Paper Title:
Daily Maximum Electric Load Forecasting with RBF Optimized by AFSA in K-Means Clustering Algorithm
  Abstract

Electric load forecasting is an important aspect in the operation of energy market. Many researchers have tried various methods and have achieved considerable results. In this paper, we used Radial Basis Function Neural Network (RBFN) to train data and forecast daily maximum electric load of a costal city in North China. In order to have a better result, we introduced Artificial Fish Swarm Algorithm (AFSA) to optimize RBF and adjust the center of K-means clustering algorithm. Data mining techniques were also employed to select indicators with impact on electric load. By comparing the forecast values and actual data, we arrived at conclusion that RBF optimized by AFSA could produce accurate result in forecasting daily maximum electric load. We also found that climate factors (temperature, humidity and air-pressure) had significant impact on daily maximum electric load.

  Info
Periodical
Key Engineering Materials (Volumes 467-469)
Edited by
Dehuai Zeng
Pages
1225-1230
DOI
10.4028/www.scientific.net/KEM.467-469.1225
Citation
W. Shen, Y. S. Sun, "Daily Maximum Electric Load Forecasting with RBF Optimized by AFSA in K-Means Clustering Algorithm", Key Engineering Materials, Vols. 467-469, pp. 1225-1230, 2011
Online since
February 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Hui Qin Sun, Zhi Hong Xue, Ke Jun Sun, Su Zhi Wang, Yun Du
Chapter 2: Manufacturing Technology
Abstract:BP neural network is currently the most widely used of neural network models in practical application in transformer fault diagnosis. BP...
789
Authors: Yang Xu
Chapter 4: Practice of Data Processing for Intelligent Systems
Abstract:This paper introduces the importance of power load forecasting, and makes forecasting based on the power load values collected in Botou City...
468
Authors: En Hua Chang, Guan Nan Zhu, Jiong Wei Chen
Chapter 5: High Voltage and Insulation Technology, and Power System Management
Abstract:Abstract. Electricity power forecasting has been always playing a vital role in power system management and planning. Inaccurate prediction...
278