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Online Search with Predictions: Pareto-optimal Algorithm and its Applications in Energy Markets
Feb. 29, 2024, 5:42 a.m. | Russell Lee, Bo Sun, Mohammad Hajiesmaili, John C. S. Lui
cs.LG updates on arXiv.org arxiv.org
Abstract: This paper develops learning-augmented algorithms for energy trading in volatile electricity markets. The basic problem is to sell (or buy) $k$ units of energy for the highest revenue (lowest cost) over uncertain time-varying prices, which can framed as a classic online search problem in the literature of competitive analysis. State-of-the-art algorithms assume no knowledge about future market prices when they make trading decisions in each time slot, and aim for guaranteeing the performance for the …
abstract algorithm algorithms applications arxiv basic cost cs.ds cs.lg electricity energy markets online search paper pareto predictions revenue search trading type uncertain units
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