Optimal operation of micro energy networks based on energy hub model

A mathematical model is constructed with the objective of optimizing total energy cost during the day, including some constraints such as input-output energy balance of the EH, electrici

Optimal operation of Micro energy networks

based on energy hub model

A Dissertation Submitted for the Degree of Doctor of Philosophy

Candidate：Ha Thanh Tung Supervisor：Prof YongJun Zhang

South China University of Technology

华南理工大学 学位论文原创性声明

本人郑重声明：所呈交的论文是本人在导师的指导下独立进行研究所 取得的研究成果。除了文中特别加以标注引用的内容外，本论文不包含任 何其他个人或集体已经发表或撰写的成果作品。对本文的研究做出重要贡 献的个人和集体，均已在文中以明确方式标明。本人完全意识到本声明的 法律后果由本人承担。

作者签名： 日期： 年 月 日

学位论文版权使用授权书

本学位论文作者完全了解学校有关保留、使用学位论文的规定，即： 研究生在校攻读学位期间论文工作的知识产权单位属华南理工大学。学校 有权保存并向国家有关部门或机构送交论文的复印件和电子版，允许学位 论文被查阅（除在保密期内的保密论文外）；学校可以公布学位论文的全 部或部分内容，可以允许采用影印、缩印或其它复制手段保存、汇编学位 论文。本人电子文档的内容和纸质论文的内容相一致。

本学位论文属于：

□保密，（校保密委员会审定为涉密学位时间： 年 月 日）

于 年 月 日解密后适用本授权书。

□不保密,同意在校园网上发布，供校内师生和与学校有共享协议 的单位浏览；同意将本人学位论文编入有关数据库进行检索，传播学位论 文的全部或部分内容。

(请在以上相应方框内打“√”)

作者签名： 日期：

指导教师签名： 日期：

作者联系电话： 电子邮箱：

摘 要

在当今经济社会活动中，能源发挥着重要的作用。一方面，能源成本是产品价值的重要影响因素；另一方面，能源的安全和由能源利用所引发的环境问题也促使人类不断探索节能以及环保的新模式，促进了科学和技术的发展革新。当前针对能源危机和环境问题，全球科学家重点关注的一个解决方案就是构建能够综合不同类型能源的能源网络，即综合能源系统。通过综合能源系统增强用户用能的可靠性、减少环境污染、提高能源综合利用效率，推进社会资源环境的可持续性发展。

能量枢纽（Energy Hub，EH）是构建综合能源系统的一个重要基础。能量枢纽模型构建了一个可连接各种类型能量，并且可以灵活响应各种负荷需求的微能源系统模型，适用于居民区以及市中心等负荷集中区。如今，城市化的快速发展导致了负荷的激增以及负荷使用类型的多样化，同时，先进的可再生能源技术以及存储和转化技术在提高能源效率方面也取得了重大的进展。因此需要新的研究方案来改进能量枢纽的结构并且解决多个能量枢纽构建的微能源网模型的最优运行的问题。本文将在能量枢纽模型的基础上，对综合微能源网的优化运行问题进行分析，本文的主要内容分为以下三个部分：

1、为突破现有 EH 建模研究的局限性，本文提出了一种扩展 EH 模型，用于提高住宅区负荷的综合能源利用效率，降低能源使用成本。这个扩展模型考虑到了太阳能

（包括太阳能的光电利用和光热应用）与电池储能系统(Battery energy storage system，BESS)相结合。在现有的能源价格及满足能源负荷需求的前提下，以一天能源使用总成本最低为目标，对 EH 中设备及外部供能的功率分配进行优化。约束条件包含了 EH 输入-输出的能量平衡，设备的容量限制以及 BESS 的荷电状态约束等。仿真算例对比分析了在不同 EH 结构的情况下，太阳能光电、光热利用和 BESS 对运行调度的影响。结果表明所提出的模型对优化用户综合用能具有较好的效益，并且，该 EH 结构和运行优化模型适用于住宅型园区的负荷。

2、EH 的结构特征和优化运行对园区供能特性和可靠性具有重大影响。为了更好地实现园区的优化供能，通过同时关注 EH 的结构特征和优化运行来协同园区的能源优化至关重要。由于目前对同时考虑 EH 系统结构及优化运行的联合优化问题缺乏研究，因此，本文研究着重于建立快速识别系统最优结构并同时满足最优运行两个目标的数学模型。具体地，本文提出了具有 12 个元件（包括能量输入、转化以及储存元件）的

EH 模型。在该优化问题中，采用二进制变量来表示元件使用与否的状态，当二进制变

量为 0 时，代表该元件未被使用，而当二进制变量为 1 时，代表该元件处于使用的状态中。通过 12 个元件的组合，本文提出了 144 种具有不同能量枢纽结构的优化场景，并针对不同场景下的能量枢纽最优运行结果进行了比较。在对优化结果进行比较后可以发现，对结构和运行进行统一优化之后得到的能量枢纽的最优结构与 144 种不同结构中对运行进行优化后成本最低的结构是相同的。因此，本文所提的数学模型能够快速准确地同时解决结构和运行的最优化问题。

3、基于对含有多个 EH 优化运行研究的不足，并考虑到可再生能源和储能系统在微能源网中逐渐广泛应用的场景，本文提出了微能源网络（MEN）的协调优化运行的方法，该微能源网络包括了光伏、风电、电网和天然气传输网、以及多个 EH。本文引入了四种不同的运行方案（单纯考虑电力作用、考虑电能和天然气的作用、考虑电力天然气以及可再生能源的作用、考虑电力天然气可再生能源以及储能共同的作用）来评估能源类型和储能系统对微能源网性能的影响。求解的结果表明，与传统的单纯电力供应网络相比，在考虑太阳能，风能和储能系统的能量枢纽基础上构造的能量枢纽效率更高。

