Antonello Giannitrapani (Università di Siena)
Bidding Strategies for Electric Power Producers from Renewable Sources in the Presence of Weather Forecasts
In this talk, we consider the problem of offering energy generated from renewable sources in an electricity market featuring “soft” penalties, i.e. penalties that are applied only if the delivered power deviates from the nominal bid more than a given relative tolerance. The optimal bidding strategy, based on the knowledge of the prior power generation statistics, is derived analytically. Then, we present a possible way to integrate weather forecasts in the bidding strategy. The proposed approach consists in classifying the days into one of several predetermined classes, for each of which an optimal generation profile is precomputed. Weather forecasts are then used to predict the class the next day will belong to so that the appropriate profile can be selected. Finally, we focus on photovoltaic (PV) power plants and show how the bidding strategy can be suitably modified in order to take into account the effects of seasonal variations and the non stationary nature of PV power generation. The performance of the optimal bidding strategy in the presence of weather forecasts is demonstrated on real data from Italian wind and PV power plants.