In this paper the problem of the minimization of active power losses in a real Smart Grid located in the area of Rome is faced by defining and solving a suited multi-objective optimization problem. It is considered a portion of the Italian electric distribution network managed by the ACEA Distribuzione S.p.A. which presents backflow of active power for 20% of the annual operative time. The network taken into consideration includes about 1200 user loads, 70 km of MV lines, 6 feeders, a thyristor voltage regulator (TVR) and 6 distributed energy sources (5 generator sets and 1 photovoltaic plant). The grid has been accurately modeled and simulated in the phasor domain by Matlab/Simulink, relying on the SimPowerSystems ToolBox, following a Multi-Level Hierarchical and Modular approach. It is faced the problem of finding the optimal network parameters that minimize the total active power losses in the network, without violating operative constraints on voltages and currents. To this aim, af

Two evolutionary computational approaches for active power losses minimization in Smart Grids / POSSEMATO, FRANCESCA; STORTI, GIANLUCA; PASCHERO, Maurizio; RIZZI, Antonello; FRATTALE MASCIOLI, Fabio Massimo. - (2013), pp. 401-406. (Intervento presentato al convegno 9th Joint World Congress on Fuzzy Systems and NAFIPS Annual Meeting, IFSA/NAFIPS 2013 tenutosi a Edmonton; Canada nel 24 June 2013 through 28 June 2013) [10.1109/ifsa-nafips.2013.6608434].

Two evolutionary computational approaches for active power losses minimization in Smart Grids

POSSEMATO, FRANCESCA;STORTI, GIANLUCA;PASCHERO, Maurizio;RIZZI, Antonello;FRATTALE MASCIOLI, Fabio Massimo
2013

Abstract

In this paper the problem of the minimization of active power losses in a real Smart Grid located in the area of Rome is faced by defining and solving a suited multi-objective optimization problem. It is considered a portion of the Italian electric distribution network managed by the ACEA Distribuzione S.p.A. which presents backflow of active power for 20% of the annual operative time. The network taken into consideration includes about 1200 user loads, 70 km of MV lines, 6 feeders, a thyristor voltage regulator (TVR) and 6 distributed energy sources (5 generator sets and 1 photovoltaic plant). The grid has been accurately modeled and simulated in the phasor domain by Matlab/Simulink, relying on the SimPowerSystems ToolBox, following a Multi-Level Hierarchical and Modular approach. It is faced the problem of finding the optimal network parameters that minimize the total active power losses in the network, without violating operative constraints on voltages and currents. To this aim, af
2013
9th Joint World Congress on Fuzzy Systems and NAFIPS Annual Meeting, IFSA/NAFIPS 2013
active power losses optimization; genetic algorithm; optimization active power losses; particle swarm optimization; smart grid
Pubblicazione in atti di convegno::04b Atto di convegno in volume
Two evolutionary computational approaches for active power losses minimization in Smart Grids / POSSEMATO, FRANCESCA; STORTI, GIANLUCA; PASCHERO, Maurizio; RIZZI, Antonello; FRATTALE MASCIOLI, Fabio Massimo. - (2013), pp. 401-406. (Intervento presentato al convegno 9th Joint World Congress on Fuzzy Systems and NAFIPS Annual Meeting, IFSA/NAFIPS 2013 tenutosi a Edmonton; Canada nel 24 June 2013 through 28 June 2013) [10.1109/ifsa-nafips.2013.6608434].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/525785
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