Renewable Integrated Power System Stability and Control

Hêmin Golpîra, earned his PhD degree from Tarbiat Modares University, Tehran, Iran. Since 2016 he has been an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Kurdistan. He was formerly an Associate Fellow at the University of Wisconsin-Madison, USA, and a Visiting Professor at the École Centrale de Lille, France.Arturo Román-Messina earned his PhD degree from Imperial College, London, UK. Since 1997 is a Professor at the Center for Research and Advanced Studies of the National Polytechnic Institute of Mexico. A Fellow of the IEEE, he is on the editorial and advisory boards of Electric Power Systems Research, and Electric Power Components and Systems.Hassan Bevrani, PhD, is a Professor and Head of Smart/Micro Grids Research Center at the University of Kurdistan. He received his doctorate in Electrical Engineering from Osaka University in Japan. He is the author and co-author of more than 6 books, 15 book chapters, and 350 journal/conference papers.

• Preface xiiiAcknowledgments xviiNomenclature xviiiList of Abbreviations and Acronyms xxi1 Introduction 11.1 Power System Stability and Control 11.2 Current State of Power System Stability and Control 41.2.1 Frequency Control 51.2.2 Voltage Control 61.2.3 Oscillation Damping 71.3 Data-Driven Wide-Area Power System Monitoring and Control 81.4 Dynamics Modeling and Parameters Estimation 101.4.1 Modeling of Frequency, Voltage, and Angle Controls 111.4.2 Parameters Estimation 121.5 Summary 14References 142 MG Penetrated Power Grid Modeling 252.1 Introduction 252.2 Basic Concepts 262.2.1 Dynamic Equivalencing 262.2.2 Background on Study Zone and External System 272.3 Power Grid Modeling 282.3.1 The Notion of Center-of Gravity (COG) 282.3.1.1 Key Concept 282.3.1.2 Basic Assumptions 322.3.1.3 Modeling Formulation 322.3.1.4 Local Frequency Estimation 332.3.1.5 Simulation Results 352.3.2 An Enhanced COG-Based Model 462.3.2.1 Key Concept 462.3.2.2 Simulation Results 492.3.3 Generalized Equivalent Model 502.3.3.1 Basic Logic 502.3.3.2 Simulation and Results 512.4 MG Equivalent Model 532.4.1 Islanded Mode 542.4.1.1 Synchronous-Based DG 542.4.1.2 Genset Model Validation 572.4.1.3 Inverter-Based DG 582.4.1.4 Inverter-Based DG Model Validation 612.4.2 Grid-Connected Mode 612.4.2.1 Basic Logic 612.4.2.2 Model Validation 632.5 Summary 67References 673 Stability Assessment of Power Grids with High Microgrid Penetration 713.1 Introduction 713.1.1 Motivation 713.1.2 Relations with Previous Literature 723.2 Frequency Stability Assessment 733.2.1 Background on Frequency Indices 733.2.1.1 Rate of Change of Frequency 733.2.1.2 Frequency Nadir 743.2.1.3 Delta Frequency Detection 743.2.2 Frequency Stability Assessment Under High MG Penetration Levels 743.2.3 Sensitivity Factors 743.2.3.1 Frequency Response 743.2.3.2 Delta Frequency Detection 773.2.4 Simulation and Results 783.3 Maximum Penetration Level: Frequency Stability 803.3.1 Basic Principle 803.3.2 Background on MG Modeling 813.3.3 Minimum Inertia Related to Frequency Nadir 823.3.4 Minimum Inertia Related to Delta Frequency Detection 843.3.5 Minimum Inertia Related to RoCoF 853.3.6 Maximum Penetration Level 863.3.7 Simulation and Results 863.3.7.1 Analysis Tools 863.3.7.2 Dynamical Simulation Results 863.4 Small-Signal Stability Assessment 903.4.1 Basic Definition 903.4.2 Key Concept 903.4.3 Simulation and Results 913.5 Maximum Penetration Level: Small-Signal Stability 933.5.1 Basic Idea 933.5.2 Simulation and Results 933.6 Voltage-Based Realization of the MG-Integrated Power Grid 943.6.1 Key Concepts 953.6.2 Jacobian Sensitivities 953.6.2.1 V-P Sensitivity 953.6.2.2 V-Q Sensitivity 963.6.3 Simulation and Results 973.7 Summary 99References 1004 Advanced Virtual Inertia Control and Optimal Placement 1034.1 Introduction 1034.2 Virtual Synchronous Generator 1044.2.1 Concept and Structure 1054.2.2 Basic Control Scheme and Applications 1064.2.3 Application in Power System Dynamic Enhancement 1084.2.3.1 Scenario 1: 10-MW Load Increase at Bus 9 1094.2.3.2 Scenario 2: 20-MW Power Command Decrease of G3 1094.2.4 Application to Power Grids with HVDC Systems 1104.3 Dispatchable Inertia Placement 1134.3.1 Frequency Dynamics Enhancement 1134.3.1.1 Background: Literature Review 1134.3.1.2 Virtual Inertia Modeling 1144.3.1.3 Experimental Verification 1164.3.1.4 Economic Modeling 1194.3.1.5 Simulation and Results 1244.3.1.6 Sensitivity Analysis 1344.3.2 Small-Signal Stability 1364.3.2.1 Objective Function 1364.3.2.2 Simulation Results 1374.4 Summary 139References 1395 Wide-Area Voltage Monitoring in High-Renewable Integrated Power Systems 1455.1 Introduction 1465.2 Voltage Control Areas: A Background 1475.2.1 Voltage Sensitivities 1485.2.2 Electrical Distances 1495.2.3 Reactive Control Zones and Pilot Nodes 1505.2.3.1 Selection of Optimal Pilot Buses 1515.2.3.2 Selection of Control Plants 1515.2.4 Other Approaches 1525.3 Data-driven Approaches 1535.3.1 Wide-Area Voltage and Reactive Power Regulation 1545.3.2 PMU-Based Voltage Monitoring 1555.4 Theoretical Framework 1555.4.1 Dynamic Trajectories 1565.4.2 Spectral Graph Theory 1575.4.3 Kernel Methods 1575.4.3.1 Markov Matrices 1595.4.3.2 The Markov Clustering Algorithm 1625.4.4 Spatiotemporal Clustering 1645.5 Case Study 1655.5.1 Sensitivity Studies 1655.5.2 Data-Driven Analysis 1695.5.3 Measurement-Based Reactive Control Areas 1715.5.3.1 Diffusion Maps 1715.5.4 Direct Clustering 1755.5.5 Correlation Analysis 1765.5.5.1 Direct Analysis of Concatenated Data 1785.5.5.2 Two-Way Correlation Analysis 1795.5.5.3 Partial Least Squares Correlation 1795.6 Summary 181References 1816 Advanced Control Synthesis 1856.1 Introduction 1856.2 Frequency Dynamics Enhancement 1866.2.1 Background: The Concept of Flexible Inertia 1866.2.2 Frequency Dynamics Propagation 1896.2.3 Inertia-Based Control Scheme 1916.2.4 Flexible Inertia: Practical Considerations 1926.2.5 Results and Discussions 1946.3 Small Signal Stability Enhancement 2006.3.1 Key Concept 2006.3.2 Control Scheme Design 2016.3.3 Simulation and Results 2046.4 Summary 207References 2077 Small-Signal and Transient Stability Assessment Using Data-Driven Approaches 2117.1 Background and Motivation 2127.2 Modal Characterization Using Data-Driven Approaches 2137.2.1 Modal Decomposition 2137.2.2 Multisignal Prony Analysis 2157.2.2.1 Standard Prony Analysis 2157.2.2.2 Modified Least-Squares Algorithm 2187.2.2.3 Multichannel Prony Analysis 2197.2.2.4 Hankel-SVD Methods 2217.2.3 Koopman and Dynamic Mode Decomposition Representations 2227.2.3.1 The Koopman Operator 2237.2.4 Dynamic Mode Decomposition 2237.2.4.1 SVD-Based Methods 2257.2.4.2 The Companion Matrix Approach 2287.2.4.3 Energy Criteria 2307.3 Studies of a Small-Scale Power System Model 2317.3.1 System Data and Operating Scenarios 2317.3.2 Exploratory Small-Signal Analysis 2347.3.3 Large System Performance 2367.3.3.1 Cases B–C 2367.3.3.2 Case D 2387.3.4 Mode Shape Identification 2417.3.5 Temporal Clustering 2427.4 Large-Scale System Study 2447.4.1 Case Study Description 2447.4.2 Renewable Generator Modeling 2457.4.3 Effect of Inverter-Based DGs on Oscillatory Stability 2457.4.4 Large System Performance 2467.4.5 Model Validation 2467.4.5.1 Reconstructed Flow Fields 2507.4.6 Identification of Mode Shapes Using DMD 2537.5 Analysis Results and Discussion 253References 2558 Solar and Wind Integration Case Studies 2598.1 General Context and Motivation 2598.2 Study System 2618.3 Wind Power Integration in the South Systems 2638.3.1 Study Region 2638.3.2 Existing System Limitations 2668.4 Impact of Increased Wind Penetration on the System Performance 2668.4.1 Study Considerations and Scenario Development 2668.4.2 Base Case Assessment 2678.4.2.1 System Oscillatory Response 2698.4.3 High Wind Penetration Case 2718.5 Frequency Response 2748.5.1 Frequency Variations 2748.5.2 Wind and Hydropower Coordination 2778.5.3 Response to Loss-of-Generation Events 2808.6 Effect of Voltage Control on System Dynamic Performance 2838.6.1 Voltage Support and Reactive Power Dispatch 2838.6.2 Effect of Voltage Control Characteristics 2838.7 Summary 288References 288Index 293

Select Guide Rating