
Optimization Planning and Operation of Electric Vehicle Charging Facilities
A Perspective From China
- 1st Edition - August 1, 2025
- Imprint: Elsevier
- Editors: Hengjie Li, Yun Zhou, Donghan Feng, Chen Fang, Nier Wang
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 4 3 9 5 2 - 0
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 4 3 9 5 3 - 7
Optimization Planning and Operation of Electric Vehicle Charging Facilities: A Perspective from China provides an in-depth understanding of core theories and advanced techno… Read more
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It highlights the application of existing technologies and includes findings from major projects funded by the National Natural Science Foundation of China, the Shanghai Science and Technology Commission, and the State Grid Corporation of China.
- Offers a comprehensive and practical guide to the optimized planning and operation of electric vehicle (EV) charging facilities that is based on experience in China
- Includes the latest research findings on EV charging infrastructure
- Covers key topics such as EV charging load modeling and prediction, charging facility optimization planning, operational optimization, charging guidance and path planning, EV-grid interaction, and participation in electricity markets
1.1 Electric Vehicles and Their Development History
1.1.1 Development History of Electric Vehicles
1.1.2 Current Status of Electric Vehicle Development
1.1.3 Impacts and Challenges of Electric Vehicles on the Power Grid
1.2 Classification and Technological Development of Electric Vehicle Charging Facilities
1.2.1 Classification Standards of Charging Facilities
1.2.2 Mainstream Charging Technologies
1.2.3 Cutting-edge Charging Technologies and Mode Innovations
1.3 Planning and Construction Requirements for Electric Vehicle Charging Facilities
1.3.1 Current Status of Charging Facility Development
1.3.2 Policy Orientation for Charging Facility Development
1.3.3 Construction Levels of Charging Facilities Domestically and Internationally
1.4 Optimization of Charging Facility Operation and Marketization Pathways
1.4.1 Operation Optimization Based on Orderly Charging
1.4.2 Case Studies of Electric Vehicle and Grid Interaction Pilots
1.4.3 Marketization Pathways and Policy Outlook for Charging Facility Operation
1.5 Summary
2. Modeling and Forecasting of Electric Vehicle Charging Load
2.1 Medium- and Long-term Forecasting Methods for Urban Electric Vehicle Ownership
2.1.1 Methods for Forecasting Electric Vehicle Market Scale
2.1.2 Forecast Models Considering Technological Evolution and Competition
2.1.3 Uncertainty Analysis Methods for Urban Electric Vehicle Ownership Forecast Models
2.2 Forecasting Spatial-Temporal Distribution of Urban Electric Vehicle Charging Load
2.2.1 Trip Chain Theory
2.2.2 Statistical Analysis Methods of Travel Characteristics
2.2.3 Wide-Area Charging Demand Modeling Based on Electric Vehicle Behavior Models
2.3 Data-Driven Ultra-Short-Term Load Forecasting Methods for Charging Stations
2.3.1 Load Forecasting Requirements for Charging Stations
2.3.2 Framework Construction Strategies for Ultra-Short-Term Load Forecasting
2.3.3 Simulation of Load Forecasting Models
2.4 Summary
3. Optimization Planning of Electric Vehicle Charging Facilities
3.1 Planning Methods for Charging Pile Clusters Based on Urban Functional Zoning
3.1.1 Modeling Methods for Electric Vehicle Charging Load
3.1.2 Multi-Spatial-Temporal Charging Models Considering Multiple Charging Facilities
3.1.3 Charging Pile Cluster Planning Model Based on Urban Functional Zoning
3.1.4 Case Analysis
3.2 Expansion Planning Methods for Urban Charging Stations
3.2.1 Expansion Planning Model for Urban Charging Stations
3.2.2 Processes and Solution Methods for Bi-Level Expansion Planning
3.2.3 Case Analysis
3.3 Case Studies and Capacity Configuration Methods for PV-Storage Charging Stations
3.3.1 Case Analysis of PV-Storage Charging Stations
3.3.2 Optimal Capacity Configuration Methods for PV-Storage Charging Stations
3.3.3 Case Analysis
3.4 Summary
4. Operation Optimization of Electric Vehicle Charging Facilities
