ℎ() the amount of heat loads in the microgrid at time slot t
() the output power of the jth controllable generator at time slot t
the minimum power of the jth controllable generator
the maximum power of the jth controllable generator

the downward ramping power of the jth controllable generator


the upward ramping power of the jth controllable generator
Project No.W1274-162
() electrical loads in the microgrid at time slot t
the minimal power of tie-line
he maximal power of tie-line

















Project No.W1274-162
Table of contents

Abstract ............................................................................................................................................. 2
Acknowledgements ........................................................................................................................... 3
Acronyms .......................................................................................................................................... 4
Symbols............................................................................................................................................. 4
Table of contents ............................................................................................................................... 8
Chapter 1. ........................................................................................................................................ 10
Introduction ..................................................................................................................................... 10
1.1 Overview ..................................................................................................................... 10
1.2 Project Motivation ....................................................................................................... 11
1.3 Aims and Objectives ................................................................................................... 12
1.4 Report Structure .......................................................................................................... 12
1.5 Background Information ............................................................................................. 13
1.5.1Microgrids ............................................................................................................. 13
Fig1.1 A typical scheme of microgrid .................................................................................... 14
1.5.2CCHP Systems ...................................................................................................... 14
Fig.1.2 Schematic diagram of a typical microgrid ................................................................. 15
Chapter 2. ........................................................................................................................................ 16
Literature review ............................................................................................................................. 16
1.2.1 Development of Energy Networks and Microgrids ...................................................... 17
1.2.2 Basic Model of Combined Heat and Power Systems .................................................... 18
1.2.3 Economical Dispatch of CHP-based Microgrids .......................................................... 19
1.2.4 United Dispatch of Heat and Power Energy in Microgrids........................................... 20
Chapter 3. ........................................................................................................................................ 22
Structure and model of a typical CCHP-based microgrid ............................................................... 22
3.1 Background ...................................................................................................................... 22
3.2 Wind and Photovoltaic Power .......................................................................................... 24
Project No.W1274-162
3.3 CCHP System .................................................................................................................. 24
3.4 Electric boiler (EB) .......................................................................................................... 25
3.5 Energy Storage ................................................................................................................. 26
3.6 Fuel cell (FC) ................................................................................................................... 28
3.7 Economical Model of CCHP System ............................................................................... 29
3.7.1 Objective Function ............................................................................................... 29
3.7.2 Constraints ........................................................................................................... 30
Chapter 4. ........................................................................................................................................ 32
Solving methods .............................................................................................................................. 32
4.1 PSO Algorithm ................................................................................................................. 33
4.2 Solution Process ............................................................................................................... 33
Fig4.1 The exact process of PSO algorithm ........................................................................... 34
Chapter 5. ........................................................................................................................................ 35
Simulation and Results.................................................................................................................... 35
5.1 Case Study ....................................................................................................................... 35
Fig 5.1 The output power of wind turbines and photovoltaic cells ........................................ 36
Tab 5.1 The parameters of components in the CCHP-based microgrid ................................. 36
Fig 5.2 The prices of electricity ............................................................................................. 37
5.2 Results .............................................................................................................................. 39
5.3 Analysis ............................................................................................................................ 43
Chapter 6. ........................................................................................................................................ 46
Conclusion and future work ............................................................................................................ 46
References ....................................................................................................................................... 48


Project No.W1274-162
Chapter 1.
Introduction
1.1 Overview
With the rapid development of multiple energy networks and energy storage
devices, the generation, transmission and consumption of electrical power, heat and
cooling power become more closely related. It is needed for people to have a unified
planning and design of heat, cooling and electrical power.
Combined cooling, heat and power (CCHP) system is the use of a heat engine or
a power station to produce electricity, cooling and heat energy in the meantime[1].
Normally, CCHP-based microgrid integrate diesel engines, wind turbines and
photovoltaic cells to produce electricity. Also, absorption chillers and micro turbines
are installed to generate heat and cooling energy.
Statistics show that in traditional thermal power plant, energy conversion
efficiency is only approximately 32%. However, using heat-transfer technology, CCHP
systems are capable of convert approximately 70%-90% of the chemical energy of the
original raw fuel into electrical power[2].
In recent years, industrial development and population growth have led to surging
in the global demand for energy. Take China as an example, as one of the world’s
biggest energy consumers, China faces the urgent task of creating a sustainable energy
structure. Researches show that the highest proportion of energy consumption in China
Project No.W1274-162
is heat power consumption (40%), which is nearly twice as that of electrical power
(25%). Since CCHP systems can reduce power generation costs and the discharge of
pollutants in microgrids, with the growing severity of energy crisis, they are drawing
more and more attention in the world.

1.2 Project Motivation
For many years, I’ve had a keen interest in new energy resources and multiple
energy networks. I read some magazines and news about wind power, solar power and
I knew the advantages and disadvantages of these new energy resources. From then on,
I have been fascinated by how these different kinds of energy were integrated in one
power network. This combined with my main interest in electrical power system formed
the basis of my choice on choosing this topic for my final year project.
Before I started my final year project, I knew that when thermal power plants are
producing electrical power, they are also generating heat at the same time. But I never
understood how heat and electric power can be combined in this process. This sent me
on a quest to investigate exactly how micro turbines and LiBr absorption chillers
contribute to the task of producing heat and cooling power while generating electricity
at the same time. After doing some researches into on the energy flow diagram of
CCHP-based microgrids, I got a better understanding of CCHP systems.
However, just being interest in this area was not the only motivational reason
behind my decision on deciding my project. Many countries today are making efforts
Project No.W1274-162
to develop a low carbon economy and green growth, so combined cooling, heat and
power energy (CCHP) is a hot topic in the electrical area. Although at present, CCHP
systems have still been studied and has not entered the widespread application stage
yet, I personally predict that CCHP systems will be commonly used in smart power
grids towards the near future.
In a word, I chose optimal operation of CCHP systems in future energy networks
as my final year project because of my self interest and good growth prospects for
CCHP systems.

