Economic consistency enhancement by optimal operation of hybrid WF-thermal-EV-fuel cell system in a power network

This work introduces an efficient operational strategy for electric vehicles (EVs) to optimize economic outcomes in a wind-integrated hybrid power system. The proposed method enhances the profitability of a combined wind-thermal-EV-fuel cell system while maintaining grid frequency stability and managing the energy states of EV storage. Accurate wind speed forecasts are crucial, as wind farms must provide projected generation data to the market controller for coordinated scheduling with thermal units. Due to wind speed variability, discrepancies between actual and predicted values can lead to mismatches in wind power output, causing financial penalties from divergence prices. To address this, the optimal deployment of the EV storage system is designed to mitigate these financial impacts. By coordinating EV, wind, and thermal operations, the approach effectively reduces wind power unpredictability and ensures economic efficiency, a necessity in competitive power markets. Four distinct energy states of the EV battery- maximum, optimal, low, and minimum, are proposed to enhance cost efficiency. The EV storage mode is dynamically adjusted based on real-time grid frequency and wind speed data. Additionally, a fuel cell is incorporated to boost economic returns further. The effectiveness of the strategy is validated using an IEEE 30-bus test system, employing sequential quadratic programming and demonstrating notable improvements over existing methods.