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Project

Stochastic energy forecasting and optimal risk-averse trading strategies on the energy market

Balance Responsible Parties of BRPs are responsible for balancing production and consumption on the Belgian energy grid. To this end, BRPs have to predict the energy needs of their customer portfolio. Based on these predictions, BRPs will choose to buy or sell energy on the Belgian electricity market. Currently, BRPs are facing a new challenge with the enormous growth of solar and wind energy production. The production of these renewable energy sources is inherently related to future weather conditions which induces a certain level of uncertainty. Therefore, this PhD will research to which extent satellite images can be used to predict solar energy production in the future. This prediction can then be used to accurately predict the future energy load of the customer portfolio of a BRP. Both predictions will be used to place optimal and risk-averse bids on the energy market.

Date:22 Dec 2022 →  Today
Keywords:Energy, Machine Learning, Optimal Control
Disciplines:Data mining, Calculus of variations and optimal control, optimisation
Project type:PhD project