This paper implements a mixed-integer quadratically constrained convex optimization program on distribution networks that have a radial structure topology for denigration of system's real power loss. The adopted m...
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ISBN:
(纸本)9781467390637
This paper implements a mixed-integer quadratically constrained convex optimization program on distribution networks that have a radial structure topology for denigration of system's real power loss. The adopted mathematical model has been solved using Cplex optimization software. The global optimality of the obtained solution is guaranteed via convex relaxation of the continuous decision variables. This overcomes a major disadvantage of using artificial intelligence techniques, specifically meta-heuristic ones, that give no assurance on the solution quality or the optimality gap. Moreover, exact representation of the network losses through the assessment of the objective's function numerical-value is obtained. This overcomes the drawbacks of using linear approximations to power flow equations. The proposed algorithm has been evaluated on two IEEE standard systems and a realistic-sized network with a comparative study with other existing algorithms in the literature.
This paper will examine the solution of the minimum loss reconfiguration problem of distribution networks that determine the optimal switches, by means of a mixed-integer quadratically-constrained programming (MIQCP) ...
详细信息
ISBN:
(纸本)9781728122205
This paper will examine the solution of the minimum loss reconfiguration problem of distribution networks that determine the optimal switches, by means of a mixed-integer quadratically-constrained programming (MIQCP) model. The proposed MIQCP model is a convex formulation, which allows to find the optimal solution using optimization solvers. Our mathematical model considers the typical operating constraints of distribution networks (radial configuration, the maximum currents or the voltage plane).The accuracy of the results and the computational performance of the proposed MIQCP model are evaluated by referring to another MIQP (Mixed Integer Quadratic programming) model already adopted for the problem of interest. We used a real distribution system of 106 nodes to show the effectiveness of the proposed model compared to another MIQP model that was tested on the same network. The mathematical model adopted has been solved using the Cplex optimization software implemented under Matlab. The overall optimality of the guaranteed solution is obtained by the convex relaxation of the continuous decision variables.
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