|
| 摘要: |
| 将浮点数编码的遗传算法应用于无功优化中。给出了在浮点数编码下的交叉、变异和逆转操作，浮点数编码不仅可以缩短染色体长度，降低算法的搜索空间，且可以避免初始化及遗传操作中生成的不可行解，从而提高算法的效率。最后，将提出的方法用于IEEE 30节点系统，得到了满意的结果。 |
| 关键词: 无功优化 遗传算法 浮点编码 |
| DOI： |
| 分类号:TM761.1 TP18 |
| 基金项目: |
|
| Reactive power optimization using float point encoding genetic algorithm |
|
BI Peng-xiang 1 MIAO Zhu-mei 2 LIU Jian 1
|
| Abstract: |
| A float point encoding genetic algorithm for reactive power optimization is presented.The crossover,mutation and inversion operations with float point encoding are proposed,which not only reduces the length of chromosome and search space,but also avoids the infeasible solutions produced during initialization and gene operations.The performance of genetic algorithms is thus improved.The proposed genetic algorithm for reactive power optimization has been tested in an IEEE30-bus power system and the satisfactory results are obtained. |
| Key words: reactive power optimization,genetic algorithms,float point encoding |
