Applied Mathematics & Information Sciences
Abstract
Yearly electricity consumption trends of most developing countries usually exhibit approximately exponential growth curves. An optimized nonhomogeneous exponential model (ONEM) is proposed as a method of forecasting electricity consumption by using trend extrapolation. The parameters of the nonhomogeneous exponential equation are obtained by using the inverse accumulated generating operation, discretizing the differential equation, minimizing the residual sum of squares (RSS), and accumulating the homogeneous exponential equation. Furthermore, to improve forecasting precision, particle swarm optimization (PSO) algorithm is used to optimize the equation parameters. To evaluate the forecasting performance for comparison, the said model and two other traditional methods are used to forecast the yearly electricity consumption of India. Empirical results show that this model is much better than traditional methods for each error analysis indicator.
Suggested Reviewers
N/A
Digital Object Identifier (DOI)
http://dx.doi.org/10.12785/amis/080316
Recommended Citation
Xu, Xiaomin; Niu, Dongxiao; Meng, Ming; and Shi, Huifeng
(2014)
"Yearly Electricity Consumption Forecasting using a Nonhomogeneous Exponential Model Optimized by PSO Algorithm,"
Applied Mathematics & Information Sciences: Vol. 08:
Iss.
3, Article 16.
DOI: http://dx.doi.org/10.12785/amis/080316
Available at:
https://digitalcommons.aaru.edu.jo/amis/vol08/iss3/16