本文采用通用代数建模系统（GAMS）对所建立的数学模型进行求解，本文得到的结论对构建小规模多能量需求的能源管理模型具有重要的指导意义。

关键词：微能源网；能量枢纽；优化运行；GAMS；BESS；最优结构

Abstract

Energy plays an essential role in all social and economic activities with deep engagement Energy cost is one of the key-driven factors contributing to industry manufactory and even other social areas such as culture and politics Energy security and environmental issues have facilitated human beings to explore energy-efficient, economical and environment-friendly models The energy network, combining various different energy categories, tends to be an innovative solution that attracts scientists’ eyeball worldwide Such energy network helps to enhance reliability, reduce environmental pollution, facilitate technology development in the energy system and promote energy sustainability Hereby energy hub (EH) can be used to build up energy network model

In terms of micro energy network (MEN), the multi-energy network operation optimization

is analyzed based on the EH model The solution is applied to the regions with highly intensive energy consumption, including residential areas, urban areas, etc Besides, the rapid urbanization has led to load volume expansion and diversified energy consumption The advanced technology of renewables integration, alongside with storage and conversion sections, has improved energy efficiency The new research proposal is required to optimize

EH structure and operations of MEN model built up by multiple EH This dissertation especially aims to resolve the following key issues:

1/ This thesis presents an extended EH model to optimize total energy use costs for loads in residential areas, with the aim to fulfill the research gap in EH modeling and improving the operational efficiency of multiple forms of energy consumption This extended model considering the involves solar energy (provided by PV and SHE) combined with Battery energy storage system (BESS) The optimization problem is set up based on daily load demand (such as electricity, heat, and cooling) and time-of-use (TOU) energy prices A mathematical model is constructed with the objective of optimizing total energy cost during the day, including some constraints such as input-output energy balance of the EH, electricity price, capacity limitation of the system, and charge/discharge power of BESS Four operational cases based on different EH structures are compared to assess the effect of solar energy applications and BESS on operational efficiency The results show that the proposed

model predicts significant changes to the characteristics of electricity and gas power bought from utilities, leading to reduced total energy cost compared to other cases They also indicate that the model is appropriate for the characteristics of residential loads

2/ The structural and optimal operation of an energy hub has a tremendous influence on the hub’s performance and reliability In order to achieve the global optimum conditions for supplying energy, it is quite essential to develop the optimization research issues by focusing

on hub system structure and operation simultaneously Based on the lack of study about joint optimization problem, this research also concentrates on establishing a mathematical model to rapidly identify the optimal model structure that simultaneously satisfies two objectives: optimizing operating costs and selecting the optimal operating structure The objective of the investigation is to penetrate into this joint optimization problem with a handy calculation method This thesis envisions an innovative methodology that prominently increases the synergy between structural and operational optimization and targets system cost affordability The generalized energy system structure is presented theoretically with all selective hub sub-modules, including electric heater (EHe) and solar sources block sub-modules To minimize energy usage cost, an energy hub is proposed that consists of 12 kinds of elements (i.e., energy resources, conversion, and storage functions) and is modeled mathematically in a General Algebraic Modeling System (GAMS), which indicates the optimal hub structure’s corresponding elements with binary variables (0, 1) Simulation results contrast with 144 various scenarios established in all 144 categories of hub structures, in which for each scenario the corresponding optimal operation cost is previously calculated These case studies demonstrate the effectiveness of the suggested model and methodology

3/ Previous peer research seldom addresses the problem of multiple EH optimal operations Considering integration of renewables and storage systems, the dissertation proposes a method to coordinate optimal operations in MEN containing electricity and natural gas networks, based on EH model The EH can be considered as the grand network node to contain various categories of energy The demands for electricity, heat, and cooling load can

be fulfilled with the application of conversion and storage devices Four different operating

up by EH, with the integration of solar energy, wind energy and storage systems, is more efficient

The General Algebraic Modeling System (GAMS) is applied to solve the optimal operating problems in this study The dissertation research contributes to the modeling and calculation for flexible and efficient energy management, meeting the demand for small-scale loads with various energy engagement

Keywords： Micro energy network; Energy Hub; Optimal operation, General algebraic

modeling system (GAMS); Optimal structure

Table of Contents

摘 要 I Abstract III Table of Contents VI

Chapter 1 Introduction and Literature review 1

1.1 Motivation 1

1.2 Literature Review 5

1.2.1 Micro energy network 5

1.2.2 Energy hub 7

1.2.3 Optimal operation of EH 10

1.3 Introduction to GAMS programming language 14

1.3.1．Algorithm and solver MINOS in GAMS programming language 16

1.3.2 Algorithm and solver BONMIN GAMS programming language 21

1.4 Research opbjectives 22

1.5 Thesis outline 23

Chapter 2 Energy hub modeling to minimise residential energy costs considering solar energy and BESS 25

2.1 Introduction 25

2.2 Energy hub model for residential area load 26

2.2.1 Some energy supply models 26

2.2.2 The proposed EH model 27

2.3 Solar and BESS technologies 30

2.3.1 Solar 30

2.3.2 BESS technology 37

2.4 Mathematical model 39

2.4.1 The objective funcion 39

2.4.2 Constraints 40

2.5 Simulation Result 43

2.5.1 Database 43

2.6 Summary 52

Chapter 3 Energy Hub’s Structural and Operational Optimization for Minimal Energy Usage Costs in Energy Systems 53

