Hybrid controller for battery operation in photovoltaic assisted EV charging station

In the current scenario, renewable energy sources (RES) are used in transport applications to minimise the dependency on fossil fuels. The electrical vehicle (EV) has contributed a vital role in smart grids with the penetration of RES. The battery connected EVs have increased in the past few years owing to numerous benefits. Thus, it is necessary to develop an optimum charging controller for the charging station to meet the energy demand. In order to accomplish this goal, hybrid fuzzy fractional order proportional integral derivative ((HFOPID)-O-2) is proposed. Meanwhile, the controlling parameters of the (HFOPID)-O-2 are tuned by all member based optimisation algorithms (AMBO). Alongside, a hybrid honey badger recurrent neural network ((HB)-B-2-RNN) provides peak power from the solar photovoltaic (SPV) module. The honey badger optimisation algorithm examines the optimum weights of the layers. The proposed method is implemented on the MATLAB/Simulink platform, and the results are compared with the existing methods. The obtained results demonstrate the proposed method's compatibility with the available techniques in the literature.

Automated summary

In the current scenario, renewable energy sources are being utilized in transport applications to reduce dependence on fossil fuels. Electric vehicles have played a crucial role in smart grids, leading to an increase in battery connected EVs due to various benefits. Thus, the development of an optimum charging controller for charging stations becomes necessary to meet the energy demand.