Оглавление
Группа авторов. DC Microgrids
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
DC Microgrids. Advances, Challenges, and Applications
Preface
1. On the DC Microgrids Protection Challenges, Schemes, and Devices – A Review
1.1 Introduction
1.2 Fault Characteristics and Analysis in DC Microgrid
1.3 DC Microgrid Protection Challenges
1.3.1 Low Inductance of DC System
1.3.2 Fast Rise Rate of DC Fault Current
1.3.3 Difficulties of Overcurrent (O/C) Relays Coordination
1.3.4 Fault Detection and Location
1.3.5 Arcing Fault Detection and Clearing
1.3.6 Short-Circuit (SC) Analysis and Change of Its Level
1.3.7 Non-Suitability of AC Circuit Breakers (ACCBs)
1.3.8 Inverters Low Fault Current Capacity
1.3.9 Constant Power Load (CPL) Impact
1.3.10 Grounding
1.4 DC Microgrid Protection Schemes
1.4.1 The Differential Protection-Based Strategies
1.4.2 The Voltage-Based Protection Strategies
1.4.3 The Adaptive Overcurrent Protection Schemes
1.4.4 Impedance-Based Protection Strategy (Distance Protection)
1.4.5 Non-Conventional Protection Schemes (Data-Based Protection Scheme)
1.5 DC Microgrid Protective Devices (PDs)
1.5.1 Z-Source DC Circuit Breakers (ZSB)
1.5.2 Hybrid DC Circuit Breakers (HCB)
1.5.3 Solid State Circuit Breakers (SSCBs)
1.5.4 Arc Fault Current Interrupter (AFCI)
1.5.5 Fuses
1.6 Conclusions
References
2. Control Strategies for DC Microgrids
2.1 Introduction: The Concept of Microgrids
2.1.1 DC Microgrids
2.2 Introduction: The Concept of Control Strategies
2.2.1 Basic Control Schemes for DC MGs. 2.2.1.1 Centralized Control Strategy
2.2.1.2 Decentralized Controller
2.2.1.3 Distributed Control
2.2.2 Multilevel Control
2.2.2.1 Primary Control
2.2.2.1.1 Conventional Droop Controller and Virtual Impedance
2.2.2.1.2 Improved Droop Controller
2.2.2.1.3 Active Current Controller
2.2.2.1.4 DC Bus Signaling
2.2.2.2 Secondary Control
2.2.2.3 Tertiary Control
2.2.2.4 Current Sharing Loop
2.2.2.5 Microgrid Central Controller (MGCC)
2.3 Control Strategies for DGs in DC MGs. 2.3.1 Control Strategy for Solar Cell in DC MGs
2.3.1.1 Control Strategy for Wind Energy in DC MGs
2.3.1.2 Control Strategy for Fuel Cell in DC MGs
2.3.1.3 Control Strategy for Energy Storage System in DC MGs
2.4 Conclusions and Future Scopes
References
3. Protection Issues in DC Microgrids
3.1 Introduction
3.1.1 Protection Challenge
3.1.1.1 Arcing and Fault Clearing Time
3.1.1.2 Stability
3.1.1.3 Multiterminal Protections
3.1.1.4 Ground Fault Challenges
3.1.1.5 Communication Challenges
3.1.2 Effect of Constant Power Loads (CPLs)
3.2 Fault Detection in DC MGs
3.2.1 Principles and Methods of Fault Detection
3.2.1.1 Voltage Magnitude-Based Detection
3.2.1.2 Current Magnitude-Based Detection
3.2.1.3 Impedance Estimation Method
3.2.1.4 Power Probe Unit (PPU) Method
3.3 Fault Location
3.3.1 Passive Approach
3.3.1.1 Traveling Wave-Based Scheme
3.3.1.2 Differential Fault Location
3.3.1.3 Local Measurement-Based Fault Location
3.3.2 Active Approach for Fault Location
3.3.2.1 Injection-Based Fault Location
3.4 Islanding Detection (ID)
3.4.1 Types of IDSs
3.4.2 Passive Detection Schemes (PDSs) for DC MGs
3.4.3 Active Detection Schemes (ADS) for DC MGs
3.5 Protection Coordination Strategy
3.6 Conclusion and Future Research Scopes
References
4. Dynamic Energy Management System of Microgrid Using AI Techniques: A Comprehensive & Comparative Study
Nomenclature
4.1 Introduction. 4.1.1 Background and Motivation
4.1.2 Prior Work
4.1.3 Contributions
4.1.4 Layout of the Chapter
4.2 Problem Statement
4.3 Mathematical Modelling of Microgrid
4.3.1 Cost Functions. 4.3.1.1 Diesel Generator
4.3.1.2 Solar Generation
4.3.1.3 Wind Generation Unit
4.3.1.4 Energy Storage System (ESS)
4.3.1.5 Transaction with Utility
4.3.2 Objective Function
4.3.3 Constraints
