Assessing the Accuracy of Different Machine Learning Classification Algorithms in Forecasting Results of Italian Ancillary Services Market
- Resource Type
- Conference
- Authors
- Bovera, Filippo; Blaco, Alessandro; Rancilio, Giuliano; Delfanti, Maurizio
- Source
- 2019 16th International Conference on the European Energy Market (EEM) European Energy Market (EEM), 2019 16th International Conference on the. :1-5 Sep, 2019
- Subject
- Power, Energy and Industry Applications
Vegetation
Computational modeling
Support vector machines
Data models
Decision trees
Predictive models
Classification algorithms
Ancillary Services Market
Decision Trees
Machine Learning
Tertiary Control
mFRR
- Language
- ISSN
- 2165-4093
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.