This study deals with decision making methodology based on fuzzy set theory to determine the optimal generation schedule of multi-objective problem with due consideration of uncertainties in system input data and system load. The stochastic models are converted into their deterministic equivalent by taking their expected values. To determine trade-off relationship between conflicting objectives in the non-inferior domain, the weighting method is exploited. In this method, the multiobjective problem is first converted into a scalar optimization problem and then weights are searched in a systematic manner. A new interactive search technique based on binary successive approximation method is devised to search weights assigned to the objectives and incremental cost to obtain the non-inferior solution. Binary coded strings are used to represent weights assigned to the objectives as well as the incremental cost and the continuous values are obtained to represent a point in the search space through mapping. Once the trade-off has been obtained, fuzzy set theory helps the Decision Maker (DM) to choose the optimal operating point over the trade-off curve and adjust the generation schedule in the most preferred economic manner. This method has shown improvement because the weights are searched for more significant digits in fixed number of iterations. The validity of the proposed method has been examined on a sample system and the results are compared with the efficient method to solve the scalar objective problem and weight pattern is searched by evolutionary search method.
展开▼
