Distribution network expansion planning and DG placement in the presence of uncertainties

被引:71
作者
Hemmati, Reza [1 ]
Hooshmand, Rahmat-Allah [2 ]
Taheri, Nabi [2 ]
机构
[1] Kermanshah Univ Technol, Dept Elect Engn, Kermanshah, Iran
[2] Univ Isfahan, Dept Elect Engn, Esfahan, Iran
关键词
Distribution network expansion planning; Distributed generation; Monte-Carlo simulation; Particle swarm optimization; Probability distribution function; Uncertainty; DISTRIBUTION-SYSTEMS; GENERATION; MODEL; ALGORITHM;
D O I
10.1016/j.ijepes.2015.05.024
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
Distribution network expansion planning (DNEP) is one of the most important tools to deal with the demand growth in a system. DNEP is usually carried out through reinforcement or installation of new components. In this paper, a new and combined methodology is used to consider several practical aspects in DNEP such as uncertainty, distributed generation (DG), load growth, electricity market and multi stage dynamic expansion are included in the planning. So that DNEP is addressed in the presence of distributed generation (DG), considering load and price uncertainties under electricity market environment. The proposed planning aims at minimizing investment and operational costs simultaneously. Since DNEP in coordination with DG planning leads to reduce planning cost; therefore, the coordinated DNEP and DG planning are presented in this paper. The proposed planning is implemented by the particle swarm optimization (PSO) technique. Besides, the uncertainties are modeled as the probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to insert the uncertainties into the programming. The proposed planning is carried out based on the 9-bus as well as Kianpars-Ahvaz test systems (Kianpars-Ahvaz is a practical network in Ahvaz province, Iran). The simulation results demonstrate the ability and effectiveness of the proposed planning to deal with uncertainties under electricity market environment. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:665 / 673
页数:9
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