• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.3
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• pp.171-177
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• 2013

This paper presents a fuzzy set method to enforce complementarity constraints (CCs) in a nonlinear interior point method (NIPM)-based optimization. NIPM is a Newton-type approach to nonlinear programming problems, but it adopts log-barrier functions to deal with the obstacle of managing inequality constraints. The fuzzy-enforcement method has been implemented for CCs, which can be incorporated in optimization problems for real-world applications. In this paper, numerical simulations that apply this method to power system optimal power flow problems are included.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.226-228
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• 2007

This paper proposes Nonlinear Interior Point Method (NIPM) including discrete control variables optimal power flow formulations. The algorithm utilizes the robustness in terms of starting point and fast convergence for large scale power system of NIPM and an introduction of rounding penalty function which is augmented in the Lagrangian function to handle discrete control variables. The derived formulation shows a simplified approach to deal with discrete control problems which is implementable in real large scale systems.