A combination approach for downstream plants to solve scheduling information asymmetry problem in electricity markets

Abstract

Hydropower generation relies heavily on neighboring upstream plants due to the natural cascading structure in hydropower systems. In competitive markets, discharging decisions become more self-interested and opaque, making it difficult for downstream plants to predict inflows and make decisions. To address this scheduling information asymmetry (SIA) problem, this paper proposes a combination approach that consists of three parts: (1) constructing a bilevel model, in which the upper-level searches for optimal parameters and the lower-level model simulates the upstream plant’s operating behavior with parameters provided by the upper-level model, (2) adopting the proposed parallel hypercubic searching algorithm (PHSA) to solve the non-convex bilevel model, and (3) accelerating the solving process using a searching domain reduction (SDR) method derived from engineering experience in the three-dimensional case. Case studies on the Lancang River show that the combination approach is efficient, accurate, and robust in estimating operational parameters and historical operating states of the rival’s upstream plant. Kruskal-Wallis and Tukey-type tests indicate that the proposed combination approach outperforms alternative methods.