Optimal distribution feeders configuration for active power losses minimization by genetic algorithms

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 (5 generator sets and 1 photovoltaic plant). Network topology can be changed by 106 breakers. The grid has been accurately modelled and simulated in the phasor domain by Matlab/Simulink, relying on the SimPowerSystems ToolBox, following a Multi-Level Hierarchical and Modular approach. Network optimization is faced by defining and solving a suited multi-objective optimization problem, considering suited constraints on nominal operative ranges on voltages and currents, as well as on generator's capability functions, in order to take into account safety and quality of service issues. To this aim it is adopted a genetic algorithm, defining a suited fitness function. Tests have been performed by feeding the simulation environment with real data concerning dissipated and generated active and reactive power values. First results are very interesting, showing that relying on evolutionary computation it is possible to yield a satisfactory power factor correction, confirming that the proposed optimization technique can be adopted as the core of a hierarchical Smart Grid control system.