3.1 Introduction 53

3.2 Design of the Model 54

3.2.1 The Energy System’s Structure 54

3.2.2 The Structural Optimization of Hub Modeling 55

3.3 Mathematical Model 58

3.3.1.The Objective Function 58

3.3.2 Constraints 58

3.4 Simulation Result 61

3.4.1 Hub Data Description 61

3.4.2 Calculation Result 63

3.4.3 Result Discussions 68

3.5 Summary 69

Chapter 4 Optimal operation of micro energy networks 77

4.1 Introduction 77

4.2 System modeling 78

4.2.1 The micro energy network based on Energy hub 78

4.2.2 Electricity network 78

4.2.3 Natural network 79

4.3 The optimal operation models 81

4.3.1 The proposed model 81

4.3.2 Mathematical model 84

4.4 Simulation results 87

4.4.1 Case studies 87

4.4.2 Database 88

4.4.3 Calculation result 92

4.5 Summary 98

Chapter 5 Conclusion and Future work 99

5.1 Conclusions 99

5.2 Contributions 100

5.3 Future work 101

References 103

List of Publications 114

Acknowledgments 117

Chapter 1 Introduction and Literature review

Chapter 1 Introduction and Literature review

1.1 Motivation

Energy is an important sector in the socio-economic development process Thus, price fluctuations, institutions or technological advances in energy exploitation and use always attract the attention of researchers and policymakers in every country in the world The 1973 oil crisis was the first bell to warn of potential energy shortages in the future when it was not being exploited and used effectively It was the energy fluctuations in this period that altered the sense of human energy use, changed the way and operating mechanism of the energy system in the world In the context of economic globalization and climate change, the issue of exploitation and optimal use of energy has become increasingly urgent and important

In the past, forms of energy such as electricity, natural gas, and heat often existed as

+ Regarding energy costs, consumers can choose different energy forms with the lowest energy costs For example, cooling needs can use electrical or thermal energy through a switch from power to cool or from heat to cool

In general, the goal of the energy network is to satisfy two economic factors and meet the varied needs of the load This model enhances reliability, reduces environmental pollution, improves stability, and achieves energy efficiency and conservation goals

As technology developed, many power supply models have been researched, applied and put into practice such as microgrids[7], virtual power plants[8], power supply system’s

which was introduced in the project "vision of the future grid"[1], proposed by ETH Zurich

EH is considered as a multifunctional system in the combination of source and loads through

EH and the connection between different forms of energy through this model In general, EH allows the optimal combination of forms of energy; This model can be considered together with storage equipment, dispersed energy sources, electric vehicles, etc

The EH model is designed to meet the needs of high-load payload such as residential areas, urban areas This load object recently has fast growth and demand increasingly used Besides, new and renewable energy technologies, storage technology and energy conversion have made great research achievements to improve the efficiency of energy exploitation and conversion Therefore, in this thesis, the EH model and the optimal operation of the energy network system are studied in the MEN suitable for the charge of residential and urban areas The proposed model helps connect and maximize the efficiency of applications from renewable energy, energy storage systems The reasons for the implementation of the thesis are analyzed in detail according to the main research contents of the thesis as follows:

First: this thesis aims to present an extended EH model to optimize total energy use costs for loads in residential areas This extended model considering the involves solar energy (provided by PV and SHE) combined with BESS:

Along with the development of the energy internet (EI), renewable energy and energy storage technology are the two solutions being rapidly developed under the pressure of rising energy demand in modern society In recent years, solar photovoltaic (PV) generation and solar heat exchanger (SHE) have been widely adopted through shortened construction time due to their modular structure and fewer restrictions on installation space[19-21] These clean energy sources will be well adapted to loads in residential areas However, before the concept

of an EH appeared at the Swiss Federal Institute of Technology in Zurich[1], no research exploited the use of solar energy in a coordinated way, including heat and electricity, rather than individually Therefore, EH modeling and optimal operation need to consider these two types of energy to fully improve the efficiency of solar energy Recently, a study [22]

Chapter 1 Introduction and Literature review

to replace proportions of electricity and gas bought from utilities However, the EH structure did not fit with the characteristics of residential loads because the output only considered the use of electricity and heat power; in addition, the need for cooling is also very high in some climates

Battery energy storage systems (BESS) are a fundamental solution to improve power supply reliability and economic efficiency of PV For example, [23] coordinated BESS with

PV in planning problems to reduce investment costs, operating and environmental pollution; [24] obtained improved economic efficiency by adjusting the load curve to reduce purchasing power costs of the system Besides, the BESS can be used to adjust the load curve by storing

BESS is an efficient energy storage method which is mentioned in some studies about the distribution grid, and there are many EH models taking into account energy storage devices to improve the operational efficiency of the system[22], [27-32] But so far, there is no research about the involvement of BESS as an integrated part of an EH model

Generally speaking, PV and SHE have transformed energy usage in residential areas, while BESS are becoming important It is very important to model an EH which includes PV, SHE and BESS to improve the operational efficiency of multiple forms of energy consumption Therefore, this study aims to present an extended EH model to optimize total energy use costs for loads in residential areas This extended model considering the involves solar energy (provided by PV and SHE) combined with BESS The proposed structure uses both air-conditioners (AC) and absorption chillers (ACh) simultaneously to meet the cooling demands of loads in residential areas and to enhance the flexibility of converting between different types of energy

Second, this thesis establishes a mathematical model to rapidly identify the optimal model structure that simultaneously satisfies two objectives include optimizing operating costs and selecting the optimal operating structure:

EH studies are primarily aimed at ensuring optimum performance with different loading patterns in a multi-energy distribution system Typically, these studies will propose adding one or more elements to alter the structure of the model For example, the extended EH structure is complemented by BESS combined with solar energy (through PV and solar

thermal equipment) to increase the efficiency of the model[12]; Research [33] compared the efficiency of energy cost savings with the traditional form of electricity and thermal power by proposing a new structure for EH (considering additional central air conditioning to meet cooling demand of the load); Studies [34], [35], [29] supplemented additional energy storage devices that increased the efficiency of EH; [36] evaluated the performance of EH in the consideration of the participation of wind energy and solar energy in four different scenarios Thus, it can be seen that the optimal energy supply for the load does not depend entirely on the operation of the model, but also depends largely on the EH structure and the properties of the transformed energy form Therefore, to achieve a comprehensive optimization goal, simultaneous optimization and optimization of EH should be made In all the actual research done so far, the optimal operation and optimization of the structure are often considered separately, and the simultaneous optimization of these two factors is rarely mentioned

There is no doubt that components selection in an EH has a great impact on system performance quality Maintaining the optimal output effects of an EH will not only rely on appropriate operation modes but also on its architecture as well as the properties of conversion and storage elements Such results found in the above studies [13,37], despite obtaining the optimum model, are highly complex when being computed due to listing all of the categories of structures In order to achieve the global optimum conditions for supplying energy, it is quite essential to develop the optimization research issues by focusing on hub system structure and operation simultaneously However, most studies ignore this joint optimization problem and just pay close attention to only a single perspective Consequently,

it is necessary to establish a mathematical model to rapidly identify the optimal model structure that simultaneously satisfies two objectives: optimizing operating costs and selecting the optimal operating structure The objective of this investigation is to penetrate into this joint optimization problem with a handy calculation method

Third, this thesis provides the optimal operation of the micro energy networks on the basis of the EH model:

Traditional forms of energy distribution through electrical systems have shown

Chapter 1 Introduction and Literature review

independent EH optimization problem have also been relatively well documented in the studies [22]，[27-32] However, for energy network models formed from multiple EHs, the influence and role of distributed energy (solar, wind) and energy storage systems have not been fully addressed enough New operational problems are solved only in the context of optimizing optimal power flow between EHs without comparing concrete efficiency between traditional energy networks and the electric power grid Therefore, based on the results of the research on completing the structure and the optimal EH calculation, mentioned in the first part of the thesis, this section focuses on establishing and calculating the optimal operation of the power network The EH is considered as a supernode connecting the microgrids (MG) and the natural gas that forms the MEN Suggested scenarios for assessing the impact of energy sources and energy storage systems on the performance of MEN

Fourth, it solves the optimization problem in the GAMS high-level programming language:

Nowadays, optimization has been widely applied in scientific research to solve practical problems The use of optimizing methods is an increasing tendency in the energy field Recent research about the optimal operation of an EH has used different approaches, different objective functions and constraints, and diverse tools including high-level programming

widely used in the optimization of EH, the GAMS[27, 33, 30, 39], uses built-in algorithms

operational problem of EH, based on the energy cost to supply residential area loads The objective is to minimize the total energy cost of the system The resulting program will be more flexible than other available application programs, along with fulfilling consumer demands

1.2 Literature Review

1.2.1 Micro energy network

MEN is an extended concept of a microgrid, which is a new development trend of traditional small power distribution networks[41] To put it simply, MEN refers to a small-

scale energy network that can connect to other energy networks or operate independently This model is suitable for people in residential areas, urban areas, parks, factories, schools, etc MEN includes power supplies, distributed energy, energy storage components and loads (Figure 1-1) Based on this concept, MEN uses key energy sources such as electricity, gas, and heat through versatile conversion systems to manage and optimize all types of energy simultaneously

MEN has the following advantages: From the point of view of energy supply, MEN can promote new and renewable energy applications, especially solar applications (photovoltaics and surface heating), combined with natural gas, electricity and other forms of energy, increase the supply From the point of view of energy supply service, MEN reduces energy costs, emissions, and peak loads while simultaneously optimizing the diversity of loads From the perspective of energy network structure, the coordinated operation of the electricity and natural gas networks will promote the development of versatile energy technology and the

Chapter 1 Introduction and Literature review

MEN is part of the integrated energy system (IES) In the world, many countries have

identified that this will be the main form of energy supply in human society from 30 -50 years The concept of IES was first introduced and applied in practice in European countries Japan

is the earliest country in Asia to deploy this problem The United States, Canada and other developed countries have soon put IES into the national energy strategy

Researchers focus primarily on technical issues of the MEN For example, the MEN structure was introduced in the study [50] The issue of MEN planning on the basis of the characteristics of electric power, heat and cold is presented in [51], [52] Optimized storage architecture References [53-60] investigate the economics and optimal control of MEN

1.2.2 Energy hub

1/ Basic Concept

The EH is defined as an integrated system in which the energy carriers can be converted, conditioned and stored Different levels of the EH are demonstrated in Figure 1-2 Within an energy hub, various forms of energy are received at the input ports, which are connected to the energy infrastructures Then at the output ports, the energy services in form of electricity and heating are delivered for further uses

Figure 1-2 Energy hub topology

Overall, the structures of an EH include input power, such as electricity and gas, which

are named Pe and Pg respectively, and output power, such as electricity and heat, which are

generation (DG) with input PDG and output LDG The features of storage (S1, S2) and

conversion (c1, c2) of electricity and heat energy are also included The EH model is

The EH has many advantages over existing power systems EH enables the connection of

a variety of energy types, especially when connected to distributed energy sources, new energy and renewable energy with traditional forms of energy Benefits of EH are shown in the following specific points:

- Increased reliability of supply: Through the combination of traditional energy and new

forms of energy, the number of supplies increases, leading to increased reliability

- Increased system performance: The energy storage system addresses the problem of

intermittent supply of renewable forms of energy such as wind and solar during periods of excess capacity and additional input at the times of higher demand In addition, EH allows for the full exploitation of new and renewable energy in various forms to maximize their energy supply For example, solar energy can be exploited simultaneously in the form of electricity and heat

- Flexible and diversified forms of energy: The demand for additional energy is not

limited to electrical energy but also heat and cooling EH allows the distribution and management and delivery of multiple forms of energy simultaneously

- Increased power optimization: The connection between multiple forms of energy

through EH allows the optimum mode of operation of the model (optimum power supply) This is of great significance in the problem of source planning and the efficient use of energy

Chapter 1 Introduction and Literature review

3/ Some research areas

So far, many scientists have carried out studies on EH, including such issues as modeling and optimization of energy flows, optimal operation, planning and investment, reliability and maintaining the stability of the model, etc Some main areas of research can be summarized in Table 1-1 as follows:

