Short-term load forecasting methods: A review

Short-term load forecasting methodsFor decision makers in the electricity sector, the decision process is complex with several different levels that have to be taken into consideration. These comprise for instance the planning of facilities and an optimal day-to-day operation of the power plant. These decisions address widely different time-horizons and aspects of the system. For accomplishing these tasks load forecasts are very important. This paper presents a comprehensive survey of the short term load forecasting. It also reviews various methodologies for short term load forecasting (STLF). Authors strongly believe that this survey article shall be very much helpful to the researchers working in the field of short term load forecasting for finding out the appropriate references and future work.

[1]  J. D. McDonald,et al.  A real-time implementation of short-term load forecasting for distribution power systems , 1994 .

[2]  Hong-Tzer Yang,et al.  Identification of ARMAX model for short term load forecasting: an evolutionary programming approach , 1995 .

[3]  Pradipta Kishore Dash,et al.  A comparison of fuzzy neural networks for the generation of daily average and peak load profiles , 1995 .

[4]  Tomonobu Senjyu,et al.  Future load curve shaping based on similarity using fuzzy logic approach , 1998 .

[5]  Gwo-Ching Liao A Novel Particle Swarm Optimization Approach Combined with Fuzzy Neural Networks for Short-Term Load Forecasting , 2007, 2007 IEEE Power Engineering Society General Meeting.

[6]  A. A. El-Keib,et al.  Advancement of statistical based modeling techniques for short-term load forecasting , 1995 .

[7]  Yuan-Yih Hsu,et al.  Short term load forecasting of Taiwan power system using a knowledge-based expert system , 1990 .

[8]  Dipti Srinivasan,et al.  Survey of hybrid fuzzy neural approaches to electric load forecasting , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[9]  W. M. Grady,et al.  Enhancement, implementation, and performance of an adaptive short-term load forecasting algorithm , 1991 .

[10]  H.-C. Wu,et al.  Automatic fuzzy model identification for short-term load forecast , 1999 .

[11]  Manuel A. Matos,et al.  Forecasting Portugal Global Load with Artificial Neural Networks , 2007, ICANN.

[12]  Gerald B. Sheblé,et al.  Short-term load forecasting by a neural network and a refined genetic algorithm , 1994 .

[13]  J. Nazarko,et al.  Estimating Substation Peaks from Load Research Data , 1997, IEEE Power Engineering Review.

[14]  W. R. Christiaanse Short-Term Load Forecasting Using General Exponential Smoothing , 1971 .

[15]  Shoichi Muto,et al.  Peak load forecasting using multiple‐year data with trend data processing techniques , 1998 .

[16]  Elham B. Makram,et al.  Harmonic load identification and determination of load composition using a least squares method , 1996 .

[17]  Michael T. Manry,et al.  Comparison of very short-term load forecasting techniques , 1996 .

[18]  I. J. Ramirez-Rosado,et al.  Distribution planning of electric energy using fuzzy models , 1996 .

[19]  Tomonobu Senjyu,et al.  Next day load curve forecasting using recurrent neural network structure , 2004 .

[20]  G. Juberias,et al.  A new ARIMA model for hourly load forecasting , 1999, 1999 IEEE Transmission and Distribution Conference (Cat. No. 99CH36333).

[21]  Dong-Chul Park,et al.  Short-Term Load Forecasting Using Multiscale BiLinear Recurrent Neural Network with an Adaptive Learning Algorithm , 2006, ICONIP.

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

[23]  Dipti Srinivasan,et al.  Evolving artificial neural networks for short term load forecasting , 1998, Neurocomputing.

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

[25]  C. Reeves Modern heuristic techniques for combinatorial problems , 1993 .

[26]  Ahmed Z. Al-Garni,et al.  Model for Electric Energy Consumption in Eastern Saudi Arabia , 1997 .

[27]  O. P. Malik,et al.  Numerical Taxonomy Method for STLF , 2002 .

[28]  S. Huang,et al.  Short-term load forecasting using threshold autoregressive models , 1997 .

[29]  W. Charytoniuk,et al.  Nonparametric regression based short-term load forecasting , 1998 .

[30]  Xiaoyu Chen,et al.  Electricity Load Forecasting Based on Support Vector Machines and Simulated Annealing Particle Swarm Optimization Algorithm , 2007, 2007 IEEE International Conference on Automation and Logistics.

[31]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[32]  D. K. Ranaweera,et al.  Application of radial basis function neural network model for short-term load forecasting , 1995 .

[33]  A. C. Liew,et al.  Fuzzy neural network and fuzzy expert system for load forecasting , 1996 .

[34]  V. Lo Brano,et al.  Forecasting daily urban electric load profiles using artificial neural networks , 2004 .

[35]  Carlos E. Pedreira,et al.  Neural networks for short-term load forecasting: a review and evaluation , 2001 .

[36]  Jae Hong Park,et al.  Composite modeling for adaptive short-term load forecasting , 1991 .

