DC Microgrids

Nikita Gupta, PhD, is a professor in the Department of Electrical Engineering, University Institute of Technology, Himachal Pradesh University, India. She received her BTech degree in electrical and electronics engineering from the National Institute of Technology, Hamirpur, India in 2011 and MTech degree in power systems from Delhi Technological University, Delhi, India in 2014. She earned her PhD from the Department of Electrical Engineering at Delhi Technological University, Delhi, India, in 2018. Her research interests include power system analysis, power quality, power electronics applications in renewable energy, and microgrids.M. S. Bhaskar, PhD, is with the Renewable Energy Lab, in the Department of Communications and Networks Engineering at the College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia. After receiving his PhD in electrical and electronic engineering from the University of Johannesburg, South Africa in 2019, he was a post-doctoral researcher in the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has several years of research experience from several universities, and he has authored over 100 scientific papers in the area of DC/AC power, receiving several awards, as well. He is a member of a number of scientific societies and is a reviewer for several technical journals and conferences, including IEEE and IET. P. Sanjeevikumar, PhD, is a professor in the Department of Business Development and Technology, CTIF Global Capsule (CGC) Laboratory, Aarhus University, Herning, Denmark. He earned his PhD in electrical engineering from the University of Bologna, Bologna, Italy, in 2012. He has nearly ten years of teaching and industry experience and has authored over 300 scientific papers, including winning several awards at conferences for having the best paper. He is a fellow or member of numerous scientific societies and associations and is an editor, associate editor, or on the boards of numerous scientific and technical journals. Dhafer J. Almakhles, PhD, is the Chairman of the of the Communications and Networks Engineering Department, and the Director of the Science and Technology Unit and Intellectual Property Office, Prince Sultan University, Saudi Arabia. He earned his PhD from The University of Auckland, New Zealand 2016. He is also the leader of the Renewable Energy Research Team and Laboratory. He is a member of multiple scientific societies and is a reviewer for a number of technical journals. Anirban Roy, PhD, is an assistant professor in the Department of Chemical Engineering at BITS Pilani Goa campus. He has published 20 articles in journals of international repute, filed eight patents, and published one book thus far. He also has ample industrial experience, as well as academic experience, in the field.

• Preface xv1 On the DC Microgrids Protection Challenges, Schemes, and Devices – A Review 1Mohammed H. Ibrahim, Ebrahim A. Badran and Mansour H. Abdel-Rahman1.1 Introduction 21.2 Fault Characteristics and Analysis in DC Microgrid 41.3 DC Microgrid Protection Challenges 71.3.1 Low Inductance of DC System 71.3.2 Fast Rise Rate of DC Fault Current 71.3.3 Difficulties of Overcurrent (O/C) Relays Coordination 71.3.4 Fault Detection and Location 81.3.5 Arcing Fault Detection and Clearing 101.3.6 Short-Circuit (SC) Analysis and Change of Its Level 131.3.7 Non-Suitability of AC Circuit Breakers (ACCBs) 161.3.8 Inverters Low Fault Current Capacity 171.3.9 Constant Power Load (CPL) Impact 171.3.10 Grounding 181.4 DC Microgrid Protection Schemes 211.4.1 The Differential Protection-Based Strategies 251.4.2 The Voltage-Based Protection Strategies 271.4.3 The Adaptive Overcurrent Protection Schemes 281.4.4 Impedance-Based Protection Strategy (Distance Protection) 291.4.5 Non-Conventional