An aggregator‐based resource allocation in the smart grid using an artificial neural network and sliding time window optimization

Abstract The success of an efficient and effective aggregator‐based residential demand response system in the smart grid relies on the day‐ahead customer incentive pricing (CIP) and the load shifting protocols. An artificial neural network model is designed to generate the day‐ahead CIP for the aggr...

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Autores principales: Yingying Zheng, Berk Celik, Siddharth Suryanarayanan, Anthony A. Maciejewski, Howard Jay Siegel, Timothy M. Hansen
Formato: article
Lenguaje:EN
Publicado: Wiley 2021
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Acceso en línea:https://doaj.org/article/8656e677de0846dca5e718bb49d7085f
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