2023 JAN 24 (NewsRx) -- By a News Reporter-Staff News Editor at Energy Daily News -- A new study on Energy - Energy and Buildings is now available. According to news reporting from Zhengzhou, People’s Republic of China, by NewsRx journalists, research stated, “Electricity consumption and load prediction, and the influence laws of usage behavior are essential 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 laws of the usage behavior.”
Funders for this research include 2022 Henan Provincial Key Science and Technology program, China national key research and development program, Science and Technology Program of China National Textile and Apparel Council.
The news correspondents obtained a quote from the research from the Zhongyuan University of Technology, “According to the pro-posed method, a model was developed and verified by taking certain regional rural residences as exam-ples, 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 values. 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.”
According to the news reporters, the research concluded: “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 character-istics and significant influencing factors, which may provide valuable data for power grid design and pho-tovoltaic power generation systems.”
This research has been peer-reviewed.
For more information on this research see: Electricity Consumption and Load Prediction Method for Chinese Rural Residences Based On the Randomness and Seasonality In Electricity Usage Behavior. Energy and Buildings, 2023;278. Energy and Buildings can be contacted at: Elsevier Science Sa, PO Box 564, 1001 Lausanne, Switzerland. (Elsevier - www.elsevier.com; Energy and Buildings - http://www.journals.elsevier.com/energy-and-buildings/)
Our news journalists report that additional information may be obtained by contacting Pengli Yuan, Zhongyuan University of Technology, School of Energy and Environment, Zhengzhou 450007, People’s Republic of China. Additional authors for this research include Ke Gao, Xinyi Zhao, Xintong Liu, Weihong Kong, Lin Duanmu and Zongshan Wang.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.enbuild.2022.112647. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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