Protection Schemes (Data-Based Protection Scheme) 321.5 DC Microgrid Protective Devices (PDs) 341.5.1 Z-Source DC Circuit Breakers (ZSB) 351.5.2 Hybrid DC Circuit Breakers (HCB) 381.5.3 Solid State Circuit Breakers (SSCBs) 421.5.4 Arc Fault Current Interrupter (AFCI) 451.5.5 Fuses 471.6 Conclusions 48References 502 Control Strategies for DC Microgrids 63Bhabani Kumari Choudhury and Premalata Jena2.1 Introduction: The Concept of Microgrids 632.1.1 DC Microgrids 642.2 Introduction: The Concept of Control Strategies 652.2.1 Basic Control Schemes for DC MGs 662.2.1.1 Centralized Control Strategy 662.2.1.2 Decentralized Controller 672.2.1.3 Distributed Control 682.2.2 Multilevel Control 682.2.2.1 Primary Control 692.2.2.2 Secondary Control 732.2.2.3 Tertiary Control 742.2.2.4 Current Sharing Loop 742.2.2.5 Microgrid Central Controller (MGCC) 742.3 Control Strategies for DGs in DC MGs 762.3.1 Control Strategy for Solar Cell in DC MGs 762.3.1.1 Control Strategy for Wind Energy in DC MGs 772.3.1.2 Control Strategy for Fuel Cell in DC MGs 772.3.1.3 Control Strategy for Energy Storage System in DC MGs 782.4 Conclusions and Future Scopes 79References 803 Protection Issues in DC Microgrids 83Bhabani Kumari Choudhury and Premalata Jena3.1 Introduction 833.1.1 Protection Challenge 843.1.1.1 Arcing and Fault Clearing Time 843.1.1.2 Stability 853.1.1.3 Multiterminal Protections 853.1.1.4 Ground Fault Challenges 853.1.1.5 Communication Challenges 863.1.2 Effect of Constant Power Loads (CPLs) 863.2 Fault Detection in DC MGs 873.2.1 Principles and Methods of Fault Detection 873.2.1.1 Voltage Magnitude-Based Detection 873.2.1.2 Current Magnitude-Based Detection 883.2.1.3 Impedance Estimation Method 883.2.1.4 Power Probe Unit (PPU) Method 883.3 Fault Location 923.3.1 Passive Approach 923.3.1.1 Traveling Wave-Based Scheme 923.3.1.2 Differential Fault Location 933.3.1.3 Local Measurement-Based Fault Location 933.3.2 Active Approach for Fault Location 943.3.2.1 Injection-Based Fault Location 943.4 Islanding Detection (ID) 943.4.1 Types of IDSs 953.4.2 Passive Detection Schemes (PDSs) for DC MGs 963.4.3 Active Detection Schemes (ADS) for DC MGs 963.5 Protection Coordination Strategy 973.6 Conclusion and Future Research Scopes 97References 974 Dynamic Energy Management System of Microgrid Using AI Techniques: A Comprehensive & Comparative Study 101Priyadarshini Balasubramanyam and Vijay K. SoodNomenclature 1024.1 Introduction 1034.1.1 Background and Motivation 1034.1.2 Prior Work 1034.1.3 Contributions 1044.1.4 Layout of the Chapter 1044.2 Problem Statement 1044.3 Mathematical Modelling of Microgrid 1054.3.1 Cost Functions 1064.3.1.1 Diesel Generator 1064.3.1.2 Solar Generation 1064.3.1.3 Wind Generation Unit 1064.3.1.4 Energy Storage System (ESS) 1074.3.1.5 Transaction with Utility 1084.3.2 Objective Function 1094.3.3 Constraints 1094.4 Optimization Algorithm 1104.4.1 Heuristic-Based Genetic Algorithm (GA) 1104.4.2 Pattern Search Algorithm (PSA) 1114.5 Results 1134.6 Conclusion 118References 1185 Energy Management Strategies Involving Energy Storage in DC Microgrid 121S. K. Rai, H. D. Mathur and Sanjeevikumar Padmanaban5.1 Introduction 1215.2 Literature Review 1235.2.1 Classic Approaches of EMS 1245.2.2 Meta-Heuristic Approach of EMS 1295.2.3 Artificial Intelligence Approach of EMS 1345.2.4 Model Predictive, Stochastic and Robust Programming Approach of EMS 1395.3 Case Study 1425.3.1 Energy Management System 1445.3.2 Objective Functions 1445.3.3 Result and Discussion 1455.4 Conclusion 151References 1516 A Systematic Approach for Solar and Hydro Resource Assessment for DC Microgrid Applications 159Sanjay Kumar, Nikita Gupta, Vineet Kumar and Tarlochan Kaur6.1 Introduction 1606.1.1 Micro Hydro and Solar PV 1626.1.2 Renewable Energy for Rural