An energy service provider would like to Machine Learning model for Forecast of the positive or negative balance of control energy in the Grid Regional Network (NRV). The aim is to be able to operate on the volatile to be able to trade more efficiently in the electricity market.
Numerous data sources are cleaned up and integrated into a unified Time series format merged. A visual and data-based Exploration of correlations and possible influencing factors will be is carried out. Subsequently, several regression and Classification models for the prediction of the balance or its Sign and application of a two-stage ensemble model created.
Es there is a prototype of a forecasting model that is geared towards this, with currently available data, the balance of control energy in 15 minutes to predict. This allows the electricity producer to position itself in the market. better position.
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