In this paper the problem of optimal reconfiguration for weakly meshed systems is dealt with; meshes are created by the presence of Favoured Customers (FC) requiring supply through two different paths in order to guarantee the maximum service continuity. Aim of the reconfiguration is to attain a network that operates with minimum power losses, and in order to account for particular needs of the FC loads, that shows the minimum overall yearly fault rate on the branches where the power required by the loads flows. Moreover the constraints concerning the bus voltage profiles, the current in branches and the power balance among HV/MV transformers supplying the network must be full-filled. Due to the intrinsic nature of the problem, for its solution a Genetic Algorithm has been adopted creating some perturbation operators that, differently from existing and well-known perturbation operators, allows to widely explore the search space still keeping the feasibility of solutions.
Augugliaro, A., Dusonchet, L., Favuzza, S., Ippolito, M.G., Riva Sanseverino, E. (2011). Optimal reconfiguration of weakly meshed distribution systems. In Proceedings of CIGRE Symposium 2011 (pp.1-6).
Optimal reconfiguration of weakly meshed distribution systems
AUGUGLIARO, Antonino;DUSONCHET, Luigi;FAVUZZA, Salvatore;IPPOLITO, Mariano Giuseppe;RIVA SANSEVERINO, Eleonora
2011-01-01
Abstract
In this paper the problem of optimal reconfiguration for weakly meshed systems is dealt with; meshes are created by the presence of Favoured Customers (FC) requiring supply through two different paths in order to guarantee the maximum service continuity. Aim of the reconfiguration is to attain a network that operates with minimum power losses, and in order to account for particular needs of the FC loads, that shows the minimum overall yearly fault rate on the branches where the power required by the loads flows. Moreover the constraints concerning the bus voltage profiles, the current in branches and the power balance among HV/MV transformers supplying the network must be full-filled. Due to the intrinsic nature of the problem, for its solution a Genetic Algorithm has been adopted creating some perturbation operators that, differently from existing and well-known perturbation operators, allows to widely explore the search space still keeping the feasibility of solutions.File | Dimensione | Formato | |
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