Multi-objective optimization of Static var Compensator in the Presence of Secondary Voltage Regulation using NSGA-II

The Hierarchical Voltage Regulation (HVR) is an efficient alternative to the traditional solutions used in the power system voltage control. It consists of three levels: primary, secondary and tertiary, among which the Secondary Voltage Regulation (SVR) level is the core of the HVR ensuring the coordination of a network area reactive power resources by controlling the voltage of the pilot bus, the area most representative bus. Moreover, in the recent years, the shunt FACTS devices, especially the Static var Compensators (SVC), have shown very good performances in local voltage control at a reasonable cost. Therefore, including these devices in the HVR scheme has become an important task. In this paper, the application of a multi-objective optimization to find the optimal placement of SVCs in the SVR environment is proposed; the objective functions to be minimized are the total power losses and the reactive power generated in the power system. The Non-dominated Sorting Genetic Algorithms II (NSGA-II) is used to generate the Pareto front which contains several optimal solutions and will be used by the Decision Maker (DM) to choose the best compromise solution. In this work, a fuzzy-based mechanism is proposed to select the best compromise solution from the Pareto set. Tests and simulations are performed on a model of the Italian power system.