Application of Classifier System and Co-Evolutionary Algorithm in Optimization of Medium-Voltage Distribution Networks Post-Fault Configuration
AbstractThe methodology of restoring power supply to consumers in case of a distribution grid failure is an important issue in literature on operation and reliability of electrical energy distribution grids. The article presents a concept of a new method which supports the operation of distribution grids operators in case of a failure using a classifier system working in tandem with a coevolutionary algorithm. The method presented in the article enables constructing scenarios for adjustments to medium voltage power distribution grids configuration (power system switchgear operation adjustments). The developed method is based on the theoretical rudiments of genetic-based machine learning systems. The method uses information on previous power distribution grid failures and enables using information from simulated grid failures. Decision variables, which take into account the reliability parameters of distribution grid elements among other things, have been described using the fuzzy set theory. The final part of the article describes sample calculations related to failures of a selected actual power distribution grid performed using the developed method. Ill. 5, bibl. 12, tabl. 1 (in English; abstracts in English and Lithuanian).
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