Strategic bidding for a price-maker hydroelectric producer: Stochastic dual dynamic programming and Lagrangian relaxation
研究了单一价格制定型水电生产者在日前电力市场中最大化收入的投标策略，结合随机对偶动态规划和拉格朗日松弛方法，并用水电丰富的洪都拉斯市场验证了模型。
In bid-based markets, energy producers seek bidding strategies that maximize their revenue. In this article, we seek the maximum-revenue bidding schedule for a single price-maker hydroelectric producer. We assume the producer sells energy in the day-ahead electricity market and has the ability to impact the market-clearing price with its bids. To obtain the price-maker hydroelectric producer’s bidding schedule, we use a combination of Stochastic Dual Dynamic Programming and Lagrangian relaxation. In this framework, we dualize the water balance equations, allowing an exact representation of the non-concave immediate revenue function, while preserving the concave shape of the future revenue function. We model inflow uncertainty and its stagewise dependence by a periodic autoregressive model. To demonstrate our approaches’ utility, we model Honduras’ electricity market assuming that the thermal producers act as price-takers and that one price-maker hydro producer operates all of the hydroelectric plants.