4.1 Operation Optimization Methods for Residential Charging Facilities
4.1.1 Energy Optimization Requirements Considering Charging Load in Residential Quarters
4.1.2 Two-Stage Real-Time Operation Optimization Methods Considering Charging Load in Residential Quarters
4.1.3 Case Analysis
4.2 Operation Optimization Methods for Commercial Building Charging Facilities
4.2.1 Future Energy Management Architecture for Commercial Buildings
4.2.2 Building Operation Optimization Methods Considering Charging Facilities
4.2.3 Case Analysis
4.3 Operation Optimization Methods for PV-Storage Charging Stations
4.3.1 Typical Operation Modes of PV-Storage Charging Stations
4.3.2 Economic Operation Strategies for PV-Storage Charging Stations
4.3.3 Case Analysis
4.4 Summary
5. Electric Vehicle Charging Guidance and Path Planning
5.1 Dynamic Road Network Models Based on Digital Map Interfaces
5.1.1 Digital Map Technology and Applications
5.1.2 Parameter Analysis of Digital Map Interfaces for Charging Guidance
5.1.3 Invocation Processes of Digital Map Interfaces for Charging Guidance
5.2 Charging Guidance Methods Based on Weighted Bipartite Graph Matching
5.2.1 Fast Charging Demand Analysis for Electric Vehicle Users
5.2.2 Fast Charging Demand Analysis for Charging Stations
5.2.3 Charging Guidance Strategies Considering Charging Conflicts
5.2.4 Case Analysis
5.3 Charging Guidance Methods Based on Improved Deferred Acceptance Algorithm
5.3.1 Charging Guidance Requirements and Reservation Service Architecture
5.3.2 Charging Matching Strategies Based on Improved Deferred Acceptance Algorithm
5.3.3 Case Analysis
5.4 Summary
6. Electric Vehicle Participation in Power Grid Regulation and Interaction
6.1 Potential Assessment of Electric Vehicle Participation in Grid Regulation
6.1.1 Modeling Methods for Potential Assessment
6.1.2 Efficient Solution Methods for Potential Assessment Models
6.1.3 Analysis of Participation Potential in Grid Regulation
6.2 Applications of Electric Vehicles in Peak Shaving and Valley Filling
6.2.1 Peak Shaving and Valley Filling for Private Charging Piles
6.2.2 Peak Shaving and Valley Filling for Public Charging Piles
6.3 Applications in Power Grid Frequency Regulation
6.3.1 Information Interaction Architecture between EVs and Grid
6.3.2 Real-Time Capability Assessment for Frequency Regulation
6.3.3 Real-Time Instruction Decomposition for Frequency Regulation
6.3.4 Case Analysis
6.4 Summary
7. Modes and Mechanisms of Electric Vehicle Participation in Electricity Markets
7.1 Overview of Global and Domestic Electricity Market Development
7.1.1 Global Electricity Market Development Overview
7.1.2 Progress of Domestic Electricity Market Reforms
7.1.3 Construction of the Shanghai Electricity Spot Market
7.2 Encouraging Policies and Typical Models for EV Market Participation
7.2.1 Domestic and International Policies Encouraging EV Market Participation
7.2.2 Analysis of Pilot Projects for EV Market Participation
7.3 Real-Time Market-Based Pricing Mechanisms for Charging Stations
7.3.1 Information Interaction Architecture
7.3.2 Modeling of Market Participants in Charging
7.3.3 Game Theory Among Charging Station Alliances
7.3.4 Case Analysis
7.4 Summary
- Edition: 1
- Published: August 1, 2025
- Imprint: Elsevier
- Language: English
HL
Hengjie Li
YZ
Yun Zhou
Dr Zhou is a lecturer and master's supervisor in the Department of Electrical Engineering at Shanghai Jiao Tong University and a part-time master's supervisor at Lanzhou University of Technology. He has led one project under the National Natural Science Foundation and four provincial and ministerial-level vertical projects
DF
Donghan Feng
CF
Chen Fang
Dr Fang received his PhD from Tsinghua University; he is currently the Deputy Director of the Science and Technology Development Department at the Electric Power Research Institute of the State Grid Shanghai Electric Power Company and an enterprise supervisor for engineering doctoral students at Shanghai Jiao Tong University. He is engaged in research and development, engineering applications, and the formulation of standards in the field of smart grids
NW