Microgrids and Methods of Analysis

By Gevork B. Gharehpetian, Hamid Reza Baghaee and Masoud M. Shabestary

The increasing penetration of distributed energy resource (DER), distributed generation (DG) and energy storage system (ESS) units in distribution grids leads to the emergence of the concepts of active distribution networks (ADNs), microgrids, and virtual power plants. Nowadays, the use of electronically-coupled distributed energy resources is of great interest that can provide the power of demand side alone or in a small electricity grid. A microgrid is a small-scale power grid in low voltage network that must be able to locally solve energy issues and enhance the flexibility and can operate either in grid-connected or islanded/autonomous mode of operation. To study them, researchers need an appropriate set of methods, software tools, analogous to those exist for large interconnected power systems.The book Microgrids and Methods of Analysis addresses systematic analysis, control/protection systems design, and optimal operation of a distribution system under high penetration of DERs analogous to those that exist for large interconnected power systems.

• Provides professional guidlines for system planners
• Explores further research, development, and optimization of existing and new microgrids
• Addresses analytical methods used for microgrid analysis using advanced research

• Language: English
• Publisher: Academic Press
• Release date: Jul 14, 2021
• ISBN: 9780128165850

Gevork B. Gharehpetian

Prof. Gevork B. Gharehpetian has been a Professor since 2007, in the Department of Electrical Engineering at Amirkabir University of Technology, Iran. He also worked with the High Voltage Institute of RWTH Aachen, Germany. He has received several honors, including being selected by the Ministry of Science Research and Technology as a Distinguished Professor of Iran; by the Iranian Association of Electrical and Electronics Engineers as a Distinguished Researcher of Iran; by the Iran Energy Association as the best Iranian researcher in Energy; by the Academy of Science of the Islamic Republic of Iran as a Distinguished Professor of Electrical Engineering; and by the National Elites Foundation for the Laureates of Alameh Tabatabaei Award. He was also awarded the National Prize in 2008, 2010, 2018 (twice), and 2019 (twice). Based on the Web of Science Database (2005-2019), he is among world's top 1% of elite scientists by Essential Science Indicators. Relevant Courses taught: Electrical Machines (II): The object of this course is to provide a foundation in the concepts and transformers and induction machines. Microgrids & Smart Grids: The object of this course is to provide a foundation in the concepts and applications of Micro and Smart Grids. Distributed Generation: The object of this course is to become familiar with the basics of the distributed power generation and their application merits and demerits in distribution system or stand-alone operation mode. FACTS: The object of this course is to provide a foundation in the concepts and application of FACTS devices in power systems. Modern Power System Elements: This course aims to provide a comprehensive, objective portrait of the future of the electric grid and the challenges and opportunities it is likely to face over the next two decades considering the new developments and research in power systems. Foundation of this book.

Book preview

Microgrids and Methods of Analysis

Gevork B. Gharehpetian

Amirkabir University of Technology, Tehran, Iran

Hamid Reza Baghaee

Amirkabir University of Technology, Tehran, Iran

Masoud M. Shabestary

University of Alberta, Edmonton, Canada

Table of Contents

Cover image

Title page

Copyright

Chapter 1. Introduction

1. Microgrids

2. Challenges

3. Purpose and target audiences

4. Benefits to the audiences

5. Outline of the book

Chapter 2. Microgrid control strategies

1. Introduction

2. Basic infrastructures for control and management of microgrids

3. Microgrid control schemes

4. Current challenges and future trends in control and management of microgrids

5. Case study 1: design of an improved hierarchical control structure

6. Case study 2: improvement of hierarchical control performance for unbalanced and nonlinear loads

7. Summary

Chapter 3. Power-flow analysis of microgrids

1. Fundamental-frequency deterministic power flow

2. Radial basis function neural networks

3. Proposed algorithm

4. Probabilistic power flow problem

5. Extension of harmonic power flow

Chapter 4. Fault analysis

1. Introduction

2. Droop method–based control, hierarchical organization

3. Direct voltage control

4. Fault model: general form

5. Simulation results

6. Summary

Chapter 5. Operation under unbalanced conditions

1. Introduction

2. Recent grid code requirements

3. Operation of interconnecting converters under unbalanced conditions

4. Voltage support methods under unbalanced conditions

5. Summary

Chapter 6. Microgrid protection

1. Introduction

2. Control system

3. Fault model of inverter-interfaced distributed energy resource units

4. Proposed fault detection method

5. Overcurrent/overload protection scheme

6. Simulation results

7. Pareto-optimal solution for coordination of overcurrent relays in interconnected networks and Multi–distributed energy resource microgrids

