Fuzzy Satisfying Multiobjective Thermal Power Dispatch Based on Surrogate Worth Trade-off Method

Abstract

In multiobjective optimization, trade-off analysis plays an important role in determining the best search direction to reach a most preferred solution. As in many cases, the objectives contradict with each other and cannot be handled by conventional scalar optimization techniques. This article deals with the multiobjective optimization problem relating to real and reactive power scheduling of thermal power generating units. In deciding the most preferred solution, operating cost, emission pollutants are the objectives undertaken to be minimized simultaneously while satisfying the security constraints. The real and reactive power line flows are obtained with the help of generalized Z-bus distribution factors (GZBDF). The non-inferior solutions, along with the trade-off functions between the conflicting objectives, are generated by implementing the ε-constraint method. Exploiting fuzzy set theory to access the indifference band, interaction with the decision maker is obtained via surrogate worth trade-off (SWT) functions of the membership functions of the objectives. The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space, so the surrogate worth trade-off functions of objectives relate the decision maker's preferences to non-inferior solutions. The goal/objectives being of fuzzy nature can be quantified by defining their membership functions. The effectiveness of the method is demonstrated on IEEE 11-bus system, which comprises 3-generators.