Table 1-1 Research domains in energy hub studies

Modeling and optimal

energy flow

[1], [12], [14], [15], [17], [18], [33], [62-66]

Proposed EH models are structured in accordance with the requirements and characteristics of the load Calculating the optimal power flow in the energy system is

derived by the EHs

Operation

[13], [28], [34], [36], [37], [38], [67], [68], [69-71]

Energy hub system operation considering energy carriers price and operation objectives

Reliability and security studies [84-92]

Calculate the reliability of the system and evaluate the protection measures in terms of different operating conditions and conditions, especially when there is a positive effect of

the energy storage system

Modeling of distributed energy

resources (DERs) technologies

in energy hub

[22], [29], [36], [93-99]

The role of DERs are modeled in energy

hub system studies

4/ Application subjects

EH is widely applied to the subjects as follows:

- Power plants

- Industrial production area

- High-rise building system

- Residential area

- Remote areas (geographically limited)

- The island area

- Commercial areas (airports, trade centers, etc)

1.2.3 Optimal operation of EH

Research on optimal operation of the EH basically can be divided into two types: Optimize single EH and optimize energy network including many different types of energy based on EHs Optimized EH operations are addressed on the basis of the following key objectives:

- minimizing energy costs[13, 27, 33];

- minimizing CO2 emissions[28, 22, 54]; and,

- maximizing net present value[25,54,55,70,98]

1/ The problem of optimal operation of single EH

a Basic model

Operating optimal energy system is a kind of optimal distribution of different types of energy to meet the operational objectives such as minimum operating costs, minimal carbon emissions or maximum benefits of new forms of energy and so on Meanwhile, it satisfies the technical constraints of the system, namely: Capacity limitation, energy balance, conversion limitation, etc The basic optimization model is expressed as follow (1-2):

min ( )s.t

Models including many different types of energy will have a different distribution L=CP

is the operating condition of the Eh model itself (energy balance equation), reflecting the total relationship between different types of energy during the conversion process expresses the binding conditions of the system and operation equipment

Rapidly increasing urbanization leads to suddenly growing residential energy use to meet various demands Typical EH models of residential energy use include electricity, heat, and cool So far, the establishment and operation of residential EH attract lots of attention from

Chapter 1 Introduction and Literature review

in Canada was conducted in [28], solving problems of peak load, minimal carbon dioxide emission, and energy usage costs; and a model suitable for the residential loads was set up in [22, 33] considering real-time pricing for optimal operation of EH

Figure 1-3 Residential energy hub structure[28]

In addition to the load in residential areas, there have been many studies about the EH in industrial load: Reference [101] conducted an analysis for small-scale combined cooling, heat, and power (CCHP) system, [102] investigated the multi-energy system with hydrogen batteries, with the objective function of maximum economic profit, while considering constraint condition of the power grid and natural gas grid

b．Consider other factors and their benefits

Energy pricing mechanism is one of the important constraints in the optimal management of energy demand: [103] was applied to calculate for 1000 households, using heat pumps to optimize switching demand between electric and thermal energy Based on the constant gas price and electricity price that changes from time to time, the research results showed that in the multi-energy system, household energy use can be met without self-regulating demand Similarly, Research [104] established mechanisms to optimize the energy cost based on electricity price through CCHP model, which optimally meet the needs of heating in winter and cooling in summer of the system

Along with the development of vehicles combining the use of electric motors and diesel motors (plug-in hybrid electric vehicle)-PHEV, the study of the EH model for this type has been expanded and gained much attention Research [27] considered the impact of household

devices based on the EH structure considering PHEV, thus determining total cost and energy conversion of the system Research [105] also examined the optimal PHEV model but got into detailed consideration of electric car models, thus establishing optimal operation problems in a consistent manner with other PHEV models Research [106] reviewed fuel cell system in the electric car with the objective function to minimize energy price and reduce environmental pollution The results showed that the electricity price and development roadmap are the two major factors that affect the optimal results

Multi-energy system has one main advantage that is the emergence of new energy Regarding this, [107] introduced the EH model considering wind power; [108] reviewed an unidentified factor of electricity price and load requirement considering wind power, electricity sale target is applied and considering the risk of selling electricity risk; [22] calculated the optimal operation of the EH model considering the involvement of solar energy Where, solar energy is converted into combined heat and electricity power; [29] built the EH model including the CCHPs and solar batteries, then calculated the optimum operation model for the system of high-rise buildings

2/ Operating networks including multiple EHs

EH models within the multi-energy system are relatively flexible, so the calculation should consider the relative constraint conditions The system structure is built in Figure 1- 4 Between the EHs are electricity, heat, gas systems, etc Between the two EHs there may have conversion between energy types, therefore it can be considered an energy hub as a network node, there is an optimized connection between energy and electricity Then there appears a concept of multiple energy systems optimal power flow

Chapter 1 Introduction and Literature review

Computational model is expressed as (1-3):

Figure 1-5Energy network including multiple EHs[113]

The object of the energy network model formed from EH is quite diverse, small-scale applied to residential areas; larger scale can be applied to the national areas In view of this, research [109] analyzed the modern energy management system to meet the load demand in the energy networks including electricity and gas The paper set up energy network model including 10 hubs Conducting comparative calculations between traditional computation methods and cloud algorithms, the calculated results showed that the model provided high performance for all households, minimized the operating costs of the system In research [110], it pointed out two aspects affecting the operation status of the multi-energy system First, the conversion devices and storage in EH and second is the demand option of the household This study established the uncertain model to describe the unlimited load, thereby considering maximizing the needs of the household Research [111] analyzed and set up the multi-energy system of the industrial port area in ShangHai - China; based on the

characteristics of this region, the study was conducted to optimize 4 different allocated areas Research [112] developed an Eh model applied to a national area, optimizing electricity and gas network in four national European regions

