• HOME
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • Chinese
Site search        
文章摘要
主动配电网的全寿命周期分布式电源规划问题研究
Research on Distributed Generation Planning of Active Distribution Network Considering Life Cycle Cost
Received:April 11, 2017  Revised:April 11, 2017
DOI:
中文关键词: 主动管理  多目标双层规划  分布式电源  粒子群算法  
英文关键词: active  management, multi-objective  bi-level  planning, distributed  generation, improved  Particle Swarm  Optimization
基金项目:
Author NameAffiliationE-mail
ZHENG Bowen* Yuxi Power Supply Bureau h_chunyi@163.com 
YANG Jun Yuxi Power Supply Bureau 576764646@qq.com 
YANG Chengchen Yuxi Power Supply Bureau 23572061@qq.com 
BAO Xiaofeng Yuxi Power Supply Bureau 54595081@qq.com 
Hits: 1946
Download times: 950
中文摘要:
      主动配电网的主动管理及主动控制特性加剧了其电源规划的难度。本文基于ADN特性提出了考虑主动管理模式的分布式电源多目标双层规划模型。上层模型以最小化系统电源侧的全寿命周期成本为目标,从而确定DG的安装配置方案;而下层则以最小化DG有功出力切除量为目标,通过采用主动管理中的DG出力控制、有载变压器分接头调节以及无功补偿装置调节等方式实现DG运行优化。利用带自适应变异的改进粒子群(IPSO)算法对上下层模型进行求解,提高了算法的求解速度并有效得到全局最优解。同时,通过对IEEE 33节点系统进行仿真分析,验证了所构建模型的合理性。
英文摘要:
      The key features of Active Distribution Network (ADN) which include active management and active control exacerbate the difficulty of its generation planning. Based on features of ADN, a multi-objective Bi-level programming model about distribution generation considering active management mode was proposed. The objective of upper level model was to minimize the total life cycle cost of power supply side in the system, thus the installation and configuration plan was obtained after optimization. Whereas the lower level model was aimed at minimizing active power curtailment value, and operation optimization of distributed generation (DG) was obtained through applying DG output control, on-load-tap-changing transformer adjustment, reactive power compensation device adjustment and other active management modes. The upper and lower model were solved by improved particle swarm optimization (PSO) algorithm with adaptive mutation, which could improve the solution speed and the global optimal effectiveness. Besides, the simulation of the IEEE 33-node system was carried out to verify the rationality of the model.
View Full Text   View/Add Comment  Download reader
Close
  • Home
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • 中文页面
Address: No.2000, Chuangxin Road, Songbei District, Harbin, China    Zip code: 150028
E-mail: dcyb@vip.163.com    Telephone: 0451-86611021
© 2012 Electrical Measurement & Instrumentation
黑ICP备11006624号-1
Support:Beijing Qinyun Technology Development Co., Ltd