Artificial neural networks for short-term energy forecasting: Accuracy and economic value

Neurocomputing

Volumn 23, Issue 1-3, 1998, Pages 71-84

  Hobbs, Benjamin F ^a   Helman, Udi ^a   Jitprapaikulsarn, Suradet ^b   Sreenivas Konda, ^b   Maratukulam, Dominic ^c  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b Case Western Reserve University   (United States)

^c ELECTRIC POWER RESEARCH INSTITUTE   (United States)

Author keywords

Demand forecasting; Economics; Neural networks

Indexed keywords

COSTS; ECONOMICS; ELECTRIC LOAD FORECASTING; ELECTRIC UTILITIES; ERRORS; MATHEMATICAL MODELS;

ERROR REDUCTION; MEAN ABSOLUTE PERCENTAGE ERROR;

NEURAL NETWORKS;

ACCURACY; ANALYTIC METHOD; ARTIFICIAL NEURAL NETWORK; ECONOMIC ASPECT; ELECTRICITY; FORECASTING; PRIORITY JOURNAL; REVIEW;

EID: 0032494994     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(98)00072-1     Document Type: Article

References (22)

1. Baldick R. A generalized unit commitment model. IEEE Trans. Power Systems. 10(1):1995;465-475.
2. Bard J.F. Short term scheduling of thermal-electric generation using Lagrangian relaxation. Oper. Res. 36(5):1988;756-766.
3. Brown R.H. Development of artificial neural networking models to predict daily gas consumption. Am. Gas Assoc. Forecasting Rev. 5:1996;1-22.
4. Campo R., Ruiz P. Adaptive weather-sensitive short term load forecast. IEEE Trans. Power Systems. 2(3):1987;592-600.
5. Comrie A.C. Comparing neural networks and regression models for ozone forecasting. J. Air Waste Management Assoc. 47(6):1997;653-663.
6. Hagan M.T., Behr S.M. The time series approach to short-term load forecasting. IEEE Trans. Power Systems. 2(3):1987;785-791.
7. Hill T., O'Connor M., Remus W. Neural network models for time series forecasts. Management Sci. 42(7):1996;1082-1092.
8. B.F. Hobbs, S. Jitprapaikulsarn, S. Konda, V. Chankong, K.A. Loparo, D.J. Maratukulam, Analysis of the value for unit commitment of improved load forecasts, IEEE Trans. Power Systems (1998) accepted.
9. Hubele N.F., Cheng C.-S. Identification of seasonal short-term forecasting models using statistical decision functions. IEEE Trans. Power Systems. 5(1):1990;40-45.
10. A. Khotanzad, A. Abaye, Adaptive Neural Network Daily Gas Sendout Forecaster (ANNDGSF), Presentation, Pattern Recognition Technologies, Inc., Dallas, TX, 10 July, 1996.
11. A. Khotanzad, R. Afkhami-Rohani, D. Maratukulam, ANNSTLF - artificial neural network short-term load forecaster - generation three, IEEE Trans. Power Systems (1998) in press.
12. Khotanzad A., Hwang R.-C., Abaye A., Maratukulam D. An adaptive modular artificial neural network hourly load forecaster and its implementation at electric utilities. IEEE Trans. Power Systems. 10(3):1995;1716-1722.
13. Liu K., Subbarayan S., Shoults R.R., Manry M.T., Kwan C., Lewis F.L., Naccarino J. Comparison of short-term load forecasting techniques. IEEE Trans. Power Systems. 11(2):1996;877-882.
14. Papalexopoulos A.D., Hao S., Peng T.-M. An implementation of a neural network based load forecasting model for the EMS. IEEE Trans. Power Systems. 9(4):1994;1956-1962.
15. Papalexopoulos A.D., Hesterberg T.C. A regression-based approach to short-term system load forecasting. IEEE Trans. Power Systems. 5(4):1990;1535-1547.
16. Park D.C., El-Sharkawi M.A., Marks II R.J. Electric load forecasting using an artificial neural network. IEEE Trans. Power Systems. 6(2):1991;442-449.
17. Peng T.M., Hubele N.F., Karady G.G. An adaptive neural network approach to one-week ahead load forecasting. IEEE Trans. Power Systems. 8(3):1993;1195-1203.
18. Rahman S., Bhatnagar R. An expert system based algorithm for short-term load forecast. IEEE Trans. Power Systems. 3(2):1988;392-399.
19. Ramanathan R., Engle R., Granger C.W.J., Vahid-Araghi F., Brace C. Short run forecasts of electricity loads and peaks. Int. J. Forecasting. 13:1997;161-174.
20. Ranaweera D.K., Karady G.G., Farmer R.G. Economic impact analysis of load forecasting. IEEE Trans. Power Systems. 12(3):1997;1388-1392.
21. Rice J.A. Mathematical Statistics and Data Analysis. 1988;Wadsworth, Pacific Grove, CA.
22. Sobajic D., Pao Y-H. Artificial neural net based dynamic security assessment for electric power systems. IEEE Trans. Power Systems. 4(1):1989;220-227.