The Analysis of Temperature Sensitivity and Load Characteristics of Taipower System

• Main Authors: Wen-Pin Chen, 陳文平
• Other Authors: Chao-Shun Chen
• Format: Others
• Language: zh-TW
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/73469991890224354048

碩士 === 國立中山大學 === 電機工程學系研究所 === 89 === Customer load characteristics plays the ndamental role for more reliable load forecasting. It can also be used to enhance the system expansion planning and economic dispatch more effectively. Besides, the system capacity shortage due to peak loading can be relieved by the strategy of energy conservation and load management with customer load models. A systematic procedure is proposed in this thesis to study the effect of temperature change to the power system load demand by using the typical load patterns of customer classes. The billing data of all service customers are retrieved to derive the daily load profile of the selected Taipower district. To verify the accuracy of the estimated load composition, the simulation results are compared to the actual load profile collected by the SCADA system. The sensitivity analysis of load demand with respect to the temperature change for each customer class is performed by statistic regression according to the actual customer power consumption and temperature data. With temperature rise, the load contribution by each customer class is updated by the corresponding temperature sensitivity and integrated together to form the new load profile of the service district. In the future, the load research will play more important role for power utility companies. Load data will be utilized to a greater extent by various departments in utility companies. For instance, the proposed load survey system can solve the customer load characteristics more accurately to support various applications. By refer the temperature sensitivity analysis based on the customer load research, can evaluate the potential of air conditioner load management to reduce the system peak loading can be inhibit. With this information, the proper incentive of cycling control of air conditioners can be designed to achieve more effective load management.