Funding entity Endesa Medios y Sistemas S.L
This project aims to identify a strategy for predicting the maximum clearing price in the real-time congestion management market, characterized as a "Pay as Bid" system. Time series prediction methods are applied. Additionally, functional time series identification and prediction models are used for forecasting residual demand curves in the market. This approach allows for characterizing the bidding strategy of market participants.
Layman's summary: This project aims to predict the maximum clearing price in the real-time congestion management market. Advanced time series prediction models will be applied to forecast the price and residual demand curves in the market.
Techniques employed: Advanced Time series models. Functional Data. Recurrent Neural Networks.
HADES_2024_S2