8. Conclusion

Chapter 7. Optimal sizing of microgrids

1. Introduction

2. Optimal hybrid wind generation/photovoltaic/battery energy storage system

3. Hybrid photovoltaic/wind generation/fuel cell network optimal design

4. Particle swarm optimization and multiple-objective particle swarm optimization algorithms

5. Simulation results

6. Conclusion

Appendix

Chapter 8. Power management in hybrid microgrids

1. Introduction

2. Basic control and management structure of microgrid

3. Hierarchical power management

4. Generalization of power management concepts to DC and hybrid AC/DC microgrids

5. Summary

Index

Copyright

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Chapter 1: Introduction

Abstract

The technology developments and concerns for global warming: Renewable/distributed energy resources (RERs/DERs), and energy storage systems (ESS). A Microgrid is a small-scale power grid in the low voltage that must be able to locally solve energy issues and enhance flexibility and can operate either in grid-connected or islanded (autonomous) modes of operation. Microgrids are low or medium-voltage grids without power transmission capabilities and are typically not geographically spread out. This chapter presents an introduction and fundamental concepts for the microgrids, along with the basic challenges and current trends of the researches for the microgrids. The purposes of the book and the main benefits for the target audiences are also explained and finally, an outline of the book and the description of the next chapters are mentioned.

Keywords

Analytical tools; Distributed energy resources; Energy storage systems; Microgrids; Renewable energy resources

1. Microgrids

A microgrid (MG) is a geographically limited low-voltage (LV) distribution network, including localized energy resources, energy storage systems (ESSs), and loads that can operate synchronously with the main grid (macrogrid) or disconnected as an isolated grid considering its physical and/or economic operational conditions [1–4]. The following definition has been presented by the US Department of Energy Microgrid Exchange Group [4]:

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 can connect and disconnect from the grid to enable it to operate in both grid-connected or islanded operation mode.

Therefore, an MG presents a framework for the application of different resources of distributed generation (DG) units, especially renewable energy resources (RER), and can have isolated and grid-connected operation modes. The ability to change its mode results in challenges in MG control and protection [2]. It can also satisfy the needs of the demand side in the form of electricity, heating, and cooling. This in turn leads to the possibility of substitution of energy carriers and improved energy efficiency due to utilization of waste heat in combined heat and power systems (or also, combined cooling heating and power systems).

It can be said that the US DOE MG Exchange Group [4] considers MG as a set of distributed energy resources (DERs), including DG units and ESSs, and loads that from the main grid side point of view, can be seen as a single controllable entity. This entity can be connected to and disconnected from the main grid considering the system conditions.

The EU research project [5] presents the MG as an LV distribution network with DERs, including fuel cells, microturbines, wind generation systems, photovoltaic panels, batteries, flywheels, etc., and flexible loads. This system should be able to operate either in on-grid (grid-connected) or in off-grid (disconnected) operation modes. The operation of DERs, also known as microsources, can result in advantages for the performance of the overall system, in case of their efficient management and coordination.

Higher energy efficiency, minimized energy consumption, decreased environmental issues, and enhanced supply reliability are advantages, which can be offered by MGs to customers and utilities. Also, reduction of losses, congestion management, regulation of voltage, and system security improvement can be achieved using MGs. The realization of the mentioned privileges may prevent new investments in the main grid for the integration of RERs and reduce the generation and transmission system expansion costs.

It is well known that the smart grid concept has been presented to

• improve the operation of power systems, e.g., using phasor measurement units;

• increase grid–customer interactions, e.g., using demand response programs and smart meters; and

• integrate new distributed system players and entities, e.g., MGs.

Therefore, the MG can be considered as a new architecture in the distribution system, which can realize the concept of smart grid for customers and utilities, and using this framework, it is possible to use the advantages of integration of a huge amount of small-scale DERs into LV networks. Using the proper combination of DERs, it is possible to have a balance between carbon emissions reduction, cost reduction, and reliable energy supply for customers.

In on-grid operation mode, MG can offer ancillary services to the main grid in the retail energy market. Also, other possible revenue streams exist [6]. In off-grid operation mode, the real and reactive power balance in MG must be established between DERs and the loads. However, an MG may change its mode of operation between these two modes, considering energy market conditions, intentional islanding need for scheduled maintenance, degraded power quality of the main grid, shortage of generated energy, or unintentional islanding due to faults [7,8].

