共 56 条
A hybrid particle swarm optimization with small population size to solve the optimal short-term hydro-thermal unit commitment problem
被引:38
作者:
Zhang, Jingrui
[1
]
Tang, Qinghui
[1
]
Chen, Yalin
[1
]
Lin, Shuang
[1
]
机构:
[1] Xiamen Univ, Dept Instrumental & Elect Engn, Xiamen, Peoples R China
来源:
基金:
中国国家自然科学基金;
关键词:
Hydro-thermal;
Unit commitment;
Particle swarm optimization;
Small population;
DIFFERENTIAL EVOLUTION ALGORITHM;
GRAVITATIONAL SEARCH ALGORITHM;
POWER-SYSTEM STABILIZERS;
GENETIC ALGORITHMS;
UNCERTAINTY;
LOAD;
DECOMPOSITION;
CONSTRAINTS;
STRATEGY;
DISPATCH;
D O I:
10.1016/j.energy.2016.05.057
中图分类号:
O414.1 [热力学];
学科分类号:
摘要:
Hydro-thermal unit commitment (HTUC) is an extension of unit commitment (UC) problems. The hydro thermal unit commitment problem considered in this study aims at minimizing the total fuel cost of thermal units while satisfying the constraints of spinning reserve, minimum online/offline, ramp rate, hydraulic networks, etc. A hybrid particle swarm optimization approach with small population size (HPSO-SP) is presented for solving the optimal short-term HTUC problem. In the proposed approach, three extra handling operations, i.e. mutation, DE-acceleration, and migration have been proposed for both binary and continuous variables to ensure the effects of small population. A repair strategy to the main equality and inequality constraints has also been employed to improve the searching efficiency of the algorithm. Several well-known UC test systems in literature are considered to test the proposed HPSO-SP approach first. After verification on UC problems, this approach is applied to solve several HTUC test systems and a practical hydro-thermal system in China. The final results show the feasibility and effectiveness of the HPSO-SP approach. (C) 2016 Elsevier Ltd. All rights reserved.
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页码:765 / 780
页数:16
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