Optimal Decision for Joint Wind-thermal Power Based on KKT and Quantum Genetic Algorithm

Abstract

Abstract: The decision-making model for joint wind-thermal power considering both economic benefit and energy conservation and emission reduction benefit is investigated by KKT and solved by quantum genetic algorithm. Considering the characteristics of wind power and thermal power, economic benefit function and energy conservation and emission reduction function are established as well as relevant constraints, and finally a multi-objective decision-making model is established. The multi-objective model is changed into single goal in KKT framework and solved by quantum genetic algorithm. A numerical example is given which suggests that the proposed KKT and quantum genetic algorithm is more accurate and with less computational time than commonly used optimization methods. It has great superiority in decision-making for joint wind-thermal power.

Key words: joint wind-thermal power system, decision-making model, KKT, quantum genetic algorithm, energy conservation and emission reduction

摘要： 研究了同时考虑节能减排效益和经济效益时,风火电联合上网的决策模型,并采用提出的KKT框架下的量子遗传算法进行模型的求解。综合考虑风电和火电的特点,建立经济效益函数和节能减排效益函数以及相关的约束条件,最终确立多目标决策模型。在KKT框架下将多目标函数转化为单目标,并利用量子遗传算法进行模型的求解。算例分析显示本文提出的KKT框架下的量子遗传算法在决策模型的求解时能够利用更少的CPU运行时间获得更优的决策结果,与其他常用的优化模型相比具有较高的优越性。

关键词: 风火电力系统, 决策模型, KKT, 量子遗传算法, 节能减排

CLC Number:

TM73

WEI Ya-nan, NIU Dong-xiao. Optimal Decision for Joint Wind-thermal Power Based on KKT and Quantum Genetic Algorithm[J]. Operations Research and Management Science, 2013, 22(2): 105-110.

魏亚楠, 牛东晓. 基于KKT和量子遗传算法的风火电联合上网最优决策[J]. 运筹与管理, 2013, 22(2): 105-110.

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