Microgrid Protection and Control

Microgrid Protection and Control
Copyright
Contents
Preface
Acknowledgments
1 The concept of microgrid and related terminologies
1.1 Introduction
1.2 Related concepts
1.2.1 Active distribution network
1.2.2 Energy internet
1.2.3 Virtual power plant
1.3 Misconceptions about microgrid
1.4 Types of microgrid
1.5 Components of microgrids
1.5.1 Distributed Generation
1.5.2 Energy storage systems
1.5.3 Power conversion system
1.5.4 Controllers and energy management system
1.5.5 Communication system
1.5.6 Loads
1.5.7 Protection system
References
2 Current industrial practice and research trends in microgrids
2.1 Introduction
2.2 The current industrial trends in microgrids
2.2.1 Microgrid global market trends
2.2.2 Microgrid application trends
2.2.3 Microgrid business models
2.2.4 Technological trends
2.2.4.1 Distributed energy resources technologies
2.2.4.2 Microgrid control and monitoring technologies
2.2.4.3 Microgrid protection technologies
2.2.4.4 Instrumentation and communication technologies
2.2.4.5 Microgrid planning, modeling, and simulation tools
2.3 Current research trends of microgrid
2.3.1 Microgrids research issues
2.3.2 Selected microgrid R&D projects
2.3.2.1 Consortium for electric reliability technology solutions
2.3.2.2 Microgrids, infrastructure resilience, and advanced controls launchpad
2.3.2.3 Renewable energy integration demonstrator singapore
2.3.2.4 Other research projects
2.3.3 International standards related to microgrids
References
3 Key technical challenges in protection and control of microgrid
3.1 Introduction
3.2 Challenges in control of microgrids
3.2.1 Low system inertia
3.2.2 Low reactance to resistance (X/R) ratio
3.2.3 Uncertainty and intermittency of renewable sources
3.2.4 Different modes of operation (grid-connected and island modes)
3.2.5 Existence and (in some cases) dominance of CBGs
3.3 Challenges in protection of microgrids
3.3.1 Different short-circuit current in island and grid-connected modes
3.3.2 Reduction in reach of impedance relays
3.3.3 Bidirectional power flows and voltage profile change
3.3.4 Dominant existence of CBGs
References
4 Short-term renewable generation and load forecasting in microgrids
4.1 Introduction
4.2 Basics and classification of renewable generation forecasting
4.3 Basics and classification of load forecasting
4.4 Short-term renewable generation and load forecasting techniques
4.4.1 Introduction
a) Physical methods
b) Time series methods
4.4.2 Physical models
4.4.2.1 Numerical weather prediction models
4.4.2.2 Sky imagery−based forecasts
4.4.3 Time series methods
4.4.3.1 Artificial neural network
4.4.3.2 Adaptive neuro-fuzzy inference system
4.4.3.3 Support vector machine
4.4.3.4 Deep neural network
4.4.3.5 Kernel function extreme learning machine
4.5 Accuracy enhancement techniques in generation and load forecasting
4.5.1 Forecast accuracy metrics
4.5.2 Factors affecting forecasting accuracy
4.5.3 Input variable selection methods
4.5.4 Data preprocessing
4.5.4.1 Fourier transform
4.5.4.2 Wavelet transform
4.5.4.3 Empirical mode decomposition
4.5.4.4 Variational mode decomposition
4.5.5 Output processing or ensembling methods
4.5.5.1 Simple averaging
4.5.5.1.1 Regression
4.5.5.1.2 Using an additional model
4.6 Application examples
4.6.1 Short-term wind forecasting using EMD and hybrid artificial intelligence technique
4.6.2 Day-ahead PV forecasting using VMD-GA-ANN
4.6.3 Short-term load forecasting using wavelet transform and LSTM
References
5 Fault and disturbance analysis in microgrid
5.1 Introduction
5.2 Distinguishing faults from dynamic and transient disturbances
5.3 Fault analysis
5.4 Advanced algorithms
5.4.1 Voltage and current THD-based algorithm
5.4.2 Park transformation-based algorithm
5.4.2.1 Symmetrical fault detection
5.4.2.2 Asymmetrical fault detection
5.4.3 Wavelet transform-based algorithm
5.4.3.1 Continuous wavelet transform
5.4.3.2 Discrete wavelet transform
5.4.3.3 Wavelet transform-based fault detection
5.4.4 Other applicable algorithms
References
6 Protection of microgrids
6.1 Introduction