4.4 Optimization Algorithm
4.4.1 Heuristic-Based Genetic Algorithm (GA)
4.4.2 Pattern Search Algorithm (PSA)
4.5 Results
4.6 Conclusion
References
5. Energy Management Strategies Involving Energy Storage in DC Microgrid
5.1 Introduction
5.2 Literature Review
5.2.1 Classic Approaches of EMS
5.2.2 Meta-Heuristic Approach of EMS
5.2.3 Artificial Intelligence Approach of EMS
5.2.4 Model Predictive, Stochastic and Robust Programming Approach of EMS
5.3 Case Study
5.3.1 Energy Management System
5.3.2 Objective Functions
5.3.3 Result and Discussion
5.4 Conclusion
References
6. A Systematic Approach for Solar and Hydro Resource Assessment for DC Microgrid Applications
6.1 Introduction
6.1.1 Micro Hydro and Solar PV
6.1.2 Renewable Energy for Rural Electrification in Indian Perspective
6.1.3 Solar Resource Assessment
6.1.4 Hydro Resource Assessment
6.1.5 Demand Assessment
6.2 Methodology. 6.2.1 Data Collection
6.2.1.1 Meteorological and Geographical Data
6.2.1.2 Discharge Data for Hydro Potential Estimation
6.3 Result and Discussion
6.3.1 ANN Architecture
6.3.2 Hydro Resource Estimation
6.4 Conclusion
References
7. Secondary Control Based on the Droop Technique for Power Sharing
7.1 Introduction
7.2 Voltage Deviation and Power Sharing Issues in Droop Technique
7.2.1 Approaches for Correcting Power and Current Sharing
7.2.2 Hybrid Secondary Control: Distributed Power Sharing and Decentralized Voltage Restoration
7.2.2.1 Dynamics and Convergence of the Power Sharing Correction
7.2.2.2 Communication Delays in Consensus-Based Algorithm
7.2.2.3 Secondary Control Modeling
7.2.2.4 Computational and Experimental Validation
7.2.3 Secondary Level Control Based on Unique Voltage-Shifting (vs)
7.2.3.1 Power Sharing and Average Voltage Convergence Analysis
7.2.3.2 Secondary Control Level Modeling
7.2.3.3 Computational and Experimental Validation
7.3 Design and Implementation of the Communication System
7.4 Conclusions
References
8. Dynamic Analysis and Reduced-Order Modeling Techniques for Power Converters in DC Microgrid
8.1 Introduction
8.2 Need of Dynamic Analysis for Power Converters
8.3 Various Modeling Techniques
8.3.1 Analysis from Modeling Method
8.4 Reduce-Order Modeling
8.4.1 Faddeev Leverrier Algorithm
8.4.1.1 Procedure for Faddeev Leverrier Algorithm
8.4.1.2 Illustrative Example with Switched-Inductor-Based Quadratic Boost Converter
8.4.2 Order Reduction of Transfer Function
8.4.3 Techniques for Model Order Reduction
8.4.4 Pole Clustering Method
8.4.5 Procedure for Improved Pole Clustering Technique
8.4.5.1 Computation of Denominator Polynomial of Lower-Dimensional Model
8.4.5.2 Computation of Numerator Polynomial of Lower-Dimensional Model
8.4.5.3 Design of Controller
8.5 Illustrative Example with the Power Converter
8.5.1 Derivation of the Denominator
8.5.2 Derivation of the Numerator
8.6 Controllers for Power Converter
8.6.1 Need of Controller
8.6.2 Types of Controller
8.7 Conclusion
References
9. Matrix Converter and Its Probable Applications
9.1 Introduction
9.2 Classification of Matrix Converter
9.2.1 Classical Matrix Converter
9.2.2 Sparse Matrix Converter
9.2.3 Very Sparse Matrix Converter
9.2.4 Ultra-Sparse Matrix Converter
9.3 Problems Associated with the MC and the Drives
9.3.1 Commutation Issues
9.3.2 Modulation Issues
9.3.3 Common-Mode Voltage and Common-Mode Current Issues
9.3.4 Protection Issues
9.4 Control Techniques
9.5 Basic Components of the Matrix Converter Fed Drive System
9.6 Industrial Applications of Matrix Converter
9.7 Summary
References
10. Multilevel Converters and Applications
10.1 Introduction
10.2 Multilevel Inverters
10.2.1 Multilevel Inverters vs. Two-Level Inverters
10.2.2 Advantages of Multilevel Converters Based on Waveforms
10.2.3 Advantages of Multilevel Converters Based on Topology
