2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS) 2013
DOI: 10.1109/ifsa-nafips.2013.6608435
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Optimal distribution feeders configuration for active power losses minimization by genetic algorithms

Abstract: In this paper we face the problem of the joint optimization of both topology and network parameters in order to minimize the total active power losses in a real Smart Grid. It is considered a portion of the Italian electric distribution network managed by the ACEA Distribuzione S.p.A. located in Rome which presents back-flows of active power for 20% of the annual operative time. It includes about 1200 user loads, 70 km of MV lines, 6 feeders, a thyristor voltage regulator (TVR) and 6 distributed energy sources… Show more

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Cited by 11 publications
(7 citation statements)
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References 7 publications
(8 reference statements)
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“…In this paper we have presented an improvement of the control system first described in [28,[34][35][36]. We performed an analysis of admissible network configurations to identify undesirable configurations that may slow down the convergence speed of the optimization procedure.…”
Section: Discussionmentioning
confidence: 99%
“…In this paper we have presented an improvement of the control system first described in [28,[34][35][36]. We performed an analysis of admissible network configurations to identify undesirable configurations that may slow down the convergence speed of the optimization procedure.…”
Section: Discussionmentioning
confidence: 99%
“…In this paper an improvement of the control system described in (Storti et al, 2013a), (Possemato et al, 2013), (Storti et al, 2013b) and (Storti et al, 2014) is presented. We propose an heuristic method to compare admissible network topologies and a criteria to order the list of such topologies aiming to improve the continuity of the objective function to the variation of the configuration parameter.…”
Section: Discussionmentioning
confidence: 99%
“…Since then, a great number of publications based on evolutionary algorithms are proposed in the literature (Storti et al, 2013a), (Possemato et al, 2013). Recently, GA is also used to solve the DFR problem with DG (Chandramohan et al, 2010), (Storti et al, 2013b). One of the main difficulties for solving the DFR problem using evolutionary algorithms is the radiality constraint.…”
Section: Introductionmentioning
confidence: 99%
“…In [3], an accelerated particle swarm algorithm was implemented to optimize the multiobjective problem of real power loss reduction, capacitors cost optimization and system stability enhancement. Introducing the weighted sum strategy, the single objective in addressing power system multiobjective was illustrated in [4]. A radial system was incorporated for the verification of the anticipated algorithm in comparison with the other heuristic methods.…”
Section: Introductionmentioning
confidence: 99%