Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques

Preface
About This Book
Contents
Editors and Contributors
Introduction to Power Quality in Microgrids
	1 Introduction
		1.1 Tidal Energy Source
		1.2 PQ Events
		1.3 PQ Mitigation Methods and Control Strategies
	2 Control Strategies for Enhancing PQ in MG
		2.1 Droop Control Method
		2.2 PQ Improvement with Controllers
	3 Application of Optimization Techniques to Analyze PQ Issues
	4 Applications of IoT and 5G Technology in Microgrid
	5 Conclusions
	References
Application of Computational Intelligence Methods for Power Quality Disturbance Detection, Classification and Mitigation in Microgrids
	1 Introduction
	2 Power Quality Issues
		2.1 Transients
		2.2 Short and Long Duration Variations
		2.3 Imbalance
		2.4 Waveform Distortion
	3 Power Quality Disturbance Detection and Classification
		3.1 Feature Extraction Techniques
		3.2 Fourier Transform and Its Variants
		3.3 Wavelet Transform
		3.4 Stockwell Transform (S-Transform)
		3.5 Gabor Transform
		3.6 Kalman Filter
		3.7 Hilbert-Huang Transform
		3.8 Mathematical Morphology
		3.9 Miscellaneous Techniques
	4 Classifier for Automatic Classification
		4.1 Artificial Neural Network
		4.2 Support Vector Machine (SVM)
		4.3 Fuzzy Logic (FL)
		4.4 Optimization Techniques
	5 Role of Computational Intelligence Methods in Power Quality Enhancement in Microgrid
		5.1 Particle Swarm Optimization (PSO)
		5.2 Fuzzy Logic (FL)
		5.3 Ant Colony Optimization (ACO)
		5.4 Artificial Neural Network (ANN)
		5.5 Other AI-Based Approaches
	6 Conclusion
	References
A Comprehensive Power Quality Mitigation Tool: UPQC
	1 Introduction
		1.1 Power Quality
		1.2 Major Power Quality Issues
		1.3 Consequences of Power Quality Issues
		1.4 Power Electronics Contribution to Power Quality Management
	2 Research Background on UPQC
		2.1 Initial Study of UPQC and Its Brief Description
		2.2 Classification of UPQC
		2.3 Different Control Approaches for UPQC
		2.4 Commercial Application and Economical Concern of UPQC
	3 Conclusions
	References
Real-Time Validation of Power Quality Enhancement Techniques in a Distribution Network
	1 Introduction
		1.1 Harmonics in Power System and Its Effect
		1.2 Power Factor and Its Effects
		1.3 Sag and Swell in the Power System
	2 Photovoltaic System with Power Quality Enhancement (PVSPQ)
	3 Real-Time Validations of PVSPQ by OPAL-RT for Power Quality Enhancement
		3.1 Reactive Power Compensation for Power Quality Enhancement
		3.2 Harmonic Distortion Compensation for Power Quality Enhancement
		3.3 Reactive Power and Harmonic Distortion Compensation for Power Quality Enhancement
	4 Conclusion
	References
Harmonic Distortion Assessment in Three-Phase Distribution Networks with the Combined Penetration of Renewable Energy and D-STATCOM
	1 Introduction
	2 Materials for Modeling of Network Components for Harmonic Analysis
		2.1 Lines
		2.2 Capacitor Banks
		2.3 Loads
		2.4 RES and D-STATCOM
	3 Harmonic Power Flow Method for Harmonic Distortion Assessment
	4 Results and Discussion
		4.1 Harmonic Solution of IEEE-13 Bus TPDN Without RES and D-STATCOM
		4.2 Case Studies on IEEE-13 Bus TPDN
		4.3 Case Studies and Discussions on IEEE-34 Bus TPDN
	5 Conclusions
	References
An Enhanced SRF Theory-Based Multifunctional Control Approach for Power Quality Improvement in Grid-Tied Photovoltaic Systems
	1 Introduction
	2 Issues Prevalent in Grid-Tied Photovoltaic (GPV) Systems
	3 Power Quality Enhancement Strategies for GPV Systems: State-of-the-Art
	4 Enhanced SRF Theory-Based Multifunctional Control Approach
		4.1 AF Mode
		4.2 RPI Mode
	5 Simulation Results and Discussions
		5.1 Case 1: Steady-State System Performance in Active Filter Mode of Operation
