Abstract
The installation of ultra-fast charging stations (UFCSs) is essential to push the adoption of electric vehicles (EVs). Given the high amount of power required by this charging technology, the integration of renewable energy sources (RESs) and energy storage systems (ESSs) in the design of the station represents a valuable option to decrease its impact on the grid and the environment. Therefore, this paper proposes a multi-objective optimization problem for the optimal sizing of photovoltaic (PV) system and battery ESS (BESS) in a UFCS of EVs. The proposed multi-objective function aims to minimize, on one side, the annualized cost of the station, and on the other side, the produced pollutant emissions. The decision variables are the number of PV panels and the capacity of the ESS to be installed. The optimization problem is reduced to a single-objective problem by applying the linear scalarization method. Then the equivalent single-objective function is optimized through a genetic algorithm (GA). The proposed optimization framework is applied to a study case and the results prove that PV and ESS could lead to a significant reduction of both the annualized cost and the pollutant emissions. Finally, a sensitivity analysis is also presented to validate the effectiveness of the proposed solution.
Highlights
In recent decades, environmental concerns are gaining ever more interest worldwide
The rated power of each pile is assumed to be 200 kW. By comparing this value with the charging profiles in FIG. 4. it can be noticed that the limit charging power is imposed by the Battery Management System (BMS) of the electric vehicles (EVs) battery and not by the infrastructure
The multi-objective function was reduced to a singleobjective problem through the weighted sum method and it was solved with genetic algorithm (GA) implemented in MATLAB
Summary
Environmental concerns are gaining ever more interest worldwide. In this context, particular attention has been dedicated to the transport sector and conventional oil vehicles, because of their high CO2 emissions and footprint [1]. Its biggest disadvantage is that of requiring large power demand, and greatly impact on the national electric grid To mitigate this aspect, renewable energy sources (RES), and energy storage systems (ESS) can be incorporated into the design of UFCS. In [7], the authors proposed a singleobjective optimization problem solved through a mixedinteger linear programming (MILP) algorithm, whose aim was to minimize the total energy costs of an ultra-fast charging station integrated by a BESS and PV system. The size of PV panels and ESS and the optimal size of a wind turbine was carried out in [8] for a stand-alone charging station, and in the objective function, the LCC of the system is minimized through a hybrid optimization algorithm.
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