An MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids. (15th November 2018)

• Record Type: Journal Article
• Authors: Cheng, Chuntian; Su, Chengguo; Wang, Peilin; Shen, Jianjian; Lu, Jianyu; Wu, Xinyu
• Is Part Of: Energy. Volume 163(2018)
• Page Start: 722
• Page End: 733
• Publication Date: 2018-11-15
• Subjects: Peak shaving -- Pumped-storage hydropower plant -- Mixed-integer linear programming -- Multiple power grids; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.08.077
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: China's power grids have constructed many large pumped-storage hydropower plants (PSHPs) to relieve their increasing peak shaving pressure. Unlike PSHPs in a single power grid, the PSHPs directly operated by the dispatch center of regional power grids are required to simultaneously provide peak regulation services for several subordinate provincial power grids. This makes the daily operation of these PSHPs very challenging for both system operators and researchers. Hence, this paper develops a Mixed-integer linear programming (MILP) based model for determining the optimal hourly scheduling of PSHPs serving several provincial power grids. The objective is to minimize the peak-valley difference of the residual load series of each power grid. The performance of individual units in the model will be considered, as well as the head effect for each unit in both generating mode and pumping mode. The study focuses mainly on the linearization of the commonly-used nonlinear objective function, constraints on the operation status of units, and turbine performance curves. These nonlinearities are then linearized with the aid of binary integer variables. The optimization results obtained from two real-world case studies are used to demonstrate that the proposed model is computationally efficient and shows good performance in relieving the peak regulation pressure of each power grid. Highlights: The proposed model could obtain near-global optima in an acceptable CPU time. The model performed well in relieving the peak shaving pressure of each power grid. The piecewise linearization techniques described are novel and suitable. The model has been integrated into the DSS for daily operation of PSHPs in ECPG.