		5.2 Case 2: Dynamic System Performance in Renewable Power Injection Mode of Operation Under Varying Insolation Conditions
	6 Conclusion
	References
Adaptive Filtering for Power Quality Features with Optimized PI Gains in Four Wires UPQC
	1 Introduction
	2 Description of UPQC
	3 Description of Control Algorithm
		3.1 Fundamental Magnitude Extraction Using RLS Algorithm
		3.2 Reference Signal Generation using RLS Algorithm for UPQC
		3.3 PI Controller Gains Estimation Using SMO
	4 Simulation Results
		4.1 Reference Load Voltage Generation using RLS Algorithm
		4.2 Reference Load Voltage Generation using RLS Algorithm
	5 Hardware Results
		5.1 PV Cell Modeling
		5.2 Observation of Dynamic Performance
		5.3 Steady-State Performance Analysis of UPQC with RLS Control Under Voltage Disturbances
	6 Conclusion
	Appendix
	1. RLS Control Parameter on UPQC
	2. RLS Control Parameter on UPQC for Hardware Setup
	References
Fractional Order High Pass Filter Based Extremum Seeking Control for Grid Connected PV System
	1 Introduction
	2 Basic Definitions of Fractional Order
	3 Solar Photovoltaic System
		3.1 Solar Cell Model
		3.2 PV Module Model
	4 Control of Solar PV System Connected to Grid
		4.1 Voltage Source Inverter Control
		4.2 Extremum Seeking Control
		4.3 Fractional Order Extremum Seeking Algorithm
	5 Proposed Fractional Order HPF Based ESC
	6 Simulation Results and Discussions
		6.1 Results Under Uniform Insolation Condition
		6.2 Results Under Variable Insolation Conditions
	7 Conclusions
	References
Design and Analysis of Maximum Power Point Tracking-Based Charging System
	1 Introduction
	2 Description of the System
		2.1 Power Stage Component
		2.2 Controller Stage Component
	3 Design of Passive Components for Buck Converter
		3.1 Filter Inductor for Buck Converter (Lf)
		3.2 Filter Capacitor for Buck Converter (Cf)
	4 Design of Passive Component of Boost Converter
		4.1 Inductance of Boost Converter
	5 Specification and Design Parameters
	6 PV Emulator: Results and Discussions
		6.1 Standard Test Condition (STC) Operation
		6.2 PV Emulator System for 300W Specification
	7 Conclusions
		7.1 Future Research Direction
	References
Fault Detection, Classification, and Location in Underground Cables
	1 Introduction
	2 Conventional Methods for Fault Classification, Location, and Detection
		2.1 Distance Relay
		2.2 Traveling Wave Method
		2.3 Impedance-Based Method
		2.4 Bridge and Step Voltage Method
		2.5 Blavier Test
		2.6 Murray Loop Test
	3 Signal Processing Methods
		3.1 Wavelet Transform (WT)
		3.2 S Transform
		3.3 Time–Time (TT) Transform
	4 Artificial Intelligence Techniques
		4.1 Fuzzy Logic-Based System
		4.2 ANFIS
		4.3 CNN
		4.4 SVM
		4.5 ANN
		4.6 LSTM
		4.7 PNN
	5 Features of Various Fault Diagnosis Techniques
	6 Conclusion
	References
Performance Analysis of Fuzzy-Based Controller for Wind and Battery Fed UPQC
	1 Introduction
	2 Structure of Proposed U-WBS
		2.1 BS System
		2.2 Wind Power Generation System (WPGS)
	3 Control Strategy of Proposed U-WBS
		3.1 STF-UVGS
		3.2 SUAPF
		3.3 SEAPF
	4 Simulation Results
	5 Conclusion
	References
Optimal Scheduling of Micro-sources in Multi-microgrid System
	1 Introduction
	2 Problem Formulation
		2.1 Sectionalization of Active Distribution System
		2.2 Objective Function
	3 Optimization Technique
		3.1 Jaya Algorithm
		3.2 Algorithm: Implementation Steps for Proposed Methodology Using Jaya Algorithm
	4 Results and Analysis
		4.1 Test System
		4.2 Scenario-1 (Operating Cost Minimization)
		4.3 Scenario-2 (Active Power Loss Minimization)
		4.4 Scenario-3 (Voltage Deviation Minimization)
	5 Conclusions
	References
MPPT Algorithms for Solar PV–Drip Irrigation System
	1 Introduction
	2 Solar PV System
