Renewable energy integration to power grids: Coordinated planning and security of electric vehicle charging networks with renewable support
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Type
ThesisThesis type
Doctor of PhilosophyAuthor/s
Lin, JiafengAbstract
The rapid growth of electric vehicles (EVs) is driving increasing demand for efficient and sustainable charging infrastructure. Integrating renewable energy sources (RESs) and battery energy storage systems (BESSs) into electric vehicle charging stations (EVCSs) offers a promising ...
See moreThe rapid growth of electric vehicles (EVs) is driving increasing demand for efficient and sustainable charging infrastructure. Integrating renewable energy sources (RESs) and battery energy storage systems (BESSs) into electric vehicle charging stations (EVCSs) offers a promising solution, but also introduces new challenges in infrastructure planning, life-cycle sustainability, and cybersecurity. At a system level, interconnected EVCSs form electric vehicle charging networks (EVCNs), which coordinate charging and vehicle-to-grid (V2G) operations while being affected by difficult-to-model joint effects of off-site factors, non-ideal battery behavior, and vulnerability of charging management centers. This thesis develops coordinated planning-and-security frameworks for renewable-supported EVCNs. Planning focuses on long-term EVCS siting and sizing, while security addresses operational-level data integrity attacks during real-time network operation. A fuzzy inference system (FIS)–integrated planning framework is proposed to capture nonlinear joint effects of off-site factors and narrow candidate locations, enabling scalable and realistic EVCS deployment with photovoltaic (PV) generation and energy storage. The framework is extended to incorporate second-life batteries alongside wind-PV-BESS systems. To address operational cybersecurity, fuzzy-Bayesian attack-recovery mechanisms are developed for EV charging management centers under data integrity attacks. These methods quantify vulnerability, identify compromised controllers, and recover power dispatch while respecting non-ideal lithium-ion battery characteristics, including SOC-dependent limits and efficiencies. Overall, this thesis advances sustainable and security operation of renewable-supported EVCNs by integrating fuzzy reasoning, practical second-life battery utilization, and attack-recovery control under realistic battery models.
See less
See moreThe rapid growth of electric vehicles (EVs) is driving increasing demand for efficient and sustainable charging infrastructure. Integrating renewable energy sources (RESs) and battery energy storage systems (BESSs) into electric vehicle charging stations (EVCSs) offers a promising solution, but also introduces new challenges in infrastructure planning, life-cycle sustainability, and cybersecurity. At a system level, interconnected EVCSs form electric vehicle charging networks (EVCNs), which coordinate charging and vehicle-to-grid (V2G) operations while being affected by difficult-to-model joint effects of off-site factors, non-ideal battery behavior, and vulnerability of charging management centers. This thesis develops coordinated planning-and-security frameworks for renewable-supported EVCNs. Planning focuses on long-term EVCS siting and sizing, while security addresses operational-level data integrity attacks during real-time network operation. A fuzzy inference system (FIS)–integrated planning framework is proposed to capture nonlinear joint effects of off-site factors and narrow candidate locations, enabling scalable and realistic EVCS deployment with photovoltaic (PV) generation and energy storage. The framework is extended to incorporate second-life batteries alongside wind-PV-BESS systems. To address operational cybersecurity, fuzzy-Bayesian attack-recovery mechanisms are developed for EV charging management centers under data integrity attacks. These methods quantify vulnerability, identify compromised controllers, and recover power dispatch while respecting non-ideal lithium-ion battery characteristics, including SOC-dependent limits and efficiencies. Overall, this thesis advances sustainable and security operation of renewable-supported EVCNs by integrating fuzzy reasoning, practical second-life battery utilization, and attack-recovery control under realistic battery models.
See less
Date
2025Rights statement
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
Faculty of EngineeringAwarding institution
The University of SydneyShare