MOPSO using Probabilistic and Deterministic criteria based on OHL’s Thermal Ratings

A. Kapetanaki, K. Kopsidas

    Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

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    Abstract

    A Population Intelligent (PI) methodology calledParticle Swarm Optimization has recently been applied to powersystem networks with the view to minimize the computationalburden of Monte Carlo Simulation in the reliability domain. Thispaper presents a novel Multi Objective Particle Swarmoptimization (MOPSO) methodology which adapts traditionalbinary PSO to multi objective PSO and intelligently prunes thestate space by using the thermal capacity of transmission linesderived from the more detailed modelling of OHLs. For theimplementation of the algorithm, deterministic metrics are usedto evaluate the loading of the lines with the view to furtherenhance the efficiency of the proposed method. The IEEE 24-busRTS is used under different case studies to validate that thefiltering based methodology achieves computational effectivenessas well as improves network performance indices.
    Original languageEnglish
    Title of host publication 18th Power Systems Computation Conference (PSCC)
    Place of PublicationIEEExplore
    PublisherIEEE
    Publication statusPublished - Aug 2014
    Event18th Power Systems Computation Conference (PSCC) - Wroclaw, Poland
    Duration: 18 Aug 201422 Aug 2014

    Conference

    Conference18th Power Systems Computation Conference (PSCC)
    CityWroclaw, Poland
    Period18/08/1422/08/14

    Keywords

    • adequacy; multi objective optimization technique; thermal rating; deterministic and probabilistic studies; network security

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