Open Access

ARTICLE

A Weighted Combination Forecasting Model for Power Load Based on Forecasting Model Selection and Fuzzy Scale Joint Evaluation

Bingbing Chen^*, Zhengyi Zhu, Xuyan Wang, Can Zhang

State Grid Nanjing Power Supply Company, Nanjing, 210019, China

* Corresponding Author: Bingbing Chen. Email:

(This article belongs to the Special Issue: Advances in Modern Electric Power and Energy Systems)

Energy Engineering 2021, 118(5), 1499-1514. https://doi.org/10.32604/EE.2021.015145

Received 25 November 2020; Accepted 21 December 2020; Issue published 16 July 2021

Abstract

To solve the medium and long term power load forecasting problem, the combination forecasting method is further expanded and a weighted combination forecasting model for power load is put forward. This model is divided into two stages which are forecasting model selection and weighted combination forecasting. Based on Markov chain conversion and cloud model, the forecasting model selection is implanted and several outstanding models are selected for the combination forecasting. For the weighted combination forecasting, a fuzzy scale joint evaluation method is proposed to determine the weight of selected forecasting model. The percentage error and mean absolute percentage error of weighted combination forecasting result of the power consumption in a certain area of China are 0.7439% and 0.3198%, respectively, while the maximum values of these two indexes of single forecasting models are 5.2278% and 1.9497%. It shows that the forecasting indexes of proposed model are improved significantly compared with the single forecasting models.

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Keywords

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