Optimal power utilizing strategy for PV-based EV charging stations considering Real-time price
Developing EVs has been established as an effective way to reduce carbon emission in development and ensure energy security by many countries. The PV-based EVCS (EV charging station) can efficiently alliviate the charging pressures of the distribution network and reduce EVs indirect emissions. A Real-time power utilizing strategy considering real-time price for PV-based EV charging station is proposed to allow EVs to participate in DR (Demand Response) and charge economically. The DR is adopted for power utilizing strategy to offer a kind of financial benefits for EVs and minimize the charging fees. The behavior mode and the CRFR mode are utilized to figure out the EV demand mode. The PSO (Paticle Swarm Optimal) algorithm is utilized to optimally allocate the charging power. The real-time price is forecasted by wavelet neural network based on the historical data and the total charging power responses to the real-time price so as to minimize charging cost. A case study is simulated to validate the proposed method.