Short-term load forecasting of power systems by gene expression programming

Neural Computing and Applications

Volumn 21, Issue 2, 2012, Pages 377-389

  Hosseini, Seyyed Soheil Sadat ^a   Gandomi, Amir Hossein ^a  

^a TAFRESH UNIVERSITY   (Iran)

Author keywords

Formulation; Gene expression programming; Short term load forecasting

Indexed keywords

ANALYSIS TOOLS; DATA SETS; DEREGULATED POWER SYSTEMS; ELECTRIC POWER INDUSTRIES; ENERGY SYSTEMS; FORMULATION; GENE EXPRESSION PROGRAMMING; LEAST SQUARES REGRESSION ANALYSIS; LOAD FORECASTING; NORTH AMERICAN; PARAMETRIC STUDY; PRACTICING ENGINEERS; PREDICTION ACCURACY; SHORT TERM LOAD FORECASTING; TOTAL LOAD;

ELECTRIC INDUSTRY; ELECTRIC UTILITIES; FORECASTING; GENETIC PROGRAMMING;

ELECTRIC LOAD FORECASTING;

EID: 84857652058     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-010-0444-y     Document Type: Article

References (39)

1. Bunn DW, Farmer ED (1985) Comparative models for electrical load forecasting. Wiley, New York.
2. Fan S, Chen L (2006) Short-term load forecasting based on an adaptive hybrid method. IEEE Trans Power Syst 21: 392-401.
3. Santos PJ, Martins AG, Pires AJ (2007) Designing the input vector to ANN-based models for short-term load forecast in electricity distribution systems. Int J Electr Power Energy Syst 29: 338-347.
4. Amjady N (2006) Day-ahead price forecasting of electricity markets by a new fuzzy neural network. IEEE Trans Power Syst 21: 887-896.
5. Fan S, Chen L (2006) Short-term load forecasting based on an adaptive hybrid method. IEEE Trans Power Syst 21: 392-401.
6. Christiaanse WR (1971) Short term load forecasting using general exponential smoothing. IEEE Trans Power Appar Syst 90: 900-911.
7. Papalexopoulos AD, Hesterberg TC (1989) A regression based approach to short term system load forecasting. In: Proceedings of PICA conference, vol 3, pp 414-423.
8. Meslier F (1978) New advances in short term load forecasting using Box and Jenkins approach. IEEE/PES Winter Meet 78: 51-55.
9. Irisarri GD, Widergren SE, Yehsakul PD (1982) On-line load forecasting for energy control center application. IEEE Trans Power Appar Syst 101: 71-78.
10. Shahidehpour M, Yamin H, Li Z (2002) Market operations in electric power systems. Wiley, New York.
11. Amjady N (2001) Short-term hourly load forecasting using time series modeling with peak load estimation capability. IEEE Trans Power Syst 16: 798-805.
12. Tay FEH, Cao LJ (2002) Support vector machines in financial time series forecasting. Neurocomputing 48: 847-861.
13. Dehdashti AS, Tudor JR, Smith MC (1982) Forecasting of hourly load by pattern recognition-a deterministic approach. IEEE Trans Power Appar Syst 101: 3290-3294.
14. Rahman S, Bhatnagar R (1988) An expert system based algorithm for short term load forecast. IEEE Trans Power Syst 3: 392-399.
15. Rahman S (1993) Generalized knowledge-based short-term load forecasting technique. IEEE Trans Power Syst 8: 508-514.
16. Ho KL, Hsu YY, Chen CF, Lee TE, Liang CC, Lai TS, Chen KK (1990) Short term load forecasting of Taiwan power system using a knowledge-based expert system. IEEE Trans Power Syst 4: 1214-1221.
17. Lambert-Torres G, Traore CO, Lagace PJ, Mukhedkar D (1990) A knowledge engineering tool for load forecasting. IEEE Symp Circuits Syst 4: 144-147.
18. Yang HT, Huang CM (1998) A new short term load forecasting approach using self organizing fuzzy ARMAX models. IEEE Trans Power Syst 13: 217-225.
19. Hippert HS, Pedreira CE, Souza RC (2001) Neural networks for short-term load forecasting: A review and evaluation. IEEE Trans Power Syst 16: 44-55.
20. Ekonomou L (2010) Greek long-term energy consumption prediction using artificial neural networks. Energy 35: 512-517.
21. Srinivasan D, Chang DS, Liew AC (1995) Demand forecasting using fuzzy neural computation, with special emphasis on weekend and public holiday forecasting. IEEE Trans Power Syst 10: 1897-1903.
22. Bakirtzis AG, Theocharis JB, Kiartzis SJ, Satsois KJ (1995) Short term load forecasting using fuzzy neural networks. IEEE Trans Power Syst 10: 1518-1524.
23. Koza JR (1992) Genetic programming, on the programming of computers by means of natural selection. MIT press, Cambridge.
24. Canakci H, Baykasoglu A, Gullu H (2009) Prediction of compressive and tensile strength of Gaziantep basalts via neural networks and gene expression programming. Neural Comput Appl 18: 1031-1041.
25. Gandomi AH, Alavi AH, Sahab MG (2010) New formulation for compressive strength of CFRP confined concrete cylinders using linear genetic programming. Mater Struct 43(7): 963-983.
26. Cabalar AF, Cevik A, Guzelbey IH (2010) Constitutive modeling of Leighton Buzzard Sands using genetic programming. Neural Comput Appl 19(5): 657-665.
27. Cevik A, Cabalar AF (2009) Modelling damping ratio and shear modulus of sand-mica mixtures using genetic programming. Expert Syst Appl 36(4): 7749-7757.
28. Gandomi AH, Alavi AH, Mirzahosseini MR, Moqaddas Nejad F (in press) Nonlinear genetic-based models for prediction of flow number of asphalt mixtures. J Mater Civl Eng ASCE. doi: 10. 1061/(ASCE)MT. 1943-5533. 0000154.
29. Ferreira C (2001) Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst 13: 87-129.
30. Oltean M, Grossan A (2003) Comparison of several linear genetic programming techniques. Adv Complex Sys 14(4): 1-29.
31. Gandomi AH, Alavi AH, Sadat Hosseini SS (2008) A discussion on genetic programming for retrieving missing information in wave records along the west coast of India. Appl Ocean Res 30: 338-339.
32. Ferreira C (2006) Gene expression programming: mathematical modeling by an artificial intelligence. Springer, Germany.
33. GEPSOFT (2006) GeneXproTools. Version 4. 0. Available online: http://www. gepsoft. com.
34. Ryan TP (1997) Modern regression methods. Wiley, New York.
35. Maravall A, Gomez V (2004) EViews software, Ver. 5. Quantitative Micro Software LLC, Irvine.
36. Perlovsky LI (2001) Neural networks and intellect. Oxford University Press, New York.
37. Specht DF (1991) A general regression neural network. IEEE Trans Neural Net 2(6): 568-576.
38. MathWorks (2007) MATLAB the language of technical computing, version 7. 4, Natick.
39. Rocha Reis AJ, Alves da Silva AP (2005) Feature extraction via multiresolution analysis for short-term load forecasting. IEEE Trans Power Syst 20(1): 189-198.