Electric Vehicle Integration in a Smart Microgrid Environment

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Foreword
Preface
Editors
Contributors
Chapter 1 Trends in Electric Vehicles, Distribution Systems, EV Charging Infrastructure, and Microgrids
	1.1 Introduction: Transportation Electrification Trends
	1.2 Distribution System Trends
	1.3 Charging Technology Trends
Chapter 2 Fog Computing for Smart Grids: Challenges and Solutions
	2.1 Introduction
	2.2 SGs
		2.2.1 Architecture
		2.2.2 Current and Upcoming Problems
	2.3 Fog Computing-Driven SG Architecture
		2.3.1 Features
		2.3.2 Fog Computing Complements the Cloud
		2.3.3 Fog Computing Helps Address SG Problems
	2.4 Current Solutions for Applying Fog Computing to SGs
		2.4.1 Fog-based SG Architecture
		2.4.2 Mainly Discussed Applications
		2.4.3 Key Problems Focused in Strategy Design
		2.4.4 Fog+
	2.5 Research Challenges and Future Directions
		2.5.1 Security and Privacy
		2.5.2 Huge Amounts of Data Processing
		2.5.3 Fog and Cloud Combination
		2.5.4 Fog Device Deployment
	2.6 Summary and Conclusions
	References
Chapter 3 Opportunities and Challenges in Electric Vehicle Fleet Charging Management
	3.1 Introduction
	3.2 EV Chargers
		3.2.1 Interfaces and Standards
		3.2.2 Features and Topologies
		3.2.3 Controls
		3.2.4 Capabilities
	3.3 EV Aggregation
	3.4 Available Ancillary Grid Services with Aggregated EVs
		3.4.1 Frequency Response and Regulation
		3.4.2 Power Smoothing
		3.4.3 Load/Generation Following
		3.4.4 Spinning Reserve
		3.4.5 Reactive Power Support
		3.4.6 Voltage Support
		3.4.7 Discussion
	3.5 Case Studies
		3.5.1 Frequency Regulation
		3.5.2 Power Smoothing
		3.5.3 Load/Generation Following
		3.5.4 Spinning Reserve
		3.5.5 Voltage and Reactive Power Support
	3.6 Challenges and Future Research Directions
		3.6.1 Technology Initiatives
		3.6.2 Economical Aspects
		3.6.3 Environmental Aspects
		3.6.4 Safety and Security
		3.6.5 Future Directions
	3.7 Conclusion
	References
Chapter 4 Challenges to Build a EV Friendly Ecosystem: Brazilian Benchmark
	4.1 Introduction
	4.2 Context and Brazilian Portrait
	4.3 Challenges and Opportunities through the Brazilian Initiatives
		4.3.1 Economy and Production
		4.3.2 Public Policies
		4.3.3 Customer Acceptance
		4.3.4 Market, Logistics, Energy Matrix, and Environment
		4.3.5 Smart Grid
	4.4 Case Study
		4.4.1 Public Perception
		4.4.2 Numeric Model
	4.5 Summary and Conclusions
	Acknowledgments
	References
Chapter 5 Coordinated Operation of Electric Vehicle Charging and Renewable Power Generation Integrated in a Microgrid
	5.1 Introduction
	5.2 The Stochastic Optimization Model
		5.2.1 Model of the Microgrid
	5.3 Scenarios and Tree Generation Procedure
		5.3.1 Scenario Generation for the V2G Parking Lot
		5.3.2 Scenario Generation for the PV Unit and Local Load
		5.3.3 Tree Generation by Using k-Means
	5.4 Microgrid Simulation Results
		5.4.1 Description of the Case Study
		5.4.2 Scenario-Based Tree Generation
		5.4.3 Solution of the Multistage Stochastic Model
	5.5 Conclusions
	Acknowledgments
	Nomenclature
	References
Chapter 6 Energy Storage Sizing for Plug-in Electric Vehicle Charging Stations
	6.1 Introduction
	6.2 Literature Review
		6.2.1 Literature on Smart Charging and Impacts of PEV Charging
		6.2.2 Literature on Charging Station Design
		6.2.3 Literature on Probabilistic Modelling of PEV Charging Infrastructures
		6.2.4 Contributions
	6.3 Demonstration and Testing Platform of a PEV Charging Infrastructure
		6.3.1 Overview of PEV Research and Testing Projects at PNDC
		6.3.2 Summary of Results
	6.4 System Model
		6.4.1 Markov-Modulated Poisson Process
		6.4.2 Matrix Geometric Approach
		6.4.3 Algorithmic Solution Technique
	6.5 Numerical Evaluations
		6.5.1 Computation of Station Parameters
		6.5.2 Charging Station Economic Analysis
	6.6 Conclusions
