Probabilistic electricity price forecasting by improved clonal selection algorithm and wavelet preprocessing

Neural Computing and Applications

Volumn 28, Issue 12, 2017, Pages 3889-3901

  Rafiei, Mehdi ^a   Niknam, Taher ^a   Khooban, Mohammad Hassan ^a  

^a SHIRAZ UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Autocorrelation function; Improved clonal selection algorithm; Prediction intervals; Probabilistic forecasting; Wavelet preprocess

Indexed keywords

ALGORITHMS; AUTOCORRELATION; COMMERCE; COSTS; DECISION MAKING; FORECASTING; LEARNING SYSTEMS;

AUTOCORRELATION FUNCTIONS; CLONAL SELECTION ALGORITHMS; PREDICTION INTERVAL; PREPROCESS; PROBABILISTIC FORECASTING;

POWER MARKETS;

EID: 84962258029     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-016-2279-7     Document Type: Article

References (28)

1. Contreras J, Espinola R, Nogales FJ, Conejo AJ (2003) ARIMA models to predict next-day electricity prices. IEEE Trans Power Syst 18:1014–1020
2. Garcia RC, Contreras J, Van Akkeren M, Garcia JBC (2005) A GARCH forecasting model to predict day-ahead electricity prices. IEEE Trans Power Syst 20:867–874
3. Conejo AJ, Plazas MA, Espinola R, Molina AB (2005) Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE Trans Power Syst 20:1035–1042
4. Xu Z, Dong Z, Liu W (1996) Neural network models for electricity market forecasting. In: Proceedings of 4th Australian workshop on signal processing and its applications, Australia
5. Darudi A, Bashari M, Javidi MH (2015) Electricity price forecasting using a new data fusion algorithm. Gener Transm Distrib IET 9:1382–1390
6. Zhou M, Yan Z, Ni Y, Li G, Nie Y (2006) Electricity price forecasting with confidence-interval estimation through an extended ARIMA approach. IEE Proc Gener Transm Distrib 153:187–195
7. Zhang L, Luh PB (2005) Neural network-based market clearing price prediction and confidence interval estimation with an improved extended Kalman filter method. IEEE Trans Power Syst 20:59–66
8. Zhao JH, Dong ZY, Xu Z, Wong KP (2008) A statistical approach for interval forecasting of the electricity price. IEEE Trans Power Syst 23:267–276
9. Wan C, Xu Z, Wang Y, Dong ZY, Wong KP (2014) A hybrid approach for probabilistic forecasting of electricity price. IEEE Trans Smart Grid 5:463–470
10. Wu H, Chan S, Tsui K, Hou Y (2013) A new recursive dynamic factor analysis for point and interval forecast of electricity price. IEEE Trans Power Syst 28:2352–2365
11. Kou P, Liang D, Gao L, Lou J (2015) Probabilistic electricity price forecasting with variational heteroscedastic Gaussian process and active learning. Energy Convers Manag 89:298–308
12. Bello A, Reneses J, Muñoz A, Delgadillo A (2015) Probabilistic forecasting of hourly electricity prices in the medium-term using spatial interpolation techniques. Int J Forecast
13. Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2:359–366
14. Amjady N (2006) Day-ahead price forecasting of electricity markets by a new fuzzy neural network. IEEE Trans Power Syst 21:887–896
15. De Castro LN, Von Zuben FJ (2002) Learning and optimization using the clonal selection principle. IEEE Trans Evol Comput 6:239–251
16. Liao G-C (2006) Application of an immune algorithm to the short-term unit commitment problem in power system operation. IEE Proc Gener Transm Distrib 153:309–320
17. Chitsaz H, Amjady N, Zareipour H (2015) Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm. Energy Convers Manag 89:588–598
18. Graps A (1995) An introduction to wavelets. IEEE Comput Sci Eng 2:50–61
19. Boix M, Canto B (2010) Wavelet transform application to the compression of images. Math Comput Model 52:1265–1270
20. Reddy MJ, Mohanta DK (2007) A wavelet-fuzzy combined approach for classification and location of transmission line faults. Int J Electr Power Energy Syst 29:669–678
21. Maheswaran R, Khosa R (2012) Comparative study of different wavelets for hydrologic forecasting. Comput Geosci 46:284–295
22. Huang G-B, Chen L, Siew C-K (2006) Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Trans Neural Netw 17:879–892
23. Rao CR, Mitra SK (1971) Generalized inverse of matrices and its applications, vol 7. Wiley, New York
24. Hamilton JD (1994) Time series analysis, vol 2. Princeton University Press, Princeton
25. Efron B (1979) Bootstrap methods: another look at the jackknife. The Annals of Statistics 1–26
26. Efron B, Tibshirani RJ (1979) An introduction to the bootstrap. CRC Press, Boca Raton
27. Website of Ontario electricity market http://www.ieso.ca
28. Website of Australian electricity market. http://www.aemo.com.au