Multivariate empirical mode decomposition based hybrid model for day-ahead peak load forecasting

Accurate day-ahead peak load forecasting is crucial not only for power dispatching but also has a great interest to investors and energy policy maker as well as government. Literature reveals that 1% error drop of forecast can reduce 10 million pounds operational cost. Thus, this study proposed a no...

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Veröffentlicht in:	Energy (Oxford) 2022-01, Vol.239, p.122245, Article 122245
Hauptverfasser:	Huang, Yanmei, Hasan, Najmul, Deng, Changrui, Bao, Yukun
Format:	Artikel
Sprache:	eng
Schlagworte:	Day-ahead peak load forecasting Decomposition Electricity Energy policy Forecasting Hybrid model Information processing Mathematical models Multivariate analysis Multivariate empirical mode decomposition (MEMD) Particle swarm optimization Particle swarm optimization (PSO) Peak load Prediction models Support vector machines
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