基于改进差分进化算法的配电网无功优化
采用改进差分进化算法（Improved Differential Evolution Algorithm，IDEA）求解配电网无功优化问题。该算法引人基于反学习的种群初始化方法，使算法得到的初始种群具有多样性，能够充分提取搜索空间的信息；引入高斯扰动机制到交叉操作中，提高了在维尺度上的种群多样性；在进化过程中融入人工蜂群搜索思想，引入蜂群加速进化与侦查操作策略，使算法能快速跳出局部最优，避免了早熟问题。建立了配电网无功优化数学模型，并采用IDE算法对IEEE30节点系统求解该模型，并与基本DE算法进行对比，仿真结果证明了所提IDE算法具有更佳的性能，能够有效的求解配电网无功优化的问题。...
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| Published in | 电测与仪表 Vol. 52; no. 17; pp. 63 - 67 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
国网内蒙古东部电力有限公司电力科学研究院,呼和浩特,010020%珠海泰坦科技股份有限公司,广东珠海,519015
2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-1390 |
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| Summary: | 采用改进差分进化算法（Improved Differential Evolution Algorithm，IDEA）求解配电网无功优化问题。该算法引人基于反学习的种群初始化方法，使算法得到的初始种群具有多样性，能够充分提取搜索空间的信息；引入高斯扰动机制到交叉操作中，提高了在维尺度上的种群多样性；在进化过程中融入人工蜂群搜索思想，引入蜂群加速进化与侦查操作策略，使算法能快速跳出局部最优，避免了早熟问题。建立了配电网无功优化数学模型，并采用IDE算法对IEEE30节点系统求解该模型，并与基本DE算法进行对比，仿真结果证明了所提IDE算法具有更佳的性能，能够有效的求解配电网无功优化的问题。 |
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| Bibliography: | improved differential evolution algorithm, reactive power optimization, anti-learning, Gaussian disturb- anee, artificial bee colony 23-1202/TH Improved differential evolution algorithm （IDEA） is used to solve the reactive power optimization of distribution network problem. An anti-learning population initialization method is introduced to the algorithm which makes the initial population diverse and is able to fully extract the information of the search space. The method introduces Gauss perturbation mechanism to the interlace operation, which improves the diversity of the population in the dimension scale. Meanwhile, the artificial colony search thoughts and the bees accelerated evolution and reconnaissance operations strategy are added into the evolution process so that the algorithm can quickly jump out of the local optimum and avoid premature. Based on the above, a distribution network reactive power optimization model is established and solves the model with IEEE30 node system adopting IDE algorithm, and t |
| ISSN: | 1001-1390 |