A new multi-objective optimization technique for generation dispatch

The economic and secure operation of power systems has significant importance. Due to technical limitations, the best economical operation point is not always the desired operating point for the system stability. In this study, first, the most economical operating point is obtained by solving the non-linear, network-constrained economic dispatch problem using genetic algorithm. Then, the system voltage stability is taken into account to compare the different possible operating points using V-Q sensitivity analysis. Finally, these two criteria are combined using the learning automata technique to achieve a multi-objective optimization solution, which corresponds to a desired operating point considering both economical operation and stability region. This is of particular interest in regions with significant concerns of voltage stability. The methodology was implemented in MATLAB and applied on a 6-bus test system. The same technique of learning automata may be applied in the future to similar problems that need multi-objective consideration.