A study on multi-objective optimal power flow under contingency using differential evolution

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Abstract

To guide the decision making of the expert engineer specialized in power system o peration and control; the practical OPF solution should take in consideration the critical situati on due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differential Evolution (DE) Optimization algorithm to solving multi obje ctive optimal power flow (OPF) in the power system with shunt FACTS devices considering v oltage deviation, power losses, and power flow branch. The proposed approach is examined an d tested on the standard IEEE-30Bus power system test with different objective functions at cr itical situations. In addition, the non smooth cost function due to the effect of valve point has been considered within the second practical network test (13 generating units). The simulation results are compared with those by the other recent techniques. From the different case studies, it is observed that the results demonstrate the potential of the proposed approach and show cl early its effectiveness to solve practical OPF under contingent operation states.

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Mahdad, B., & Srairi, K. (2013). A study on multi-objective optimal power flow under contingency using differential evolution. Journal of Electrical Engineering and Technology, 8(1), 53–63. https://doi.org/10.5370/JEET.2013.8.1.053

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