Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

On Statistical Modeling and Forecasting of Energy Usage in Smart Grid

Published

Author(s)

Wei Yu, Dou An, David W. Griffith, Qingyu Yang, Guobin Xu

Abstract

Developing effective energy resource management in the smart grid is challenging because the entities in both the demand and supply sides experience various uncertainties. This paper addresses the issue of quantifying uncertainties on the energy demand side and the developed techniques in the paper can be applied to the energy generation side as well. The statistical modeling analysis approaches are developed to derive a statistical distribution of energy usage and the machine learning based approaches such as the Support Vector Machines (SVM) and neural network are developed to conduct the accurate forecasting on energy usage. The extensive experiments of proposed approaches are conducted using a real-world meter reading data set. The experimental data shows that the statistical distribution of meter reading data can be largely approximated with a Gaussian distribution and the two SVM-based machine learning approaches achieve a high accuracy of energy usage forecasting. Extensions to other smart grid applications (e.g., forecasting energy generation and determining optimal demand response) are discussed as well.
Citation
Security and Communication Networks

Keywords

Statistical Modeling Analysis, Energy Usage Forecasting, Machine Learning, Real-world Meter Reading Data, Smart Grid Statistical Modeling Analysis, Energy Usage Forecasting, Machine Learning, Real-world Meter Reading Data, Smart Grid

Citation

Yu, W. , An, D. , Griffith, D. , Yang, Q. and Xu, G. (2014), On Statistical Modeling and Forecasting of Energy Usage in Smart Grid, Security and Communication Networks (Accessed June 13, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created October 7, 2014, Updated October 12, 2021