Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability

Power load forecasting, dynamic forecasting, and pricing are the topics included in this study. The forecasting model used in this study, Long Short-Term Memory (LSTM), was extended to provide dynamic forecasts. Dynamic forecasts and improved forecasting performance are necessary for creating a dynamic pricing strategy for electric vehicle (EV) charging. The available capacity of the local distribution grid determines the dynamic price. The limited grid capacity can result in restrictions for charging electric vehicles. Additionally, dynamic forecasting and dynamic pricing are the bases for a booking system that enables customers to reserve a time slot for charging their vehicles. Photovoltaic (PV) generation and the maximum free grid capacity are considered to provide incentives for charging at certain times. Finally, a comparison is made between the effects of EV charging on the grid with and without the dynamic pricing approach and the booking system.