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Electric Distribution Network Expansion Under Load-Evolution Uncertainty Using an Immune System Inspired Algorithm

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5 Author(s)
Carrano, E.G. ; Dept. of Electr. Eng., Univ. Fed. de Minas Gerais, Belo Horizonte ; Guimaraes, F.G. ; Takahashi, R.H.C. ; Neto, O.M.
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This paper addresses the problem of electric distribution network expansion under condition of uncertainty in the evolution of node loads in a time horizon. An immune-based evolutionary optimization algorithm is developed here, in order to find not only the optimal network, but also a set of suboptimal ones, for a given most probable scenario. A Monte-Carlo simulation of the future load conditions is performed, evaluating each such solution within a set of other possible scenarios. A dominance analysis is then performed in order to compare the candidate solutions, considering the objectives of: smaller infeasibility rate, smaller nominal cost, smaller mean cost and smaller fault cost. The design outcome is a network that has a satisfactory behavior under the considered scenarios. Simulation results show that the proposed approach leads to resulting networks that can be rather different from the networks that would be found via a conventional design procedure: reaching more robust performances under load evolution uncertainties

Published in:

Power Systems, IEEE Transactions on  (Volume:22 ,  Issue: 2 )

Date of Publication:

May 2007

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