Event-Triggered-Based Distributed Cooperative Energy Management for Multienergy Systems

This paper investigates the issues of day-ahead and real-time cooperative energy management for multienergy systems formed by many energy bodies. To address these issues, we propose an event-triggered-based distributed algorithm with some desirable features, namely, distributed execution, asynchrono...

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Veröffentlicht in:IEEE transactions on industrial informatics Jg. 15; H. 4; S. 2008 - 2022
Hauptverfasser: Li, Yushuai, Zhang, Huaguang, Liang, Xiaodong, Huang, Bonan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.04.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Cogeneration
Communication
Communications systems
Computer simulation
Distributed algorithm
Distributed algorithms
energy hub
Energy management
event-triggered
Mathematical analysis
multienergy system
Optimization
Real time
Real-time systems
Resistance heating
Solar heating
System reliability
Variations
Water heating
ISSN:1551-3203, 1941-0050
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Zusammenfassung:This paper investigates the issues of day-ahead and real-time cooperative energy management for multienergy systems formed by many energy bodies. To address these issues, we propose an event-triggered-based distributed algorithm with some desirable features, namely, distributed execution, asynchronous communication, and independent calculation. First, the energy body, seen as both energy supplier and customer, is introduced for system model development. On this basis, energy bodies cooperate with each other to achieve the objective of maximizing the day-ahead social welfare and smoothing out the real-time loads variations as well as renewable resource fluctuations with the consideration of different timescale characteristics between electricity and heat power. To this end, the day-ahead and real-time energy management models are established and formulated as a class of distributed coupled optimization problem by felicitously converting some system coordinates. Such problems can be effectively solved by implementing the proposed algorithm. With the effort, each energy body can determine its owing optimal operations through only local communication and computation, resulting in enhanced system reliability, scalability, and privacy. Meanwhile, the designed communication strategy is event-triggered, which can dramatically reduce the communication among energy bodies. Simulations are provided to illustrate the effectiveness of the proposed models and algorithm.
Bibliographie:ObjectType-Article-1
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2018.2862436