State evaluation in composite power system reliability using genetic algorithms guided by fuzzy constraints

A new method for composite-system state evaluation using genetic algorithms (GA) is proposed. The objective of GA is to minimize load curtailment for each sampled state. Minimization is based on the DC load flow model. System constraints are represented by fuzzy membership functions. Membership value indicates the degree of satisfaction of each constraint for an individual in a GA population. The GA fitness function is a combination of these membership values. The proposed method has the advantage of allowing sophisticated load curtailment strategies, which lead to more realistic load point indices. Application to a simple test system using different load curtailment philosophies is given.