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

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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.

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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

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−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

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() 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

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() electrical loads in the microgrid at time slot t

the minimal power of tie-line

he maximal power of tie-line

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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

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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

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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

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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

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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

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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

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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

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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

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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,

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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.

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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.

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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

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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

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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.

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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

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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.

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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

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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,

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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:

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() = (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 −

()

ℎ

∆ (3-8)

In this formula, () is thermal storage capacity at time slot t, while is its

heat losing rate.

ℎ

() and () are heat absorbing power and heat releasing

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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

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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

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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

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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)

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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

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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)

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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

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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.

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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

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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

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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

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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

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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

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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

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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

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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

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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.

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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).

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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,

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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.

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