Sensitivity analysis to connect distributed generation

被引:19
|
作者
de Souza, A. R. R. [1 ,2 ]
Fernandes, T. S. P. [1 ]
Aoki, A. R. [1 ,2 ]
Sans, M. R. [1 ,2 ]
Oening, A. P. [2 ]
Marcilio, D. C. [2 ]
Omori, J. S. [3 ]
机构
[1] Univ Fed Parana, Dept Elect Engn, BR-81531990 Curitiba, PR, Brazil
[2] Inst Technol Dev LACTEC, BR-81531980 Curitiba, PR, Brazil
[3] Energy Co Parana, BR-80420170 Curitiba, Parana, Brazil
关键词
Sensitivity analysis; Distributed generation; Genetic algorithms; Optimal power flow; DG ALLOCATION; LOSSES; OPTIMIZATION; RELIABILITY; ALGORITHM;
D O I
10.1016/j.ijepes.2012.10.004
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
One of the alternatives to reduce costs in a power system is the application of distributed generation (DG). Although inherent flexibilities of DG, the point of connection must be carefully chosen in order to avoid any hazardous impact. Normally, this choice is based on loss minimization, improvement of the voltage profile and reduction of the power flows through the lines. The search field of this problem is vast. In order to diminish it, this article assumes that only some buses of the network are candidates to the connection. Thus, one of the main objectives of this work is the proposition of a sensitivity analysis that indicates the best buses to realize the connection. Due to peculiarities of this proposed analysis, the voltage phasor is represented by the rectangular form. To test it, a conventional allocation's methodology is implemented and solved using genetic algorithms (GA) together with an optimal power flow (OPF). A purely radial feeder of one distribution company in Brazil, with 2678 buses and a typical network of 70 buses are chosen to present the results of the methodology. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:145 / 152
页数:8
相关论文
共 50 条
  • [31] Using SAS/CONNECT® to control a distributed application
    Williams, R
    PROCEEDINGS OF THE TWENTY-THIRD ANNUAL SAS USERS GROUP INTERNATIONAL CONFERENCE, 1998, : 597 - 602
  • [32] Sensitivity analysis of distributed erosion models: Framework
    Cheviron, B.
    Gumiere, S. J.
    Le Bissonnais, Y.
    Moussa, R.
    Raclot, D.
    WATER RESOURCES RESEARCH, 2010, 46
  • [33] SENSITIVITY ANALYSIS OF DISTRIBUTED PARAMETER-SYSTEMS
    KODA, M
    SEINFELD, JH
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1982, 27 (04) : 951 - 955
  • [34] Sensitivity Analysis of a Physically Based Distributed Model
    Dukic, Vesna
    Radic, Zoran
    WATER RESOURCES MANAGEMENT, 2016, 30 (05) : 1669 - 1684
  • [35] ANALYSIS OF THE SENSITIVITY FUNCTION FOR THE NETWORKS WITH DISTRIBUTED PARAMETERS
    VOROPAYEV, PV
    IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENII RADIOELEKTRONIKA, 1988, 31 (11): : 21 - 25
  • [36] A sensitivity-based approach for studying stability impact of distributed generation
    Nguyen, Tony B.
    Pai, M. A.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (08) : 442 - 446
  • [37] Power flow sensitivity based optimal configuration method of distributed generation
    Liu, Sheng
    Xu, Zheng
    Hua, Wen
    Huang, Hongyang
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2015, 36 (11): : 2802 - 2809
  • [38] A Composite Sensitivity Factor Based Method for Networked Distributed Generation Planning
    Zhang, Cuo
    Xu, Yan
    Dong, ZhaoYang
    Ma, Jin
    2016 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), 2016,
  • [39] Distributed Generation Management: an Optimal Sensitivity Approach for Decentralized Power Control
    Calderaro, V.
    Galdi, V.
    Massa, G.
    Piccolo, A.
    2012 3RD IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE (ISGT EUROPE), 2012,
  • [40] Impact of distributed generation on distribution contingency analysis
    Kotamarty, Sujatha
    Khushalani, Sarika
    Schulz, Noel
    ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (09) : 1537 - 1545