English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62805/95882 (66%)
Visitors : 3906963      Online Users : 584
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/60714


    Title: A computer package for optimal multi-objective var planning in large scale power systems
    Authors: 蕭瑛東;Hsiao, Ying-tung;Chiang, Hsiao-dong;Liu, Chun-chang;Chen, Yuan-lin
    Contributors: 淡江大學電機工程學系
    Date: 1994-05
    Issue Date: 2011-10-15 00:45:40 (UTC+8)
    Publisher: Piscataway: Institute of Electrical and Electronics Engineers
    Abstract: This paper presents a simulated annealing based computer package for multi-objective, VAr planning in large scale power systems-SAMVAR. This computer package has three distinct features. First, the optimal VAr planning is reformulated as a constrained, multi-objective, nondifferentiable optimization problem. The new formulation considers four different objective functions related to system investment, system operational efficiency, system security and system service quality. The new formulation also takes into consideration load, operation and contingency constraints. Second, it allows both the objective functions and equality and inequality constraints to be nondifferentiable; making the problem formulation more realistic. Third, the package employs a two-stage solution algorithm based on an extended simulated annealing technique and the E-constraint method. The first-stage of the solution algorithm uses an extended simulated annealing technique to find a global, noninferior solution. The results obtained from the first-stage provide a basis for planners to prioritize the objective functions such that a primary objective function is chosen and tradeoff tolerances for the other objective functions are set. The primary objective function and the trade-off tolerances are then used to transform the constrained multi-objective optimization problem into a single-objective optimization problem with more constraints by employing the E-constraint method. The second-stage uses the simulated annealing technique to find the global optimal solution
    Relation: IEEE Transactions on Power Systems 9(2), pp.668-676
    DOI: 10.1109/59.317676
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

    Files in This Item:

    File SizeFormat
    index.html0KbHTML374View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback