Microgrid Technologies

Sharmeela Chenniappan, PhD, is an associate professor in the Department of EEE, CEG campus, Anna University, Chennai, India. She has 20 years of teaching experience at both the undergraduate and postgraduate levels and has done a number of research projects and consultancy work in renewable energy, power quality and design of power quality compensators for various industries. She is currently working on future books for the Wiley-Scrivener imprint.Sivaraman Palanisamy has an M.E. in power systems engineering from Anna University, Chennai and is an assistant engineering manager at a leading engineering firm in India He has more than six years of experience in the field of power system studies and related areas and is an expert in many power systems simulation software programs. He is also currently working on other projects to be published under the Wiley-Scrivener imprint.Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He is a fellow in multiple professional societies and associations and is an editor and contributor for multiple science and technical journals in this field. Like his co-editors, he is also currently working on other projects for Wiley-Scrivener.Jens Bo Holm-Nielsen currently works at the Department of Energy Technology, Aalborg University and is Head of the Esbjerg Energy Section. Through his research, he helped establish the Center for Bioenergy and Green Engineering in 2009 and serves as the head of the research group. He has vast experience in the field of bio-refineries and biogas production and has served as the technical advisory for many industries in this field.

• Foreword xxiAcknowledgements xxiii1 A Comprehensive Review on Energy Management in Micro-Grid System 1Sanjay Kumar, R. K. Saket, Sanjeevikumar Padmanaban and Jens Bo Holm-Nielsen1.1 Introduction 21.2 Generation and Storage System in MicroGrid 61.2.1 Distributed Generation of Electrical Power 61.2.2 Incorporation of Electric Car in Micro-Grid as a Device for Backup 71.2.3 Power and Heat Integration in Management System 81.2.4 Combination of Heat and Electrical Power System 91.3 System of Energy Management 101.3.1 Classification of MSE 101.3.1.1 MSE Based on Conventional Sources 101.3.1.2 MSE Based on SSE 101.3.1.3 MSE Based on DSM 111.3.1.4 MSE Based on Hybrid System 111.3.2 Steps of MSE During Problem Solving 111.3.2.1 Prediction of Uncertain Parameters 121.3.2.2 Uncertainty Modeling 121.3.2.3 Mathematical Formulation 121.3.2.4 Optimization 131.3.3 Micro-Grid in Islanded Mode 131.3.3.1 Objective Functions and Constraints of System 131.3.4 Micro-Grid Operation in Grid-Connected Mode 141.3.4.1 Objective Functions and Constraints of the Systems 141.4 Algorithms Used in Optimizing Energy Management System 161.5 Conclusion 19References 202 Power and Energy Management in Microgrid 25Jayesh J. Joglekar2.1 Introduction 252.2 Microgrid Structure 262.2.1 Selection of Source for DG 272.2.1.1 Phosphoric Acid Fuel Cell (PAFC) 272.2.1.2 Mathematical Modeling of PAFC Fuel Cell 272.3 Power Flow Management in Microgrid 312.4 Generalized Unified Power Flow Controller (GUPFC) 332.4.1 Mathematical Modeling of GUPFC 342.5 Active GUPFC 382.5.1 Active GUPFC Control System 392.5.1.1 Series Converter 402.5.1.2 Shunt Converter 422.5.2 Simulation of Active GUPFC With General Test System 432.5.3 Simulation of Active GUPFC With IEEE 9 Bus Test System 432.5.3.1 Test Case: 1—Without GUPFC and Without Fuel Cell 452.5.3.2 Test Case: 2—Without GUPFC and With Fuel Cell 472.5.3.3 Test Case: 3—With GUPFC and Without Fuel Cell 482.5.3.4 Test Case: 4—With GUPFC and With Fuel Cell 492.5.3.5 Test Case: 5—With Active GUPFC 492.5.4 Summary 522.6 Appendix General Test System 532.6.1 IEEE 9 Bus Test System 53References 553 Review of Energy Storage System for Microgrid 57G.V. Brahmendra Kumar and K. Palanisamy3.1 Introduction 583.2 Detailed View of ESS 603.2.1 Configuration of ESS 603.2.2 Structure of ESS With Other Devices 603.2.3 ESS Classifications 623.3 Types of ESS 623.3.1 Mechanical ESS 623.3.2 Flywheel ESS 633.3.3 CAES System 643.3.4 PHS System 653.3.5 CES Systems 663.3.6 Hydrogen Energy Storage (HES) 673.3.7 Battery-Based ESS 683.3.8 Electrical Energy Storage (EES) System 713.3.8.1 Capacitors 713.3.8.2 Supercapacitors (SCs) 723.3.9 SMES 733.3.10 Thermal Energy Storage Systems (TESS) 743.3.10.1 SHS 753.3.10.2 Latent 753.3.10.3 Absorption 753.3.10.4 Hybrid ESS 763.4 Comparison of Current ESS on Large Scale 773.5 Importance of Storage in Modern Power Systems 773.5.1 Generation Balance and Fluctuation in Demand 773.5.2 Intermediate Penetration of Renewable Energy 773.5.3 Use of the Grid 803.5.4 Operations on the Market 803.5.5 Flexibility in Scheduling 803.5.6 Peak Shaving Support 803.5.7 Improve the Quality of Power 813.5.8 Carbon Emission Control 813.5.9 Improvement of Service Efficiency 813.5.10 Emergency Assistance and Support for Black Start 813.6 ESS Issues and Challenges 813.6.1 Selection of Materials 823.6.2 ESS Size and Cost 823.6.3 Energy Management System 833.6.4 Impact on the Environment 833.6.5 Issues of Safety 833.7 Conclusion 84Acknowledgment 85References 854 Single Phase Inverter Fuzzy Logic Phase Locked Loop 91Maxwell Sibanyoni, S.P. Daniel Chowdhury and L.J. Ngoma4.1 Introduction 914.2 PLL Synchronization Techniques 924.2.1 T/4 Transport Delay PLL 954.2.2 Inverse Park Transform PLL 964.2.3 Enhanced PLL 974.2.4 Second Order Generalized Integrator Orthogonal Signal Generator Synchronous Reference Frame (SOGI-OSG SRF) PLL 984.2.5 Cascaded Generalized Integrator PLL (CGI-PLL) 994.2.6 Cascaded Delayed Signal Cancellation PLL 1004.3 Fuzzy Logic Control 1014.4 Fuzzy Logic PLL Model 1034.4.1 Fuzzification 1034.4.2 Inference Engine 1054.4.3 Defuzzification 1084.5 Simulation and Analysis of Results 1104.5.1 Test Signal Generator 1104.5.2 Proposed SOGI FLC PLL Performance Under Fault Conditions 1134.5.2.1 Test Case 1 1134.5.2.2 Test Case 2 1144.5.2.3 Test Case 3 1154.5.2.4 Test Case 4 1154.5.2.5 Test Case 5 1164.5.2.6 Test Case 6 1174.6 Conclusion 118Acknowledgment 118References 1195 Power Electronics Interfaces in Microgrid Applications 121Indrajit Sarkar5.1 Introduction 1225.2 Microgrid Classification 1225.2.1 AC Microgrid 1225.2.2 DC Microgrids 1245.2.3 Hybrid Microgrid 1265.3 Role of Power Electronics in Microgrid Application 1275.4 Power Converters 1285.4.1 DC/DC Converters 1285.4.2 Non-Isolated