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  4. A demand side management with appliance controllability analysis in smart home
 
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A demand side management with appliance controllability analysis in smart home

Journal
Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
Pages
556-561
Date Issued
2020
Author(s)
Hong J.-H
Hong D.-Y
Yao L.-H
LI-CHEN FU  
DOI
10.1109/SGES51519.2020.00104
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102757653&doi=10.1109%2fSGES51519.2020.00104&partnerID=40&md5=47216bd9684deafad06990cd5ef5e34e
https://scholars.lib.ntu.edu.tw/handle/123456789/581409
Abstract
As global energy consumption keeps increasing, the energy efficiency has become an important issue. Demand-side management (DSM) system is a technology that can be used to solve this issue. In many houses, there are some time periods in a day when inhabitants have high electricity demands, and these peaks will cause a burden on the smart grid. In order to solve energy efficiency problem, the demand-side management system can help users to postpone non-immediately needed demands to off-peak hour subject to the mechanism of real-time pricing policy. In addition, with the development of Internet of Things technology, the devices which have internet module can form a home area network, enabling DSM to monitor the entire state of the house and to control appliances. However, due to the uncertainty of user behavior, it is hard to find the good control policy for energy saving, considering that different users may have various habits and the appliance usage tends to be irregular. Therefore, the ability of DSM will be restricted in order to avoid disturbing the user comfort. In the proposed work, a smart home demand-side management system within home area network was implemented, including multiple agents with reinforcement learning for managing different appliances, energy storage system, and renewable energy. The proposed system also keeps the user's comfort based on the activity of user and controllability of appliances. As a result, the simulation studies show that the proposed DSM system can reduce 42.36% peak demand value and achieve 32.79% cost reduction. The cost reduction value can be further increased by 22.41% when the concept of energy self-awareness is combined into demand-side management system. ? 2020 IEEE
Event(s)
2020 International Conference on Smart Grids and Energy Systems, SGES 2020
Subjects
Ambient intelligence; Automation; Behavioral research; Cost reduction; Data storage equipment; Demand side management; Electric energy storage; Electric power transmission networks; Energy efficiency; Energy utilization; Home networks; Multi agent systems; Reinforcement learning; Smart power grids; Controllability analysis; Electricity demands; Energy storage systems; Home area network; Internet of things technologies; Real time pricing; Renewable energies; Simulation studies; Energy management systems
SDGs

[SDGs]SDG7

Other Subjects
Ambient intelligence; Automation; Behavioral research; Cost reduction; Data storage equipment; Demand side management; Electric energy storage; Electric power transmission networks; Energy efficiency; Energy utilization; Home networks; Multi agent systems; Reinforcement learning; Smart power grids; Controllability analysis; Electricity demands; Energy storage systems; Home area network; Internet of things technologies; Real time pricing; Renewable energies; Simulation studies; Energy management systems
Type
conference paper

臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

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