Data-driven auxiliary bidding tools for electricity market is expected to complete two tasks. The first is to predict market quotes based on the ultimate learning machine. The second is the characterization of the user utility function based on inverse reinforcement learning. This tool will help traders in the electricity market to improve trading efficiency and avoid risks.
2018 Galaxy --CUHKSZ Student Entrepreneur Project