Risk-Based Energy Management: DC, AC and Hybrid AC-DC Microgrids

Risk-Based Energy Management: DC, AC and Hybrid AC-DC Microgrids defines the problems and challenges of DC, AC and hybrid AC-DC microgrids and considers the right tactics and risk-based scheduling to tackle them. The book looks at the intermittent nature of renewable generation, demand and market price with the risk to DC, AC and hybrid AC-DC microgrids, which makes it relevant for anyone in renewable energy demand and supply. As utilization of distributed energy resources and the intermittent nature of renewable generations, demand and market price can put the operation of DC, AC and hybrid AC-DC microgrids at risk, this book presents a timely resource.

• Discusses both the challenges and solutions surrounding DC, AC and hybrid AC-DC microgrids
• Proposes robust scheduling of DC, AC and hybrid AC-DC microgrids under uncertain environments
• Includes modeling upstream grid prices, renewable resources and intermittent load in the decision-making process of DC, AC and hybrid AC-DC microgrids

• Language: English
• Publisher: Academic Press
• Release date: Jul 20, 2019
• ISBN: 9780128174920

Book preview

Iran

Preface

Sayyad Nojavan¹, Mahdi Shafieezadeh² and Noradin Ghadimi³, ¹University of Bonab, Bonab, Iran, ²Sharif University of Technology, Tehran, Iran, ³Ardabil Branch, Islamic Azad University, Ardabil, Iran

Penetration of renewable energy sources (RESs) in the power system is increasing day by day all around the world. Generating clean energy, coping with environmental effects, and depleting fossil fuel sources are just some of motivation for utilizing RESs in the system. Besides all those advantages, RESs have disadvantages, such as volatile power output, which may affect power system performance negatively. Among different RESs, wind and solar energy sources are considered the most promising sources, which are widely utilized in the current power system. To accommodate the current power system with the RESs and to overcome the disadvantages of these sources, the concept of microgrids (MGs) is developed, which are defined as a combination of controllable loads and distributed energy resources that can be utilized in grid-connected or islanded modes. In the grid-connected mode, the MG can exchange energy with the upstream grid, while in the remote area the isolated MGs can be utilized to supply the required load. Benefits of implementing MGs in the power system can be counted as reducing power-generating cost, reducing greenhouse gas emissions, and reducing energy losses. The MGs can be classified from different point of views. For example, according to operational frequency they are grouped as AC, DC, and hybrid AC/DC MGs. In another classification, as said before, MGs are divided in two groups, grid-connected and islanded. Based on the control strategy of the MGs, they are grouped as centralized and decentralized. Finally, by taking application of MGs into account, MGs can be classified as utility/military and residential/commercial/industrial.

In the structure of any type of MGs, the battery storage systems can be implemented to cope with the volatile and uncertain power output of RES sources. The battery storage systems store excessive generated energy by wind turbines and photovoltaic systems, and the stored energy can be used when the system encounters a lack of power generation of RESs. It is worth noting that the battery storage units behave as the load when it is charging and act as a generating unit when it is discharged.

Besides the uncertainties of power generation of RESs, there are other uncertain parameters in the system. The power price in the market is the most important one, which can considerably affect the total operating cost of the MGs in grid-connected mode. The effects of all of the mentioned uncertainties in the system should be well studied and different strategies should be developed. To do so, different methods have been developed. Stochastic programming, robust optimization approach, and the information gap decision theory are the most important and effective tools to model any uncertain parameter in the system. Each of these methods has its own advantages and disadvantages. For example, the stochastic programming method can be utilized to model uncertainty when a distribution of the uncertain parameter is available; however, this method suffers from high computational time.

In recent years, the demand response programs have been implemented in the power system to reduce the total operation cost. These programs, which are divided into time-based, incentive-based, and compulsory programs, reduce total operating cost by transferring the load from peak periods to off-peak periods. It this way, construction of new power plants to supply the peak load, which are used only few hours during a year, can be postponed.

Considering these issues, it can be concluded that the developing energy management system for MGs is vital. The optimal energy management of MGs is investigated from different points of view in 13 chapters that are briefly introduced here. In chapter 1, an introduction to the MGs is provided. Deterministic-based energy management of a DC MG is solved in Chapter 2. The stochastic programming, robust optimization, and information gap decision theory methods are used to solve the energy management of a DC MG in uncertain environment in Chapters 3-5, respectively. In Chapter 6, deterministic-based energy management of AC MG is considered. To model the impact of uncertainty of power price on operation of AC MG, the stochastic programming, robust optimization, and information gap decision theory methods are implemented in Chapter 7-9, respectively. Furthermore, deterministic-based energy management of hybrid AC/DC MG is developed in Chapter 10. Finally, the stochastic programming, robust optimization, and information gap decision theory methods are implemented in Chapter 11-13, respectively in order to obtain uncertainty-based energy management of hybrid AC/DC MG.

Chapter 1

Energy management concept of AC, DC, and hybrid AC/DC microgrids

Sayyad Nojavan¹, Hamed Pashaei-Didani², Arash Mohammadi² and Hamed Ahmadi-Nezamabad²,    ¹Department of Electrical Engineering, University of Bonab, Bonab, Iran,    ²Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

Abstract

By increasing environmental effects of using fossil fuels to generate electric power, development and utilization of renewable energy sources (RESs) including wind turbine and photovoltaic systems are increasing every day, all around the world. To accommodate the traditional power systems with RESs, the concept of microgrid (MG) is provided, defined as a combination of controllable loads and distributed energy resources that can be utilized in grid-connected or islanded modes. In this chapter, first different types of MGs are detailed and then different energy management systems developed in the literature are provided. In addition, different objective functions, constraints, and communication systems utilized in the literature are presented.

