Energy-Economic-Environmental (3E) Optimisation of Grid-Connected Electric Vehicle Charging Station for a University Campus in Caparica, Portugal

Approximately one quarter of the European Union’s (EU’s) CO2 emissions originate from the transport sector, of which road transport, such as cars and heavy-duty vehicles, contributes roughly 72%. Moreover, according to the European Automobile Manufacturers’ Association, 92% of cars in the EU are internal combustion engine vehicles powered by fossil fuels. Therefore, boosting the adoption of Electric Vehicles (EVs) is considered one of the most prominent solutions for reducing GHG emissions and achieving the EU’s climate targets. To increase EV adoption and fulfil the demand of EV users, adequate EV Charging Stations (EVCSs) are required. Nevertheless, since most EVCSs are supplied by electricity grids that remain predominantly fossil fuel-based, their operation entails substantial indirect GHG emissions. A prominent approach to reducing grid-related emissions is integrating renewable energy sources (RESs) with EVCSs, thereby lowering emissions and alleviating grid stress. Although promising, the energy, economic, and environmental (3E) benefits of this integration remain insufficiently explored. Therefore, this study develops and applies a 3E optimisation framework to assess the feasibility and performance of RES-powered EVCS at NOVA University Lisbon (UNL). Data was collected from the UNL parking area, such as time of arrival, and time of departure. Also, a rule-based algorithm was developed to curate data and estimate the EVCS load profile. Furthermore, HOMER optimisation software was employed to evaluate four scenarios, including (i) an EVCS based on PV, Wind Turbine (WT), and the grid, (ii) an EVCS based on PV and the grid, (iii) an EVCS based on WT and the grid, and (iv) an EVCS based only on energy withdrawal from the grid (base scenario). Under the adopted techno-economic assumptions, in the most optimised scenario, economic and environmental analyses illustrate significant improvements over the base scenario: CO2 emissions are five times lower, and cost of energy is significantly lower, resulting in significantly lower EV charging costs for users. The results demonstrate that, through developed feasibility studies, researchers, decision-makers, and stakeholders can reach better conclusions about EVCS planning and management.