engleski

Fuzzy Models Used For Long Term Distribution Planning Under Uncertainty

In the paper a long-term planning method based on evolutionary algorithms devised by the Authors is explained with special emphasis on calculations and decision making using fuzzy numbers. The proposed methods can cope with important features such as uncertainty in loads, tentative distributed generation, reliability parameters (e.g. mean time to switch, mean time to repair, expected frequency of failures) and changes in prices and costs. The search for the optimal solution is aimed at robust decisions, or in other words, the solution is expected not only to be economical and technically desirable, but also to perform well in any plausible future or, at least, to be sufficiently flexible when facing any unpredictable future. The major advantage of using fuzzy sets instead of a scenario approach is that fuzzy sets take care of an infinite number of demand and generation scenarios in a holistic way. The model and evolutionary algorithms have been applied intensively to real life power distribution systems showing its potential applicability to large scale systems.

electric distribution planning; optimization; evolutionary algorithms; fuzzy sets; uncertainty

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