DC/DC Converters 1295.4.2.1 Maximum Power Point Tracking (MPPT) 1305.4.3 Isolated DC/DC Converters 1355.4.4 AC to DC Converters 1375.4.5 DC to AC Converters 1395.5 Conclusion 143References 1436 Reconfigurable Battery Management System for Microgrid Application 145Saravanan, S., Pandiyan, P., Chinnadurai, T., Ramji, Tiwari., Prabaharan, N., Senthil Kumar, R. and Lenin Pugalhanthi, P.6.1 Introduction 1466.2 Individual Cell Properties 1476.2.1 Modeling of Cell 1476.2.1.1 Second Order Model 1476.2.2 Simplified Non-Linear Model 1486.3 State of Charge 1496.4 State of Health 1506.5 Battery Life 1506.6 Rate Discharge Effect 1516.7 Recovery Effect 1526.8 Conventional Methods and its Issues 1526.8.1 Series Connected 1526.8.2 Parallel Connected 1546.9 Series-Parallel Connections 1546.10 Evolution of Battery Management System 1556.10.1 Necessity for Reconfigurable BMS 1566.10.2 Conventional R-BMS Methods 1566.10.2.1 First Design 1576.10.2.2 Series Topology 1586.10.2.3 Self X Topology 1586.10.2.4 Dependable Efficient Scalable Architecture Method 1596.10.2.5 Genetic Algorithm-Based Method 1606.10.2.6 Graph-Based Technique 1616.10.2.7 Power Tree-Based Technique 1626.11 Modeling of Reconfigurable-BMS 1636.12 Real Time Design Aspects 1646.12.1 Sensing Module Stage 1656.12.2 Control Module Stage 1656.12.2.1 Health Factor of Reconfiguration 1666.12.2.2 Reconfiguration Time Delay and Transient Load Supply 1666.12.3 Actuation Module 1676.12.3.1 Order of Switching 1676.12.3.2 Stress and Faults of Switches 1696.12.3.3 Determining Number of Cells in a Module 1706.13 Opportunities and Challenges 1716.13.1 Modeling and Simulation 1716.13.2 Hardware Design 1716.13.3 Granularity 1716.13.4 Hardware Overhead 1726.13.5 Intelligent Algorithms 1726.13.6 Distributed Reconfigurable Battery Systems 1726.14 Conclusion 173References 1737 Load Flow Analysis for Micro Grid 177Sivaraman Palanisamy, Dr. Sharmeela Chenniappan and Dr. S. Elango7.1 Introduction 1777.1.1 Islanded Mode of Operation 1787.1.2 Grid Connected Mode of Operation 1787.2 Load Flow Analysis for Micro Grid 1797.3 Example 1797.3.1 Power Source 1807.4 Energy Storage System 1807.5 Connected Loads 1827.6 Reactive Power Compensation 1827.7 Modeling and Simulation 1827.7.1 Case 1 1827.7.2 Case 2 1847.7.3 Case 3 1877.7.4 Case 4 1897.7.5 Case 5 1917.8 Conclusion 193References 1958 AC Microgrid Protection Coordination 197Ali M. Eltamaly, Yehia Sayed Mohamed, Abou-Hashema M. El-Sayed and Amer Nasr A. Elghaffar8.1 Introduction 1978.2 Fault Analysis 2008.2.1 Symmetrical Fault Analysis 2018.2.2 Single Line to Ground Fault 2028.2.3 Line-to-Line Fault 2048.2.4 Double Line-to-Ground Fault 2068.3 Protection Coordination 2088.3.1 Overcurrent Protection 2098.3.2 Directional Overcurrent/Earth Fault Function 2118.3.3 Distance Protection Function 2148.3.4 Distance Acceleration Scheme 2178.3.5 Under/Over Voltage/Frequency Protection 2198.4 Conclusion 221Acknowledgment 224References 2249 A Numerical Approach for Estimating Emulated Inertia With Decentralized Frequency Control of Energy Storage Units for Hybrid Renewable Energy Microgrid System 227Shubham Tiwari, Jai Govind Singh and Weerakorn Ongsakul9.1 Introduction 2289.2 Proposed