6.2 Requirements of microgrid protection
6.3 Differences between protection of traditional power system and microgrids
6.4 Design of protection system for microgrids
6.4.1 Overcurrent protection
6.4.1.1 Coordination of overcurrent protection
6.4.2 Differential protection
6.4.3 Distance protection
6.4.4 Voltage-based protection
6.4.5 Adaptive protection
6.4.6 Machine learning-based protection schemes
6.5 Centralized protection for microgrids
6.6 Protection of looped microgrids
6.7 Earthing system in protection of microgrids
References
7 Dynamic control of microgrids
7.1 Introduction
7.2 Dynamic characteristic of microgrids
7.3 Modeling of dynamic disturbance system for microgrid
7.3.1 Modeling of power control loop
7.3.1.1 Modeling of phase angle generation
7.3.1.2 Modeling of reactive power control (voltage amplitude generation)
7.3.1.3 Modeling of double loop control (voltage and current control loops)
7.3.1.4 Modeling of low-pass filter
7.3.1.5 Modeling the distribution (microgrid) network
7.3.1.6 Modeling the load
7.3.1.7 Approximated linear model
7.4 State-space model and analysis of dynamic disturbance stability
7.4.1 Designing small-signal stability model of microgrid
7.4.1.1 Power controller
7.4.1.2 Voltage controller
7.4.1.3 Current controller
7.4.1.4 Low-pass filter
7.4.1.5 Distribution network model
7.4.1.6 Load model
7.4.1.7 Virtual resistor model
7.4.2 Eigenvalues and analysis of state-space model of dynamic control
7.4.2.1 Eigenvalue sensitivity to filter inductance Lf
7.4.2.2 Eigenvalue sensitivity to the transformer inductance Lt
7.4.2.3 Eigenvalue sensitivity to real power droop gain m
7.4.2.4 Eigenvalue sensitivity to reactive power droop gain n
7.4.2.5 Eigenvalue sensitivity to virtual resistance Rvir
7.5 Active damping and impedance reconstruction for improving dynamic stability
7.5.1 Realization of control strategy
7.5.1.1 Active damping
7.5.2 High-pass function damping
References
8 Transient control of microgrids
8.1 Introduction
8.2 Transient characteristics of microgrids
8.2.1 Causes for the transient disturbances in microgrids
8.2.1.1 Switching between grid-connected and island modes
8.2.1.2 Heavy load on/off switching
8.2.1.3 Major DG on/off switching
8.2.1.4 Fault clearing
8.2.2 System parameters during transient disturbances
8.2.2.1 Voltage sag and frequency drop of microgrid
8.3 Design of transient disturbance control system
8.3.1 Objectives of transient disturbance control system of a microgrid
8.3.2 Control strategies for transient disturbances in microgrids
8.3.2.1 Frequency/voltage droop control
8.3.2.1.1 Supplementary control to the droop control strategy
8.3.2.2 Energy storage system
8.3.2.3 Virtual synchronous generator in transient disturbance control
8.3.2.3.1 Eigenvalues analysis for the damping coefficient Dω
8.3.2.3.2 Filter inductance sensitivity analysis with eigenvalues by comparing the VSG and droop control systems
8.3.3 Hardware requirements of transient control systems
8.4 Identifying different kinds of faults from transient disturbances
8.5 Frequency and voltage ride-through
8.5.1 Frequency ride-through
8.5.2 Voltage ride-through
8.6 Application examples: practical experiment and simulation of transient disturbance control system
8.6.1 Transient control
8.6.1.1 Simulation results for transient control systems
8.6.1.2 Field testing results for the transient control device
References
9 Tertiary control of microgrid
9.1 Introduction
9.2 Optimal energy dispatching control in microgrids
9.2.1 Introduction
9.2.2 Mathematical modeling
9.2.2.1 Linear models
9.2.2.2 Nonlinear models
9.2.2.3 Multiobjective optimization modeling
9.2.2.4 Uncertainties modeling
9.2.2.5 Costs modeling
9.2.2.6 Constraint functions
9.2.3 Optimal energy dispatching algorithms for microgrid
9.2.3.1 Jaya algorithm
9.2.3.2 Whale optimization algorithm
9.2.3.3 Biogeography-based optimization algorithm
9.2.3.4 Markov decision process algorithm
9.2.3.5 Stackelberg game approach algorithm
9.2.3.6 Consensus theory-based algorithms
9.2.3.7 Particle swarm optimization algorithm
9.2.3.8 Imperialist competitive algorithm