	Acknowledgement
	Bibliography
Chapter 7 Innovative Methods for State of the Charge Estimation for EV Battery Management Systems
	7.1 Introduction
	7.2 Literature Review
		7.2.1 Battery Management System
	7.3 State-of-Charge Estimation
		7.3.1 Kalman Filter Algorithm
			7.3.1.1 Extended Kalman Filter
			7.3.1.2 Central Difference Kalman Filter
			7.3.1.3 Adaptive Extended Kalman Filter
		7.3.2 Sliding Mode Observer
		7.3.3 Backpropagation Neural Network
			7.3.3.1 Forward Propagation
			7.3.3.2 Backward Propagation
	7.4 Conclusion
	7.5 Framework for Integrating EV Energy Storage Systems
	Nomenclature
	References
Chapter 8 High-Voltage Battery Life Cycle Analysis with Repurposing in Energy Storage Systems (ESS) for Electric Vehicles
	8.1 Introduction
	8.2 Literature Review
		8.2.1 Conventional Cars and Electrical Vehicles
		8.2.2 Life Cycle
		8.2.3 Manufacture
			8.2.3.1 Battery Cell
			8.2.3.2 Packaging
			8.2.3.3 Battery Management System
			8.2.3.4 Battery Pack Assembly
			8.2.3.5 Solutions to Minimize the Impact Due to Manufacturing
		8.2.4 Battery Life cycle Analysis with Repurposing in Energy Storage Systems (ESS)
			8.2.4.1 First Use in Electric Vehicles
			8.2.4.2 Second Use in Energy Storage Systems
		8.2.5 Environmental Approaches for Battery Disposal
			8.2.5.1 Introduction and Background Information
			8.2.5.2 Currently Applied Recycling Techniques
	8.3 Methodology
		8.3.1 Power Peak Shaving
			8.3.1.1 A Sample of Current Simple Comparative Algorithms
		8.3.2 The Proposed Simple Comparative Algorithm
			8.3.2.1 Definition of Variables
			8.3.2.2 Solution Flow
	8.4 The Methodology Study Design
	8.5 Factors of the the Methodology’s Ideal Environment
		8.5.1 Drivers
		8.5.2 Barriers
	8.6 Case Study
		8.6.1 System Briefing
		8.6.3 System Parameters & Assumptions
	8.7 Results
	8.8 Conclusion
	Acknowledgements
	Bibliography
Chapter 9 Charging Infrastructure for Electric Taxi Fleets
	9.1 Introduction: Background and Driving Forces
	9.2 Commercial Electric Taxi Fleets
		9.2.1 Case Study: Uber Electric Vehicle Trial in London
		9.2.2 Case Study: Ola Electric Mobility Pilot
		9.2.3 Key Findings from the Study of Fleet Operations
	9.3 Important Charging-Related Aspects of Electric Cars
		9.3.1 Battery Capacity and Range
		9.3.2 Charger Capacity and Charging Time
		9.3.3 Factors Affecting Charging Time
	9.4 Charging Technologies for Electric Cars
		9.4.1 EV Charging Standards
		9.4.2 Charger Classifications Worldwide
		9.4.3 Charging Technologies
			9.4.3.1 AC Charging
			9.4.3.2 DC Charging
			9.4.3.3 Wireless Charging
			9.4.3.4 Battery Swapping
		9.4.4 Charging Technology Trends
			9.4.4.1 Mobile EV Charging
			9.4.4.2 Solar EV Charging
		9.4.5 Charging Station Safety
	9.5 Categories of Commercial Four-Wheeler Passenger Fleet
		9.5.1 Ride-Hailing Fleet
		9.5.2 Corporate Fleet
	9.6 Plausible Locations for Charging Electric Taxi Fleet
		9.6.1 Charging Facilities for Taxi Fleet
			9.6.1.1 Public Charging Hubs for En route Charging
			9.6.1.2 Charging Facility at Public Parking Spaces
			9.6.1.3 Captive Charging Facilities
		9.6.2 Critical Factors for Siting Charging Facilities
	9.7 Techniques for Locating Charging Facilities
		9.7.1 Analytic Hierarchy Process (AHP)
		9.7.2 Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)
		9.7.3 Rationale for Using AHP and TOPSIS
	9.8 Configuring a Charging Facility for an Electric Taxi Fleet
		9.8.1 Selection of Charging Technology
			9.8.1.1 Identification of Charging Technologies for Evaluation
			9.8.1.2 Selection of Parameters for Decision-Making
			9.8.1.3 Deciding Relative Weights of Parameters
			9.8.1.4 Ranking of Parameters
			9.8.1.5 Preparing Decision Matrix
	9.9 Recommendations for Fleet Charging
		9.9.1 Public Chargers Are Required to Support Fleet
		9.9.2 Role of AC Charging for Fleet
	9.10 Grid Interaction and Integration of Fleet
