International Journal of Energy Engineering          
International Journal of Energy Engineering(IJEE)
Frequency: Yearly
Editor-in-Chief: Prof. Sri Bandyopadhyay(Australia)
Day-ahead Electricity Price Forecasting Using PSO -Based LLWNN Model
Full Paper(PDF, 214KB)
Price forecasting has become an important activity for market participants in electric power industry for developing their bidding strategies. The work presented in this paper makes use of particle swarm optimization based local linear wavelet neural networks (LLWNN) to find the Market Clearing Price (MCP) for a given period, with a certain confidence level. The results of the new method show significant improvement in the price forecasting process.
Keywords:Electricity Price, Forecasting, Wavelet Neural Network (WNN), Local Linear Wavelet Neural Network (LLWNN), Particle Swarm Optimization (PSO), Market Clearing Price (MCP), Weekly Mean Absolute Percentage Error (WMAPE)
Author: Prasanta kumar Pany1, Sakti Prasad Ghoshal2
1.Department of Electrical Engineering, DRIEMS,Cuttack, Odisha, India
2.Department of Electrical Engineering, National Institute of Technology, Durgapur, West Bengal, India
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