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      A Distributed Event-Triggered Control Strategy for DC Microgrids Based on Publish-Subscribe Model Over Industrial Wireless Sensor Networks

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          Abstract

          This paper presents a complete design, analysis, and performance evaluation of a novel distributed event-triggered control and estimation strategy for DC microgrids. The primary objective of this work is to efficiently stabilize the grid voltage, and to further balance the energy level of the energy storage (ES) systems. The locally-installed distributed controllers are utilised to reduce the number of transmitted packets and battery usage of the installed sensors, based on a proposed event-triggered communication scheme. Also, to reduce the network traffic, an optimal observer is employed which utilizes a modified Kalman consensus filter (KCF) to estimate the state of the DC microgrid via the distributed sensors. Furthermore, in order to effectively provide an intelligent data exchange mechanism for the proposed event-triggered controller, the publish-subscribe communication model is employed to setup a distributed control infrastructure in industrial wireless sensor networks (WSNs). The performance of the proposed control and estimation strategy is validated via the simulations of a DC microgrid composed of renewable energy sources (RESs). The results confirm the appropriateness of the implemented strategy for the optimal utilization of the advanced industrial network architectures in the smart grids.

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          Most cited references34

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          Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks

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            Smart Grid Technologies: Communication Technologies and Standards

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              To Sample or not to Sample: Self-Triggered Control for Nonlinear Systems

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                Author and article information

                Journal
                09 June 2019
                Article
                10.1109/TSG.2018.2856893
                1906.03623
                ce4b3db9-ace4-4c3a-926d-8d58b8d69a14

                http://creativecommons.org/licenses/by/4.0/

                History
                Custom metadata
                eess.SP cs.DC cs.MA cs.NI cs.SY

                Performance, Systems & Control,Artificial intelligence,Networking & Internet architecture,Electrical engineering

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