Short term electric load forecasting by wavelet transform and grey model improved by PSO (particle swarm optimization) algorithm

STLF (short term electric load forecasting) plays an important role in the operation of power systems. In this paper, a new model based on combination of the WT (wavelet transform) and GM (grey model) is presented for STLF and is improved by PSO (particle swarm optimization) algorithm. In the proposed model, the weather data including mean temperature, mean relative humidity, mean wind speed, and previous days load data are considered as the model inputs. Also, the wavelet transform is used to eliminate the high frequency components of the previous days load data and improve the accuracy of prediction. To improve the accuracy of STLF, the generation coefficient of GM is enhanced using PSO algorithm. To verify its efficiency, the proposed method is used for New York's and Iran's load forecasting. Simulation results confirm favourable performance of the proposed method in comparison with the previous methods studied.

[1]  Rahmat-Allah Hooshmand,et al.  A hybrid intelligent algorithm based short-term load forecasting approach , 2013 .

[2]  Saifur Rahman,et al.  A generalized knowledge-based short-term load-forecasting technique , 1993 .

[3]  Shiro Masuda,et al.  A research on short term load forecasting problem applying improved grey dynamic model , 2011 .

[4]  Dug Hun Hong,et al.  Short-term load forecasting for the holidays using fuzzy linear regression method , 2005 .

[5]  Jianzhou Wang,et al.  An adaptive fuzzy combination model based on self-organizing map and support vector regression for electric load forecasting , 2012 .

[6]  Ali Deihimi,et al.  Application of echo state networks in short-term electric load forecasting , 2012 .

[7]  N. Bigdeli,et al.  Data analysis and short term load forecasting in Iran electricity market using singular spectral analysis (SSA) , 2011 .

[8]  Farshid Keynia,et al.  Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm , 2009 .

[9]  Sunil Kumar Sinha,et al.  Intelligent Hybrid Wavelet Models for Short-Term Load Forecasting , 2010, IEEE Transactions on Power Systems.

[10]  T. Hesterberg,et al.  A regression-based approach to short-term system load forecasting , 1989, Conference Papers Power Industry Computer Application Conference.

[11]  S. A. Soliman,et al.  Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model , 2004 .

[12]  H. Mori,et al.  Deterministic Annealing Clustering for ANN-Based Short-Term Load Forecasting , 2001, IEEE Power Engineering Review.

[13]  N Amjady,et al.  Midterm Demand Prediction of Electrical Power Systems Using a New Hybrid Forecast Technique , 2011, IEEE Transactions on Power Systems.

[14]  Q. Henry Wu,et al.  Generalized Locally Weighted GMDH for Short Term Load Forecasting , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[15]  Xiao-Jun Zeng,et al.  Short-Term and Midterm Load Forecasting Using a Bilevel Optimization Model , 2009, IEEE Transactions on Power Systems.

[16]  Jian Ye,et al.  A new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting , 2008 .

[17]  N. Amjady,et al.  Short-Term Bus Load Forecasting of Power Systems by a New Hybrid Method , 2007, IEEE Transactions on Power Systems.

[18]  S. Fan,et al.  Short-term load forecasting based on an adaptive hybrid method , 2006, IEEE Transactions on Power Systems.

[19]  Li-Chang Hsu,et al.  Forecasting the output of integrated circuit industry using genetic algorithm based multivariable grey optimization models , 2009, Expert Syst. Appl..

[20]  Chao-Ming Huang,et al.  Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting , 1995 .

[21]  Babak Nadjar Araabi,et al.  Combination of Singular Spectrum Analysis and Autoregressive Model for Short Term Load Forecasting , 2007, 2007 IEEE Lausanne Power Tech.

[22]  Ismet Erkmen,et al.  Intelligent short-term load forecasting in Turkey , 2006 .

[23]  S. Pandian,et al.  Fuzzy approach for short term load forecasting , 2006 .

[24]  Xiang Zhou,et al.  Short-term power load forecasting using grey correlation contest modeling , 2012, Expert Syst. Appl..