The application of fuzzy logic in a hybrid fuzzy knowledge-based system for multiobjective optimization of power distribution system operations

The role of fuzzy logic is described in a hybrid fuzzy knowledge-based system, which permits the use of crisp and fuzzy rules as well as numerical methods, for multiobjective optimization of power distribution system operations. Fuzzy logic allows for the inclusion of multiple conflicting objectives, soft constraints, and expert knowledge of system behavior that cannot be quantified To illustrate fuzzy rules, heuristics for daily transformer aging and overall system conversion following an optimization procedure are described in detail. Fuzzy sets are defined for each fuzzy antecedent of the fuzzy rules: transformer aging, voltage level guidelines, recent temperature trend, and line section loadng. A standardized degree of desirability is developed using fuzzy sets to express the fuzzy consequent. Some rules are better suited to fuzzification than others. When there is uncertainty associated with antecedents or consequents or when a standardized degree of desirability is needed for the consequent, then the particular antecedents or consequents of the rules are best fuzzified The fuzzy knowledge base effectively models imprecise knowledge and resolves conflicts.