Title page for etd-0627101-151951


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URN etd-0627101-151951
Author Hung-Chih Wu
Author's Email Address jimwu@mail.nsysu.edu.tw
Statistics This thesis had been viewed 5588 times. Download 2070 times.
Department Electrical Engineering
Year 2000
Semester 2
Degree Ph.D.
Type of Document
Language zh-TW.Big5 Chinese
Title A Fuzzy Modeling Method for Small Area Load Forecast
Date of Defense 2001-06-01
Page Count 105
Keyword
  • Fuzzy Modeling
  • Load Forecast
  • Abstract In a more competitive environment, load forecast serves two different applications. First, load forecast results can be used by the retailers of power to study their opportunities and plan their business strategies. Second, accurate projections of load are useful for T&D operators in performing system operation and expansion studies. Several key elements in their market and system planning studies have strong location factors that the spatial load forecast can address. In this dissertation, a package that integrates a Geographic Information System (GIS) used for automatic mapping and facility management (AM/FM) and a spatial load forecast module is presented. The interface functions and the procedure of the fuzzy logic based spatial load forecast module are described. Simulation studies are performed on a metropolitan area of Kaohsiung, Taiwan.
    The conventional fuzzy modeling has a drawback in that the fuzzy rules or the fuzzy membership functions are determined by trial and error. In this dissertation an automatic model identification procedure is proposed to construct the fuzzy model for short-term load forecast. In this method an analysis of variance is used to identify the influential variables on the system load. To setup the fuzzy rules, a cluster estimation method is adopted to determine the number of rules and the membership functions of variables involved in the premises of the rules. A recursive least square method is then used to determine the coefficients in the conclusion parts of the rules. None of these steps involves nonlinear optimization and all steps have well-bounded computation time.
    Advisory Committee
  • Sheng-Nian Yeh - chair
  • Chi-Jui Wu - co-chair
  • Ching-Tsai Pan - co-chair
  • Li Wang - co-chair
  • Chao-Shun Chen - co-chair
  • Chan-Nan Lu - advisor
  • Files
  • etd-0627101-151951.pdf
  • indicate access worldwide
    Date of Submission 2001-06-27

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