Translated Title

Reliability Prediction of Power Grid Systems Based on Multi-kernel Support Vector Machine

Translated Abstract

To　improve　the　reliability　prediction　performance　of　power　grid　system,multiple　objective　functions　were　con-structed　and　multi-kernel　support　vector　machine　algorithm　was　used　to　predict　reliability.The　reliability　evaluation　objec-tive　functions　were　established　by　screening　three　key　indicators　of　power　supply　availability,average　outage　time　and　average　outage　times　of　from　the　grid　sample　features,and　the　reliability　index　features　are　trained　by　multi-kernel　support　vector　machine.The　multi-kernel　combination　types　of　Gaussian　kernel　function,polynomial　kernel　function　and　Sigmoid　kernel　function　were　used　to　obtain　the　reliability　prediction　results　of　power　grid　system　through　multi-kernel　support　vec-tor　machine　solving　of　different　objective　functions,and　then　the　better　kernel　function　combination　type　for　reliability　prediction　was　determined.The　results　show　that　with　reasonable　selection　of　kernel　function　combination　and　grid　relia-bility　index,multi-kernel　support　vector　machine　has　high　prediction　accuracy　and　good　stability　in　power　supply　availa-bility,average　outage　time　and　average　outage　times,and　the　reliability　prediction　accuracy　of　the　combination　type　of　Gaussian　kernel　function　and　Sigmoid　kernel　function　is　the　best,the　combination　type　of　Gaussian　kernel　function,poly-nomial　kernel　function　and　Sigmoid　kernel　function　has　the　best　predictive　stability.

Translated Keyword

multi-kernel function
objective function
reliability of power grid system
support vector machine

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WF:perioarticalsdjcxy202404011

Language

Chinese

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