In this study, an efficient approach is proposed to find best real power generation participation for improving static voltage stability and reducing total generation cost. Therefore, loadability limit index is used to assess static voltage stability security margin, which is associated to the point of voltage collapse. Based on it, a toolbox is developed to recognize the loadability margin by using Lagrangian method. Finally, the mentioned problem is modeled as a non-linear and multiobjective optimization problem. In this paper, Hybrid Genetic Algorithm Particle Swarm Optimization (HGAPSO) and Particle Swarm Optimization (PSO) algorithms are applied to find out best generation direction. This problem is performed as a hierarchical optimization problem. In first stage, an algorithm is used to search possible solution area and reach tradeoff between secure and economic direction of real power generations. In second stage of proposed approach, respectively to each generation pattern, power system voltage stability margin and generation cost are evaluated during search algorithm. The simulations are performed on IEEE 14 and IEEE 30 bus test systems to find best generation direction.
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