Robust Optimization for the Self-Scheduling and Bidding Strategies of a Hydroproducer Considering the Impacts of Crossing Forbidden Zones

Abstract

Giant hydrounits are usually accompanied by multiple head-dependent forbidden zones (FZs). FZs intensify hydropower systems’ head effects and affect the safe and economic operations in a deregulated market environment, especially in southwest China. This paper addresses the self-scheduling and bidding strategies of a typical hydroproducer (the Longtan hydroplant, the leading plant on the Hongshuihe River, one of the most important plants in the West-East Electricity Transmission Project in China) with irregular forbidden zones (IFZs) in a day-ahead market. Considering the impacts of crossing IFZs and the head effects, a robust optimization-based approach to maximize profits was developed to establish market-oriented strategies under asymmetric price intervals and is solved by an iterative algorithm.The complicated model with nonconvex and nonlinear features was recast into a robust mixed-integer linear programming (MILP) model. Finally, the optimal self-scheduling of a hydroproducer with IFZs in southwest China was used to show the effectiveness of the proposed model. The optimization results demonstrated that the proposed model can effectively incorporate the head effects and the impacts of crossing IFZs to maximize profits; furthermore, the model significantly reduced the phenomenon of crossing IFZs and provided more executable, stable, and safe generation scheduling. Additionally, the proposed model can obtain more profitable optimal bidding strategies than the model that ignores the impacts of crossing IFZs.