Energy Management System for the Integration of Electric Vehicles in the Smart Grid
Amid the global pursuit of sustainability, Electric Vehicles (EVs) and solar energy source (PV) have emerged as transformative technologies with the potential to revolutionize the transportation and energy sectors. EVs promise to reduce greenhouse gas emissions and decrease the reliance on fossil fuels. EVs act as mobile energy storage devices with significant capacity. When connected to the grid, they can absorb excess electricity during periods of high renewable energy generation and release it during peak demand, effectively acting as grid batteries. Meanwhile, PV systems offer a clean and renewable energy source that can be harnessed at the point of generation, reducing stress on the grid, and promoting energy independence. However, the seamless integration of these technologies into the existing electricity grid presents multifaceted challenges that must be addressed to fully unlock their potential. This thesis delves into the dynamic relationship between PV systems and EVs, with a specific focus on transactive energy management as a pivotal means to optimize their interaction with the distribution networks. EVs, predominantly in a parked state, present an untapped opportunity for active engagement in transactive markets, enabling the sale of surplus energy to the grid during periods of favourable pricing, thereby affording novel revenue streams to EV owners. The central goal of this research is to develop frameworks that enable the efficient exchange of energy between PV-integrated distribution networks and EVs while considering technical, social and economic aspects. One of the core challenges lies in the technical integration of PV-EV systems with the distribution networks. This encompasses optimizing EV charging schedules, managing bidirectional power flows, accounting for system uncertainties and accurate forecasting strategies. The objective is to optimize the utilization of PV for EV charging and maximize the active involvement of EVs in transactive energy markets, thereby increasing the reliability and stability of the distribution network. Moreover, the thesis explores various transactive models that facilitate energy exchange, such as peer-to-peer energy trading and aggregator-based markets. The models are evaluated in terms of feasibility, benefits, and challenges, with a particular focus on their applicability in the context of workplace PV-integrated EVs. To optimize energy transactions, the thesis develops advanced algorithms that leverage real data including PV generation patterns, EV charging behaviour, electricity prices, and market dynamics. These algorithms are designed to minimize costs while considering system uncertainties to ultimately promote more efficient energy usage. The thesis substantiates its findings through real-world case studies and simulations. Range anxiety, being the biggest barrier to the adoption of EVs, is considered in designing the transactive energy management system while minimizing operational costs. In conclusion, this research underscores the critical importance of transactive energy management for PV-integrated workplace electric vehicles. By addressing the complex technical, economic, and operational challenges, this work contributes to the broader efforts aimed at harnessing the full potential of EV-based transactive energy markets and advancing the global energy transition. The proposed methods in this research are generic, theoretically flexible, and capable of being applied to the distribution networks to smartly manage EVs’ participation in transactive energy markets.
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