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Towards Multi-Objective Optimization of Cost and Power Loss for Optimal Power Flow in Smart Grid

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An improved multi-objective multi-verse optimization (IMOMVO) algorithm is proposed for solving multi-objective optimal power flow (MOOPF) problem with uncertain renewable energy sources (RESs). Cross pollination steps of flower pollination algorithm (FPA) along with crowding distance and non-dominating sorting approach is incorporated with the basic MOMVO algorithm to further enhance the exploration, exploitation and for well distributed Pareto-optimal solution. To confirm the effectiveness of the proposed IMOMVO algorithm, modified IEEE 30-bus system with three cases are implemented by considering the total generation cost minimization, active power losses, and emission. The simulation results obtained with IMOMVO is compared with MOMVO, NSGA-II, and MOPSO, which reveal the capability of the proposed IMOMVO in terms of solution optimality and distribution.
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