Long term load forecasting using K-Means clustering and ANN approach

This study implements the Kmean+ANN based Load forecasting technique to predict the load of Amritsar and Pathankot station. Artificial Neural Network (ANN) is one of the emerging methods used for forecasting the load. This method shown good results in different power station problems included planning, protection, designing, control & security analysis and fault diagnosing. In this paper, it is illustrated that from last few years the load forecasting has been widely adopted and this is due to increase in the demand for electric power and this had also resulted in an increase of generating sources expenditure. In most of the cases, it had been implemented in utilizes to determine the number of resources required to fulfill the demands of the project. The major focus area of the research was load prediction of two different stations for 9 upcoming years. In this study work past 18 years load information was collected and different years were select as base years and after that, the author had implemented the k-mean clustering and ANN method to predict load for upcoming nine years.

[1]  R. Buizza,et al.  Neural Network Load Forecasting with Weather Ensemble Predictions , 2002, IEEE Power Engineering Review.

[2]  Julio Usaola,et al.  Probabilistic load flow with correlated wind power injections , 2010 .

[3]  Naeem Arbab,et al.  Factor Affecting Short Term Load Forecasting , 2014 .

[4]  Qi Wu,et al.  Power load forecasts based on hybrid PSO with Gaussian and adaptive mutation and Wv-SVM , 2010, Expert Syst. Appl..

[5]  Hassan Soltan,et al.  A methodology for Electric Power Load Forecasting , 2011 .

[6]  Lambros Ekonomou,et al.  Electricity demand load forecasting of the Hellenic power system using an ARMA model , 2010 .

[7]  M.Y. Hassan,et al.  Short term load forecasting using data mining technique , 2008, 2008 IEEE 2nd International Power and Energy Conference.

[8]  Wei-Chiang Hong,et al.  Application of chaotic ant swarm optimization in electric load forecasting , 2010 .

[9]  Haiyan Lu,et al.  Combined modeling for electric load forecasting with adaptive particle swarm optimization , 2010 .

[10]  Milena Stankovic,et al.  Mid-term load forecasting using recursive time series prediction strategy with support vector machines , 2010 .

[11]  Ross Baldick,et al.  A strategic review of electricity systems models , 2010 .

[12]  Carlos Maté,et al.  Electric power demand forecasting using interval time series: A comparison between VAR and iMLP , 2010 .

[13]  M. R. AlRashidi,et al.  LONG TERM ELECTRIC LOAD FORECASTING BASED ON PARTICLE SWARM OPTIMIZATION , 2010 .

[14]  Zita Vale,et al.  Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming , 2010 .

[15]  A. B. M. Shawkat Ali,et al.  Identification of typical load profiles using K-means clustering algorithm , 2014, Asia-Pacific World Congress on Computer Science and Engineering.

[16]  Saeid Nahavandi,et al.  Load Forecasting and Neural Networks: A Prediction Interval-Based Perspective , 2010 .

[17]  Andrea Garulli,et al.  Load forecasting for active distribution networks , 2011, 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies.

[18]  Saeid Nahavandi,et al.  Construction of Optimal Prediction Intervals for Load Forecasting Problems , 2010, IEEE Transactions on Power Systems.

[19]  M. Talaat,et al.  A New Approach for Short-Term Load Forecasting Using Curve Fitting Prediction Optimized by Genetic Algorithms , 2012 .

[20]  Karl Aberer,et al.  Electricity load forecasting for residential customers: Exploiting aggregation and correlation between households , 2013, 2013 Sustainable Internet and ICT for Sustainability (SustainIT).

[21]  Tingting Guo,et al.  Short-Term Load Forecasting for Electric Power Systems Using the PSO-SVR and FCM Clustering Techniques , 2011 .

[22]  Azuraliza Abu Bakar,et al.  Application of the k-means clustering algorithm to predict load shedding of the Southern Electrical Grid of Libya , 2014, Fourth edition of the International Conference on the Innovative Computing Technology (INTECH 2014).

[23]  Desheng Dash Wu,et al.  Power load forecasting using support vector machine and ant colony optimization , 2010, Expert Syst. Appl..

[24]  Che Guan.  Wavelet Neural Network Based Very Short-term Load Forecasting and Prediction Interval Estimation , 2013 .

[25]  S. J. Kiartzis,et al.  A neural network short term load forecasting model for the Greek power system , 1996 .

[26]  K. Daljeet,et al.  Long Term Load Forecasting Using Soft Computing Techniques , 2015 .

[27]  Jian Wang,et al.  Short, medium and long term load forecasting model and virtual load forecaster based on radial basis function neural networks , 2010 .