| 引用本文: | 冯兴田,孙添添,马文忠.配电网电能质量调节装置集散配置策略[J].电力系统保护与控制,2015,43(24):33-39. |
| FENG Xingtian,SUN Tiantian,MA Wenzhong.Centralized and dispersed allocation strategy of power quality regulating devices in distribution network[J].Power System Protection and Control,2015,43(24):33-39 |
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| 摘要: |
| 配电网结构复杂，负荷多样，存在多种电能质量问题，需采用相应的电能质量调节装置进行改善。通过分析配电网的电能质量问题的特点及四种电能质量调节装置的特性和适用范围，提出了配电网电能质量调节装置集散配置策略。根据现场工况和用户需求建立数学模型，提出优化配置的目标函数和约束条件。详细分析基于功能、装置、投资的集散配置策略的实施方案和特点，有机结合集中、分散配置，基于遗传算法形成协调统一的集散配置策略。仿真算例对以IEEE33节点为架构的配电网安装的电能质量调节装置进行了优化配置分析，结果表明，集散配置策略有效解决电能质量问题，优化配置了需投入的装置。 |
| 关键词: 电能质量 集散配置 遗传算法 D-FACTS装置 优化目标 |
| DOI：10.7667/j.issn.1674-3415.2015.24.006 |
| 分类号: |
| 基金项目:国家自然科学基金项目(51477184，51207170)；中央高校基本科研业务费专项资金项目(14CX02085A) |
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| Centralized and dispersed allocation strategy of power quality regulating devices in distribution network |
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FENG Xingtian, SUN Tiantian, MA Wenzhong
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College of Information and Control Engineering, China University of Petroleum (East China), Qingdao 266580, China
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| Abstract: |
| Distribution network (DN) has complicate structure and different loads which lead to many kinds of power quality problems. Power quality regulating equipments (PQRE) should be adopted to improve the problems. Characteristics and applicability of four PQREs and power quality problems of DN are analyzed. And PQREs centralized and dispersed allocation strategy (CDAS) of DN is proposed. The target function and constraint condition of optimal allocation are presented and mathematical model is established according to field conditions and customer requirement. CDAS implementing plan and feature are analyzed in detail based on function, equipment and investment. Unified CDAS is formed by combining centralized allocation with dispersed allocation based on genetic algorithm. Simulation example analyzes optimal allocation of PQREs in distribution network with IEEE 33 nodes. The results show that CDAS effectively solves power quality problems and optimizes installed equipments. |
| Key words: power quality centralized and dispersed allocation genetic algorithm D-FACTS equipments optimal target |
