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量子进化算法在电力系统无功优化中的应用 被引量:13

Application of quantum-inspired evolutionary algorithm in reactive power optimization
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摘要 量子进化算法QEA(Quantum-insp ired evolutionary algorithm)将量子理论引入进化计算领域,是一种基于量子计算概念的进化策略算法。它采用量子比特为基本信息位进行个体编码,使用量子态的么正变换(量子门变换)实现个体的进化,同时利用量子编码的多态叠加性以及“全干扰交叉”可以有效克服进化过程中的早熟现象,因此它比传统进化算法具有更快的收敛速度和全局寻优能力。该文将该算法应用于电力系统无功优化问题,提出基于QEA算法的无功优化模型,并对算法参数进行了研究,提出了合适的量子变异参数。运用该算法对IEEE6、30节点系统进行了仿真计算,计算结果验证了模型和算法的有效性。 Quantum-inspired evolutionary algorithm (QEA) is a kind of evolutionary strategy algorithms inspired by quantum computing. It uses quantum hit as the smallest unit of information-chromosome and quantum-gate as a primary variation operator to drive the individuals toward the better. QEA makes full use of superposition of states and whole interference to avoid pre-maturity, so it has rapid convergence and global search capacity. This paper presents a model of reactive power optimization based on QEA and studies its parameters. To demonstrate its effectiveness and applicability, the simulations are carried out on IEEE6 and IEEE30 bus system. The resuits show the validity of the proposed model and algorithm.
出处 《继电器》 CSCD 北大核心 2005年第18期30-35,共6页 Relay
关键词 无功优化 量子进化算法 么正变换 全干扰交叉 量子量测塌陷 reactive power optimization quantum-inspired evolutionary algorithm unitary transformation whole interferencecrossover quantum measurement sink
作者简介 娄素华(1974-),女,博士研究生,讲师,研究方向为电力系统运行分析与规划,电力系统可靠性;E-mail:yusaier02@163.com 吴耀武(1963-),男,副教授,从事电力系统及其自动化方向科研和教学工作,研究方向为电力系统运行分析与规划。
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