On the impact of topological properties of smart grids in power losses optimization problems

• We face the power losses minimization problem on a real smart grid.
• A genetic algorithm performs the joint PFC and DFR optimization.
• Some admissible network configurations violate constraints on currents and voltages.
• Such violations depend only on topological properties of the network configurations.
• Removing these configurations from search space leads to performances improvements.

Power losses reduction is one of the main targets for any electrical energy distribution company. In this paper, we face the problem of joint optimization of both network topology and distributed generator parameters in a real smart grid. We consider a portion of the Italian electric distribution network managed by the ACEA Distribuzione S.p.A. located in Rome, Italy. We perform both the power factor correction (PFC) for tuning the generators and the distributed feeder reconfiguration (DFR) to set the optimal state of the breakers. This joint optimization problem is faced considering a suitable objective function and by adopting genetic algorithms as global optimization strategy. We analyze admissible network configurations, showing that some of these violate constraints on current and voltage at branches and nodes. Such violations depend only on topological properties of the network configurations. We perform experiments by feeding the simulation environment with real data concerning samples of dissipated and generated active and reactive power values of the ACEA smart grid. Results show that removing the configurations violating the electrical constraints from the solution space leads to important improvements in terms of power losses reduction. Moreover, we provide also an electrical interpretation of the phenomenon using graph-based pattern analysis techniques.