Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources

This paper proposes a distributed optimization algorithm for scheduling the energy consumption of multiple smart homes with distributed energy resources. In the proposed approach, the centralized optimization problem for home energy management is decomposed into a two-level optimization problem, cor...

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Main Authors: Il-Young Joo, Dae-Hyun Choi
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8000317/
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spelling doaj-b122c8f0adc444c686d6fb21100c53f92021-03-29T20:11:44ZengIEEEIEEE Access2169-35362017-01-015155511556010.1109/ACCESS.2017.27349118000317Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy ResourcesIl-Young Joo0Dae-Hyun Choi1https://orcid.org/0000-0002-9248-9522School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South KoreaSchool of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South KoreaThis paper proposes a distributed optimization algorithm for scheduling the energy consumption of multiple smart homes with distributed energy resources. In the proposed approach, the centralized optimization problem for home energy management is decomposed into a two-level optimization problem, corresponding to the local home energy management system (LHEMS) at the first level and the global home energy management system (GHEMS) at the second level. The controllable household appliances (e.g., air conditioner and washing machine) are scheduled in the LHEMS within the consumer's preferred appliance scheduling and comfort level, while the energy storage system and power trading between households are scheduled in the GHEMS. In the simulation study, the proposed distributed algorithm shows almost equivalent performance to the centralized algorithm in terms of the electricity cost and the consumer's comfort level. The impact of different network topologies on the proposed algorithm is also analyzed, and the result provides insight into the selection of the optimal network configuration in view of the consumer's electricity cost saving.https://ieeexplore.ieee.org/document/8000317/Home energy management system (HEMS)energy consumption schedulingdemand side managementdistributed algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Il-Young Joo
Dae-Hyun Choi
spellingShingle Il-Young Joo
Dae-Hyun Choi
Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources
IEEE Access
Home energy management system (HEMS)
energy consumption scheduling
demand side management
distributed algorithm
author_facet Il-Young Joo
Dae-Hyun Choi
author_sort Il-Young Joo
title Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources
title_short Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources
title_full Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources
title_fullStr Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources
title_full_unstemmed Distributed Optimization Framework for Energy Management of Multiple Smart Homes With Distributed Energy Resources
title_sort distributed optimization framework for energy management of multiple smart homes with distributed energy resources
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2017-01-01
description This paper proposes a distributed optimization algorithm for scheduling the energy consumption of multiple smart homes with distributed energy resources. In the proposed approach, the centralized optimization problem for home energy management is decomposed into a two-level optimization problem, corresponding to the local home energy management system (LHEMS) at the first level and the global home energy management system (GHEMS) at the second level. The controllable household appliances (e.g., air conditioner and washing machine) are scheduled in the LHEMS within the consumer's preferred appliance scheduling and comfort level, while the energy storage system and power trading between households are scheduled in the GHEMS. In the simulation study, the proposed distributed algorithm shows almost equivalent performance to the centralized algorithm in terms of the electricity cost and the consumer's comfort level. The impact of different network topologies on the proposed algorithm is also analyzed, and the result provides insight into the selection of the optimal network configuration in view of the consumer's electricity cost saving.
topic Home energy management system (HEMS)
energy consumption scheduling
demand side management
distributed algorithm
url https://ieeexplore.ieee.org/document/8000317/
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AT daehyunchoi distributedoptimizationframeworkforenergymanagementofmultiplesmarthomeswithdistributedenergyresources
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