A Hybrid Method of Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm for Medium Term Electricity Price Forecasting

  • Intan Azmira Wan Abdul Razak Universiti Teknikal Malaysia Melaka
  • Nik Nur Atira Nik Ibrahim Universiti Teknikal Malaysia Melaka
  • Izham Zainal Abidin Universiti Tenaga Nasional
  • Yap Keem Siah Universiti Tenaga Nasional
  • Aidil Azwin Zainul Abidin Universiti Tenaga Nasional
  • Titik Khawa Abdul Rahman King Abdulaziz University

Abstract

Predicting electricity price has now become an important task for planning and maintenance of power system. In medium term forecast, electricity price can be predicted for several weeks ahead up to a year or few months ahead. It is useful for resources reallocation where the market players have to manage the price risk on the expected market scenario. However, researches on medium term price forecast have also exhibit low forecast accuracy. This is due to the limited historical data for training and testing purposes. Therefore, an optimization technique of Bacterial Foraging Optimization Algorithm (BFOA) for Least Square Support Vector Machine (LSSVM) was developed in this study to provide an accurate electricity price forecast with optimized LSSVM parameters and input features. So far, no literature has been found on feature and parameter selections using the LSSVM-BFOA method for medium term price prediction. The model was examined on the Ontario power market; which is reported as among the most volatile market worldwide. Monthly average of Hourly Ontario Electricity Price (HOEP) for the past 12 months and month index are selected as the input features. The developed LSSVM-BFOA shows higher forecast accuracy with lower complexity than the existing models.

Downloads

Download data is not yet available.
Published
03-09-2019
How to Cite
Wan Abdul Razak, I. A., Nik Ibrahim, N. N. A., Zainal Abidin, I., Keem Siah, Y., Zainul Abidin, A. A., & Abdul Rahman, T. K. (2019). A Hybrid Method of Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm for Medium Term Electricity Price Forecasting. International Journal of Integrated Engineering, 11(3). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/4689