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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Auteurs principaux: Yingying Zheng, Berk Celik, Siddharth Suryanarayanan, Anthony A. Maciejewski, Howard Jay Siegel, Timothy M. Hansen
Format: article
Langue:EN
Publié: Wiley 2021
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Accès en ligne:https://doaj.org/article/8656e677de0846dca5e718bb49d7085f
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