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基于量子免疫克隆算法的多目标无功优化
罗 毅, 多靖赟
华北电力大学 控制与计算机工程学院,北京 102206
摘要:
结合量子计算原理和免疫克隆算子,提出一种解决多目标无功优化问题的量子免疫克隆算法。该算法采用量子比特编码,使一个量子抗体可以同时表征多个信息状态,进而增加了种群的多样性;采用量子重组与量子非门操作的搜索策略,将全局搜索和局部寻优有机结合,确保所得解集快速有效地从不可行域边缘和可行域内部向最优Pareto前端逼近;采用目标函数值与理想化目标的接近程度来评价解的优劣性,有效降低了传统算法各目标函数值加权叠加过程中对权重选取的依赖性。IEEE 14节点系统仿真测试结果表明,该算法能有效提高系统运行的经济性和安全性。
关键词:  多目标优化  无功  免疫克隆算子  量子计算原理  量子重组  量子非门  模型
DOI:
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基金项目:国家自然科学基金资助项目(60974051)
Multi-objective reactive power optimization based on quantum immune colonial algorithm
LUO Yi, DUO Jingyun
School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China
Abstract:
Combined with the quantum computation theory and immune colonial operator,a quantum immune colonial algorithm is put forward for solving the problem of multi-objective reactive power optimization,which adopts the quantum bit code to represent more information states by one quantum antibody for increasing the diversity of population,applies the searching strategy of quantum restructure and quantum negater operation to combine global search with local optimal for ensuring the approach of solution set from the edge of the infeasible region or the feasible region to the optimal Pareto front,and uses the proximity between objective function value and ideal objective to evaluate the superiority of solution for effectively reducing the dependence of traditional algorithms on the weight selection during the weighted superposition of each objective function. Result of simulative test for IEEE 14-bus system shows that,the proposed algorithm improves the economy and security of system operation effectively.
Key words:  multi-objective optimization  reactive power  immune colonial operator  quantum computation principle  quantum restructure  quantum negater  models

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