Distribution network optimization has been classically formulated by considering a single objective function. More recently, a number of approaches have been formulated to address the presence of multiple objectives, in particular exploiting multi-objective tools to deal with conflicting objectives. This paper provides an analysis of the requirements that have to be satisfied by meta-heuristic tools in order to be efficiently used in multi-objective distribution system reconfiguration, mainly referring to maintaining the network radial and to treat the equality and inequality constraints. Comparisons of the multi-objective versions of a genetic algorithm and of a particle swarm optimization tool are shown on the basis of the results obtained on a classical test system.

Comparison of multi-objective optimization approaches for distribution system reconfiguration / Mazza, Andrea; Chicco, Gianfranco; Russo, Angela. - ELETTRONICO. - (2013). (Intervento presentato al convegno IEEE Grenoble PowerTech (POWERTECH), 2013 tenutosi a Grenoble, France nel 16-20 June 2013) [10.1109/PTC.2013.6652482].

Comparison of multi-objective optimization approaches for distribution system reconfiguration

MAZZA, ANDREA;CHICCO, GIANFRANCO;RUSSO, ANGELA
2013

Abstract

Distribution network optimization has been classically formulated by considering a single objective function. More recently, a number of approaches have been formulated to address the presence of multiple objectives, in particular exploiting multi-objective tools to deal with conflicting objectives. This paper provides an analysis of the requirements that have to be satisfied by meta-heuristic tools in order to be efficiently used in multi-objective distribution system reconfiguration, mainly referring to maintaining the network radial and to treat the equality and inequality constraints. Comparisons of the multi-objective versions of a genetic algorithm and of a particle swarm optimization tool are shown on the basis of the results obtained on a classical test system.
2013
9781467356671
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2583547
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo