Real coded genetic algorithm approach with random transfer vectors-based mutation for short-term hydro-thermal scheduling

被引:32
|
作者
Haghrah, Amirarslan [1 ]
Mohammadi-ivatloo, Behnam [1 ]
Seyedmonir, Seyedehnegar [1 ]
机构
[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
关键词
genetic algorithms; hydrothermal power systems; power generation scheduling; nonlinear programming; concave programming; real coded genetic algorithm approach; random transfer vectors-based mutation; short-term hydrothermal scheduling; thermal plants; hydraulic system constraints; electric system constraints; nonlinear problem; nonconvex problem; valve-point effects; transmission losses; GA approach; RCGA-RTVM; LEARNING BASED OPTIMIZATION; DIFFERENTIAL EVOLUTION; DISPATCH PROBLEMS; SYSTEM;
D O I
10.1049/iet-gtd.2014.0322
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
The short-term hydro-thermal scheduling involves scheduling of hydro and thermal generations to minimise the fuel cost of thermal plants in a horizon of planning time while meeting various hydraulic and electric system constraints. The problem is considered as a non-linear and non-convex problem involving valve-points effects and transmission losses with a set of equality and inequality constraints. In this study, a novel promising approach is represented with an innovated mutation method utilising genetic algorithm (GA). The proposed real coded GA approach with random transfer vectors-based mutation (RCGA-RTVM) is applied to two test systems with different characteristics. The effectiveness of the proposed RCGA-RTVM is validated by the obtained results. Comparison of the obtained results with recently developed methods shows the superiority of the proposed algorithm.
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页码:75 / 89
页数:15
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