Keywords

AC microgrids; DC microgrids; hybrid AC/DC microgrids; energy management systems; renewable energy sources; distributed energy resources

Contents

1.1 Introduction 1

1.2 Classification of microgrids 2

1.3 Operation strategies and constraints 4

1.4 Communication system 4

1.5 Energy management system 5

References 8

1.1 Introduction

Supplying ever-increasing energy demands considering environmental effects of fossil fuels such as climate change [1] has made developing renewable energy sources (RESs) necessary, as they are environmentally friendly energy sources [2]. Providing clean energy and mitigating emission of greenhouse gases are the main advantages of RESs including wind, solar, hydro, fuel cell, tidal power, and biomass. Among them, solar and wind are considered the most promising energy sources [1]. In the literature, RESs are referred to as distributed energy resources (DERs) [3,4], which are on-site power generation units that do not require any transmission equipment, resulting in a reduction of energy loss in a distribution system. The power generation of DERs, especially wind and solar, are volatile due to their dependency on meteorological factors [5]. Therefore, it is better to couple DERs with energy storage systems (ESSs) and microconventional generation units to cope with uncertain power output of these sources.

To accommodate DERs with traditional power systems, the concept of microgrid (MG) is developed [6]. MGs are defined as a combination of controllable loads and DERs that can be utilized in grid-connected or islanded modes.

Various advantages can be achieved by implementing MGs, including improving voltage profile, implementing demand response programs [7], reducing energy loss, using cogeneration units to supply heat load, and reducing line outages [8]. However, an MG faces different challenges and limitations. High investment cost of DERs, optimal energy management of RESs, and the raised problem of protection issues and lack of regulatory standards can be counted as the most important challenges that an MG faces [9].

The MGs can be classified from the different point of views. For example, according to operational frequency, MGs are grouped as AC, DC, and hybrid AC/DC, each of which will be detailed in the following chapters. In another classification, as mentioned earlier, MGs are divided into two groups, grid-connected and islanded; more information about these groups is provided in the following section.

Developing energy management systems (EMSs) for MGs is one of the most important research areas due to high penetration of renewable energy resources. EMSs should provide a balance between load and supply, and satisfy different operational and economic constraints of the system.

1.2 Classification of microgrids

Fig. 1.1 presents the classification of MGs including operating mode, power type, phase, application, and control topics. As it can be seen, the phase is divided into two subgroups, single phase and three phases, and the control is grouped as centralized and decentralized. According to Fig. 1.1, the MGs can be classified considering their application, which is categorized as residential/commercial/industrial and utility and military.

Figure 1.1 Classification of microgrids.

In one division, the MGs are classified as grid-connected or islanded modes, each with its own advantages and disadvantages. In each mode, utilized DERs in the MG are connected to a power electronic interface to satisfy protection, metering, and control objectives. In the grid-connected mode, MGs can exchange energy, which can make profit by selling energy to the upstream grid during high-price periods. On the other hand, the grid-connected MGs should switch to islanded mode when there is a failure in the upstream grid. Finally, it should be noted that to improve the system operation, optimal management of the MGs is necessary in this mode. Optimal operation of different AC, DC, and hybrid AC/DC MGs is detailed in the following chapters.

AC MGs are the most common type of MGs because of direct implementation of distributed generation power sources in the system. In DC MGs, considerable energy saving is achieved due to fewer converters compared with AC MGs. By increasing DC loads in the system and in order to benefit from advantages of both AC and DC MGs, hybrid AC/DC MGs have drawn more attention recently. Fig. 1.2 depicts the structure of AC, DC, and hybrid AC/DC MGs.

Figure 1.2 Structure of (A) AC microgrid, (B) DC microgrid, and (C) hybrid AC/DC microgrid.

1.3 Operation strategies and constraints

To get optimal energy management of any type of MG, different strategies can be taken into account including operation and loss cost, emission cost, demand response incentives, interruption and outage cost, energy transaction cost, and so on. Fig. 1.3 provides most common strategies in MG operation.

Figure 1.3 Strategies in microgrid operation.

Each of these strategies should provide optimal operation of MGs subjected to different constraints including energy balance, network constraints, demand response, reactive power support, reliability, limits of ESSs, and constraints of the generating units. Fig. 1.4 provides the most important constraints of the system.

Figure 1.4 Constraints in microgrid operation.

1.4 Communication system

In MGs, communication infrastructure is required to coordinate different DERs and implement demand response programs by sharing information with each other. To do so, a reliable, continuous, accurate, fast communication infrastructure, without any disconnections and disturbances, is necessary to transfer data between local controllers, MG central controller, and sensors. Such infrastructures may impose a high investment cost, however, according to the number of required repeaters to cover the geographical area of the MG and improve transmitted signal quality.

For a safe, reliable, and effective connection between different parts of an MG, various wireless and wired communication technologies have been proposed in the literature. Coverage area, latency, quality of service, coverage area, power consumption, and reliability are the most important criteria that should be taken into account to choose the optimal selection among the developed wireless and wired technologies. By taking data rate and coverage area into account, WiMAX [10], 4G [11], and passive potential networks can be considered the most powerful communication structures; followed by 2G [12], narrowband power line communication, and coaxial cables; and finally, Bluetooth [13], Z-wave [14], and Zigbee [13] are among the weakest communication technologies. It is obvious that by increasing data rate and coverage area, the investment cost of the communication system will be