1.3 Aims and Objectives
This final year project aims to investigate the most economical operation mode of
CCHP in a comprehensive energy network. In this project, an operation model of
microgrid which contains CCHP system is to be established, its economical operation
mode is to be investigated. PSO algorithm is to be used to solve optimal problems. The
results from this investigation are helpful for people to make informed decisions when
planning optimal joint-dispatch mode of microgrids.

1.4 Report Structure
The structure of this report is organized as follows:

Chapter 1 Introduces motivation and objectives, structure of this report and
Project No.W1274-162
some background information on microgrids and CCHP systems. This information is
required to be read so as to have an idea of what the chapters that follow refer to.
Chapter 2 Literature review. Introduces some previous researches which were
carried out on CCHP systems.
Chapter 3 describes the model that I built for a CCHP-based microgrid. This
Chapter includes many arithmetic expressions.
Chapter 4 Methods. Introduces PSO algorithm and a software named lingo,
which were used to solve optimization problems in this project.
Chapter 5 Show and explain the results of optimization problem, and the
results were compared with the separate generation of power and heat mode, as well as
ordering power by heat.
Chapter 6 Summarize the whole final year project.
References
Finally, lingo programming codes are attached in the Appendix.

1.5 Background Information
1.5.1 Microgrids
CCHP systems are generally applied in microgrids. Microgrid is a localized
grouping of distributed electricity sources and loads (such as distributed generators,
storage devices, or controllable loads). It is normally connected to and synchronous
with the main electrical grid, but sometimes it can function independently, depending
Project No.W1274-162
on dispatch of the main electrical grid[3].

Fig1.1 A typical scheme of microgrid
A microgrid usually has 4 basic components: local generation (ex. Diesel
generators), consumption (ex. Lighting heating system of buildings), energy
storage, and point of common coupling(PCC).


1.5.2 CCHP Systems
Combined cooling, heat and power system (CCHP) is the use of a heat engine or
a power station to generate electricity and useful heat, cooling power at the same time.
It refers to the simultaneous generation of electricity and useful heating and cooling
from the combustion of a fuel or a photovoltaic heat collector. Combined heat and
power plants are usually installed close to the consumers so that the performance of the
electricity transmission and distribution network can be increased.
The schematic diagram of a typical CCHP-based microgrid is as follows, the
voltage of the main electric power grid is 10kV, and the voltage of micro grid is 3.8kV
Project No.W1274-162





Fig.1.2 Schematic diagram of a typical microgrid
Figure 1.2 shows there are varied forms of power generation in a CCHP-based
microgrid, such as using some green energy (wind turbines, photovoltaic cells), non-
renewable energy (micro turbines, fuel cells and diesel turbines) to generate electricity.
Moreover, there are storage systems in a microgrid. Figure 1.2 also demonstrates that
there are three main energy flows in this kind of microgrid. They are heat loads,
electrical loads and cooling loads. CCHP system, which contains micro turbine and
LiBr absorption chiller can satisfy the heat and electrical energy needs at the same time.
CHP
Cooling load
Network
PCC
WT PV ES FC
Electrical load
Heat
Storage
Thermal load
Radiator
Absorption
chiller
Micro
turbine
MGCC
Communication and control network
Cooling Power Transmission Electrical Power Transmission
Thermal Power Transmission
Project No.W1274-162
Besides, the redundant heat which is produced in the generation process will be
absorbed by LiBr absorption chiller and be changed into cooling power so as to meet
the uses’ requirements.


















Chapter 2.
Literature review
Many researches have been done on energy internet, microgrids, and the modeling,
Project No.W1274-162
designing and economic dispatch of the CCHP systems.
1.2.1 Development of Energy Networks and Microgrids
The organization and operation of global energy industry have been changed
rapidly since the 1980s. This is mainly caused by 3 factors. The first one is that
widespread use of fossil energy leads to serious environmental pollution climate change.
Secondly, the mode of economic development in some developing countries which
relies on traditional industries proves unstainable. The last reason is because computer
and communication technologies are improving rapidly nowadays. Many scientists
around the world are investigating clean, efficient and sustainable energy internet, so
that the increasingly acute energy crisis can be solved.
In order to provide solutions to global energy related problems, Jeremy Rifkin
defined the conception of Energy Internet in his book [4]: Electrical power system is
the core of energy internet, while internet and other advanced information technology
is the basis. Using distributed renewable energy resources as its main primary energy,
Energy Internet can be combined with communication network, thermal network,
transportation network, natural gas network. Charging facilities planning, operation line
planning of electric vehicles and some other related problems connects electrical power
system to the transportation network. For example, where the charging piles are located
and where dwellers like to drive their car will influence traffic flow in a city. Whereas
residents driving activities will be affected by urban traffic network planning, which
will definitely affect electrical power system loads.
Project No.W1274-162
Energy Internet construction has the flowing main benefits:
(1) Fossil energy can be shifted into renewable energy.
(2) Large-scale distributed power supply can be connected to the main
electrical power grid.
(3) Deploying hydrogen and other storage technologies.
(4) Internet technology will be used to transform the electrical power grid.
(5) Transitioning the transport fleet to electric, plug-in and fuel cell vehicles.
In recent years, research numerous microgrids demonstration projects have been
constructed around America, Japan, and Europe. Most of the researches focus on
Intelligent Microgrid, energy use diversification and energy supply individuation.


