Abstract
This paper proposes a novel computing paradigm aimed at solving constrained optimization problems in electric power systems (a.k.a. optimal power flow analysis). The insight is to formulate the OPF problem by a proper set of ordinary differential equations, whose equilibrium points correspond to the optimization problem solutions. Starting from the Lyapunov theory, it will be shown that this artificial dynamic system could be designed to be stable with an exponential asymptotic convergence to equilibrium points. This important feature allows the analyst to overcome some of the inherent limitations of the traditional iterative minimization algorithms that can fail to converge due to the highly nonlinearities of the first-order conditions. Extensive simulation studies aimed at assessing the effectiveness of the proposed computing paradigm are presented and discussed.
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