辅导案例-W1274-162

  • May 15, 2020

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 − () 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 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.

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