Renewable Integrated Power System Stability and Control

Chapter 1 1.1 Power System Stability and Control 2 1.2 Current State of Power System Stability and Control 5 1.2.1 Frequency Control 6 1.2.2 Voltage Control 7 1.2.3 Oscillation Damping 8 1.3 Data-Driven Wide-Area Power System Monitoring and Control 10 1.4 Dynamics modelling and parameters estimation 13 1.4.1 Modelling of frequency, voltage, and angle controls 14 1.4.2 Parameters Estimation 15 1.5 Summary 17 References 17 Chapter 2 2.1 Introduction 2 2.2 Basic Concepts 2 2.2.1 The Notion of Dynamic Equivalencing 2 2.2.2 Background on Study Zone and External System 3 2.3 Power Grid Modelling 4 2.3.1 The Notion of Center-of Gravity (COG) 4 2.3.1.1 Key Concept 5 2.3.1.2 Basic Assumptions 9 2.3.1.3 Modelling Formulation 9 2.3.1.4. Local Frequency Estimation 10 2.3.1.5 Simulation Results 12 2.3.2 An Enhanced COG-Based Model 25 2.3.2.1 Key Concept 25 2.3.2.2 Simulation Results 28 2.3.3 Generalized Equivalent Model 29 2.3.3.1 Basic logic 29 2.3.3.2 Simulation and Results 30 2.4 MG equivalent model 34 2.4.1 Islanded Mode 35 2.4.1.1 Synchronous-based DG 35 2.4.1.2 Genset Model Validation 38 2.4.1.3 Inverter-based DG 39 2.4.1.3 Inverter-based DG Model validation 41 2.4.2. Grid-Connected Mode 42 2.4.2.1 Basic Logic 42 2.4.2.2 Model Validation 44 2.5 Summary 47 References 47 Chapter 3 3.1 Introduction 2 3.1.1 Motivation 2 3.1.2. Relations with previous literature 3 3.2 Frequency Stability Assessment 4 3.2.1 Background on Frequency Indices 4 3.2.2 Frequency stability assessment under high MG penetration levels 5 3.2.3 Sensitivity Factors 6 3.2.4 Simulation and Results 9 3.3 Maximum Penetration Level: Frequency Stability 13 3.3.1 Basic Principle 13 3.3.2 Background on MG Modeling 13 3.3.3 Minimum Inertia Related to Frequency Nadir 14 3.3.4 Minimum Inertia related to Delta Frequency Detection 16 3.3.5 Minimum Inertia related to RoCoF 17 3.3.6 Maximum Penetration Level 17 3.3.7 Simulation and Results 18 3.4 Small Signal Stability Assessment 22 3.4.1 Basic Definition 22 3.4.2 Key Concept 23 3.4.3 Simulation and Results 24 3.5 Maximum penetration level: Small Signal Stability 26 3.5.1 Basic Principle 26 3.5.2 Simulation Results 27 3.6 Voltage-Based Realization of the MG-Integrated Power Grid 28 3.6.1 Key concepts 28 3.6.2 Jacobian sensitivities 28 3.6.6 Simulation Results 30 3.7 Summary 33 3.6 References 33 Chapter 4 4.1 Introduction 2 4.3 Dispatchable Inertia Placement 13 4.3.1 Frequency Dynamics Enhancement 13 4.3.1.1 Background: Literature Review 13 4.3.1.2 Virtual Inertia Modelling 14 4.3.1.2.1 Concept 14 4.3.1.2.2 MUSIC Analysis: Notion and Application 15 4.3.1.3 Experimental Verification 16 4.3.1.4 Economic Modelling 20 4.3.1.5 Simulation results 25 4.3.1.6 Sensitivity Analysis 35 4.3.2 Small Signal Stability 37 4.3.2.1 Objective Function 37 4.3.2.2 Simulation Results 38 4.3 Summary 40 References 40 Chapter 5 5.1 Introduction 2 5.2 Background: The Notion of Voltage-control Areas 3 5.2.1 Voltage sensitivities 4 5.2.2 Electrical distances 5 5.2.3 Reactive control zones and pilot nodes 7 5.2.4 Other approaches 8 5.3 Measurement-based Approaches 9 5.3.1 Wide-area voltage and reactive power regulation 9 5.3.2 PMU-based voltage monitoring 11 5.4 Theoretical Framework 11 5.4.1 Dynamic trajectories 11 5.4.2 Spectral graph theory 12 5.4.3 Kernel methods 13 5.4.4 Spatio-temporal clustering 19 5.5 Case study 20 5.5.1 Sensitivity studies 21 5.5.2 Data-driven analysis 25 5.5.3 Measurement-based reactive control areas 27 5.5.4 Direct clustering 29 5.5.5 Correlation analysis 32 5.6 Summary 35 References 36 Chapter 6 6.1 Introduction 2 6.2 Frequency Dynamics Enhancement 2 6.2.1 Background: The Notion of Flexible Inertia 2 6.2.2 Frequency Dynamics Propagation 6 6.2.3 Inertia-Based Control Scheme 9 6.2.4 Flexible Inertia: Practical Considerations 11 6.2.5 Results and Discussions 12 6.3 Small Signal Stability Enhancement 19 6.3.1 Key Concept 19 6.3.2 Control Scheme Design 19 6.3.3 Simulation Results 23 6.4 Summary 26 References 26 Chapter 7 7.1 Background and Driving Forces 2 7.2 Modal Characterization Using Data-driven Approaches 3 7.2.1 Modal decomposition 3 7.2.2 Multi signal Prony analysis 5 7.2.3 Koopman and dynamic mode decomposition representations 11 7.2.4 Dynamic mode decomposition 12 7.3 Studies of a Small-scale Power System Model 19 7.3.1 System data and operating scenarios 19 7.3.2 Exploratory small-signal analysis 21 7.3.3 Large system performance 23 7.3.4 Mode shape identification 28 7.3.5 Temporal clustering 30 7.4 Large-scale System Study 31 7.4.1 Case study description 32 7.4.2 Renewable generator modeling 32 7.4.3 Effect of inverter-based DG on oscillatory stability 34 7.4.4 Large system performance 34 7.4.5 Model validation 36 7.4.6 Identification of mode shapes using DMD 40 7.5 Analysis Results and Discussion 40 References 41 Chapter 8 8.1 General Context and Motivation 2 8.2 Study Area 3 8.3 Wind power integration in the south systems 4 8.3.1 Study region 5 8.3.2 Existing system limitations 7 8.4 Impact of increased wind penetration on the system performance 8 8.4.1 Study considerations and scenario development 8 8.4.2 Base case assessment 9 8.4.3 High wind penetration case (Case D) 12 8.5 Frequency response 15 8.5.1 Frequency variations 15 8.5.2 Wind and hydropower coordination 18 8.5.3 Response to loss-of-generation events 21 8.6 Effect of voltage control on system dynamic performance 23 8.6.1 Voltage support and reactive power dispatch 24 8.6.2 Effect of voltage control characteristics 24 8.7 Summary 28 References 2