电力市场下日无功计划优化模型和算法的研究

针对电力市场下无功辅助服务的特点，提出了计及无功费用的日无功计划数学模型，并应用一种充分结合免疫原理和遗传算法各自优点的混合优化策略来求解该模型。该算法模拟免疫系统中抗体的自我平衡机制，调节遗传算法中个体浓度的抑制和促进；利用免疫记忆功能，实现了优良基因片的重组，提高遗传算法的总体搜索能力。依据抗体结构的可变区和稳定区，该文提出基于有效负荷变化指标的专家知识来对个体的基因进行修补，使遗传算法的优化过程具有指导性。IEEE30节点系统的计算和分析表明了该文所提出模型和算法的正确性和实用性。

STUDY ON THE MODEL AND ALGORITHM OF DAILY REACTIVE POWER SCHEDULING IN ELECTRICITY MARKET

A mathematical model considering cost of reactive power is proposed for daily reactive power scheduling in electricity market. To solve this complicated problem, this paper presents a mixed optimization strategy that sufficiently combines the advantages of immune theory and genetic algorithm (GA). The density of individuals is regulated automatically by simulating homeostatic mechanism of antibody in immune system. The function of immunological memory is used to recombine good gene and improve ability of searching. According to variable region and stable region of antibody, an expert knowledge based on effective variety of load is presented for gene modification of individuals. The proposed model and algorithm are applied to IEEE30 system, and the numerical results verify the correctness and validity of them.