Multi-Agent Systems Based Adaptive Protection for Smart Distribution Network

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Taylor & Francis

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info:eu-repo/semantics/openAccess

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Özet

The smart power grid has been developed and improved constantly to be able to incorporate protection, automation, communication, and advanced control methods. As a result, the smart power grid system protection is expected to be modernized and given the ability to handle the future complexity that emanates from the integration of Distributed Generations (DGs). An Adaptive Multi-Agent System (MAS) can enhance power system protection and make it more reliable, faster, selective, and robust. In this paper, a novel MAS-based adaptive protection technique that suits smart grid applications is proposed. The proposed protection technique consists of agents that communicate with each other and their environment. The agents used in the proposed technique are Short Circuit Current Calculation Agent (SCCA), Load Flow Calculation Agent (LFA), Setting Calculation Agent (SCA), Logic and Operating Agent (LOA), Coordination and Optimization Agent (COA), and Network Configuration Mapping Agent (NCMA). The proposed technique can adapt to the changing conditions in the smart grid. The DigSILENT PowerFactory software is used to verify the proposed technique using a real Distribution Network in the Antalya vicinity of Turkey. The achieved results show that the method can provide fast and selective protection for the smart grid with increased integration of DGs.

Açıklama

Scientific and Technological Research Institution of Turkey (TUBITAK): TUBITAK-3501

Anahtar Kelimeler

Adaptive protection, Distribution networks, Distributed generation, Over current protection, Multi-agent system, Self-healingsmart grid

Kaynak

Electric Power Components and Systems

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Scopus Q Değeri

Cilt

49

Sayı

18-19

Künye

Shobole, A. A.. (2021). Multi-Agent Systems Based Adaptive Protection for Smart Distribution Network. Electric Power Components and Systems, 49(18-19), 1432–1444. https://doi.org/10.1080/15325008.2022.2131937.

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