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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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/ |
work_keys_str_mv |
AT ilyoungjoo distributedoptimizationframeworkforenergymanagementofmultiplesmarthomeswithdistributedenergyresources AT daehyunchoi distributedoptimizationframeworkforenergymanagementofmultiplesmarthomeswithdistributedenergyresources |
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1724195122823823360 |