ANN for multi-objective optimal reactive compensation of a power system with wind generators

In this paper, we develop a method aimed to impose an acceptable voltages profile and to reduce active losses of an electrical supply network including wind generators in real time. These tasks are ensured by acting on capacitor and reactor banks implemented in the load nodes. To solve this problem, we minimize multi-objective functions associated to the active losses and the compensation devices cost under constraints imposed on the voltages and the reactive productions of the various banks. The minimization procedure was realised by the use of evolutionary algorithms. After a training phase, a neural model has the capacity to provide a good estimation of the voltages, the reactive productions and the losses for actual curves of the load and the wind speed, in real time.