Robust PV-BESS Scheduling for a Grid With Incentive for Forecast Accuracy

This paper proposes a robust cost-optimal scheduling of a battery energy storage system (BESS) integrated with a photovoltaic power plant (PV). A power grid with an incentive policy is considered. Power transactions between the grid and its energy resources are normally charged according to the hourly price. Additional hourly incentive is provided if the day-ahead submitted schedule is maintained. Accurate forecasting and robust scheduling are essential for PV-BESS owners to maximize both revenues. The PV power forecast model, which is based on an RNN, uses a CNN discriminator to decrease the gap between its open-loop training and closed-loop test dynamics. The application of a GAN concept to the model training process ensures a stable day-ahead hourly forecast performance. The robust BESS scheduling model handles the remaining forecast error as a box uncertainty set to consider the cost…