	Nomenclature
	Works Cited
Chapter 10 Machine Learning-Based Day-Ahead Market Energy Usage Bidding for Smart Microgrids
	10.1 Introduction
	10.2 Different Aspects of EVs
	10.3 Description of Power Market Stakeholder Interaction Model
		10.3.1 Activity Diagram
		10.3.2 Data Flow Diagram
		10.3.3 ER Diagram
	10.4 AI Strategies
		10.4.1 Artificial Neural Networks
		10.4.2 Autoregressive Moving Average
		10.4.3 Support Vector Machine
	10.5 Overall Demonstration
	10.6 Case Studies
		10.6.1 Forecasting of Energy Price
		10.6.2 Aggregate Demand-Supply System
		10.6.3 xEV Market Analysis and Forecast
	10.7 Result
	10.8 Conclusion
	Nomenclature
	References
Chapter 11 Smart Microgrid-Integrated EV Wireless Charging Station
	11.1 Introduction
	11.2 Solar PV Module Configuration with a Wireless Charging System
	11.3 Solar to EV Battery Feasibility Analysis
	11.4 Wireless Charging System for EVs
	11.5 Finite Element Analysis Modeling and Simulation of the WPT Coils for Magnetic Analysis
	11.6 Results and Discussion
	11.7 Conclusion
	Acknowledgment
	References
Chapter 12 Shielding Techniques of IPT System for Electric Vehicles’ Stationary Charging
	12.1 Introduction
	12.2 Components of Transmitter and Receiver Pad
		12.2.1 Conductive Wires
		12.2.2 Flux Concentrator
		12.2.3 EMF Shielding
			12.2.3.1 Passive Shielding
			12.2.3.2 Active Shielding
			12.2.3.3 Reactive Shielding
	12.3 Conclusion
	Acknowledgment
	References
Chapter 13 Economic Placement of EV Charging Stations within Urban Areas
	13.1 Introduction
	13.2 The Problem of Choosing Charging Stations’ Locations
	13.3 Methodologies for Placing Charging Stations
	13.4 Economics of Charging Station Placement
	13.5 Case Study: Applying an Agent-Based Network Graph Placement Method on Cairo, Egypt
	References
Chapter 14 Environmental Impact of the Recycling and Disposal of EV Batteries
	14.1 Introduction
		14.1.1 Battery Repurposing and Clearance for Sustainable Society
	14.2 Delaying Recycling through Repurposing
		14.2.1 Repurposing
	14.3 Economic Aspects
		14.3.1 Identifying Domestic Demand
		14.3.2 Identifying Industrial Demand
	14.4 Standards for Reusing EV Batteries
	14.5 Environmental Impacts of EV Batteries | EVBs
		14.5.1 Raw Material Manufacturing Effects
		14.5.2 Battery Manufacturing Effects
		14.5.3 Thermal Gas Emission
		14.5.4 Chemical Hazards
	14.6 Battery Dismantling and Handling Health Hazards
		14.6.1 Lithium-Ion Battery Landfill
		14.6.2 Impact of Recycling on the Environment
		14.6.3 Recycling of EV Batteries
	14.7 Environmental Aspects of Reuse
	14.8 Environmental Aspects of Recycling
	14.9 Recycling
		14.9.1 Recycling Methods
		14.9.2 Mechanical Procedure | MP
		14.9.3 Pyro Metallurgical Procedure | PM
		14.9.4 Hydrometallurgical Procedure | HP
		14.9.5 Direct Recycling Procedure | DRP
	14.10 Best Practices of Lithium-Ion Battery Recycling
		14.10.1 Umicore Company
		14.10.2 Retrieve Technologies
		14.10.3 Onto Technology
	14.11 Safety Indicators
	14.12 Dismantling and Storage
		14.12.1 Reorganizing and Screening
	14.13 Technological Initiatives
	14.14 Conclusion
	14.15 Recommendations and Future Directions
	References
Chapter 15 Design and Operation of a Low-Cost Microgrid-Integrated EV for Developing Countries: A Case Study
	15.1 Introduction
		15.1.1 Central Power Station System
		15.1.2 Distributed Generation System
	15.2 The Design Scheme of Proposed Microgrid System
		15.2.1 Modifications in the Proposed Grid-Connected PV System
		15.2.2 Layout of the Proposed Control Strategy
	15.3 Detailed Controller Design and Its Working
		15.3.1 Mode Selector Controller
		15.3.2 Source Selector Controller
	15.4 Hardware Implementation of the Designed Controllers
		15.4.1 The Experimental Setup and Results
	15.5 Hardware in the Loop Testing of Proposed Strategy
		15.5.1 Hardware in Loop Results
	15.6 Conclusion
	References
Index