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在对遗传算法深入研究的基础上 ,针对其求解时间过长的问题 ,引入优化搜索路径的思路 ,提出无功功率分层分块优化控制和进化灵敏度分析的方法 ,对常规遗传算法搜索路径的随机性和变异、交叉这两种遗传操作进行本质上的改善。另外 ,在常规无功优化目标函数的基础上 ,提出了包含“调节代价”的目标函数。通过对算例的优化计算结果可以看出 ,文中介绍的无功优化算法比常规算法优越 ,计算速度快 ,实用性强
Based on the deep research of genetic algorithm, aiming at the problem of too long solution time, the idea of optimizing search path is introduced, and the method of hierarchical control and evolutionary sensitivity analysis of reactive power is put forward. Randomization and mutation, cross these two genetic operations to make an essential improvement. In addition, based on the objective function of conventional reactive power optimization, an objective function containing “adjustment cost” is proposed. Through the calculation results of the example, we can see that the reactive power optimization algorithm introduced in this paper is superior to the conventional one, the calculation speed is fast, and the practicality is strong