참고문헌
- A. J. Al-Shareef, E. A. Mohamed, and E. Al-Judaibi, "Next 24-hours load forecasting using artificial neural network for the western area of Saudi Arabia," Journal of King Abdulaziz University: Engineering Science, vol. 19, no. 2, pp. 25-40, 2008. http://dx.doi.org/10.4197/eng.19-2.2
- B. H. Wang, "Short-term electrical load forecasting using neuro-fuzzy model with error compensation," International Journal of Fuzzy Logic and Intelligent Systems, vol. 9, no. 4, pp. 327-332, Dec. 2009. https://doi.org/10.5391/IJFIS.2009.9.4.327
- C. Guan, P. B. Luh, M. A. Coolbeth, Y. Zhao, L. D. Michel, Y. Chen, C. J. Manville, P. B. Friedland, and S. J. Rourke, "Very short-term load forecasting: multilevel wavelet neural networks with data pre-filtering," in Proceedings of 2009 IEEE Power & Energy Society General Meeting, Calgary, 2009, pp. 1-8. http://dx.doi.org/10.1109/PES.2009.5275296
- C. L. L. Hor, S. J. Watson, and S. Majithia, "Daily load forecasting and maximum demand estimation using ARIMA and GARCH," in Proceedings of 2006 International Conference on Probabilistic Methods Applied to Power Systems, Stockholm, 2006, pp. 1-6. http://dx.doi.org/10.1109/PMAPS.2006.360237
- C. Ying, P. B. Luh, C. Guan, Y. Zhao, L. D. Michel, M. A. Coolbeth, P. B. Friedland, and S. J Rourke, "Short-term load forecasting: similar day-based wavelet neural networks," IEEE Transactions on Power Systems, vol. 25, no. 1, pp. 322-330, Feb. 2010. http://dx.doi.org/10.1109/TPWRS.2009.2030426
- D. K. Ranaweera, N. F. Hubele, and A. D. Papalexopoulos, "Application of radial basis function neural network model for short-term load forecasting," IEE Proceedings - Generation, Transmission and Distribution, vol. 142, no. 1, pp. 45-50, Jan. 1995. http://dx.doi.org/10.1049/ip-gtd:19951602
- L. M. Saini, "Peak load forecasting using Bayesian regularization, resilient and adaptive backpropagation learning based artificial neural networks," Electric Power Systems Research, vol. 78, no. 7, pp. 1302-1310, Jul. 2008. http://dx.doi.org/10.1016/j.epsr.2007.11.003
- N. Lu and J. Z. Zhou, "Particle swarm optimization-based RBF neural network load forecasting model," in Proceedings of 2009 Asia-Pacific Power and Energy Engineering Conference, Wuhan, 2009, pp. 1-4. http://dx.doi.org/10.1109/APPEEC.2009.4918588
- M. Ghomi, M. H. Goodarzi, and M. Goodarzi, "Peak load forecasting of electric utilities for west province of IRAN by using neural network without weather information," in Proceedings of 2010 12th International Conference on Computer Modelling and Simulation, Cambridge, 2010, pp. 28-32. http://dx.doi.org/10.1109/UKSIM.2010.14
- M. Rahimbasiri, M. B. Menhaj, and A. R. Kian, "Modeling and forecasting short-term electricity load: a comparison of methods with an application to west Azarbaijan data," in Proceedings of 24nd International Power System Conference, Tehran, 2009, pp. 1-11.
- R. E. Abdel-Aal, "Short-term hourly load forecasting using abductive networks," IEEE Transactions on Power Systems, vol. 19, no. 1, pp. 164-173, Feb. 2004. http://dx.doi.org/10.1109/TPWRS.2003.820695
- A. J. R. Reis and A. P. Alves da Silva, "Feature extraction via multiresolution analysis for shortterm load forecasting," IEEE Transactions on Power Systems, vol. 20, no. 1, pp. 189-198, Feb. 2005. http://dx.doi.org/10.1109/TPWRS.2004.840380
- S. Fan and L. N. N. Chen, "Short-term load forecasting based on an adaptive hybrid method," IEEE Transactions on Power Systems, vol. 23, no. 1, pp. 392-401, Feb. 2006. http://dx.doi.org/10.1109/TPWRS.2005.860944
- S. Fan, K. Methaprayoon, and W. J. J. Lee, "Multiregion load forecasting for system with large geographical area," IEEE Transactions on Industry Applications, vol. 45, no. 4, pp. 1452-1459, Jul-Aug. 2009. http://dx.doi.org/10.1109/TIA.2009.2023569
- S. Tian and L. Tuanjie, "Short-term load forecasting based on RBFNN and QPSO," in Proceedings of 2009 Asia-Pacific Power and Energy Engineering Conference, Wuhan, 2009, pp. 1-4. http://dx.doi.org/10.1109/APPEEC.2009.4918746
- T. Rashid and T. Kechadi, "A practical approach for electricity load forecasting," in Proceedings ofWorld Academy of Science, Engineering and Technology, Rome, 2005, pp. 201-205.
- T. Senjyu, P. Mandal, K. K. Uezato, and T. Funabashi, "Next day load curve forecasting using hybrid correction method," IEEE Transactions on Power Systems, vol. 20, no. 1, pp. 102-109, Feb. 2005. http://dx.doi.org/10.1109/TPWRS.2004.831256
- T. Senjyu, P. Mandal, K. K. Uezato, and T. Funabashi, "Next day load curve forecasting using recurrent neural network structure," IEE Proceedings - Generation, Transmission and Distribution, vol. 151, no. 3, pp. 388-394, May. 2004. http://dx.doi.org/10.1049/ip-gtd:20040356
- Y. Lu, X. Lin, and W. Qi, "The method of short-term load forecasting based on the RBF neural network," in Proceedings of Cired 2005: 18th International Conference and Exhibition on Electricity Distribution, Turin, 2005, pp. 1-4.
- Y. Zhao, P. B. Luh, C. Bomgardner, and G. H. Beerel, "Short-term load forecasting: multi-level wavelet neural networks with holiday correction," in Proceedings of 2009 IEEE Power & Energy Society General Meeting, Calgary, 2009, pp. 1-7. http://dx.doi.org/10.1109/PES.2009.5275304
- Z. Y. Zia and L. Tian, "Short-term power load forecasting based on fuzzy-RBF neural network," in Proceedings of International Conference on Risk Management & Engineering Management, Beijing, 2008, pp. 349-352. http://dx.doi.org/10.1109/ICRMEM.2008.41
- Z. Yun, Z. Quan, S. Caixin, L. Shaolan, L. Yuming, and S. Yang, "RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment," IEEE Transactions on Power Systems, vol. 23, no. 3, pp. 853-858, Aug. 2008. http://dx.doi.org/10.1109/TPWRS.2008.922249
- R. Storn and K. Price, "Differential evolution, a simple and efficient heuristic strategy for global optimization over continuous spaces," Journal of Global Optimization, vol. 11, no. 4, pp. 341-359, Dec. 1997. http://dx.doi.org/10.1023/A:1008202821328
피인용 문헌
- Improving economic values of day-ahead load forecasts to real-time power system operations vol.11, pp.17, 2017, https://doi.org/10.1049/iet-gtd.2017.0517