Methodology 2319.2.1 Response in Conventional Grids 2319.2.2 Strategy for Digital Inertia Emulation in Hybrid Renewable Energy Microgrids 2329.2.3 Proposed Mathematical Formulation for Estimation of Digital Inertia Constant for Static Renewable Energy Sources 2359.3 Results and Discussions 2389.3.1 Test System 2389.3.2 Simulation and Study of Case 1 2419.3.2.1 Investigation of Scenario A 2419.3.2.2 Investigation of Scenario B 2439.3.2.3 Discussion for Case 1 2459.3.3 Simulation and Study of Case 2 2469.3.3.1 Investigation of Scenario A 2469.3.3.2 Investigation of Scenario B 2489.3.3.3 Discussion for Case 2 2509.3.4 Simulation and Study for Case 3 2509.3.4.1 Discussion for Case 3 2519.4 Conclusion 252References 25310 Power Quality Issues in Microgrid and its Solutions 255R. Zahira, D. Lakshmi and C.N. Ravi10.1 Introduction 25610.1.1 Benefits of Microgrid 25710.1.2 Microgrid Architecture 25710.1.3 Main Components of Microgrid 25810.2 Classification of Microgrids 25810.2.1 Other Classifications 25910.2.2 Based on Function Demand 25910.2.3 By AC/DC Type 25910.3 DC Microgrid 26010.3.1 Purpose of the DC Microgrid System 26010.4 AC Microgrid 26110.5 AC/DC Microgrid 26210.6 Enhancement of Voltage Profile by the Inclusion of RES 26310.6.1 Sample Microgrid 26310.7 Power Quality in Microgrid 26710.8 Power Quality Disturbances 27010.9 International Standards for Power Quality 27010.10 Power Quality Disturbances in Microgrid 27110.10.1 Modeling of Microgrid 27110.11 Shunt Active Power Filter (SAPF) Design 27210.11.1 Reference Current Generation 27410.12 Control Techniques of SAPF 27610.13 SPWM Controller 27710.14 Sliding Mode Controller 27710.15 Fuzzy-PI Controller 27810.16 GWO-PI Controller 27910.17 Metaphysical Description of Optimization Problems With GWO 28110.18 Conclusion 284References 28511 Power Quality Improvement in Microgrid System Using PSO-Based UPQC Controller 287T. Eswara Rao, Krishna Mohan Tatikonda, S. Elango and J. Charan Kumar11.1 Introduction 28811.2 Microgrid System 28911.2.1 Wind Energy System 29011.2.1.1 Modeling of Wind Turbine System 29011.2.2 Perturb and Observe MPPT Algorithm 29111.2.3 MPPT Converter 29111.3 Unified Power Quality Conditioner 29311.3.1 UPQC Series Converter 29311.3.2 UPQC Shunt APF Controller 29511.4 Particle Swarm Optimization 29711.4.1 Velocity Function 29711.4.2 Analysis of PSO Technique 29811.5 Simulation and Results 29911.5.1 Case 1: With PI Controller 30011.5.2 Case 2: With PSO Technique 30111.6 Conclusion 304References 30512 Power Quality Enhancement and Grid Support Using Solar Energy Conversion System 309CH. S. Balasubrahmanyam, Om Hari Gupta and Vijay K. Sood12.1 Introduction 30912.2 Renewable Energy and its Conversion Into Useful Form 31212.3 Power System Harmonics and Their Cause 31312.4 Power Factor (p.f.) and its Effects 31612.5 Solar Energy System With Power Quality Enhancement (SEPQ) 31712.6 Results and Discussions 32012.6.1 Mode-1 (SEPQ as STATCOM) 32012.6.2 Mode-2 (SEPQ as Shunt APF) 32012.6.3 Mode-3 (SEPQ as D-STATCOM) 32212.7 Conclusion 326References 32713 Power Quality Improvement of a 3-Phase-3-Wire Grid-Tied PV-Fuel Cell System by 3-Phase Active Filter Employing Sinusoidal Current