Category: Time-Series Forecasting
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Trading to Protect the Grid: A Reinforcement Learning Trading Agent in Electricity Markets
In this project, I designed an AI trading agent for electricity markets using deep reinforcement learning, trained with curriculum learning. The agent showcases strong performance in day-ahead power markets by taking in price and grid forecasts (that I developed myself using transformer models) and outputting optimal bids for the next…
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Time-Series Forecasting for Day-Ahead Markets
Modern electricity markets are highly dynamic systems. Across a day, the electricity price can fluctuate rapidly and reach peaks several factors higher than the baseline or reach lows of negative prices. This volatility requires accurate forecasters in order to make decisions in such an uncertain environment. In this project, I…