Optimal bidding for large-scale hydropower stations serving multiple power grids in multi-regional monthly electricity markets

Abstract

Driven by the development of the multi-level and unified electricity market in China, large-scale hydropower stations serving multiple power grids (LHSMPGs) have recently been required to enter into multiple regional electricity transactions. However, due to the multiple uncertainties of runoff and electricity prices, complex operation constraints, and difficulties in quantifying opportunity costs, formulating reliable bidding strategies for multi-regional monthly auction markets to maximize profits presents a challenge for LHSMPGs in China. Accordingly, in this study, we propose a tractable bidding optimization method for LHSMPGs in multi-regional monthly electricity markets. First, a scenario-based method is developed to describe the uncertainties in runoff and multi-regional electricity prices, as well as their cross-correlations. Then, a stochastic programming model is developed to coordinately optimize the piecewise bidding curves in multi-regional auction markets. The model considers the opportunity cost of bid quantities and complex monthly electricity allocation requirements during the whole time horizon of a year. Moreover, a monthly-rolling solution framework is designed to solve the stochastic programming model to ensure that the latest actual data can be dynamically considered to improve the accuracy of declaration. The application of the proposed method is verified through two cases based on the Xiluodu Hydropower Station, which ranks fourth in the world in terms of installed capacity. The results demonstrate that optimizing bidding curves in multi-regional monthly auction markets coordinately can enhance gross revenues and electricity sales. Moreover, a sensitivity analysis reveals that an excessively large or small allocation proportion of electricity between annual and monthly markets would weaken the guiding role of monthly auction markets in optimizing the allocation of hydropower resources and exacerbate the uneven distribution of hydropower generation between flood and dry seasons.