Control Strategy 329Rudranarayan Senapati, Sthita Prajna Mishra, Rajendra Narayan Senapati and Priyansha Sharma13.1 Introduction 33013.2 Active Power Filter (APF) 33313.2.1 Shunt Active Power Filter (ShPF) 33413.2.1.1 Configuration of ShPF 33413.2.2 Series Active Power Filter (SAF) 33513.2.2.1 Configuration of SAF 33613.3 Sinusoidal Current Control Strategy (SCCS) for APFs 33713.4 Sinusoidal Current Control Strategy for ShPF 34213.5 Sinusoidal Current Control Strategy for SAF 34913.6 Solid Oxide Fuel Cell (SOFC) 35313.6.1 Operation 35413.6.2 Anode 35513.6.3 Electrolyte 35513.6.4 Cathode 35613.6.5 Comparative Analysis of Various Fuel Cells 35613.7 Simulation Analysis 35613.7.1 Shunt Active Power Filter 35813.7.1.1 ShPF for a 3-φ 3-Wire (3P3W) System With Non-Linear Loading 35813.7.1.2 For a PV-Grid System (Constant Irradiance Condition) 36013.7.1.3 For a PV-SOFC Integrated System 36413.7.2 Series Active Power Filter 36613.7.2.1 SAF for a 3-φ 3-Wire (3P3W) System With Non-Linear Load Condition 36613.7.2.2 For a PV-Grid System (Constant Irradiance Condition) 36813.7.2.3 For a PV-SOFC Integrated System 37013.8 Conclusion 373References 37314 Application of Fuzzy Logic in Power Quality Assessment of Modern Power Systems 377V. Vignesh Kumar and C.K. Babulal14.1 Introduction 37814.2 Power Quality Indices 37914.2.1 Total Harmonic Distortion 37914.2.2 Total Demand Distortion 38014.2.3 Power and Power Factor Indices 38014.2.4 Transmission Efficiency Power Factor (TEPF) 38114.2.5 Oscillation Power Factor (OSCPF) 38214.2.6 Displacement Power Factor (DPF) 38314.3 Fuzzy Logic Systems 38314.4 Development of Fuzzy Based Power Quality Evaluation Modules 38414.4.1 Stage I: Fuzzy Logic Based Total Demand Distortion 38514.4.1.1 Performance of FTDDF Under Sinusoidal Situations 38814.4.1.2 Performance of FTDDF Under Nonsinusoidal Situations 38914.4.2 Stage II—Fuzzy Representative Quality Power Factor (FRQPF) 39014.4.2.1 Performance of FRQPF Under Sinusoidal and Nonsinusoidal Situations 39314.4.3 Stage III—Fuzzy Power Quality Index (FPQI) Module 39514.4.3.1 Performance of FPQI Under Sinusoidal and Nonsinusoidal Situations 39714.5 Conclusion 401References 40115 Applications of Internet of Things for Microgrid 405Vikram Kulkarni, Sarat Kumar Sahoo and Rejo Mathew15.1 Introduction 40515.2 Internet of Things 40815.2.1 Architecture and Design 40915.2.2 Analysis of Data Science 41015.3 Smart Micro Grid: An IoT Perspective 41015.4 Literature Survey on the IoT for SMG 41115.4.1 Advanced Metering Infrastructure Based on IoT for SMG 41415.4.2 Sub-Systems of AMI 41415.4.3 Every Smart Meter Based on IoT has to Provide the Following Functionalities 41615.4.4 Communication 41715.4.5 Cloud Computing Applications for SMG 41815.5 Cyber Security Challenges for SMG 41915.6 Conclusion 421References 42316 Application of Artificial Intelligent Techniques in Microgrid 429S. Anbarasi, S. Ramesh, S. Sivakumar and S. Manimaran16.1 Introduction 43016.2 Main Problems Faced in Microgrid 43116.3 Application of AI Techniques in Microgrid 43116.3.1 Power Quality Issues and Control 43216.3.1.1 Preamble of Power Quality Problem 43216.3.1.2 Issues with Control and Operation of MicroGrid Systems 