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

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...

Full description

Bibliographic Details
Main Authors: Yingying Zheng, Berk Celik, Siddharth Suryanarayanan, Anthony A. Maciejewski, Howard Jay Siegel, Timothy M. Hansen
Format: Article
Language:English
Published: Wiley 2021-12-01
Series:IET Smart Grid
Subjects:
optimisation
neural nets
smart power grids
power engineering computing
demand side management
pricing
Online Access:https://doi.org/10.1049/stg2.12042

Internet

https://doi.org/10.1049/stg2.12042

Similar Items