[37]  M. El-Hawary,et al.  Load forecasting via suboptimal seasonal autoregressive models and iteratively reweighted least squares estimation , 1993 .

[38]  Larry D. Paarmann,et al.  Adaptive online load forecasting via time series modeling , 1995 .

[39]  Dongxiao Niu,et al.  Research on Neural Networks Based on Culture Particle Swarm Optimization and Its Application in Power Load Forecasting , 2007, Third International Conference on Natural Computation (ICNC 2007).

[40]  Milde M. S. Lira,et al.  Using Genetic Algorithm to Develop a Neural-Network-Based Load Forecasting , 2007, ICANN.

[41]  Hiroyuki Mori,et al.  Fuzzy inference models for short-term load forecasting with tabu search , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[42]  Chao-Ming Huang,et al.  A particle swarm optimization to identifying the ARMAX model for short-term load forecasting , 2005 .

[43]  S. Muto,et al.  Regression based peak load forecasting using a transformation technique , 1994 .

[44]  A. Girgis,et al.  A hybrid wavelet-Kalman filter method for load forecasting , 2000 .

[45]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[46]  K Padmakumari,et al.  Long term distribution demand forecasting using neuro fuzzy computations , 1999 .

[47]  Z.A. Bashir,et al.  Short-Term Load Forecasting Using Artificial Neural Network Based on Particle Swarm Optimization Algorithm , 2007, 2007 Canadian Conference on Electrical and Computer Engineering.

[48]  M. Crawford,et al.  An Adaptive Nonlinear Predictor with Orthogonal Escalator Structure for Short-Term Load Forecasting , 1989, IEEE Power Engineering Review.

[49]  Mo-Yuen Chow,et al.  Application of fuzzy multi-objective decision making in spatial load forecasting , 1998 .

[50]  Y.-Y. Hsu,et al.  Fuzzy expert systems: an application to short-term load forecasting , 1992 .

[51]  David Infield,et al.  Optimal smoothing for trend removal in short term electricity demand forecasting , 1998 .

[52]  Saifur Rahman,et al.  Analysis and Evaluation of Five Short-Term Load Forecasting Techniques , 1989, IEEE Power Engineering Review.

[53]  A. E. Eiben,et al.  Introduction to Evolutionary Computing , 2003, Natural Computing Series.

[54]  K. L. Lo,et al.  The application of short-term adaptive forecasting techniques in energy management for the control of electrical load , 1989 .

[55]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[56]  Suresh Kumar Bhaskaruni Short Term Load Forecasting Using Artificial Neural Networks , 2014 .

[57]  Yunfang Xie,et al.  Short-Term Load Forecasting Based on the Method of Genetic Programming , 2007, 2007 International Conference on Mechatronics and Automation.

[58]  Saudi Arabia,et al.  SHORT-TERM PEAK DEMAND FORECASTING IN FAST DEVELOPING UTILITY WITH INHERIT DYNAMIC LOAD CHARACTERISTICS , 1990 .

[59]  Derek W. Bunn,et al.  Large neural networks for electricity load forecasting: Are they overfitted? , 2005 .

[60]  P. Mastorocostas,et al.  Fuzzy modeling for short term load forecasting using the orthogonal least squares method , 1999 .

[61]  R.-H. Liang,et al.  Fuzzy linear programming: an application to hydroelectric generation scheduling , 1994 .

[62]  Z. S. Elrazaz,et al.  Unified weekly peak load forecasting for fast growing power system , 1989 .

[63]  Gwo-Ching Liao,et al.  Application of a fuzzy neural network combined with a chaos genetic algorithm and simulated annealing to short-term load forecasting , 2006, IEEE Transactions on Evolutionary Computation.

[64]  Muhammad Asim Qayyum,et al.  SHORT-TERM PEAK DEMAND FORECASTING IN FAST DEVELOPING UTILITY WITH INHERIT DYNAMIC LOAD CHARACTERISTICS , 1990 .

[65]  Marios M. Polycarpou,et al.  Short Term Electric Load Forecasting: A Tutorial , 2007, Trends in Neural Computation.

[66]  Mo-Yuen Chow,et al.  Application of fuzzy logic technology for spatial load forecasting , 1996, Proceedings of 1996 Transmission and Distribution Conference and Exposition.

[67]  Raj Aggarwal,et al.  Advanced hybrid genetic algorithm for short-term generation scheduling , 2001 .

[68]  H. Mori,et al.  Optimal fuzzy inference for short-term load forecasting , 1995 .

[69]  John V. Ringwood,et al.  Forecasting Electricity Demand on Short, Medium and Long Time Scales Using Neural Networks , 2001, J. Intell. Robotic Syst..

[70]  E. Gonzalez-Romera,et al.  Monthly Electric Energy Demand Forecasting Based on Trend Extraction , 2006, IEEE Transactions on Power Systems.

[71]  O. Hyde,et al.  An adaptable automated procedure for short-term electricity load forecasting , 1997 .

[72]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[73]  J. Vermaak,et al.  Recurrent neural networks for short-term load forecasting , 1998 .