43316.3.1.3 AI Techniques for Improving Power Quality Issues 43416.3.2 Energy Storage System With Economic Power Dispatch 43816.3.2.1 Energy Storage System in Microgrid 43816.3.2.2 Need for Intelligent Approaches in Energy Storage System 44016.3.2.3 Intelligent Methodologies for ESS Integrated in Microgrid 44116.3.3 Energy Management System 44416.3.3.1 Description of Energy Management System 44416.3.3.2 EMS and Distributed Energy Resources 44516.3.3.3 Intelligent Energy Management for a Microgrid 44616.4 Conclusion 448References 44917 Mathematical Modeling for Green Energy Smart Meter for Microgrids 451Moloko Joseph Sebake and Meera K. Joseph17.1 Introduction 45117.1.1 Smart Meter 45217.1.2 Green Energy 45317.1.3 Microgrid 45317.1.4 MPPT Solar Charge Controller 45417.2 Related Work 45417.3 Proposed Technical Architecture 45617.3.1 Green Energy Smart Meter Architecture 45617.3.2 Solar Panel 45617.3.3 MPPT Controller 45617.3.4 Battery 45717.3.5 Solid-State Switch 45717.3.6 Electrical Load 45717.3.7 Solar Voltage Sensor 45717.3.8 Batter Voltage Sensor 45817.3.9 Current Sensor 45817.3.10 Microcontroller 45817.3.11 Wi-Fi Module 45817.3.12 GSM/3G/LTE Module 45917.3.13 LCD Display 45917.4 Proposed Mathematical Model 45917.5 Results 462Conclusion 468References 46918 Microgrid Communication 471R. Sandhya and Sharmeela Chenniappan18.1 Introduction 47118.2 Reasons for Microgrids 47318.3 Microgrid Control 47418.4 Control Including Communication 47418.5 Control with No Communication 47518.6 Requirements 47818.7 Reliability 47818.8 Microgrid Communication 47918.9 Microgrid Communication Networks 48118.9.1 Wi-Fi 48118.9.2 WiMAX-Based Network 48218.9.3 Wired and Wireless-Based Integrated Network 48218.9.4 Smart Grids 48218.10 Key Aspects of Communication Networks in Smart Grids 48318.11 Customer Premises Network (CPN) 48318.12 Architectures and Technologies Utilized in Communication Networks Within the Transmission Grid 485References 48719 Placement of Energy Exchange Centers and Bidding Strategies for Smartgrid Environment 491Balaji, S. and Ayush, T.19.1 Introduction 49119.1.1 Overview 49119.1.2 Energy Exchange Centers 49219.1.3 Energy Markets 49319.2 Local Energy Centers and Optimal Placement 49519.2.1 Problem Formulation (Clustering of Local Energy Market) 49619.2.2 Clustering Algorithm 49619.2.3 Test Cases 49719.2.4 Results and Discussions 49819.2.5 Conclusions for Simulations Based on Modified K Means Clustering for Optimal Location of EEC 50119.3 Local Energy Markets and Bidding Strategies 50319.3.1 Prosumer Centric Retail Electricity Market 50419.3.2 System Modeling 50519.3.2.1 Prosumer Centric Framework 50519.3.2.2 Electricity Prosumers 50519.3.2.3 Modeling of Utility Companies 50719.3.2.4 Modeling of Distribution System Operator (DSO) 50719.3.2.5 Supply Function Equilibrium 50719.3.2.6 Constraints 50819.3.3 Solution Methodology 50919.3.3.1 Game Theory Approach 50919.3.3.2 Relaxation Algorithm 51119.3.3.3 Bi-Level Algorithm 51119.3.3.4 Simulation Results 51219.3.3.5 Nikaido-Isoda Formulation 51319.3.4 Case Study 51319.3.4.1 Plots 51419.3.4.2 Anti-Dumping 51419.3.4.3 Macro-Control 51419.3.4.4 Sensitivity Analysis 514Conclusion 517References 518Index 521