Day similarity metric model for short-term load forecasting supported by PSO and artificial neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-021-01286-6.pdf
Reference40 articles.
1. Hong T (2010) Short term electric load forecasting (doctoral dissertation). North Carolina State University, Raleigh, North Carolina
2. Selakov A, Cvijetinović D, Milović L, Mellon S, Bekut D (2014) Hybrid PSO–SVM method for short-term load forecasting during periods with significant temperature variations in city of burbank. Appl Soft Comput 16:80–88
3. Chen Y, Luh PB, Guan C, Zhao Y, Michel LD, Coolbeth MA, Friedland PB, Rourke SJ (2010) Short-term load forecasting: similar day-based wavelet neural networks. IEEE Trans Power Syst 25(1):322–330
4. Mandal P, Senjyu T, Urasaki N, Funabashi T (2006) A neural network based several-hour-ahead electric load forecasting using similar days approach. Electr Power Energy Syst 28:367–373
5. Mandal P, Senjyu T, Funabashi T (2006) Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market. Energy Convers Manage 47(15–16):2128–2142
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