Multiple energy systems optimal power flow including multiple EHs showed that it can improve power quality and reliability of the system In Study [113], it analyzed the energy network consisting of 3 EHs The calculated results showed that this system can meet the node voltage stability, reduce losses in the grid as well as reduce the cost of gas into electrical energy Then, in Study [114], they optimized the multi-energy network consisting of multiple

EH considering power grid voltage limit, reduced amplitude of price and electricity conversion as well as reduced overall system losses

Optimization objective function of multiple Ehs is also quite diverse; including the encouragement on the use of new energy, minimum total costs, etc In Research [115], it established the complex structure of the multi-energy network consisting of multiple EHs, considering outside factors of EH as well as the impact of energy storage devices, DG to the energy network So, Research [116] analyzed 20 kV networks consisting of 9 nodes combined with CHP system, heat conversion devices, substations, considering reactive power costs, encouraging additional reactive power system to ensure system stability Research [117] analyzed the side of energy retail markets, energy system including electricity and gas which was optimized considering the energy prices and costs for the risk in the system A study [16] reviewed the characteristics of storage devices and power load forecasting, which proposed the Model Predictive Control (MPC)

1.3 Introduction to GAMS programming language

GAMS was developed to solve big optimization mathematical problems and can solve many optimization problems such as:

Linear Programming

Nonlinear Programming

Nonlinear Programming with Discontinuous derivatives

Chapter 1 Introduction and Literature review

Mixed Integer Nonlinear Programming, Relaxed Mixed Integer Nonlinear Programming

It must be emphasized that GAMS is not a built-in application program in the power system such as WASP-III, EMTP, PSS/E, PSS/ADEPT… that is a tool, a machine language,

to build calculation program based on a full understanding of the power system, energy networks

GAMS is a high-level programming language in applying to calculate large and complex models The model is presented briefly and simply, allowing to use algebraic connections and independent description with the algorithm Moreover, GAMS provides several optimization algorithms through some built-in solvers as shown in Table 1-2

Table 1-2: The algorithm modules in GAMS

CPLEX, SNOPT, BDMLP

Programming structure in GAMS includes the following basic components:

i) Set (declare of data array size)

ii) Scalar, parameter, table (declaration and data entry)

iii) Variables (variable declaration)

iv) Equations (declarations and building math equations such as objective function, constraints, limits…)

v) Model and Solver (construct problem and revoke solvers)

vi) Output (print result)

Every optimization problem can be programmed on the GAMS using the above basic components Data entry section can be performed simply by assigning directly, in vector, or

in table form Like other programming languages, GAMS can use commands such as THEN, WHILE, LOOP, etc

IF-The most flexible part in GAMS is to build MODEL problem with one single MODEL including objective function and constraint equations The user can program many MODEL

by changing the number of constraint equations and objective function without changing the programming structure This feature is useful when you need to solve a problem with many different

1.3.1．Algorithm and solver MINOS in GAMS programming language

GAMS provides a language, programming environment, and solvers, an algorithm that allows algorithms to be used to find optimal results with open problem models established by the programmer ( used)

The solver MINOS can perform optimal searches for large-scale nonlinear problems The reduced-gradient algorithm, combined with the quasi-newton algorithm, is used to find the optimal solution for the nonlinear problem However, in each case, GAMS uses different algorithms to achieve the highest efficiency Theoretical basis presented in the study [40, 118] GAMS/MINOS is designed to solve large optimization problems with the objective function of the form :

where: F(x) consists of nonlinear components of the objective function with the variable

Chapter 1 Introduction and Literature review

The x component is described as nonlinear variable and the component y is described as linear variables, equations (1-5) are nonlinear contraints and equations (1-6) are linear contraints Constraints (1-7) are for the upper and lower limits of the variable

1/ Linear problem solving method

Without the components F(x) and f(x) the problem becomes linear Then, there is no difference between the variables x and y (which represent the linear components) so we use x instead of y and the linear problem can be expressed as:

where: x is the variable of GAMS and s is the base variable, each constraint s x has a variable

value For convenience in computing, the component b is synthesized in the components GAMS/MINOS solves the linear problem by using a monotonal algorithm when

constraints (1-9) and (1-10) are split into groups base variables (xB) and non-base variables

with permutation vectors (x,s) as (1-11) where B is the square matrix

Normally, each non-base variable within its limit and the base variable takes any value that satisfies the constraint (base variables can be calculated by solving the linear equation

which the column B is replaced by the column of N and vice versa, until the transformation can reduce the value of cTx

2/ Linear problem solving method

If F(x) exists, the problem becomes nonlinear and GAMS/MINOS solves these problems

by a reduced-gradient algorithm in conjunction with the quasinewton algorithm Then, the

contraint Ax + Is =0 is split in the form (1-12) where xB is the base variable and xN is the base variable, xs are the super base variables

At one step, the base and super base variables are within the limit ( in the error range δ)

variables that are allowed to move in any desired directions Therefore, it will improve the convergence of the problem The base variables can be adjusted to further satisfy the linear

constraints If x s has not been improved, it is possible to identify matrices B, S and N according to the present value, and some non-base variables are selected to add to S, the

iteration process is performed to increase the value of s Each step of the reduced-gradient

algorithm is called a loop At all steps, if a base or supper-base variable encounters a limit, non-base variables are implemented and the value of s decrease For a linear function, a simplex algorithm is used with the number of super base variables that oscillate between 0 and 1

An important feature of GAMS/MINOS is the use of the quasi-newton algorithm to optimize the super-base variables This can achieve convergence in any iterative process where B, S, N partitions remain constant By determining q through the equation:

where: g is the gradient of F(x), R is the triangular matrix which is approximated by

with gB is the gradient of the objective function associated with the base variables The same

