Exploiting weather forecasts for sizing photovoltaic energy bids

In this work, we study the problem of optimizing energy bids for a photovoltaic (PV) power producer taking part into a competitive electricity market characterized by financial penalties for generation shortfall and surplus. The optimal bidding strategy depends on the statistics of the PV power generation and on the monetary penalties applied. We show how to tune the bidding strategy on the basis of the weather forecasts. To this purpose, an optimization procedure is devised to mitigate the risk associated with the intermittent nature of PV generation and maximize the expected profit of the producer. We also investigate an approach to properly take into account the seasonal variation and non stationary nature of PV power generation statistics, by exploiting the knowledge of the amount of energy that the plant can generate under clear-sky conditions. The proposed bidding strategy is validated on a real data set from an Italian PV plant.