For the secure operation of the Power system network, all credible contingencies must be ranked according to their severity, and corrective measures should be taken accordingly so that they can be prevented before they occur in real-time. Considering all possible contingencies would take more time; so, to minimize time taken, only critical contingencies are considered, and they are being ranked using three-layered neural network based upon their Fuzzy Performance Index (FPI). FPI is formulated by considering (i) voltage violations, (ii) MVA flow violations and (iii) voltage stability margin/system loadability margin. To reduce the dimension of network; feature selection using fuzzy curves is employed. Performance of the proposed network is tested in IEEE 30-bus system.

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Neuro-Fuzzy Approach to Contingency Ranking

  • Abhisek Mishra,
  • Sushil Chauhan,
  • Soumitri Jena,
  • Maneesh Kumar

摘要

For the secure operation of the Power system network, all credible contingencies must be ranked according to their severity, and corrective measures should be taken accordingly so that they can be prevented before they occur in real-time. Considering all possible contingencies would take more time; so, to minimize time taken, only critical contingencies are considered, and they are being ranked using three-layered neural network based upon their Fuzzy Performance Index (FPI). FPI is formulated by considering (i) voltage violations, (ii) MVA flow violations and (iii) voltage stability margin/system loadability margin. To reduce the dimension of network; feature selection using fuzzy curves is employed. Performance of the proposed network is tested in IEEE 30-bus system.