| Optimal Power Flow (OFF ) problem derived from conventional economic dispatch theory and was defined as the determination of the optimal settings for control variables in a power network respecting various constraints1. Based on the existing control measures in power system, because of shunt capacitance/reactance and transformer taps, we know in math the optimal power flow problem is Mixed-Integer NonLinear Programming (MINLP) involving both discrete and continuous variables. But till now, as for this question, we don't find an effective method to solve it. In past, optimal power flow math model was simplified from every kind. Usually we take discrete variables as continuous variables, when we get the results we make discrete variables values to the nearest integer values. This manner unavoidably produces second optimal results that have error with optimal results.A new algorithm for rigorous optimal power flow problem is presented, which based on Primal-Dual Interior Point Method ( PDIPM ) under perturbed Karush-Kuhn-Tucker (KKT) conditions and Branch-and-Bound Method (BBM) . The new algorithm effectively considers the discrete variables' character, adopts PDIPM seeking optimal solution in global feasible region and uses BBM dealing with the discrete variables, develops the idea of typical interior point method solving nonlinear programming optimal power flow, at last successfully solves the rigorous optimal power flow problem.In chapters, Numerical simulations on test systems that range in size from 4, 14 to 118 buses and numerical comparison that PDIPM and the method of only considering shunt capacitance/reactance parameter being discrete variables and the method of considering shunt capacitance/reactance and transformer parameter all being discrete variables, have shown that the proposed algorithm is promising and superior for the rigorous optimal power flow of mixed-integer programming due to its robustness and precise.
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