Electricity Consumption and Load Prediction Method for Chinese Rural Residences Based on the Randomness and Seasonality in Electricity Usage Behavior

54 Pages Posted: 26 Sep 2022

See all articles by Pengli Yuan

Pengli Yuan

affiliation not provided to SSRN

Lin Duanmu

Dalian University of Technology

Zongshan Wang

Dalian University of Technology

Ke Gao

affiliation not provided to SSRN

Xinyi Zhao

affiliation not provided to SSRN

Xintong Liu

affiliation not provided to SSRN

Weihong Kong

affiliation not provided to SSRN

Abstract

Electricity consumption and load prediction, and the influence regulation of usage behavior are the essential components for smart grid and policy guidance. This paper presents an electricity consumption and load prediction method based on a stochastic model considering the randomness and seasonality in the usage behavior of appliances, with the aim of exploring the influence regulation of usage behavior. According to the proposed method, model was developed and verified by taking certain regional rural residences as examples, and the influence of model inputs on electricity consumption and load were explored. The results showed that the modeled total electricity consumption of individual and regional rural residences were consistent with the actual value. The prediction accuracy of the model could be improved by more than 30% compared with the deterministic model results. Furthermore, the model could reasonably capture the electricity load profiles on a daily as well a seasonal basis. Our research provides a comprehensive framework to predict the electricity consumption and load for Chinese rural residences from sampling and data acquisition to model development, and to preliminarily explore the power demand characteristics and the significant factors, which may provide valuable data for power grid design and photovoltaic power generation systems.

Keywords: Chinese rural residences, electricity consumption and load, prediction model, usage behavior, stochastic model.

Suggested Citation

Yuan, Pengli and Duanmu, Lin and Wang, Zongshan and Gao, Ke and Zhao, Xinyi and Liu, Xintong and Kong, Weihong, Electricity Consumption and Load Prediction Method for Chinese Rural Residences Based on the Randomness and Seasonality in Electricity Usage Behavior. Available at SSRN: https://ssrn.com/abstract=4230484 or http://dx.doi.org/10.2139/ssrn.4230484

Pengli Yuan (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Lin Duanmu

Dalian University of Technology ( email )

Huiying Rd
DaLian, LiaoNing, 116024
China

Zongshan Wang

Dalian University of Technology ( email )

Huiying Rd
DaLian, LiaoNing, 116024
China

Ke Gao

affiliation not provided to SSRN ( email )

No Address Available

Xinyi Zhao

affiliation not provided to SSRN ( email )

No Address Available

Xintong Liu

affiliation not provided to SSRN ( email )

No Address Available

Weihong Kong

affiliation not provided to SSRN ( email )

No Address Available

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