A method to solve a multi-objective optimal power flow (MOOPF) problem with multiple and competing objective functions (OF) is presented. The modified flower pollination algorithm and the normal boundary intersection ...
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A method to solve a multi-objective optimal power flow (MOOPF) problem with multiple and competing objective functions (OF) is presented. The modified flower pollination algorithm and the normal boundary intersection method are used in a complementary way to determine the Pareto front solution of the MOOPF problem. To help in the decision making process, an intuitive criterion based on the centroid concept is proposed to select the best compromise solution from the Pareto frontier. To demonstrate the capabilities of the proposed method, different OFs are combined to calculate the Pareto front solution on the IEEE 30 bus test system. Finally, a comparison of the proposed centroid based method against the well-known fuzzy membership and entropy criterions is provided in the results section.
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