Chapter 1 Introduction and Literature review

If the constraint function is nonlinear, and exists an f(x), GAMS/MINOS use the

enhancement Lagrange algorithm proposed in the study [118] with a sequence of major loops

to be performed, each loop being solved with linearized constraints The constraint of a linearization problem is a set of nonlinear constraints as well as limit and initial constraints

by changing the value of f(x) as the expression (1-17) f(x k ), J(x k) is the value of the constraint

the i-th constraint function)

 given is expressed in (1-18) Therefore, the subproblem is solved in the kth loop with the

(1-19)

GAMS/MINOS uses a reduced-gradient algorithm to solve the objective functions (1-18) with constraints (1-19) Similar to the linear probblem, the secondary variables are introduced

Az + Is = 0 and are expressed as:

is shown in Figure 1-6

The nonlinear function in this solver must be a continuous function, that is, derivatives are present, often using continuous variables In a given region bounded by constraints and

variables, objective functions, and convex constraints, the optimal solution obtained is a global optimization In contrast, the result may be one of the local optimizations and not guaranteed to be global optimization In this case, it is necessary to identify another ‘close enough’ point for local optimization as a global optimization There is no general rule to determine the ‘close enough’ point, which is difficult for many mathematical problems

Figure 1-6 Solver MINOS solves nonlinear problems

Solve and obtain values

Input initial value

Transform constraint function to

Bx B +Sx s +Nx N =0

Select initial value

X (0) =(x 1(0) x 2(0) , … x n(0) ), k=0

(0) , 

Chapter 1 Introduction and Literature review

1.3.2 Algorithm and solver BONMIN GAMS programming language

BONMIN (Basic Open-source Nonlinear Mixed INteger programming) is an experimental open-source C++ code for solving general MINLP (Mixed Integer Nonlinear Programming), implementing branch-and-bound, branch-and-cut, and outer approximation algorithms[119]

BONMIN can handle mixed-integer nonlinear programming models which functions should be twice continuously differentiable The BONMIN link in GAMS supports continuous, binary, and integer variables, special ordered sets, branching priorities, but no semi-continuous or semi-integer variables

BONMIN implements six different algorithms：

B-BB (default): a simple branch-and-bound algorithm based on solving a continuous

algorithm is like the one implemented in the solver SBB

B-OA: an outer-approximation based decomposition algorithm based on iterating solving and improving of a MIP relaxation and solving NLP subproblems[121, 122]; this algorithm is like the one implemented in the solver DICOPT

B-QG: an outer-approximation based branch-and-cut algorithm based on solving a continuous linear program at each node of the search tree, improving the linear program by

B-Hyb: a branch-and-bound algorithm which is a hybrid of B-BB and B-QG and is based

on solving either a continuous nonlinear or a continuous linear program at each node of the search tree, improving the linear program by outer approximation, and branching on integer variables[124]

B-ECP: a Kelley's outer-approximation based branch-and-cut algorithm inspired by the settings used in the solver FilMINT[125]

B-iFP: an iterated feasibility pump algorithm[126]

The algorithms are exact when the problem is convex, otherwise they are heuristics For convex MINLPs, experiments on a reasonably large test set of problems have shown that B-Hyb is the algorithm of choice (it solved most of the problems in 3 hours of computing

time) Nevertheless, there are cases where B-OA (especially when used with CPLEX as MIP subproblem solver) is much faster than B-Hyb and others where B-BB is interesting B-QG and B-ECP corresponds mainly to a specific parameter setting of B-Hyb but they can be faster

in some cases B-iFP is more tailored at finding quickly good solutions to very hard convex MINLP For nonconvex MINLPs, it is strongly recommended to use B-BB (the outer-approximation algorithms have not been tailored to treat nonconvex problems) Although even B-BB is only a heuristic for such problems, several options are available to try and improve the quality of the solutions it provides

1.4 Research opbjectives

The thesis sets out the following research objectives:

1/ Proposing an extended EH model that is suitable for residential areas while considering solar energy and BESS

2/ Studying on the optimal operation of the proposed model with the goal of minimizing energy cost of EH (including electricity and natural gas purchased from the corresponding system) The constraints include power tariffs, equipment switching limits, power limits, input/output energy balance, charge/discharge power capacity of BESS

3/ Optimizing the EH through different operating scenarios to assess the effects of solar energy and BESS on the efficiency of the operation

4/ Simultaneously solving two problems of optimizing the structure and the operation of

EH to achieve a comprehensive optimization The optimal operation problem is constructed from the mathematical model using binary variables (0, 1) denoting the selected state of the corresponding element forming the optimal EH structure

5/ Optimizing the operation of EH (consisting of 12 elements) through 144 different operating scenarios The operating scenario varies from simple to complex forms given that they always meet the demand for electricity, heat and cooling of the load

6/ Building a model of micro-power network formed by the EHs, in which the EH connects electricity, natural gas, solar, wind and energy storage systems at a small scale

Chapter 1 Introduction and Literature review

7/ Optimizing the operation of MEN with the least operating cost The cost of operation includes the cost of energy use and the cost of greenhouse gas emissions Mathematical constraints include the balancing of the power grid, natural gas, energy balancing of the EHs, charge/discharge power capacity of the BESS, and the energy price

8/ Solving the optimization problems and grid analysis using the advanced GAMS programming language

Chapter 2 presents the problem of building an extended EH model that considers solar and BESS First, it analyzes and compares the advantages and disadvantages of some energy supply models mentioned previously Based on that, it considers proposing the appropriate

EH model considering two solar and BESS factors Next, it constructs the optimal EH operation problem including the objective function and the mathematical constraints Finally,

it performs calculations with different operating scenarios to assess the impact of solar energy (PV, SHE) and BESS on EH’s performance