1.2.2 Basic Model of Combined Heat and Power Systems
So far, numerous researches conducted experiments about the model and methods
of microgrids economic dispatch. However, very little relevant research has been
carried out to investigate combined heat and power systems.
In [5], Wang took heating buildings as an example, proposed a new economical
operation mode for CHP systems, which combines CHP generator, electric boiler,
refrigeration equipment, heat coil all together.
Papers such as [6] and [7] are works on analyses of energy efficiency goals for two
different operation mode of CHP systems: In the first mode, electricity is based on heat
and in the second mode, electricity plays the leading role.
Project No.W1274-162
Paper [8] which was written by Wang Rui and his team is a revealing study on
stochastic optimization model for CHP systems. Wang considered randomness of new
energy power and electrical loads in microgrids in his article, but the model he
constructed for CHP systems lacks diversity.
Apart from that, Cho H evaluated the linear programming models of CHP systems
in his research [9], and he also described energy flow of microgrids in details. However,
the energy flow graph in his article is so complex that it is hard to understand, besides,
when there are too many nodes in a microgrid, the energy relationship cannot be fully
demonstrated in his graph.

1.2.3 Economical Dispatch of CHP-based Microgrids
Currently, most researches on economic dispatch of CHP-based microgrids mainly
focus on power supply optimizing, storage capacity and optimal reserve storage
capacity. For example, in [10], Chen Jie applied a modified genetic algorithm to find
out optimal operation of the merged power microgrids.
Wu Xiong developed the linearization techniques to solve the economic generation
scheduling of a microgrid in his article[11], he makes a contribution to the research of
converting the optimization problem into a mixed-integer linear programming (MILP)
problem. He also compared the MILP method with the genetic algorithm. Moreover, in
[12], Wu Xiong analysed the economic and energy-saving effect of CHP and energy
storage. Through comparing the economic benefits between the non-CHP microgrids
Project No.W1274-162
and CHP-based microgrids, he showed to us that CHP systems and energy storage can
reduce the operation costs of microgrids.
Previous researchers have done a lot of work on economic dispatch of microgrids,
modelling different units and solving the optimization problems, and the uncertainty of
new energy power. However, almost all of them take the peak load shifting measures
when they are optimizing the power of every unit in a microgrid, which means that they
do not take time-of-use electricity price and load levels into consideration. Therefore,
there is a need to further investigate how to build a suitable model to optimize
interactive power and energy storage in microgrids, so that the operation costs can be
minimized.

1.2.4 United Dispatch of Heat and Power Energy in
Microgrids
Nowadays, most researches conducted on united dispatch of heat and power
energy in microgrids mainly focus on optimal economic operation of microgrids and
improvement of primary energy ratio. Fubara investigated a typical microgrid including
renewable energy, electronic energy storage, heat storage, CCHP system, heat loads and
power energy in his paper[13], he also analyzed the optimal output of each unit in this
type of microgrid, considering depreciation costs, maintenance costs, fuel costs, heat
selling benefits and the interaction costs between the microgrid and main network.
Besides, on the basis of studying components characteristics and structure of
Project No.W1274-162
typical CCHP system, Wang Chengshan proposed a newly bus-based structure for
system description and designed a dispatch model of microgrid for the purpose of
optimization in [14].
Apart from that, Brahman and Honarmand make contributions to the research of a
residential energy hub model which receives electricity, natural gas and solar radiation
at its input port to supply required electrical, heating and cooling demands on the output
port[15].
Paper [16] written by Xu Lizhong developed an optimization mode in order to
schedule electricity and heat production in microgrids under a recent market
environment considering the operation constraints and the variability of wind power
generation. This model is able to optimize the operation costs of power energy and heat
energy, meanwhile consider the minimization of the actual flow deviation at the point
of common coupling (PCC) from the scheduled values.
In these studies, researchers investigated united economy of heat energy and power
energy. However, very little research has been conducted to investigate the relationship
between heat energy and power energy.
Project No.W1274-162
Chapter 3.
Structure and model of a typical
CCHP-based microgrid
3.1 Background
Compared to traditional electric grid, microgrid is an autonomous entity. It can be
connected to a large substation of the main electric grid through a change-over switch.
Varies distributed power generation which is contained in microgrids have the
advantages of being efficient, flexible and environmentally friendly. Besides,
microgrids have sufficient power transmission and distribution resources, and it can
benefit people in reducing the total of operational costs and centralized electric
transmission line loss, compared to traditional thermal power plant and centralized
generation technology. Meanwhile, distributed power generation can sh0-ift electricity
from peak periods to off peak periods, thus it can increase the using time of generators
and the reliability of power supply in microgrids. Therefore, distributed power
generation is often deemed as a strong support of large power grids. In the last few
years, distributed generation technology has been advanced to the schedule all over the
world. There is no doubt that distributed generation technology will be one of the major
trends in power system development in the days to come. Common distributed power
generation includes micro turbines, diesel turbines, fuel cells, photovoltaic cells, wind
Project No.W1274-162
turbines and so on.
However, with the widespread use and continuous researches of distributed power
generation, the problems of expensive access costs and demanding control of
distributed power generation gradually stand out. In order to avoid these problems and
make full use of its advantages, researchers developed micro-grid technology. A
microgrid is a group of interconnected loads and distributed energy resources within
clearly defined electrical boundaries that acts as a single controllable entity with respect
to the grid. A microgrid has to serve double duty: for power generation enterprises, a
microgrid can be deemed as a controllable unit; for customers, a microgrid will be used
as a power supply to satisfy the diversified demand of users. That is to say, in microgrids,
micro sources can operate in grid-connected mode or can operate in island, and it is
capable of transmitting energy between grid-connected mode as well as islanding mode.
Besides, it offers a great solution to supply electricity when an emergency or power
shortage occurs during power interruption in microgrids. Moreover, microgrid has the
advantages of integrating different kinds of renewable energy generation without
demanding re-design of the distribution system [17].
In this chapter, a model of distributed power generation and related auxiliary
equipment characteristics in a typical CCHP-based microgrid is to be developed, based
on the diagram which was proposed in Chapter 2. Besides, the economic model of
maintenance costs, depreciation costs and fuel costs is also to be built.

