Project description:
This project develops a data-driven, household-centric framework to assess when vehicle-to-grid (V2G) participation is economically viable for private electric vehicle owners. Using large-scale travel surveys from the UK, US, and Australia together with historical electricity price signals, we construct representative daily mobility profiles and optimise overnight charging/discharging schedules under realistic constraints such as plug-in uncertainty and next-day travel requirements. Battery wear is internalised via a transparent throughput-based degradation cost, enabling robust scenario and sensitivity analysis. The resulting outputs quantify profitability boundaries across mobility contexts, markets, and service assumptions (including potential frequency-service revenue stacking).
Project description
The project develops an optimization based framework to evaluate and improve the full life cycle economy of grid connected utility scale photovoltaic power plants. The framework considers the investment and replacement costs of key equipment (such as inverter and energy storage), time-varying operation and maintenance costs and efficiency losses (power constraints, SOC dynamics, etc.), as well as the market income under the restriction of actual electricity price and grid connection and transmission.
The core method is to establish a cross time discrete optimization model on an hourly scale to jointly optimize the output of the inverter and the charging and discharging of energy storage, so as to maximize the net income under the premise of meeting the requirements of grid connection and operation.
