Electric vehicle (EV) smart charging is becoming increasingly important in supporting the electricity grid through frequency regulation services and facilitating the shift to renewable energy. However, EV availability and energy forecasting has emerged as a new field of research, yet it is not fully evaluated in combination with electricity markets. Therefore, this study aims to explore the economic potential of EV availability and energy forecasts when EVs participate in the spot and frequency markets. The method takes into consideration the settlement stage in both markets: frequency containment reserve (FCR) and the spot market. The model is composed of vehicle-to-grid (V2G) optimization for a workplace charging station using an individual EV smart charging model, which optimizes one vehicle. The inputs are historical electricity market and frequency data, while the output is the total electricity cost calculated for a German case study.

The results show that an accurate forecast for availability is crucial for EV smart charging. The availability forecast error contributes to higher penalties from FCR, with larger penalties experienced during summer months. A sensitivity analysis explores the underestimation of the energy content of the EV. This case shows that underestimating the charging session energy need by 50% is equivalent to a completely failed availability forecast. Additionally, an error in the energy content forecast could result in a rise in imbalance settlement costs, which are more prominent during winter months. For a future case study, the simulation could evaluate combining both the energy content and the availability forecast errors with real-world EV data and applying the optimization to multiple chargers.