Customized decentralized autonomous organization based optimal energy management for smart buildings
In recent years, the unprecedented rising urbanization level and proliferation of distributed energy sources (DES) are motivating the transition of smart building from consumer to prosumer. In the context of mitigating upstream emission via reducing reliance on utility grids, the key challenge becom...
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| Published in: | Applied energy Vol. 376; p. 124223 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
15.12.2024
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| Subjects: | |
| ISSN: | 0306-2619 |
| Online Access: | Get full text |
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| Summary: | In recent years, the unprecedented rising urbanization level and proliferation of distributed energy sources (DES) are motivating the transition of smart building from consumer to prosumer. In the context of mitigating upstream emission via reducing reliance on utility grids, the key challenge becomes realizing autonomous and economically optimal energy management within smart buildings. This paper innovatively proposes a Decentralized Autonomous Organization (DAO)-based energy management framework for smart buildings, where the mechanism of day-ahead scheduling DAO considering peer-to-peer (P2P) energy sharing is specifically investigated. Besides, a sequential preference satisfaction mechanism is designed to customize participants’ special demands, thereby achieving effective energy matching. Considering potential communication failures between buildings in practical operations, this study develops a communication failure robust distributed algorithm to minimize operational costs and safeguard building’s privacy. Extensive numerical studies for highly DES penetrated smart buildings successfully offers an operation cost reduction of 33.7% when considering preference satisfaction and P2P energy sharing in the day-ahead scheduling problem. Simulation results also demonstrates that the algorithm in this work excels in resisting potential communication failure during operation.
•A DAO-based energy management framework is proposed for smart buildings.•Peer-to-peer energy sharing is incorporated in the day-ahead scheduling problem.•A preference satisfaction mechanism is modeled to customize participant’s demand.•A communication failure robust distributed algorithm is developed. |
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| ISSN: | 0306-2619 |
| DOI: | 10.1016/j.apenergy.2024.124223 |