		2.1 Modeling of Photovoltaic Module
		2.2 Design of Boost Converter
	3 MPPT Methods
		3.1 P&O Algorithm
		3.2 Incremental Conductance MPPT Algorithm
		3.3 Reference Cell—Current Scaling MPPT Algorithm
		3.4 Modified (P&O) MPPT Method
	4 Performance of MPPTAlgorithms
		4.1 Perturb and Observe (P&O) Algorithm
		4.2 Incremental Conductance Based MPPT Algorithm
		4.3 Reference Cell—Current Scaling MPPT Algorithm
		4.4 Modified P&O MPPT Algorithm
	5 Drip Irrigation
	6 Conclusion
	References
Analysis of Various Speed Control Methods for PMSM Drive-Based Electric Vehicles
	1 Introduction
	2 Modelling of Permanent Magnet Synchronous Motor
	3 Strategies and Methods for Control
		3.1 Field-Oriented Control
		3.2 Sensorless Control
	4 Neural Network Control
	5 Fuzzy Logic Controller
	6 Conclusion
	References
Short-Term Load Forecasting Using Jaya Algorithm
	1 Introduction
		1.1 Related Work
		1.2 Contributions to the Work
	2 STLF Using Fuzzy Logic
		2.1 Block Diagram and Flowchart of Fuzzy Logic
		2.2 Detailed Modeling of STLF for Fuzzy Logic
	3 Jaya Algorithm (JA)
	4 Artificial Neural Network (ANN)
		4.1 Proposed Method of Implementing ANN
	5 Results and Discussion
		5.1 Results of STLF Using Fuzzy Logic (FL)
		5.2 Results of STLF Using Jaya Algorithm (JA)
		5.3 Results of STLF Using Artificial Neural Network (ANN)
		5.4 Comparison of MAPE of Three Proposed Computing Methods
	6 Conclusion
	References
Optimal Power Flow by Different Modern Optimization Techniques
	1 Introduction
	2 OPF: A General Overview
		2.1 Variables
		2.2 Constraints
		2.3 Objective Function
	3 Generic OPF Problem Formulation
	4 The Solution to the Problem of OPF
	5 Optimal Power Flow Recent Optimization Methods
		5.1 Bio-Inspired and Swarm Optimization Techniques
		5.2 Techniques for Human-Inspired Optimization
		5.3 Optimization Techniques Inspired by Physics
		5.4 Evolutionary-Inspired Optimization Techniques
		5.5 Hybrid Optimization Techniques
		5.6 Artificial Neural Networks (ANN) and Fuzzy Logic Approach
	6 Comparison Between the Recent Approaches
	7 Conclusion
	References
Review on Microgrids: Types, Challenges, Opportunities, Uncertainties, and Their Modeling
	1 Introduction
	2 What Is a Microgrid?
	3 Classification of Microgrids
		3.1 Remote Microgrids
		3.2 Campus Microgrids
		3.3 Military Microgrids
		3.4 Residential Microgrids
		3.5 Commercial Microgrids
	4 Microgrid Architectures
		4.1 AC Microgrids
		4.2 DC Microgrids
		4.3 AC–DC Microgrids
	5 Challenges in Microgrids
		5.1 Social Causes
		5.2 Technical Causes
		5.3 Economic Causes
		5.4 Environmental Causes
	6 Opportunities in Microgrids
		6.1 Safe Islanding Systems
		6.2 Load Fluctuation Absorbent
		6.3 Harmonics Free System
		6.4 Software-Defined Systems
		6.5 Cost-Efficient DERs
		6.6 Stable Systems
		6.7 Healthcare Benefits
		6.8 Artificial Intelligence Efficient
		6.9 Controlled Systems
		6.10 Nature-Friendly Systems
	7 Uncertainties in Microgrid and Modeling
		7.1 Uncertainty on the Side of Source
		7.2 Uncertainty on the Grid Side
		7.3 Uncertainty in the System
		7.4 Uncertainty on the Energy Storage Side
		7.5 Trading Methods
	8 Modeling of Various Components in Microgrids
		8.1 Modeling of Controllable Loads
		8.2 Modeling of Storage
		8.3 Modeling of Feature-Dependent Generation
		8.4 Modeling of Controllable Generation
	9 Conclusions
	References
Load Frequency Control in Two-Area Interconnected Systems Using DE-PID and PSO-PID
	1 Introduction
	2 Modeling of System
		2.1 Primary Loop of LFC
		2.2 Secondary Loop of LFC
		2.3 System Representation
	3 Problem Formulation and Solving Methods
		3.1 PID Controller
		3.2 Tuning Methods
	4 Test Results and Discussions
	5 Conclusions
	References