Electrification in Indian Perspective 1626.1.3 Solar Resource Assessment 1636.1.4 Hydro Resource Assessment 1666.1.5 Demand Assessment 1676.2 Methodology 1686.2.1 Data Collection 1686.2.1.1 Meteorological and Geographical Data 1686.2.1.2 Discharge Data for Hydro Potential Estimation 1686.3 Result and Discussion 1726.3.1 ANN Architecture 1726.3.2 Hydro Resource Estimation 1766.4 Conclusion 178References 1797 Secondary Control Based on the Droop Technique for Power Sharing 183Waner W.A.G. Silva, Thiago R. de Oliveira, Rhonei P. Santos and Danilo I. Brandao7.1 Introduction 1847.2 Voltage Deviation and Power Sharing Issues in Droop Technique 1867.2.1 Approaches for Correcting Power and Current Sharing 1907.2.2 Hybrid Secondary Control: Distributed Power Sharing and Decentralized Voltage Restoration 1977.2.2.1 Dynamics and Convergence of the Power Sharing Correction 2007.2.2.2 Communication Delays in Consensus-Based Algorithm 2037.2.2.3 Secondary Control Modeling 2047.2.2.4 Computational and Experimental Validation 2087.2.3 Secondary Level Control Based on Unique Voltage-Shifting (vs) 2157.2.3.1 Power Sharing and Average Voltage Convergence Analysis 2187.2.3.2 Secondary Control Level Modeling 2237.2.3.3 Computational and Experimental Validation 2267.3 Design and Implementation of the Communication System 2307.4 Conclusions 234References 2358 Dynamic Analysis and Reduced-Order Modeling Techniques for Power Converters in DC Microgrid 241Divya Navamani J., Lavanya A., Jagabar Sathik, M.S. Bhaskar and Vijayakumar K.8.1 Introduction 2428.2 Need of Dynamic Analysis for Power Converters 2438.3 Various Modeling Techniques 2458.3.1 Analysis from Modeling Method 2498.4 Reduce-Order Modeling 2538.4.1 Faddeev Leverrier Algorithm 2538.4.1.1 Procedure for Faddeev Leverrier Algorithm 2538.4.1.2 Illustrative Example with Switched- Inductor-Based Quadratic Boost Converter 2548.4.2 Order Reduction of Transfer Function 2578.4.3 Techniques for Model Order Reduction 2578.4.4 Pole Clustering Method 2588.4.5 Procedure for Improved Pole Clustering Technique 2588.4.5.1 Computation of Denominator Polynomial of Lower-Dimensional Model 2598.4.5.2 Computation of Numerator Polynomial of Lower-Dimensional Model 2618.4.5.3 Design of Controller 2618.5 Illustrative Example with the Power Converter 2628.5.1 Derivation of the Denominator 2638.5.2 Derivation of the Numerator 2648.6 Controllers for Power Converter 2658.6.1 Need of Controller 2658.6.2 Types of Controller 2658.7 Conclusion 267References 2679 Matrix Converter and Its Probable Applications 273Khaliqur Rahman9.1 Introduction 2749.2 Classification of Matrix Converter 2759.2.1 Classical Matrix Converter 2779.2.2 Sparse Matrix Converter 2779.2.3 Very Sparse Matrix Converter 2779.2.4 Ultra-Sparse Matrix Converter 2789.3 Problems Associated with the MC and the Drives 2809.3.1 Commutation Issues 2809.3.2 Modulation Issues 2809.3.3 Common-Mode Voltage and Common-Mode Current Issues 2809.3.4 Protection Issues 2819.4 Control Techniques 2829.5 Basic Components of the Matrix Converter Fed Drive System 2839.6 Industrial Applications of Matrix Converter 2899.7 Summary 294References 29410 Multilevel Converters and Applications 299P. Prem, Jagabar Sathik and K.T. Maheswari10.1 Introduction 30010.2 Multilevel Inverters 30110.2.1 Multilevel Inverters vs. Two-Level Inverters 30110.2.2 Advantages of Multilevel Converters Based on Waveforms 30310.2.3 Advantages of Multilevel Converters Based on Topology 30410.3 Traditional Multilevel Inverter Topologies 30510.3.1 Diode Clamped Multilevel Inverter 30510.3.1.1 Features of DCMLI 30810.3.1.2 Advantages of DCMLI 30810.3.1.3 Disadvantages of DCMLI 30810.3.1.4 Applications of DCMLI 30910.3.2 Flying Capacitor Multilevel Inverter 30910.3.2.1 Features of FCMLI 31210.3.2.2 Advantages