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Multi-population evolutionary computing based multi-agent smart distribution system service restoration

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Abstract

Distribution system service restoration is a process of restoring power outages through changing the on/off status of sectionalizing and tie switches within the whole power outage in a distribution system altered accordingly with its topological structure. Multi-agent Systems (MASs) can be applied for distribution system service restoration, an engineering optimization problem that can be addressed through metaheuristics, of a distribution system because service restoration planning can be made in parallel among intelligent software agents embedded inside sectionalizing and tie switches and feeders to form a distributed multi-agent environment such that the time of power restoration can be reduced. Service restoration planning can be built upon an MAS. This paper presents a three-tiered MAS-based Multi-Population Parallel Genetic Algorithm (MPPGA) and demonstrates its preliminary implementation to achieve service restoration planning for smart distribution system service restoration, which serves as a meta service restoration planner to perform efficient and fast switching operation for smart distribution system service restoration. The presented three-tiered MAS-based MPPGA is implemented, in Java programming language, on a Java Agent DEvelopment (JADE for short) platform, where in evolutionary computation (1) multiple populations are coevolved and (2) selection, crossover, and mutation operations for genetic search are parallelized. The effectiveness/feasibility of the presented three-tiered MAS-based MPPGA is demonstrated by a simulated distribution system and reported with simulation results.

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Acknowledgements

The Ministry of Science and Technology, Taiwan, under grant no. MOST 109-2221-E-027-121-MY2 supported in part this paper.

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  1. Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei, 106344, Taiwan

    Yu-Hsiu Lin

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Lin, YH. Multi-population evolutionary computing based multi-agent smart distribution system service restoration. Electr Eng 104, 3295–3311 (2022). https://doi.org/10.1007/s00202-022-01547-y

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