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

## TL;DR

This paper introduces a distributed event-triggered control and estimation approach for DC microgrids using a publish-subscribe model over industrial wireless sensor networks, aiming to enhance stability and energy management.

## Contribution

It proposes a novel event-triggered control scheme combined with an optimal observer based on a modified Kalman consensus filter for efficient microgrid management.

## Key findings

- Reduced network traffic and sensor energy consumption.
- Effective stabilization and energy balancing demonstrated in simulations.
- Validated suitability for industrial wireless sensor networks.

## 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.