An MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids
Chuntian Cheng,
Chengguo Su,
Peilin Wang,
Jianjian Shen,
Jianyu Lu and
Xinyu Wu
Energy, 2018, vol. 163, issue C, 722-733
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.
Keywords: Peak shaving; Pumped-storage hydropower plant; Mixed-integer linear programming; Multiple power grids (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544218316098
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:163:y:2018:i:c:p:722-733
DOI: 10.1016/j.energy.2018.08.077
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().