10.3 Traditional Multilevel Inverter Topologies
10.3.1 Diode Clamped Multilevel Inverter
10.3.1.1 Features of DCMLI
10.3.1.2 Advantages of DCMLI
10.3.1.3 Disadvantages of DCMLI
10.3.1.4 Applications of DCMLI
10.3.2 Flying Capacitor Multilevel Inverter
10.3.2.1 Features of FCMLI
10.3.2.2 Advantages of FCMLI
10.3.2.3 Disadvantages of FCMLI
10.3.2.4 Applications of FCMLI
10.3.3 Cascaded H Bridge Multilevel Inverter
10.3.3.1 Features of CHBMLI
10.3.3.2 Advantages of CHBMLI
10.3.3.3 Disadvantages of CHBMLI
10.3.3.4 Applications of CHBMLI
10.4 Advent of Active Neutral Point Clamped Converter
10.4.1 Comparison with Traditional Topologies
10.4.2 Advantages of ANPC MLI
10.4.3 Disadvantages of ANPC MLI
10.5 Conclusion
References
11. A Quasi Z-Source (QZS) Network-Based Quadratic Boost Converter Suitable for Photovoltaic-Based DC Microgrids
11.1 Introduction
11.2 Proposed Converter
11.3 Steady-State Analyses
11.4 Comparison with Other Structures
11.5 Converter Analyzes in Discontinuous Conduction Mode (DCM)
11.6 Simulation Results
11.7 Real Voltage Gain and Losses Analyzes
11.8 Dynamic Behavior of the Proposed Converter
11.9 The Maximum Power Point Tracking (MPPT)
11.10 Conclusions
11.11 Appendix
References
12. Research on Protection Strategy Utilizing Full-Scale Transient Fault Information for DC Microgrid Based on Integrated Control and Protection Platform
12.1 Introduction
12.2 Topological Structure and Grounding Model of Studied Microgrid. 12.2.1 Proposed DC Distribution Network Topology
12.2.2 Neutral Grounding Model. 12.2.2.1 Grounding Position Selection
12.2.2.2 Grounding Mode Selection
12.3 Fault Characteristics of DC Microgrid
12.3.1 DC Unipolar Fault Characteristics
12.3.2 DC Bipolar Fault Characteristics
12.4 DC Microgrid Protection Strategy. 12.4.1 Protection Zone Division and Protection Configuration. 12.4.1.1 Protection Zone Division
12.4.1.2 Protection Configuration
12.4.2 Integrated Control and Protection Platform
12.4.3 Fault Isolation and Recovery Strategy Utilizing Full-Scale Transient Fault Information
12.4.3.1 Unipolar Fault Isolation and Recovery of DC Line/Bus
12.4.3.2 Bipolar Fault Isolation and Recovery of DC Line/Bus
12.5 Simulation Verification
12.5.1 Verification under DC Unipolar Fault. 12.5.1.1 Metal Short Circuit Fault of DC Line
12.5.1.2 Unipolar Fault with High Transition Resistance
12.5.1.3 High Resistance Unipolar Fault with Parallel Resistance Switching Strategy
12.5.2 Verification under DC Bipolar Fault
12.6 Conclusion
References
13. A Decision Tree-Based Algorithm for Fault Detection and Section Identification of DC Microgrid
Acronyms
Symbols
13.1 Introduction
13.2 DC Test Microgrid System
13.3 Overview of Decision Tree-Based Proposed Scheme
13.4 DC Microgrid Protection Using Decision Tree Classifier
13.5 Performance Evaluation
13.5.1 Mode Detection Module
13.5.2 Fault Detection/Classification
13.5.3 Section Identification
13.5.4 Comparative Analysis of the Proposed Scheme with other DC Microgrid Protection Techniques
13.6 Conclusion
References
14. Passive Islanding Detection Method Using Static Transfer Switch for Multi-DGs Microgrid
14.1 Introduction
14.1.1 Technical Challenges of Microgrid and Benefits
14.1.2 System with Multi-DGs
14.1.3 Power Sharing Methods
14.1.3.1 Conventional Droop Control Method
14.2 Islanding
14.2.1 Challenges with Islanding
14.2.2 Different Standards for Microgrid
14.2.3 Islanding Detection Methods
14.3 Static Transfer Switch (STS)
14.3.1 Simulation Results of STS
14.4 Proposed Scheme of Islanding. 14.4.1 Proposed PV System
14.4.2 Mathematical Analysis of Harmonic Extraction
14.5 Flow Chart
14.6 Simulation Results
14.7 Experimental Results
14.8 Conclusion
References
Index
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