Load forecasting techniques and methodologies: A review

Electricity demand forecasts are extremely important for energy suppliers and other participants in electric energy generation, transmission, distribution and markets. Accurate models for electric power load forecasting are essential to the operation and planning of a utility company. Load forecasts are extremely important for energy suppliers and other participants in electric energy generation, transmission, distribution and markets. This paper presents a review of electricity demand forecasting techniques. The various types of methodologies and models are included in the literature. Load forecasting can be broadly divided into three categories: short-term forecasts which are usually from one hour to one week, medium forecasts which are usually from a week to a year, and long-term forecasts which are longer than a year. Based on the various types of studies presented in these papers, the load forecasting techniques may be presented in three major groups: Traditional Forecasting technique, Modified Traditional Technique and Soft Computing Technique.

[1]  R.J. Marks,et al.  Potential of artificial neural networks in power system operation , 1990, IEEE International Symposium on Circuits and Systems.

[2]  A. D. Kulkarni,et al.  A neuro-expert system for planning and load forecasting of distribution systems , 1999 .

[3]  R. E. Brown,et al.  Long range spatial load forecasting using non-uniform areas , 1999, 1999 IEEE Transmission and Distribution Conference (Cat. No. 99CH36333).

[4]  J.R. McDonald,et al.  A specification of neural network applications in the load forecasting problem , 1992, [Proceedings 1992] The First IEEE Conference on Control Applications.

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

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

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

[8]  Dong Gyu Lee,et al.  Genetic programming model for long-term forecasting of electric power demand , 1997 .

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

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

[11]  Dong-Xiao Niu,et al.  Support Vector Machine Model in Electricity Load Forecasting , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[12]  Yi Xiong Jin.  Meteorological Factors Considered Load Decoupling Forecasting Techniques , 2011 .

[13]  H. Willis,et al.  Comparison Tests of Fourteen Distribution load Forecasting Methods , 1984, IEEE Transactions on Power Apparatus and Systems.

[14]  Craig Stuart Carlson.  Fuzzy logic load forecasting with genetic algorithm parameter adjustment , 2012 .

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

[16]  P. Schuster,et al.  Effects of Finite Population Size and Other Stochastic Phenomena in Molecular Evolution , 1985 .

[17]  Wang Peng,et al.  Input dimension reduction for load forecasting based on support vector machines , 2004, 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings.

[18]  G. Ramakrishna,et al.  Results of Egyptian unified grid hourly load forecasting using an artificial neural network with expert system interface , 1996 .

[19]  Qia Ding,et al.  Long-Term Load Forecast Using Decision Tree Method , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[20]  Q. Henry Wu,et al.  Electric Load Forecasting Based on Locally Weighted Support Vector Regression , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[21]  L. Mili,et al.  Electric Load Forecasting Based on Statistical Robust Methods , 2011, IEEE Transactions on Power Systems.

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

[23]  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.

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

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

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

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

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

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

[30]  Feng-Feng Zhu,et al.  Short-Term Load Forecasting Based on Fuzzy C-Mean Clustering and Weighted Support Vector Machines , 2007, Third International Conference on Natural Computation (ICNC 2007).

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

[32]  G. T. Heinemann,et al.  The Relationship Between Summer Weather and Summer Loads - A Regression Analysis , 1966 .

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

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

[35]  S.R. Abbas,et al.  Electric Load Forecasting Using Support Vector Machines Optimized by Genetic Algorithm , 2006, 2006 IEEE International Multitopic Conference.

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

[37]  Chih-Chou Chiu,et al.  Combining a neural network and a rule-based expert system for short-term load forecasting , 1997 .

[38]  Ming Lu,et al.  Proceedings of the Third International Conference on Machine Learning and Cybernetics , 2004 .

[39]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

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

[41]  Francis Eng Hock Tay,et al.  Modified support vector machines in financial time series forecasting , 2002, Neurocomputing.

[42]  Hong-Tzer Yang,et al.  A new short-term load forecasting approach using self-organizing fuzzy ARMAX models , 1998 .

[43]  Ming-Wei Chang,et al.  Load forecasting using support vector Machines: a study on EUNITE competition 2001 , 2004, IEEE Transactions on Power Systems.

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

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

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

[47]  Robert J. Marks,et al.  Electric load forecasting using an artificial neural network , 1991 .

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

[49]  M. G. Unde,et al.  SHORT-TERM LOAD FORECASTING USING ANN TECHNIQUE , 2012 .

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

[51]  Magdi S. Mahmoud,et al.  Neuro-short-term load forecast of the power system in Kuwait , 1997 .

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

[53]  Hiroyuki Mori,et al.  A preconditioned fast decoupled power flow method for contingency screening , 1995 .

[54]  G. Gross,et al.  Short-term load forecasting , 1987, Proceedings of the IEEE.

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

[56]  J. C. Hwang,et al.  The application of artificial neural networks to substation load forecasting , 1996 .

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

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

[59]  Rajarshi Das,et al.  A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization , 1989, ICGA.

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

[61]  Azzam-ul Asar,et al.  A specification of neural network applications in the load forecasting problem , 1994, IEEE Trans. Control. Syst. Technol..

[62]  Robert E. Smith,et al.  A genetic algorithm based approach to thermal unit commitment of electric power systems , 1995 .

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

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

[65]  Ming-Wei Chang,et al.  Load Forecasting Using Support Vector Machines: A Study on EUNITE Competition 2001 , 2004, IEEE Transactions on Power Systems.

[66]  E. H. Barakat,et al.  New model for peak demand forecasting applied to highly complex load characteristics of a fast developing area , 1992 .

[67]  En Sup Yoon,et al.  Weighted support vector machine for quality estimation in the polymerization process , 2005 .

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

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

[70]  H. L. Willis,et al.  Forecasting electric demand of distribution system planning in rural and sparsely populated regions , 1995 .

[71]  Pan Lu,et al.  Electricity Load Forecasting Based on Adaptive Quantum-Behaved Particle Swarm Optimization and Support Vector Machines on Global Level , 2008, 2008 International Symposium on Computational Intelligence and Design.

[72]  Thong Ngee Goh,et al.  Forecasting of electricity consumption: a comparison between an econometric model and a neural network model , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

[73]  John J. Grefenstette,et al.  Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

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

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

[76]  Kwang-Ho Kim,et al.  Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert systems , 1995 .

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

[78]  S. Sachdeva,et al.  Load Forecasting using Fuzzy Methods , 2008, 2008 Joint International Conference on Power System Technology and IEEE Power India Conference.

[79]  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.

[80]  Yoh-Han Pao,et al.  Unsupervised/supervised learning concept for 24-hour load forecasting , 1993 .

[81]  Hesham K. Alfares,et al.  Electric load forecasting: Literature survey and classification of methods , 2002, Int. J. Syst. Sci..

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

[83]  John R. Williams,et al.  Towards Accurate Electricity Load Forecasting in Smart Grids , 2012, DBKDA 2012.

[84]  Tharam S. Dillon,et al.  Short term load forecasting using an adaptive neural network , 1991 .

[85]  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).

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