An improved PSO technique for short-term optimal hydrothermal scheduling

被引:149
作者
Hota, P. K. [1 ]
Barisal, A. K. [1 ]
Chakrabarti, R. [2 ]
机构
[1] UCE, Dept Elect Engn, Burla 768018, Orissa, India
[2] Jadavpur Univ, Dept Elect Engn, Kolkata, India
关键词
Dynamic search-space squeezing strategy; Hydrothermal scheduling; Particle swarm optimization; Practical constraints; Multichain reservoirs; Differential evolution; PARTICLE SWARM OPTIMIZATION; ECONOMIC-DISPATCH; ALGORITHM; PLANTS; POWER;
D O I
10.1016/j.epsr.2009.01.001
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents a new approach to the Solution of optimal power generation to short-term hydrothermal scheduling problem, using improved particle swarm optimization (IPSO) technique. The practical hydrothermal system is highly complex and possesses nonlinear relationship of the problem variables, cascading nature of hydraulic network, water transport delay and scheduling time linkage that make the problem of finding global optimum difficult using standard optimization methods. In this paper ail improved PSO technique is suggested that deals with an inequality constraint treatment mechanism called as dynamic search-space squeezing strategy to accelerate the optimization process and simultaneously, the inherent basics of conventional PSO algorithm is preserved. To show its efficiency and robustness, the proposed IPSO is applied on a multi-reservoir cascaded hydro-electric system having prohibited operating zones and a thermal unit with valve point loading. Numerical results are compared with those obtained by dynamic programming (DP), nonlinear programming (NLP), evolutionary programming (EP) and differential evolution (DE) approaches. The simulation results reveal that the proposed IPSO appears to be the best in terms of convergence speed, solution time and minimum cost when compared with established methods like EP and DE. (C) 2009 Elsevier B.V. All rights reserved.
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页码:1047 / 1053
页数:7
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