Multiobjective load dispatch by evolutionary optimization technique based weightage pattern search method

With the increasing dependence of industry, agriculture and day-to-day household comfort upon the continuity of electric supply, the reliability of power systems has assumed great importance. Therefore, the objectives of the power system such as economy, gaseous emission, security etc. must be properly coordinated in arriving at operational optimal power dispatch. The methodology, which simultaneously satisfies multiple contradictory criteria/goals, is called multiobjective optimization. In this article, cost, NOX emission, SO2 emission, CO2 emission, overloading of lines due to active and reactive power flow on transmission lines are undertaken as individual objectives to be minimized simultaneously. Normally, interactive multiobjective problems are solved to generate non-inferior solution surface because of their conflicting nature. Afterwards, the decision maker (DM) is provided with effective tools to resolve the conflict among participating objectives and arrives at a 'best' compromising solution. In this study, the weighting method is used to generate non-inferior solutions for the DM in which the problem is solved many times for different set of weights. The 'best' compromised solution has been obtained by searching for the optimal weight pattern using evolutionary optimization method. The weightage pattern that gives a non-inferior solution is chosen as the 'best' when it attains maximum satisfaction level from the membership function of the participating objectives. The proposed method circumvents the exhaustive evaluation of complete non-inferior surface needed. The validity of the proposed method has been demonstrated on a 25-bus sample system comprising five generators.