Hybrid multi‐agent‐based adaptive control scheme for AC microgrids with increased fault‐tolerance needs. Issue 1 (11th December 2019)

• Record Type: Journal Article
• Authors: Bintoudi, Angelina D.; Zyglakis, Lampros; Tsolakis, Apostolos C.; Ioannidis, Dimosthenis; Hadjidemetriou, Lenos; Zacharia, Lazaros; Al‐Mutlaq, Nisrein; Al‐Hashem, Mohammad; Al‐Agtash, Salem; Kyriakides, Elias; Demoulias, Charis; Tzovaras, Dimitrios
• Is Part Of: IET renewable power generation. Volume 14:Issue 1(2020)
• Page Start: 13
• Page End: 26
• Publication Date: 2019-12-11
• Subjects: power generation control -- fault tolerance -- distributed power generation -- adaptive control -- multi‐agent systems -- centralised control -- distributed control; hybrid multiagent‐based adaptive control scheme -- AC microgrids -- increased fault‐tolerance needs -- adaptive primary microgrid control scheme -- hybrid multiagent system -- MAS -- distributed control modes -- droop‐based primary control level -- microgrid energy reserves -- AC‐coupled units -- secondary level -- microgrid units operation -- dedicated asset agents -- microgrid asset -- energy storage system -- preassigned agent -- complex control objectives -- supervising agent operational -- supervising agent tasks -- hybrid scheme -- separate physical microgrids -- fault scenarios -- conventional control methodologies -- hybrid approach -- control framework exhibits unique characteristics -- reconfigurability -- fault tolerance; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2019.0468
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : This paper presents a fault‐tolerant secondary and adaptive primary microgrid control scheme using a hybrid multi‐agent system (MAS), capable of operating either in a semi‐centralised or distributed manner. The proposed scheme includes a droop‐based primary level that considers the microgrid energy reserves in production and storage. The secondary level is responsible for: a) the microgrid units' coordination, b) voltage and frequency restoration and c) calculation of the droop/ reversed‐droop coefficients. The suggested architecture is arranged upon a group of dedicated asset agents that collect local measurements, take decisions independently and, collaborate in order to achieve more complex control objectives. Additionally, a supervising agent is added to fulfill secondary level objectives. The hybrid MAS can operate either with or without the supervising agent operational, manifesting fast redistribution of the supervising agent tasks. The proposed hybrid scheme is tested in simulation upon two separate physical microgrids using three scenarios. Additionally, a comparison with conventional control methodologies is performed in order to illustrate further the operation of a hybrid approach. Overall, results show that the proposed control framework exhibits unique characteristics regarding reconfigurability and fault‐tolerance, while power quality and improved load sharing are ensured even in case of critical component failure.