Modification method to deal with the accumulation effects for summer daily electric load forecasting. (December 2015)

• Record Type: Journal Article
• Authors: Li, Yang; Bao, Yu-Qing; Yang, Bin; Chen, Chu; Ruan, Wenjun
• Is Part Of: International journal of electrical power & energy systems. Volume 73(2015:Dec.)
• Page Start: 913
• Page End: 918
• Publication Date: 2015-12
• Subjects: Load forecasting -- Accumulation effect -- Genetic-algorithm -- Neural network; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2015.06.027
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A modification method to deal with the accumulation effect is proposed. The proposed method modifies the relationship between the temperature and the load. Genetic algorithm is adopted to optimize the parameters of the modification function. Abstract: Due to the summer heat, electric load is sometimes influenced by the accumulation effect: the load is not only affected by the present temperature, but also affected by the continuous high-temperature in the last a few days. This paper proposes a method to deal with the accumulation effect. In the proposed method, the temperature variable used in the forecasting model is modified as a function of present and historical temperatures. To enhance the predicting power of the modified temperature, genetic-algorithm (GA) is adopted to get the optimal parameters of the modification function. The testing results show that the modification of the temperature can improve the accuracy of summer load forecasting.