A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets

Market agents with renewable resources face amplified uncertainty when forecasting energy production to securely place bids in electricity markets. To deal uncertainties, stochastic modelling has been applied optimize the bidding strategy of these market agents. However, studies found literature usually focus on day-ahead and balancing markets, leaving aside intraday markets that could be used correct positions as gets resolved. This paper proposes a multistage decision-aid algorithm based linear programming three different - day-ahead, intraday, balance The agent represents Virtual Power Plant wind, solar PV, storage technologies, its participation was compared DA BM only. Results show participating all increased profit achieved by VPP 10.1% while also decreasing incurred imbalances 63.8%. results demonstrate having accurate tools multi-settlement framework considering uncertainties daily operations is key successful integration into power systems.