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A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy.

Authors :
Feng, Zhong-kai
Niu, Wen-jing
Wang, Wen-chuan
Zhou, Jian-zhong
Cheng, Chun-tian
Source :
Energy. May2019, Vol. 175, p618-629. 12p.
Publication Year :
2019

Abstract

Abstract Recently, the booming electricity demand and intermittent energy has sharply increased the peak shaving pressure in China. However, for a majority of regional power grids in China, the installed capacity of flexible energy (like hydropower and pumped-storage) is small and the thermal plants are asked to respond the sudden load change at peak periods. The existing method based on specialist experience and historical information may generate inferior solutions and fail to reduce the peak pressure. Thus, a practical mixed integer linear programming (MILP) model is developed for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy, where the goal is chosen to minimize the peak-valley difference of the residual load series obtained by subtracting all the thermal generation from the original load curve while satisfying the necessary physical constraints. The MILP model is used to the thermal system in the China's largest regional power grid, East China Power Grid. The simulations show that the MILP model can effectively smooth the residual load curve by gathering power generation of thermal plants at peak periods. Therefore, an alternative tool is provided to alleviate the peak pressure of thermal-dominant regional power grid in China. Highlights • This work is from peak operation of thermal system in China's regional power grid. • A mixed integer linear programming model is firstly developed to solve this problem. • The objective is to minimize the peak-valley difference of the residual load series. • The MILP model obtains satisfying results in reducing peak loads of power system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
175
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
135930235
Full Text :
https://doi.org/10.1016/j.energy.2019.03.117