Active Power Losses Constrained Optimization in Smart Grids by Genetic Algorithms

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 ACEA Distribuzione S.p.A. network which presents backflow of active power for 20% of the annual operative time. The network taken into consideration includes about 100 nodes, 25 km of MV lines, three feeders and three distributed energy sources (two biogas generators and one 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 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 encouraging and show that the proposed optimization technique can be adopted as the core of a hierarchical Smart Grid control system.