Project No.W1274-162
3.2 Wind and Photovoltaic Power
Sometimes it is hard to predict how much wind and photovoltaic power we can
get at a certain time on a certain day, because wind power is influenced by wind speed
and photovoltaic power varies with solar radiation and temperature. Since the output
power of wind turbines and photovoltaic cells are only affected by environmental
factors, they are considered to be fixed in this model, which means that they are viewed
as uncontrollable generators in this paper.
Since wind and photovoltaic power are both environmental-friendly and do not
consume primary energy when they are utilized to generate electrical power, I only
consider their maintenance costs during run time. The expressions of costs at time slot
t are denoted as follows
,() = ,() (3-1)
,() = ,() (3-2)
,() , ,() are maintenance costs of the wind turbine (WT) and
photovoltaic cell (PV) at time slot t respectively. , and , are maintenance
costs each unit power of them respectively. Besides, (), () are wind power
and photovoltaic power output at time slot t.

3.3 CCHP System
The key components of Combined cooling, heat and power system (CCHP system)
are micro turbine and LiBr absorption chiller. High level heat energy produced from
Project No.W1274-162
burning natural gas can do work to drive micro turbine to generate power energy. The
high-temperature waste heat will be absorbed by absorption chillers for heating
buildings or be changed into cooling energy for the customers.
Researches show that the changing environment has little effect on combustion
efficiency and power generation, and it can be neglected in the actual computation.
The mathematical model of micro turbine is
() =
()(1−()−)
()
(3-3)
−ℎ() = ()ℎℎ (3-4)
Where is loss rate of heat dissipation. () ,() ,() are exhaust heat,
electric power and generating efficiency of micro turbine respectively. −ℎ() is the
quantity of heat produced by absorption chiller at time slot t. ℎ, ℎ are coefficient
of performance and recovery rate of absorption chiller respectively.
The fuel costs of micro turbine at time slot t is
() = 4
()∆
()×
(3-5)
Where ∆ is scheduling unit time, () is fuel costs of micro turbines at time
slot t, and is low calorific value of natural gas, conventionally 9.7KW·h.

3.4 Electric boiler (EB)
Electric boiler is a kind of machine which uses natural gas as primary energy to
supply heat energy to microgrids directly. Electric boilers can be simply installed and
controlled flexibly, which is why they are commonly used in microgrids. Moreover,
Project No.W1274-162
they can cooperate with CCHP systems to satisfy heat loads demand and they can play
a role of peak shaving as well as valley filling. The model of an electric boiler is not
complex and it is only affected by its self-characteristics and the amount of heat loads
which are demanded by customers.
The mathematical model of electric boiler is established as:
() = () (3-6)
Where () and () are heat power and electric power of electric boiler
at time slot t respectively, is efficiency of electricity transforming to heat for
electric boiler. The consumption of electric boiler is part of the electrical loads of
microgrid.

3.5 Energy Storage
Energy storage is the capture of energy produced at one time for use at a later time,
including thermal storage and electrical storage in the model of CCHP systems. It can
decouple the fluctuate energy supply from the fairly inelastic energy demand [18] so
that higher system flexibility can be achieved.
In economic dispatch of microgrids, energy storage can make contributions to shift
electricity from peak periods to off peak periods and reduce the total of operational
costs. It mainly consists of energy-type storage (such as batteries) and power-type
storage (such as super capacitor). In this model, we use energy-type storage, and
mathematical equations for electric energy storage (ES) are presented as follows:
Project No.W1274-162
() = (1 − )( − 1) + [ℎ() −
()

]∆ (3-7)
Where () is energy storage capacity at time slot t, is its self-discharge
rate. Besides, ℎ() and () are charging power and discharging power of
energy storage respectively. When energy storage is charging, it will have no
discharging power, which means that () should be 0, and vice versa. is
charging/discharging efficiency of electric energy storage.
In real life, users may need different amount of heat loads and electrical loads at
certain times in a day. When there are less heat loads than electrical loads demand by
customers, some of the generators will be limited by heat loads. Thus they will be not
able to run at their full potential. On the contrary, when there are less electrical loads
than heat loads required by customers, redundant power will not be economically used.
However, using thermal storage systems, people can solve the problem that the heat
loads and electrical loads do not match the power to heat ratio in a microgrid. As a result,
heat energy and electrical energy can be administered by a coordinate way to obtain
benefits and objectives.
Coventional thermal storage (HS) includes large-scale heat storage tank, electric
boiler system with heat accumulator and so on. Its feature can be given as the
relationship between storage capacity, input/output capacity, thermal efficiency. The
dynamic mathematics model of thermal storage can be expressed as:
() = (1 − )( − 1) + ℎ()ℎ −
()

∆ (3-8)
In this formula, () is thermal storage capacity at time slot t, while is its
heat losing rate.

