User-expected price-based demand response algorithm for a home-to-grid system
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Li, Xiao Hui | - |
dc.contributor.author | Hong, Seung Ho | - |
dc.date.accessioned | 2021-06-23T00:22:25Z | - |
dc.date.available | 2021-06-23T00:22:25Z | - |
dc.date.issued | 2014-01 | - |
dc.identifier.issn | 0360-5442 | - |
dc.identifier.issn | 1873-6785 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/24102 | - |
dc.description.abstract | Demand response algorithms can cut peak energy use, driving energy conservation and enabling renewable energy sources, as well as reducing greenhouse-gas emissions. The use of these technologies is becoming increasingly popular, especially in smart-grid scenarios. We describe a home-to-grid demand response algorithm, which introduces a UEP ("user-expected price") as an indicator of differential pricing in dynamic domestic electricity tariffs, and exploits the modern smart-grid infrastructure to respond to these dynamic pricing structures. By comparing the UEP with real-time utility price data, the algorithm can discriminate high-price hours and low-price hours, and automatically schedule the operation of home appliances, as well as control an energy-storage system to store surplus energy during low-price hours for consumption during high-price hours. The algorithm uses an exponential smoothing model to predict the required energy of appliances, and uses Bayes' theorem to calculate the probability that appliances will demand power at a given time based on historic energy-usage data. Simulation results using pricing structures from the Ameren Illinois power company show that the proposed algorithm can significantly reduce or even eliminate peak-hour energy consumption, leading to a reduction in the overall domestic energy costs of up to 39%. (C) 2013 Elsevier Ltd. All rights reserved. | - |
dc.format.extent | 13 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Pergamon Press Ltd. | - |
dc.title | User-expected price-based demand response algorithm for a home-to-grid system | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1016/j.energy.2013.11.049 | - |
dc.identifier.scopusid | 2-s2.0-84891487544 | - |
dc.identifier.wosid | 000330814700039 | - |
dc.identifier.bibliographicCitation | Energy, v.64, pp 437 - 449 | - |
dc.citation.title | Energy | - |
dc.citation.volume | 64 | - |
dc.citation.startPage | 437 | - |
dc.citation.endPage | 449 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Thermodynamics | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Thermodynamics | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.subject.keywordPlus | SMART GRIDS | - |
dc.subject.keywordPlus | SIDE MANAGEMENT | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | Demand response | - |
dc.subject.keywordAuthor | Home-to-grid | - |
dc.subject.keywordAuthor | Smart grid | - |
dc.subject.keywordAuthor | User expected price | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0360544213010190?via%3Dihub | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.