4.6 Article

A multi-agent system for distribution network restoration in future smart grids

Journal

ENERGY REPORTS
Volume 7, Issue -, Pages 8083-8090

Publisher

ELSEVIER
DOI: 10.1016/j.egyr.2021.08.186

Keywords

Distribution network restoration; Multi-agent; Self-healing; Smart grid

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Funding

  1. Sultan Qaboos University (SQU) [SR/ENG/ECED/17/1]

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The paper proposes a decentralized restoration method for smart grids, which avoids computational burden and provides good solutions. By pre-calculating the power transfer within the outage area, restoration is converted into a binary integer linear optimization problem which can be easily solved.
A main feature of future smart grids is their self-healing capability, which allows fault location, isolation and service restoration to be done automatically. Restoration is a combinatorial non-linear optimization problem for which conventional mathematical programming techniques and heuristic methods become computationally very costly. This paper proposes a decentralized restoration method that avoids the computational burden of fully centralized optimization techniques while still providing good solutions and avoiding single points of failure. By pre-calculating the amount of power that can be transferred from other feeders without violating their limits, restoration within the outage area is converted into a binary integer linear optimization problem which can be easily solved. To prove its effectiveness, different case scenarios were tested on 14-bus and 70-bus systems. The multi-agent system was implemented in JAVA Agent Development Framework (JADE) and MATLAB was employed for the main algorithms within each agent. The outcomes were compared to those of previously proposed centralized and decentralized approaches, proving that the method proposed shows better computational efficiency than the centralized approach and better results than the decentralized approach. Therefore, the proposed algorithm provides an overall improved solution. (C) 2021 The Authors. Published by Elsevier Ltd.

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