() and () are heat absorbing power and heat releasing
Project No.W1274-162
power of thermal storage respectively. Similar to electric energy storage, thermal has
no releasing power when it is absorbing heat energy, which means that ()
should be 0, vice versa. Besides, ℎ is heat absorbing/releasing efficiency of thermal
storage.

3.6 Fuel cell (FC)
A fuel cell is a device that converts the chemical energy from a fuel into electricity
through a chemical reaction of positively charged hydrogen ions with oxygen of another
oxidizing agent[19]. Fuel cell not only has a high efficiency but also no pollution. So it
is focused by the entire world. In this model, proton exchange membrane (PEM) fuel
cell is utilized. The PEM fuel cell is a type of fuel cell which is attractive for low power
levels and for application that need quick start up and response to load
changes. Because fuel cells are mainly used as electric power supply in microgrids, the
waste heat of fuel cells is not considered in this model. The relationship between fuel
costs and electric power of fuel cells at time slot t is:
() = 4
()∆
()×
(3-9)
Where () , () and () are the fuel costs, generating power and
generating efficiency of fuel cells at time slot t.
Some generators (such as micro turbines, electric boilers and fuel cells) are
characterized by their compact size, energy saving and are also easy to operate, they
are also called controllable generators (CG). The power output of these controllable
Project No.W1274-162
generators is subject to their ramping power.

3.7 Economical Model of CCHP System
3.7.1 Objective Function
The objective of economic dispatch of microgrids is to minimize the total costs by
arranging the output power of each unit reasonably, under the condition that the
operation restraints of different units are satisfied. Because renewable generators (like
photovoltaic cells and wind turbines) use new energy to generate electricity, their
generation costs are negligible compared to traditional generators and usually can be
ignored. The operation costs of micro turbines and fuel cells include fuel costs, start-up
costs and maintenance costs. Electric boilers do not use fuel, so I only consider its
maintenance costs and start-up costs. As for wind turbines and photovoltaic cells, as
mentioned before, their output power are viewed to be fixed and I only consider their
maintenance costs in this paper. Moreover, because heat energy and cooling energy are
mutually transforming through LiBr absorption chiller and their mathematical
expressions are similar, cooling energy is not taken into account in this project.
What’s more, when connected with main electric grid as a whole, a microgrid will
purchase electricity from external power grids if the internal power supply cannot
satisfy the load demand or it is not economical to use internal power supply for the
purpose of generating electricity. Therefore, the total costs of microgrid should also
contain purchase costs. To sum up, the objective function of economic dispatch for
Project No.W1274-162
CCHP-based microgrids can be expressed as:
MIN = ∑ [() + () + () + () − ()]∆
24
=1 (3-10)
() = () + () (3-11)
() =
()+()
2
() +
()−()
2
|()| (3-12)
() = ∑
5
=1 |()| (3-13)
() = ∑ max {0, () − ( − 1)}
3
=1 ,
(3-14)
() = ℎℎ() (3-15)
Where is the total costs, (), (), (), () and () are the
fuel costs, power interaction costs, maintenance costs, start-up costs and heat selling
benefits at time slot t respectively. () is the interactive power between microgrid
and main electric grid at time slot t. () and () are sale price and purchase
price of exchanged electricity at time slot t respectively. is unit maintenance costs
of the ith unit (including MTs, FCs, EBs, WTs and PVs). () is output power of the
ith unit at time slot t. () is the operational state of the jth controllable generator
(including micro turbines, fuel cells and electric boilers), if a controllable generator is
running, then () should be 1, otherwise () should be 0. ,
is the start-up
and shut-down costs per time of the jth controllable generator. ℎ is unit heat
purchase price and ℎ() is the amount of heat loads in the microgrid at time slot t.

3.7.2 Constraints
The model of the optimal operation of CCHP-based microgrids is subject to the
operational constraints of each unit in microgrid and system-wide constraints. The
Project No.W1274-162
component constraints are listed as follows, including the operation constraints of
controllable generators and energy storage:
The output power of controllable generators should not exceed the limit, and the
variation should not exceed the maximal ramping power.
≤ () ≤ (3-16)

∆ ≤ () − ( − 1) ≤
∆ (3-17)
In (3-16), () is the output power of the jth controllable generator (including
electric boilers, micro turbines and fuel cells) at time slot t, and are the
minimum power and maximum power of the jth controllable generator respectively,
which rely on the generators’ characteristics. In (3-17),
and

are the
downward ramping power and upward ramping power of the jth controllable generator
respectively.
As for energy storage, operation constraints of it mainly include capacity
constraints, charging/discharging constraints, and the amount of energy stored in the
tank at the beginning and the end of circle should be equal. These constraints can be
expressed as follows: (because the constraints of electric energy storage and thermal
storage are the same, only the constraints of electricity are listed in order to avoid
repetition.)
≤ () ≤ (3-18)
0 ≤ () ≤ , (3-19)
0 ≤ ℎ() ≤ , (3-20)
(0) = (24 × ∆) (3-21)
Project No.W1274-162
Where is the total capacity of electric energy storage. , are
the maximum value and minimum value of state of charge (SOC) for energy storage
respectively, range from 0 to 1. Besides, , and , are the maximum value
of discharging and charging power of energy storage respectively, which are affected
by the amount of energy stored in the bank at time slot t-1.
Apart from the component constraints, a CCHP-based microgrid still needs to
satisfy the energy balance constraints and tie-line power constraints, which can be
expressed as follows:
() + () + () + () − ℎ()
+() + () = () + () (3-22)
−ℎ() + () − ℎ(t)+ =ℎ() (3-23)
≤ () ≤ (3-24)
In (3-22), () is electrical loads in the microgrid at time slot t. In (3-24),
and are the minimal power and maximal power of tie-line.


