Multi-Objective Optimal Power Flow using Fuzzy Supported Ant Lion Algorithm

نویسندگان

  • J. Radha
  • S. Subramanian
  • M. Abirami
چکیده

The purpose of this paper is to solve a multiobjective electric power dispatch problem, which is a multiple non-commensurable objective problem, minimizes operating cost, adhering pollution norms, low transmission loss and no violations on voltage levels subject to various constraints. Improved control settings such as generator powers, bus voltage magnitudes, transformer taps and shunt capacitor settings for individual and simultaneous minimization of objectives are obtained by as new algorithm called Ant Lion Optimization (ALO). Fuzzy based approach is used to extract the best compromise solution from the trade off front. The best solution records of IEEE-30 bus, IEEE-118 bus and New England power systems are updated in this work. To further demonstrate the efficiency and effectiveness of the ALO based OPF, it has been compared with other state of the art evolutionary algorithms on this domain. Comprehensive simulation results with various case studies show a great potential for application of ALO in multi-objective OPF problems. Keywords—Ant Lion Optimizer; Emission; Multi-Objective Optimal Power Flow; Voltage Stability; Quadratic Cost

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تاریخ انتشار 2016