Assessing the Accuracy of Different Machine Learning Classification Algorithms in Forecasting Results of Italian Ancillary Services Market

Ancillary Services Market in Italy is knowing a period of reformation: Distributed Generators and loads are now enabled for the provision of dispatching resources. This calls for the development of fast, cheap and reliable tools to be used by operators with poor awareness about energy markets. In this paper a first approach to the problem is proposed: Machine Learning-based Classification models are developed and tested over a set of pre-processed market data. Then, a selected model based on Decision Trees is further elaborated to test its sensitivity with respect to hyperparameters tuning and learning techniques. Results highlighted the possibility to exploit this kind of models to integrate market-based logic in the control and automation of Distributed Generators and microgrids.