Chapter 4.
Solving methods
In this paper, I use PSO algorithm and lingo software to solve this optimization
Project No.W1274-162
problem. Lingo software has some advantages of the software operational research in
modeling and solving of optimization problems. It can formulize problems quickly as
well as easy to read, understand and modify, which dramatically increases the efficiency
of solving this kind of problem[20].

4.1 PSO Algorithm
Particle swarm optimization(PSO) algorithm is a method of resolving optimal
problems. Any set of coordinates in the n-dimensional space stands for a solution to the
optimal problem, called particle. It has a concrete value of fitness function. Each
particle also has a position in the search-space and an associated velocity. Particles
move in accordance with the velocity and their best positions. As a result, a migration
of swarm will get closer and closer to the global optimum.

4.2 Solution Process
According to the economical dispatch model of CCHP-based microgrids
established in Chapter 3, the optimization problem that needs to be solved can be
expressed as:
min ((), ()) (4-1)
Project No.W1274-162
This optimization problem contains a lot of high-dimension variables and it is a
non-linear dynamic optimizing problem. PSO algorithm was used to solve it. The exact
optimizing process of PSO algorithm is shown in Fig. 4.1:
Fig4.1 The exact process of PSO algorithm
If Pbest>gbest, gbest=pbest.
Otherwise gbest remain the same
Start
Input basic data, algorithm parameters
and the range of decision variables
Random initialization of the swarm
calculate the fitness of each particle (pbest)
Computation of global best value (g)
Updating of velocities and positions
Computation of the fitness of each particle (pbest)
Reach the maximal number of iterations or gbest
meet the conditions?
NO
YES
End
Project No.W1274-162
Chapter 5.
Simulation and Results
5.1 Case Study
In the case study, the testing environment is Dell Ins14-7460-D1725, 2.70Ghz with
dual core four threads. The program is developed using LINGO 11.0.
The case is based on a real-world grid-connected CCHP-based microgrid in
Northern China. The real-time prices in Shandong Province, China on 3 March 2016
are adopted. This microgrid contains wind turbines, photovoltaic cells, CCHP system,
electric boilers, fuel cells, electric energy storage and thermal storage. Unit scheduling
time ∆ in this paper is 1 hour. The interactive power remains constant during one hour.
Besides, in order to use energy effectively, the waste heat which produced by micro
turbines is fully absorbed by LiBr absorption chillers.
Based on the wind speeds and illumination intensity, () and () can
be calculated and shown in Fig. 4.2.
Project No.W1274-162

Fig 5.1 The output power of wind turbines and photovoltaic cells
The parameters of components in the CCHP-based microgrid are listed in Tab.
5.1.
Tab 5.1 The parameters of components in the CCHP-based microgrid
Unit /KW /KW /(KW·h) /(KW·h) /¥

WT 40 0 / / 0.0196 /
PV 30 0 / / 0.0235 /
MT 65 15 300 60 0.0250 1.94
FC 40 5 120 120 0.0260 1.2
EB 50 0 180 300 0.0160 2.74
grid 60 -60 / / / /
Let initial state of all the controllable generators be a stopped status (which means
that (0) =0). Besides, recovery rate of absorption chiller ℎ is set to be 0.9,
coefficient of performance of absorption chiller ℎ is 0.95, and
loss rate of heat dissipation is 15%. Besides, unit heat purchase price ℎ is set to
be 0.1 ¥/(KW·h).
0
5
10
15
20
25
30
35
40
45
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
P
o
w
er
/K
W
Time/h
wind power photovoltaic power
Project No.W1274-162
The prices of electricity (including sale price of exchanged electricity () and
purchase price of exchanged electricity ()) at difference time of a day are shown
in Fig 5.2. And Fig 5.3 displays the heat loads and electrical loads in microgrid.

Fig 5.2 The prices of electricity
In this article, 24 hours of a day are divided into three periods: peak periods are
10:00-15:00, 18:00-21:00 (when () and () ≥0.4¥), valley period are 00:00-
07:00, 23:00-24:00 (when () and () ≤ 0.2¥), and flat periods are 07:00-
10:00, 15:00-18:00, 21:00-23:00.

0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
p
ri
ce

time/h
purchase price of exchanged electricity
sale price of exchanged electricity
Project No.W1274-162

Fig 5.3 The heat loads and electrical loads in microgrid
The parameters of energy storage are set up in Tab 5.2.
Tab 5.2 Parameters of energy storage
Type / /ℎ , , (0)
/(0)

Electric
storage
0.001 0.9 0.2 0.8 37.5 37.5 30 120
Thermal
storage
0.01 0.9 0 0.9 45 45 0 135
To demonstrate the benefits of CCHP systems, the results in two other common
dispatch mode for microgrid are also calculated. In this paper, the total costs of
microgrid in three different operation modes are compared:
(1) Mode 1: Separate generation of power and heat. Heat energy is supplied by
boilers (heating efficiency of a boiler is 85%), while power energy is supplied
by electric energy storage and all kinds of micro sources. In this mode, heat
network and power network are separate and irrelevant.
(2) Mode 2: Following heat load mode. Firstly, calculate the output power of
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
lo
ad
/K
W
Time/h
electrical loads heat loads
Project No.W1274-162
micro turbines and electric boilers depending on the load demand in microgrid.
And then determine the output power of other units in microgrid according to
the electric load demand.
(3) Mode 3: Cogeneration of heat and power, which is the method used in this
paper (CCHP systems).


5.2 Results
Based on calculations in LINGO, the power load balance conditions in microgrid
under three different modes are shown in Fig 5.4-Fig 5.6.