MGs can improve the system reliability, and also, the resilience of the network versus extreme weather conditions and natural disasters, which can result in huge damages to power systems [7,8]. Also, using multiobjective optimization algorithms, MG energy management system can enhance efficiency and resiliency and reduce the costs [9–11].

2. Challenges

To preserve the mentioned advantages and use the presented opportunities of MGs, their challenges must be studied and addressed in their protection and control systems design. To study conventional distribution systems, there are some typical assumptions, which are no longer valid for MG investigations, and these new conditions can result in new challenges. Also, some transmission system challenges can be observed in MGs, which must be considered in detail [7]. The most important challenges of MGs, which will be discussed in this book, are as follows:

• Bidirectional power flow: The conventional power flow in power systems is from the main grid to passive distribution networks. The integration of DG units in distribution systems, which can now be considered as an active distribution network, has changed this condition. Now, it is possible to have a reverse power flow. In this case, the contribution of DGs in fault current will affect the fault current pattern, and as a result, the coordination of protection relays and the performance of voltage control systems must be revised [7].

• Stability: The DERs control system and control systems of other devices installed in distribution systems such as reactive power controllers can have interactions and result in local oscillations, which can endanger the small-signal stability of the system. Also, MGs should operate in both operation modes, but a transition from isolated mode to on-grid mode can lead to transient stability issues for MG components [7,12]. Some researches on DC MG have shown that these MGs can improve the system performance better than AC MGs [13,14].

• Modeling: To overcome MG problems, they must be modeled and studied before practical implementation and application. Many solutions have been investigated and presented for power systems in the literature, which is based on verified and well-known assumptions. But these assumptions are not valid for MG modelings such as three-phase balanced conditions, inductive behavior of lines, and constant–power loads. As a result, new models should be suggested and used [7].

• Low inertia: The conventional synchronous generators can obtain enough inertia versus power system oscillations and transients. In MGs, an increase in penetration level of inverter-interfaced DERs (IIDERs) in distributions systems and MGs can result in the reduction of the system inertia. Especially in the isolated mode of operation of MGs, any disturbance can cause significant voltage and frequency variations, if a proper control system is not designed [7], or ESSs such as battery or flywheel are not used [15]. To overcome this issue, the researchers have suggested the application of virtual synchronous generators, which are inverters mimicking synchronous generators' characteristics to provide virtual inertia to MGs.

• Uncertainty: Highly correlated variations of power system resources lead to less uncertainty in bulk power systems. But, in MGs, stochastic load behavior during different periods and intermittent weather conditions are two main uncertainties, which affect the reliable and economic operation of an MG. In islanded mode, uncertainties are more challenging. The power balance must be satisfied between demand and supply over an extended time horizon.

3. Purpose and target audiences

Considering the ever-increasing penetration level of IIDERs and MGs in power systems, researchers need a set of software and hardware tools similar to the ones used for bulk power systems for

• steady-state and fault studies,

• design of control and protection systems, and

• determination of optimal conditions.

This book aims to offer solutions for these studies in MGs. Therefore, it can be used by researchers and professional engineers, working in the electrical power industry, professors, and electrical engineering postgraduate students. Also, this book is useful for the BS students, working on their final thesis.

This book will be useful for utility engineers not only in the countries that are now planning to restructure their power system and implement MGs but also in the countries, whose MGs have been implemented before and now their systems are in operation. Moreover, all around the world, the researchers who are working in the field of the MGs can use the methods presented in this book for their new researches.

4. Benefits to the audiences

This book has two major benefits to the audiences, as follows:

• Using new analytical solutions for solving MGs operational problems

• Gaining new insight into MGs studies

This book aims to provide useful insight for the researchers in aspects of MG planning, operation, control, and protection. To form the backbone of this book, the information mentioned in the recently published papers and researches has been used in all the chapters. Also, discussion of related international standards has been provided in some sections of the book, to make it more useful for industry experts.

The focuses of previously published books in this field are mainly on architecture and control of MGs. However, the authors of this book have tried to provide analytical solutions to facilitate the analysis of MGs and cover some research gaps identified in the literature. This book addresses the technical challenges in MGs planning, operation, protection, and control.

5. Outline of the book

To achieve the aforementioned purposes, the rest of the book is organized as follows: In Chapter 2, the basic control strategies of MGs are reviewed. Also, we model an improved hierarchical control structure and discuss the basic challenges in the control of MGs. In Chapter 3, we present a three-phase AC/DC power flow algorithm for balanced and unbalanced MGs and extend it for harmonic and probabilistic power flow algorithm. Chapter 4 describes the MG fault analysis method along with current limiting strategies and fault ride-through (FRT) requirements. The operation of MGs in unbalanced situations is discussed in Chapter 5. In Chapter 6, we discuss the protection strategies for MGs. Chapter 7 describes the optimal sizing of hybrid MGs based on numerical algorithms, and finally, the power management strategies of MGs will be discussed in Chapter 8.

References

1. Hatziargyriou N, Asano H, Iravani R, Marnay C. Microgrids.  IEEE Power Energy Mag.  July 2007;5(4):78–94.

2. Venkatraman R, Khaitan S.K. A survey of techniques for designing and managing microgrids. In:  Proc. IEEE Power & Energy Society General Meeting, Denver, CO, USA . July 2015:1–6.

3. F. Katiraei, R. Iravani, N. Hatziargyriou, A. Dimeas, Microgrids management, IEEE Power Energy Mag., vol. 6, no. 3, pp. 54 – 65, (M).

4. reportDOE Microgrid Workshop Report, [online]: https://www.energy.gov/sites/prod/files/Microgrid%20Workshop%20Report%20August%202011.pdf.

5. Hatziargyriou N.  Microgrids Architectures and Control . John Wiley and Sons Ltd; 2014: 978-1-118-72068-4:4. .

6. Stadler M, Cardoso G, Mashayekh S, Forget T, DeForest N, Agarwal A, Schönbein A.Value streams in microgrids: a literature review.  Appl. Energy . January 2016;162:980–989.

7. Saleh M, Esa Y, Mohamed A. Communication-based control for DC microgrids.  IEEE Trans. Smart Grid . March 2019;10(2):2180–2195.

8. Olivares D.E, et al. Trends in microgrid control.  IEEE Trans. Smart Grid . July 2014;5(4):1905–1919.

9. Jin M, Feng W, Liu P, Marnay C, Spanos C. MOD-DR: microgrid optimal dispatch with demand response.  Appl. Energy . February 2017;187:758–776.

10. Tenti P, Caldognetto T. On microgrid evolution to local area energy network (E-LAN).  IEEE Trans. Smart Grid . March 2019;10(2):1567–1576.

11. Mashayekh S, Stadler M, Cardoso G, Heleno M. A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids.  Appl. Energy . February 2017;187:154–168.

12. Saleh M.S, Althaibani A, Esa Y, Mhandi Y, Mohamed A.A. Impact of clustering microgrids on their stability and resilience during blackouts. In:  Proc. International Conference on Smart Grid and Clean Energy Technologies (ICSGCE) . October 2015:195–200 Offenburg, Germany.

13. Dragicevic T, Lu X, Vasquez J, Guerrero J.M. DC microgrids–Part I: a review of control strategies and stabilization techniques.  IEEE Trans. Power Electron.  July 2016;31(7):4876–4891.

14. Dragicevic T, Lu X, Vasquez J, Guerrero J.M. DC microgrids—Part II: a review of power architectures, applications, and standardization issues.  IEEE Trans. Power Electron.  May 2016;31(5):3528–3549.

15. Kim Y.S, Kim E.S, Moon S.I. Frequency and voltage control strategy of standalone microgrids with high penetration of intermittent renewable generation systems.  IEEE Trans. Power Syst.  January 2016;31(1):718–728.

Chapter 2: Microgrid control strategies

Abstract

In this chapter, first, we briefly review the basic control structure of microgrids. Then, we are looking for solutions that can improve the stability of the hierarchical control structure and its performance for nonlinear and unbalanced loads. The presented hierarchical control scheme adds a new control loop to control the reactive power reference by a fuzzy logic controller to have the benefit of increasing the system stability margins. In addition to the small-signal events, it maintains the stability of microgrids faced with large-signal disturbances such as short circuits, line outage, heavy motor starting, etc., and improves fault ride-through capability. Next, we propose a harmonic virtual impedance and voltage compensation scheme to enhance the system’s performance for nonlinear and unbalanced loading conditions. In all cases, power-sharing to loads and network is sufficiently done. To demonstrate the effectiveness of the proposed hierarchical controller, simulation studies have been performed on a microgrid consisting of four units of distributed generation with local loads and in the presence of the main grid using MATLAB/SIMULINK software (offline Simulations) and OPAL-RT real-time digital simulator for verification.