A Comprehensive Analysis of the Application of Swarm Intelligence Techniques to the Economic Load Dispatch Problem
	1 Introduction
	2 Problem Formulation of ELD
		2.1 Cost Function of Economic Dispatch
		2.2 Constraints
	3 Swarm Intelligence-Based Optimization Algorithm
		3.1 Particle Swarm Optimization (PSO)
		3.2 Ant Colony Optimization (ACO)
		3.3 Cuckoo Search Algorithm (CSA)
		3.4 Artificial Bee Colony Algorithm
		3.5 Firefly Algorithm
		3.6 Bat Algorithm
		3.7 Other Swarm Intelligence Algorithms
		3.8 Hybrid Swarm Intelligence Algorithm
	4 Conclusions
	References
Design of Observer-Based Robust Double Integral Sliding Mode Controller for Grid-Connected PV System
	1 Introduction
	2 Literature Review on Controllers for Grid-Tied PV Microgrid
	3 Design of Grid-Tied PV Microgrid
	4 Design of Grid-Tied PV Microgrid
	5 Water Droplet Optimization (WEO) Algorithm
		5.1 MVP
		5.2 DVP
		5.3 RVP
	6 Results and Discussion
	7 Conclusions
	References
An Introduction to Demand Response in the Microgrid
	1 Introduction
	2 Research Gap
	3 Research Objectives
	4 Problem Modeling
		4.1 Decision Variables
		4.2 Constraints
		4.3 Methods Employed
	5 Theoretical Case Study
		5.1 Queries and Conclusions at Peak Scheduling Hours
		5.2 Forecasting and Its Issues
		5.3 Rebound Effect and Its Impacts on MCP and TCT
	6 Conclusion
	References
Active Power Load Data Dimensionality Reduction Using Autoencoder
	1 Introduction
	2 Materials and Methods
		2.1 Autoencoder
		2.2 Active Power Load Dataset
	3 Results and Discussion
		3.1 Optimal Batch Size
	4 Conclusions
	References
Design of Misalignment-Tolerant Orthogonal Wireless Power Transfer Coils for Unmanned Aerial Vehicles
	1 Introduction
	2 Design of STMR-Based WPT System
		2.1 Schematic Diagram of STMR-Based WPT System for UAV
		2.2 Schematic Diagram of OTCTC-MR-Based WPT System for UAV
		2.3 Expressions for WPT System Circuit Parameters
	3 Design of STMR and OTCTC-MR WPT Coils
		3.1 Design of STMR-Based WPT System
		3.2 Design of OTCTC-MR-Based WPT System
	4 Simulation of WPT Systems and Results
		4.1 Simulation of STMR-Based WPT System
		4.2 Simulation of OTCTC-MR-Based WPT System
	5 Conclusions
	References
Energy Storage Technologies for Next-Generation Electrical Power Systems
	1 Introduction
	2 Classification of Energy Storage Systems (ESSs)
	3 Battery Energy Storage System (ESS)
		3.1 Modeling of Battery ESS
		3.2 State of Charge (SOC) of a Battery
		3.3 Total Energy and Power of a Battery
	4 Classification of Energy Storage Batteries
		4.1 Lead–Acid Batteries
		4.2 Lithium–Ion (Li-Ion) Batteries
		4.3 Nickel–Metal Hydride (Ni-MH) Batteries
		4.4 Nickel–Cadmium (Ni-Cd) Batteries
		4.5 Nickel–Zinc (NiZn) Batteries
	5 Supercapacitors and Fuel Cells
		5.1 Supercapacitors (SCs)
		5.2 Fuel Cells (FCs)
	6 Non-electrochemical Storage
		6.1 Compressed Air Energy Storage (CAES)
		6.2 Flywheel
	7 Hybrid Energy Storage System (HESS)
	8 Conclusions
	References
Modeling and Sizing of the Hybrid Renewable System Opting Genetic Algorithm
	1 Introduction
	2 Introduction to Genetic Algorithm-Based Model
	3 System Modeling
		3.1 Modeling of Components
		3.2 Modeling Based on Economic Analysis
	4 Simulation and Optimization of Sizes of Components
		4.1 Simulation Attempt
		4.2 Optimization of Component Sizes Based on Genetic Algorithm
	5 Inputs for Simulation
	6 Development of Optimization
	7 Discussion Based on Results
		7.1 Mathematical Modeling Results of Solar Panels
		7.2 Results Obtained on Analysis of Solar Data
		7.3 Results Based on Sizing Optimization of Hybrid System
		7.4 Discussion of Result of Best Optimized Case Study
	8 Generalization of Results
	9 Design of the Optimized Case of Hybrid Energy System
	10 Conclusion
	References
Author Index
Subject Index