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URN etd-0620102-150742
Author Chih-Hung Chen
Author's Email Address No Public.
Statistics This thesis had been viewed 5386 times. Download 1572 times.
Department Electrical Engineering
Year 2001
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title The Temperature Sensitivity Analysis of Power System Load Demand with Neural Networks
Date of Defense 2002-06-14
Page Count 89
Keyword
  • Load Survey
  • Neural Networks
  • Temperature Sensitivity
  • Abstract The Temperature Sensitivity Analysis of Power System Load Demand with Neural Networks
    Chih-Hung Chen* Chao-Shun Chen**
    Institute of Electrical Engineering
    National Sun Yat-Sen University
    Kaohsiung, Taiwan, R.O.C.
    ABSTRACT
    The analysis of customer load characteristic plays the fundamental role of power system operation. Based on the load survey study, the load pattern of each customer class is derived to achieve more effective load forecast for system planning to reduce the risk of system capacity shortage.
    For the load survey study, a stratified sampling method has been used to select the proper size of customers for meter installation to collect the customer power consumption. By the way, the customer load patterns derived can represent the load behavior of whole customer population. The standardized daily load pattern of each customer class has been solved with the mean per-unit method of customer load. According to the total power consumption by all customers within the same class and considering the corresponding daily load pattern, the daily load profile of the customer class is then determined. The standard daily load pattern of each customer class and total power consumption within the territory of service districts of Taipower system are integrated to construct Taipower system daily load profile. The temperature sensitivity analysis of customer power consumption is performed for each customer class by applying neural networks. The proposed method has been used to investigate the change of power consumption due to temperature rise for each district and Taipower system. For the districts with high ratio of the air conditioner loading, the increase of power consumption is in proportion to the temperature. It is concluded that the research of temperature sensitivity on power consumption can support power system operation and better capacity planning of power system in the future.
    *Author **Advisor
    Advisory Committee
  • Chan-Nan Lu - chair
  • Ming-Yuan Cho - co-chair
  • Jong-Chuy Hwang - co-chair
  • Chao-Shun Chen - advisor
  • Files
  • etd-0620102-150742.pdf
  • indicate access worldwide
    Date of Submission 2002-06-20

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