of FCMLI 31210.3.2.3 Disadvantages of FCMLI 31210.3.2.4 Applications of FCMLI 31310.3.3 Cascaded H Bridge Multilevel Inverter 31310.3.3.1 Features of CHBMLI 31510.3.3.2 Advantages of CHBMLI 31510.3.3.3 Disadvantages of CHBMLI 31610.3.3.4 Applications of CHBMLI 31610.4 Advent of Active Neutral Point Clamped Converter 31610.4.1 Comparison with Traditional Topologies 31910.4.2 Advantages of ANPC MLI 32010.4.3 Disadvantages of ANPC MLI 32010.5 Conclusion 322References 32211 A Quasi Z-Source (QZS) Network-Based Quadratic Boost Converter Suitable for Photovoltaic-Based DC Microgrids 325Amir Ghorbani Esfahlan and Kazem Varesi11.1 Introduction 32611.2 Proposed Converter 32811.3 Steady-State Analyses 33111.4 Comparison with Other Structures 33511.5 Converter Analyzes in Discontinuous Conduction Mode (DCM) 33511.6 Simulation Results 34211.7 Real Voltage Gain and Losses Analyzes 34611.8 Dynamic Behavior of the Proposed Converter 35211.9 The Maximum Power Point Tracking (MPPT) 35411.10 Conclusions 35611.11 Appendix 357References 35812 Research on Protection Strategy Utilizing Full-Scale Transient Fault Information for DC Microgrid Based on Integrated Control and Protection Platform 361Shi Bonian and Sun Gang12.1 Introduction 36212.2 Topological Structure and Grounding Model of Studied Microgrid 36312.2.1 Proposed DC Distribution Network Topology 36312.2.2 Neutral Grounding Model 36612.2.2.1 Grounding Position Selection 36612.2.2.2 Grounding Mode Selection 36612.3 Fault Characteristics of DC Microgrid 36712.3.1 DC Unipolar Fault Characteristics 36812.3.2 DC Bipolar Fault Characteristics 37012.4 DC Microgrid Protection Strategy 37312.4.1 Protection Zone Division and Protection Configuration 37312.4.1.1 Protection Zone Division 37312.4.1.2 Protection Configuration 37512.4.2 Integrated Control and Protection Platform 37612.4.3 Fault Isolation and Recovery Strategy Utilizing Full-Scale Transient Fault Information 37812.4.3.1 Unipolar Fault Isolation and Recovery of DC Line/Bus 37812.4.3.2 Bipolar Fault Isolation and Recovery of DC Line/Bus 38012.5 Simulation Verification 38412.5.1 Verification under DC Unipolar Fault 38612.5.1.1 Metal Short Circuit Fault of DC Line 38612.5.1.2 Unipolar Fault with High Transition Resistance 38612.5.1.3 High Resistance Unipolar Fault with Parallel Resistance Switching Strategy 38612.5.2 Verification under DC Bipolar Fault 39012.6 Conclusion 394References 39513 A Decision Tree-Based Algorithm for Fault Detection and Section Identification of DC Microgrid 397Shankarshan Prasad Tiwari and Ebha KoleyAcronyms 398Symbols 39813.1 Introduction 39813.2 DC Test Microgrid System 40013.3 Overview of Decision Tree-Based Proposed Scheme 40113.4 DC Microgrid Protection Using Decision Tree Classifier 40313.5 Performance Evaluation 40413.5.1 Mode Detection Module 40813.5.2 Fault Detection/Classification 40913.5.3 Section Identification 40913.5.4 Comparative Analysis of the Proposed Scheme with other DC Microgrid Protection Techniques 41213.6 Conclusion 416References 41714 Passive Islanding Detection Method Using Static Transfer Switch for Multi-DGs Microgrid 421Rahul S. Somalwar and S. G. Kadwane14.1 Introduction 42214.1.1 Technical Challenges of Microgrid and Benefits 42414.1.2 System with Multi-DGs 42514.1.3 Power Sharing Methods 42614.1.3.1 Conventional Droop Control Method 42614.2 Islanding 42714.2.1 Challenges with Islanding 42714.2.2 Different Standards for Microgrid 42814.2.3 Islanding Detection Methods 42814.3 Static Transfer Switch (STS) 43114.3.1 Simulation Results of STS 43214.4 Proposed Scheme of Islanding 43514.4.1 Proposed PV System 43514.4.2 Mathematical Analysis of Harmonic Extraction 43614.5 Flow Chart 43714.6 Simulation Results 43814.7 Experimental Results 44114.8 Conclusion 445References 446Index 449