| 引用本文: | 吴忠强,赵立儒,贾文静,吴昌韩.计及DG与STATCOM的配电网重构优化策略[J].电力自动化设备,2016,36(1): |
| WU Zhongqiang,ZHAO Liru,JIA Wenjing,WU Changhan.Optimal reconfiguration of distribution network with DG and STATCOM[J].Electric Power Automation Equipment,2016,36(1): |
|
| 摘要: |
| 采用一种改进遗传算法（GA）实现配电网重构，其考虑了配电网近期的发展变化，将分布式发电（DG）与静止无功补偿器（STATCOM）引入配电网模型中，探讨它们对配电网重构和提高电能质量的影响。采用十进制与二进制混合编码方式和特殊的交叉与变异操作避免GA不可行解的产生，采用云算法改进交叉率与变异率以提高GA的收敛性。对IEEE 33节点配电网进行仿真，结果表明所提出的改进GA可有效地实现网络重构，DG与STATCOM的引入能有效提高配电网的供电质量和可靠性。 |
| 关键词: 网络重构 配电网 遗传算法 云模型 分布式发电 静止无功补偿器 |
| DOI： |
| 分类号: |
| 基金项目:河北省自然科学基金资助项目（F2012203088） |
|
| Optimal reconfiguration of distribution network with DG and STATCOM |
|
WU Zhongqiang, ZHAO Liru, JIA Wenjing, WU Changhan
|
|
Key Lab of Industrial Computer Control Engineering of Hebei Province，College of Electrical Engineering，Yanshan University，Qinhuangdao 066004，China
|
| Abstract: |
| An improved GA（Genetic Algorithm） is applied to realize the DNR（Distribution Network Recon-figuration），which introduces DG（Distributed Generation） and STATCOM into the distribution network model to include its recent development. The influences of DG and STATCOM on DNR and power quality improvement are discussed. The hybrid binary and decimal coding method and the special crossover and mutation operation are adopted to avoid the infeasible solutions of GA. The cloud algorithm is applied to improve the crossover rate and mutation rate for enhancing the convergency of GA. The simulative results for IEEE 33-bus distribution network prove that the proposed method realizes the DNR effectively and the application of DG and STATCOM enhances the power quality and reliability successfully. |
| Key words: network reconfiguration distribution network genetic algorithms cloud model distributed power generation STATCOM |
