M.E. Cruz Victorio
Distributed Real-Time Power Management in Microgrids using Multi-agent Control with Provisions of Fault Tolerance
Cruz Victorio, M.E.; Kazemtabrizi, B.; Shahbazi, M.
Authors
Dr Behzad Kazemtabrizi behzad.kazemtabrizi@durham.ac.uk
Associate Professor
Dr Mahmoud Shahbazi mahmoud.shahbazi@durham.ac.uk
Associate Professor
Abstract
This paper presents a distributed real-time control scheme based on multi-agent systems for cost optimisation of a micro-grid using real-time dynamic price estimation. The real-time prices are forecast using realistic UK energy price data via a Markov Chain Monte Carlo algorithm. A backup mechanism for main containers of the agent platform is implemented to improve fault tolerance of the control system, addressing the single point of failure problem at the hardware and software levels. The Multi-Agent system developed in JAVA and run with Raspberry Pi controls a simulated microgrid in an OPAL-RT real-time simulator to test the accuracy of the estimation method, the capacity of the control to realise power management at minimal supply cost, and uninterrupted operation in case of container faults.
Citation
Cruz Victorio, M., Kazemtabrizi, B., & Shahbazi, M. (2020, June). Distributed Real-Time Power Management in Microgrids using Multi-agent Control with Provisions of Fault Tolerance. Presented at 29th IEEE International Symposium on Industrial Electronics, Delft, Netherlands
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 29th IEEE International Symposium on Industrial Electronics |
Start Date | Jun 17, 2020 |
End Date | Jun 19, 2020 |
Acceptance Date | Apr 27, 2020 |
Online Publication Date | Jul 30, 2020 |
Publication Date | 2020 |
Deposit Date | May 26, 2020 |
Publicly Available Date | Nov 27, 2020 |
Pages | 108-113 |
Series ISSN | 2163-5145 |
Book Title | 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) : proceedings. |
DOI | https://doi.org/10.1109/isie45063.2020.9152548 |
Public URL | https://durham-repository.worktribe.com/output/1140570 |
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