The Power Loading Forecasting and Optimizing the Contract Capacity: A Case Study of An University

• Main Authors: Huang, Yi-Jing, 黃怡菁
• Other Authors: Chang, Yung-Chia
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/t994nd

碩士 === 國立交通大學 === 管理學院工業工程與管理學程 === 107 === This paper uses the seasonal ARIMA model to predict the maximum demand for electricity in the future and uses mathematical programming method to construct a mathematical model for the cost of electricity for Taiwan Power Company, so as to find out the monthly optimal contract capacity for the next year as a reference for adjusting the contract capacity. By doing so, we can reduce the financial burden of electricity cost for electricity users and achieve energy conservation goals. Based on the case in this study, the forecast accuracy is good with the MAPE of 12.7%~21.7% by using the seasonal ARIMA model and the cost of electricity saved by 5.9% after finding out the monthly optimal contract capacity by mathematical model we proved. Therefore, the research method used in this paper can be used as a reference for the electricity users to set the contract capacity with Taiwan Power Company.