Fig 5.4 Power load balance condition under mode 1
-60
-40
-20
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
P
o
w
er
/K
W
Time/h
Mode 1
micro turbines fuel cells
wind turbines photovoltaic cells
electric energy storage interactive power
power load
Project No.W1274-162

Fig 5.5 Power load balance condition under mode 2

Fig 5.6 Power load balance condition under mode 3
Fig 5.7-Fig 5.9 reflect the heat balance condition in microgrid under 3 different
modes.
-100
-50
0
50
100
150
200
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
P
o
w
er
/K
W
Time/h
Mode 2
micro turbines fuel cells
electric boilers electric energy storage
interactive power wind turbines
photovoltaic cells power load
-100
-50
0
50
100
150
200
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
P
o
w
er
/K
W
Time/h
Mode 3
micro turbines fuel cells wind turbines
photovoltaic cells electric energy storage interactive power
electric boilers power load
Project No.W1274-162

Fig 5.7 heat balance condition of microgrid under mode 1


Fig 5.8 heat balance condition of microgrid under mode 2
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
h
ea
t
p
o
w
er
/K
W
Time/h
Mode 1
系列1 系列2
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
h
ea
t
p
o
w
er
/
K
W
Time/h
Mode 2
micro turbines electric boilers heat load
Project No.W1274-162

Fig 5.9 heat balance condition of microgrid under mode 3
Moreover, Tab 5.3 reflect the operation costs of microgrid under 3 different
modes.
Tab 5.3 operation costs of microgrid under 3 different modes (¥/day)
Costs Mode 1 Mode 2 Mode 3
Fuel costs of MT 341.964 1357.583 718.1635
Fuel costs of FC 318.1234 157.2904 294.56
Fuel costs of BL 843.2714 / /
Start-up costs 3.14 10.96 8.22
Maintenance costs 83.70433 56.47743 50.22339
Heat selling
benefits
278.11 278.11 278.11
Interaction costs 962.68387 365.9192 352.926
Project No.W1274-162
Total costs 2274.777 1670.120 1145.982
5.3 Analysis
Table 5.3 describes operational costs of microgrid under three different modes.
From the table, we can see clearly that mode 3 costs least money of microgrid during
run time (only 1145.982 ¥/day), followed by mode 2 (1670,120 ¥/day). What’
noticeable, mode 1 costs more than twice as much as that of mode 3. In this chapter,
comparison and discussion were done with these three different modes in order to verify
the benefits of CCHP systems.
In mode 1, heat and power were dispatched separately without affecting each other.
Fig 5.7 illustrates that Boiler was the only provider of heat loads and it stayed opened
during the 24 hours. Besides, the heat power of boiler was equivalent to the amount of
heat loads in microgrid. Micro turbines, fuel cells and electric energy storage functioned
together in order to satisfy the electric loads demand, based on constraints mentioned
above. Because the waste heat produced by micro turbines was not been utilized in
mode 1, the fuel costs of BL were quite expensive, which made mode 1 not economical.
In mode 2, electricity was ordering by heat, and heat loads are mainly supplied by
micro turbines. When the heat energy produced by micro turbines were not able to meet
the needs, electric boilers would be turned on and made up the difference. (Fig 5.8) The
power of micro turbines, electric boilers, energy storage and interactive power
collectively met the electric loads in microgrid. Because heat efficiency of micro
turbines is higher than that of boilers, the total costs under mode 2 were lower than
Project No.W1274-162
under mode 1. However, the output power of micro turbines and electric boilers were
limited by heat loads, which means that they could not give their potentials to full play
or some of them were idle, resulting in wasting of resources.
In mode 3, energy storage was utilized in order to eliminate the limitation of the
output power of MTs and EBs. All the units in microgrid worked together with the
purpose of minimizing operational costs. A unified objective function was used to
optimize the power generation costs as well as the heat supply costs, which means that
heat energy and power energy were combined under this mode. Heat loads and electric
loads were supplied by MT, FC, EB, PV, WT, ES, HS together, based on generation
costs and operational constraints. Tab 5.3 gives the information that mode 3 spent most
of the money on MT fuel (718.1635¥, nearly 63% of the total costs). However, the total
costs of it were the least among the three modes.
It can be seen from Fig 5.6 that in mode 3, EBs would use electricity to generate
heat energy during valley periods (when the purchase price of exchanged electricity is
much lower than other time periods), which means that power energy would join in the
dispatch of heat energy. During peak periods (when the purchase price of exchanged
electricity is higher than other time periods), MTs would increase the amount of
heat/power generation so as to take the place of interactive power and EBs to satisfy
the load demand, which made contributions to reduce the exchanged electricity bought
from main electrical grid. As for flat periods, HS release heat energy to reduce the
output power of MTs.
The primary energy ratio of three modes are presented in Tab 5.4.
Project No.W1274-162


Tab 5.3 primary energy ratio of three modes
Mode primary energy ratio
Mode 1 80.67%
Mode 2 89.24%
Mode 3 88.59%
It can be seen from Tab 5.3 that primary energy ratio of mode 2 and mode 3 are
both higher than mode 1, but mode 2 is slightly higher than mode 3. This is mainly
because in mode 3, heat power of EBs and MTs were not based on heat loads in
microgrid, and there was some heat energy lost through heat energy storage.
By the analysis above, the cogeneration of heat and power energy (mode 3) is the
most cost-saving and effective way to operate a microgrid, compared to separate
generation of power and heat (mode 1) and ordering power by heat (mode 2).








Project No.W1274-162
Chapter 6.
Conclusion and future work
To reiterate, this project was conducted with the objective of investigating optimal
operation of CCHP in a comprehensive energy network. A model of CCHP-based
microgrid was established, the optimal operation of it was calculated using PSO
algorithm and the total costs of three different operation modes were compared in this
project.
From the result generated, it was found that the power load demand is satisfied
with the supply of different kinds of components in the microgrid. In addition, the
outcome also showed that CCHP system can help people to reduce the operation costs
as well as improve rate of energy utilization. When there is insufficient electricity
supply, the energy supply can be transformed from CCHP systems to satisfy the power
load demand. With the coordination of CCHP systems, microgrid is able to guarantee
the security of the bulk power system.
Moreover, Lingo is the developing environment I used during the whole project.
It is indeed a very convenient and popular mathematical tool, which is usually used to
solve optimal problems. Therefore, learning and mastering Lingo is a great progress I
have got in this project.
However, this project has some limitations. I only considered some operation
constraints and energy balance constraints when I was calculating the results. However,
Project No.W1274-162
system load flow also limits the operation of CCHP-based microgrid. Also, although
CCHP systems can bring some negative impacts to the environment, environmental
costs were not considered in this project. In addition, microgrid has both island and
grid-connected modes, but only grid-connected microgrid was discussed.
Due to the limitations, my future work will be focused on the environmental costs
of CCHP systems and system load flow of CCHP-based microgrid. Also, other than
grid-connected mode microgrid, my future investigation can be extended to cover the
island mode microgrid. Since energy crisis around the world is getting more and more
serious, CCHP systems need to be further developed and studied. With the development
of a smart grid, I believe more and more achievements will appear to make
contributions to CCHP systems.









Project No.W1274-162
References
[1] Gambino, G., et al. Optimal operations and load allocation of a power plant
equipped with a CCHP feeding power, steam and cold water to an industrial
plant. in Control Conference (ECC), 2016 European. 2016. IEEE.
[2] Qin, Z., et al., Energy integration and economical optimization of small scale
cchp system. 2006.
[3] Stadler, M., Gonçalo Cardoso, Salman Mashayekh, Thibault Forget, Nicholas
DeForest, Ankit Agarwal, and Anna Schönbein, Value Streams in Microgrids: A
Literature Review. Applied Energy, 2015.
[4] Rifkin, J., The third industrial revolution. Engineering & Technology, 2008.
3(7): p. 26-27.
[5] Wang, J.-J., Y.-Y. Jing, and C.-F. Zhang, Optimization of capacity and operation
for CCHP system by genetic algorithm. Applied Energy, 2010. 87(4): p. 1325-
1335.
[6] Mago, P. and L. Chamra, Analysis and optimization of CCHP systems based on
energy, economical, and environmental considerations. Energy and Buildings,
2009. 41(10): p. 1099-1106.
[7] Liu, M., Y. Shi, and F. Fang, A new operation strategy for CCHP systems with
hybrid chillers. Applied energy, 2012. 95: p. 164-173.
[8] Wang Rui, G.W., Wu zhi, economical optimization of CHP-based microgrids
including renewable energy. Automation of Electric Power Systems, 2011.
35(8): p. 22-27.
[9] Cho, H., et al., Evaluation of CCHP systems performance based on operational
cost, primary energy consumption, and carbon dioxide emission by utilizing an
optimal operation scheme. Applied Energy, 2009. 86(12): p. 2540-2549.
[10] Chen J, Y.X., Zhu L, optimal multi-objective economical dipatch of microgrids.
Proceedings of The Chinese Society for Electrical Engineering, 2013. 33(19):
p. 57-66.
[11] Wu X, W.X., Wang JX, Economic Generation Scheduling of a Microgrid using
Mixed integer programming. Electric Power Automation Equipment, 2013.
33(28): p. 2-8.
[12] WU Xiong, W.X., BIE Zhaohong,WANG Jianxue, Economic operation of
microgrid with combined heat and power system. Electric Power Automation
Equipment, 2013. 33(8): p. 1-6.
[13] Fubara, T.C., F. Cecelja, and A. Yang, Modelling and selection of micro-CHP
systems for domestic energy supply: The dimension of network-wide primary
energy consumption. Applied Energy, 2014. 114: p. 327-334.
[14] Wenjian, W.C.H.B.G.L.Z.D.L., A General Modeling Method for Optimal
Dispatch of Combined Cooling, Heating and Power Microgrid. 33, 2013. 31: p.
26-33.
[15] Brahman, F., M. Honarmand, and S. Jadid, Optimal electrical and thermal
Project No.W1274-162
energy management of a residential energy hub, integrating demand response
and energy storage system. Energy and Buildings, 2015. 90: p. 65-75.
[16] Xu, L., et al., Combined scheduling of electricity and heat in a microgrid with
volatile wind power. Dianli Xitong Zidonghua, 2011.
[17] Salam, A., A. Mohamed, and M. Hannan, Technical challenges on microgrids.
ARPN Journal of engineering and applied sciences, 2008. 3(6): p. 64-69.
[18] Swider, D.J., Compressed Air Energy Storage in an Electricity System With
Significant Wind Power Generation. IEEE Transactions on Energy Conversion,
2007. 22(1): p. 95-102.
[19] Khurmi, R. and R. Sedha, Material science. 2004: S. Chand & Company.
[20] Liu, B. and N. Jin. An application of lingo software to solve dynamic
programming problem in the field of environmental protection. in 2015 IEEE
Advanced Information Technology, Electronic and Automation Control
Conference (IAEAC). 2015.
















51作业君 51作业君

Email:51zuoyejun

@gmail.com

添加客服微信: ITCSdaixie