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IDLab Ghent university -imec
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Control-oriented scenario trees can significantly enhance decision-making in uncertain environments, achieving higher profits and better risk management than traditional methods.
Integrating forecasting directly into the reinforcement learning loop can enhance EV charging decisions by significantly reducing energy waste and improving overall system performance.
S3TS achieves up to 51% cost reductions in non-linear scheduling scenarios, revolutionizing energy planning under uncertainty.