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Optimum allocation of FACTS devices under load uncertainty based on penalty functions with genetic algorithm

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Abstract

This paper presents genetic algorithm optimization method with a suitable objective function to determine optimum location and rated values of FACTS devices by taking into account changes in the power system load over time. In this study, annual daily load profile is considered as a whole instead of an instant load profile while looking for optimum size and location of FACTS devices. For this reason, to simplify the optimization procedure, a graph-based panelized objective function is developed, which can be used in a mixed integer search heuristic optimization technique. This paper focuses on the evaluation of the simultaneous use of thyristor controlled series capacitor and static VAR compensator. The proposed method allows including, in a simple way, the long term load profile in the planning stage to improve the power system performance using FACTS devices. After the optimization process, the performance of the proposed method has been tested on the IEEE-30 bus system with several annual test load profiles. The planning horizon is included in the optimization framework and the impact of planning horizon result is presented to compare with that of single load profile. The optimization strategy is shown to lead a significant reduction in the voltage and line violations under the long term test load profiles.

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Authors and Affiliations

  1. Department of Electrical-Electronics Engineering, Ege University, 35100, Bornova, Izmir, Turkey

    Cevdet Ersavas

  2. Department of Electrical-Electronics Engineering, Dokuz Eylul University, 35160, Buca, Izmir, Turkey

    Engin Karatepe

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  1. Cevdet Ersavas
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  2. Engin Karatepe
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Correspondence to Engin Karatepe.

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Ersavas, C., Karatepe, E. Optimum allocation of FACTS devices under load uncertainty based on penalty functions with genetic algorithm. Electr Eng 99, 73–84 (2017). https://doi.org/10.1007/s00202-016-0390-5

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  • DOI: https://doi.org/10.1007/s00202-016-0390-5

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