The Temperature Sensitivity Analysis of Power System Load Demand with Neural Networks

• Main Authors: Chih-Hung Chen, 陳智宏
• Other Authors: Chao-Shun Chen
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/81922560173227919958

碩士 === 國立中山大學 === 電機工程學系研究所 === 90 === 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