9.2.4 Role of soft computing tools in microgrid control
9.3 Demand side management and control of microgrids
9.3.1 Introduction
9.3.2 Demand side management in microgrids
9.3.3 Demand response alternatives
9.3.3.1 Load management in the demand response
9.3.3.2 Price-based demand response
9.3.4 Intelligent demand response algorithms
9.3.4.1 Decision-making auction algorithm
9.3.4.2 Heuristic-based evolutionary algorithm
9.3.4.3 Greedy ratio algorithm
9.3.4.4 Distributed demand response algorithm
9.4 Energy efficiency of microgrids
9.4.1 Advanced energy efficiency services
9.4.2 Classified energy consumption data analysis
9.4.3 Energy efficiency assessment and analysis model
9.4.4 Energy efficiency diagnosis and optimization model
9.4.5 Energy efficiency data statistics report
9.5 Application example: simulation of microgrid central controller for energy management of resilient low-carbon microgrid
9.5.1 The microgrid platform and simulation model
9.5.2 Functions and overview of the MGCC
9.5.3 Operating algorithm of the MGCC
9.5.4 Testing procedure
9.5.5 Testing results
References
10 Communication requirements of microgrids
10.1 Introduction
10.2 Role of communication in microgrids
10.3 Communication media for application in microgrid
10.3.1 Copper cable
10.3.2 Fiber optics
10.3.3 Wireless communication
10.4 Communication protocols for application in microgrid
10.4.1 Internet Protocol
10.4.2 Modbus
10.4.3 Distributed Network Protocol
10.4.4 IEC 61850
10.4.5 Implementation of IEC 61850-based microgrid communication
10.4.5.1 FPGA-based communication for the 10kV microgrid
10.4.5.1.1 Background
10.4.5.1.2 Brief introduction of SV/GOOSE protocol-based communication
10.4.5.1.3 Realization of SV/GOOSE message communication
10.4.5.1.4 Description of FPGA based SV/GOOSE communication
10.4.5.2 The FPGA communication module for the 10kV microgrid system
10.4.5.2.1 A mechanism between central controller and local acquisition devices
10.4.5.2.2 A mechanism between the central controller and local controllers
10.4.5.2.3 A mechanism between local control devices
10.4.5.3 Interactive data format of FPGA and DSP
10.4.5.3.1 DSP writes to data zone
10.4.5.3.2 DSP receives from data zone
References
11 Application cases of industrial park microgrids' protection and control
11.1 Background
11.2 Demonstrational microgrid testbed
11.2.1 Introduction
11.2.2 Architecture and components
11.2.2.1 Wind turbines
11.2.2.2 Photovoltaic system
11.2.2.3 Microturbines
11.2.2.4 Diesel generators
11.2.2.5 Energy storage systems
11.2.3 Functional components
11.2.3.1 Data acquisition and control terminal devices
11.2.3.1.1 Electrical data acquisition terminal device
11.2.3.1.2 Thermal data acquisition terminal device
11.2.3.1.3 Gas data acquisition terminal device
11.2.3.1.4 End-user smart terminal devices
11.2.3.2 Communication system
11.2.3.3 Central monitoring and control system
11.2.3.4 Cloud computing technology
11.2.3.5 Renewable generation and load forecasting
11.2.3.6 Optimal dispatching
11.2.3.7 Dynamic and transient disturbance control systems
11.2.3.8 Protection system
11.2.4 Advanced functions
11.2.4.1 Energy conservation and efficiency services
11.2.4.2 Customized services
11.2.4.3 Grid auxiliary services
11.2.5 Operational results
11.2.5.1 Fault protection
11.2.5.2 Transient and dynamic disturbance stability
11.2.5.3 Renewable generation and load forecasting
11.3 Industrial microgrid
11.3.1 Introduction
11.3.2 Architecture and components
11.3.2.1 Photovoltaic system
11.3.2.2 Wind turbine
11.3.2.3 Energy storage system
11.3.3 Core technologies
11.3.4 Functional components
11.3.4.1 Renewable generation and load forecasting
11.3.4.2 Scheduling method
11.3.4.3 Transient and dynamic stability control systems
11.3.4.4 Demand side management
11.3.4.5 Communication network
11.3.4.6 Monitoring and control
11.3.5 Operational results
11.3.5.1 Fault and protection system
11.3.5.2 Transient disturbance suppression
11.3.5.3 Dynamic disturbance suppression
11.3.5.4 Seamless switching between grid-connected and island modes
References
Index