Keywords

Decentralized control; Hierarchical control structure; Microgrids; Power management; Power-sharing; Stability

1. Introduction

The ever-increasing penetration of distributed energy resources (DERs), including renewable energy resources (RERs) and energy storage systems (ESSs), and also technoeconomic application of power electronics converters in distribution networks (DNs), result in a need for new frameworks such as active distribution networks (ADNs) [1], microgrids (MGs) [2–4], and virtual power plants (VPPs) [5]. These frameworks can realize the application of DERs, such as wind generation (WG) systems, photovoltaic (PV) generation units, fuel cells (FCs), microturbines [6,7], and also electric vehicles (EVs). Integration of RERs and ESSs into low-voltage DNs leads to many advantages such as improved power quality (PQ), enhanced voltage stability, and elevated reliability [8–10]. Also, they can reduce greenhouse gas emissions and other negative environmental impacts. However, the RERs also result in new challenges such as coordination of protection relays for both directions of current flow, islanding protection of MG, energy quality-based distribution, and energy management of MGs considering their intermittent generation. In general, the performance of distributed generation (DG) units in MGs depends on their operating point and the protection system settings [11–13].

In this chapter, we introduce basic architecture and discuss for challenges and trends in the operation, management, and control of future ADNs toward modern smart MGs.

2. Basic infrastructures for control and management of microgrids

Fig. 2.1 illustrates a typical multilayer block diagram representation for general structure of MG control system [15–18]. In the lowest layer, we have all the physical components, including interfacing power converters (PCs), DERs, and MG elements, such as loads, transformers, transmission lines, switchgears, etc.

Figure 2.1 General structure of microgrid control system [14].

The basic functions such as local generation and consumption control and management of ESSs are realized by the local control layer, which usually follows the commands sent by upper-level controllers. The highest control level of MG fulfills the function of supervisory control and data acquisition (SCADA). This control level is also known as MG supervisory controller (MGSC), energy management system (EMS), or microgrid central controller (MCC). This control level should provide important tasks such as power quality control, support of ancillary services, involvement in the energy market, and optimization of system performance by enhancing its intelligence level [15]. As shown in Fig. 2.1, the higher-level operators, i.e., distribution network operator (DNO) and market operator (MO) affect the MGSC/EMS. This interaction needs the availability of information and communication technology (ICT). The requirements and characteristics of MGs bring more challenges to MGSC/EMS [15,16]. For example, energy management system must be able to provide intentional or unintentional smooth transition between off-grid (islanded) and on-grid (grid-connected) modes, handle demand side management programs, and manage RERs using advanced scheduling and dispatching strategies [19].

3. Microgrid control schemes

DG units in MGs can be controlled in grid-forming (voltage-controlled), grid-feeding (voltage-controlled), or grid-supporting (voltage/current-controlled) modes [20]. The control strategies used in grid-feeding inverters have been presented in Ref. [21]. This section focuses on the control strategies of grid-forming and grid-supporting DGs, which play the main role in power sharing and balancing of MGs. After discussion of these DGs converters, grid-feeding and grid-supporting converters will be presented as well.

The grid-forming control strategies can be classified considering their requirements for a communication system. They include master/slave control [4,10,22,23] centralized control [24,25], decentralized control [26,27], distributed control [26,27], and hierarchical control [6,9,17,28].

Essentially, there are four basic communication-assisted schemes for control of large-scale systems (LSSs). These systems almost include different coupled subsystems, which have some interactions together. Based on the theory of LSSs [29], they can be controlled based on centralized, decentralized, distributed, and hierarchical control structures. These control schemes are illustrated in Figs. 2.2A–2.6D, and their main salient features are summarized as follows.

3.1. Centralized control

Design of the centralized controllers for LSSs is complicated because of their intrinsic computational complexities, reliability constraints, and limitations of the communication bandwidth. As shown in Fig. 2.2A, all computations are performed in centralized controller (which have all the information of the system) and necessary commands are transmitted to the actuators. When the system (in this chapter, MG) become larger and larger, the amount of computations in the centralized controller will be extensively increased. So, the required computation time is increased and controller show slow and inefficient performance which is not acceptable in real-time applications. Moreover, communication between subsystems and centralized controllers demand fast two-way high-bandwidth communication (HBC) which results in increasing investment costs. More importantly, the centralized control strategy has low reliability because failure in the controller, will stop the operation of whole plant. Besides the mentioned disadvantages, if a controllable agent (such as DG/ESS unit or PHEV charging station) is added to the microgrid, the centralized controller should be redesigned or at least essential changes are required. To sum up, the benefits and disadvantages of centralized control structure are summarized in Table 2.1.

Figure 2.2 Basic block diagram representation of control architectures based on theory of large-scale systems [29]: (A) centralized control, (B) decentralized control, (C) distributed control, and (D) hierarchical control.

Table 2.1