Chapter 3 solves the problem of simultaneous optimization and EH operation The contents of this chapter first show the full structure of EH by the current energy system model Next, it formulates the problem and introduces the problem-solving method to find the optimal operating structure of the EH model The mathematical model includes the objective function and the constraints added with 12 binary variables corresponding to 12 devices included in the proposed EH configuration The optimized EH structure is compared against all different operating scenarios to assert the correctness of the proposed method through the total operating cost of each alternative EH’s optimized model is especially compared to the highest energy-cost operating scenario and fully structured operating scenario for analyzing and evaluating the impact of structural change

Chapter 4 presents the problem of optimally calculating the operation of the MEN by the

EH model First, the structure of MEN consists of electrical and natural gas networks with problems of energy balance and system structure explained Next, it sets up an optimal

operating problem of MEN is considered with four different cases which simultaneously meet the demand of heat, electricity, and cool of 6 load’s nodes Finally, it analyzes and discusses the results

Chapter 5 presents the key conclusions and research contributions that have been made

in this thesis and identifies future research directions

Chapter 2 Energy hub modeling to minimise residential energy costs considering solar energy and BESS

Chapter 2 Energy hub modeling to minimize residential energy costs considering solar energy and BESS

2.1 Introduction

As introduced in the introduction of the thesis, the optimal operation of the energy network was investigated at the MEN by the EH model EH is a solution suitable for load subjects such as residential areas and urban areas This chapter aims to optimize total energy costs in an operational model of a novel EH in a residential area The optimization problem is set up based on daily load demand (such as electricity, heat, and cooling) and time-of-use (TOU) energy prices The extended EH model considers the involvement of PV generation, solar heat exchanger (SHE), and BESS A mathematical model is constructed with the objective of optimizing total energy cost during the day, including some constraints such as input-output energy balance of the EH, electricity price, capacity limitation of the system, and charge/discharge power of BESS Four operational cases based on different EH structures are compared to assess the effect of solar energy applications and BESS on the operational efficiency The results show that the proposed model predicts significant changes in the characteristics of electricity and gas power bought from utilities, leading to reduced total energy cost compared to other cases

Section 2.2 presents the complete EH model is proposed considering solar energy and BESS The role of BESS technology in managing solar energy through SHE and PV is proposed in Section 2.3 Section 2.4 introduces the objective function and other mathematical constraints of the optimization model Simulation results for four cases with different structures are compared in Section 2.5 to assess the impact of solar energy (PV, SHE) and BESS on the operational efficiency of EH, especially the maximum capacity use of BESS Finally, the conclusion is provided in Section 2.6

2.2 Energy hub model for residential area load

2.2.1 Some energy supply models

Finding solutions, energy supply models that are appropriate to the characteristics and demands of the load is always a matter of primary concern in the energy field Traditional forms of energy supply using only electric energy are no longer suitable Electricity, although having great advantages in exploitation, transmission, storage, and use; However, this type of energy also has some drawbacks, such as the fact that the heat transfer devices are distributed from small and unfocused power sources, leading to complex load management problems Figure 2-1a shows that electricity is the main form of energy supplied to heat and power loads through distribution converters This model, though simple in structure, is easy to operate, but not highly reliable

For more convenience in managing energy demand, the power supply system is further divided as shown in Figure 2-1b This model shows that the heat load was provided independently from natural gas through a boiler (GB) This architecture has the advantage of reducing the power supply from the power system and improving the load management capacity However, the output power is electricity and heat which are independent, no mutual support that leads to improved power supply reliability but not significant

Figure 2-1The traditional model

To overcome these limitations, the study [33] introduced the structured EH model shown

in Figure 2-2 In which, power is provided through the grid and the microturbine Heat (including heat and cooling) is provided by Air-Conditioner, Microturbine and Gas boiler

Chapter 2 Energy hub modeling to minimise residential energy costs considering solar energy and BESS

MT and AC quite is flexible Although this model saves of up to 11.6% over traditional method; however, this study does not explicitly investigate the demand for cooling of the load while this demand is currently very high, especially in residential and urban areas

Heat and cooling demand Electrical demand

Transformer

Air-Conditioner Micro turbine

Gas boiler

Figure 2-2 EH model for loads in residential areas, according to the reference[33]

2.2.2 The proposed EH model

1/ Basic structure of EH for residential loads

To meet the cooling demand of the load, EH is designed as a combined of cooling, heat,

load is supplied by the distribution grid and the power generation unit A part of the heat of the Power Generation Unit (PGU) is collected to meet the cooling and heat needs through Ach and Heating Unit The remaining heat is converted from natural gas through an Auxiliary Boiler According to this structure, three types of energy can be supplied simultaneously, including electricity, heat, and cooling Compared to conventional forms of energy supply, CCHP is highly efficient, low GHG emissions and highly reliable

Figure 2-3A typical CCHP system[5]

In general, in EH studies, the cooling demand for the load is largely met through two AC and Ach devices However, previous studies rarely mentioned the simultaneous configuration

of these two devices Therefore, the basic EH structure, shown in Figure 2-4 is proposed, wherein central air conditioning systems AC and ACh meet the diversity of cooling loads

Cooling demand Heat demand Electrical demand Output

Figure 2-4Basic structure of EH for residential loads

2/ Extended EH model for residential loads

As more and more DG and energy storage devices are installed in distribution systems and residential areas, research in that field will help to promote energy development The residential load is mainly distributed in the delta region; therefore, it is necessary to choose suitable types of DG and energy storage system

At present, the application of solar energy through PV and solar heat exchanger (SHE) has been widely applied This clean energy solution is very suitable for people in the residential area due to lower fuel costs and operating, installation time (due to modular structure), and unrestricted to installation space Thus, solar energy with two PV and SHE applications are selected in the extended EH structure

Energy storage technology is increasingly being focused and developed In particular, the BESS is one of the solutions to bring high efficiency, especially when combined with PV BESS is considered to be an efficient energy storage method that has been mentioned in numerous studies on distribution grids, such as adjusting the load graph by storing electricity during off-peak hours and discharging during peak hours, combined with PV in the planning