Application of artificial intelligence-based techniques in controlling the statcom used for compensation for voltage dips in DFIG-based grid-connected wind power system

Abstract

Severe voltage sag in weak power systems connected to DFIG-based wind farms may lead to voltage instability. In such cases, FACTS devices like static synchronous compensator (STATCOM) can provide voltage support at the point of common coupling (PCC) by dynamic injection of reactive power. In this research attempt, three artificial intelligence-based techniques have been used to control the STATCOM—fuzzy logic, particle swarm optimization (PSO) and a combination of fuzzy logic and PSO. The STATCOM, controlled by the three proposed techniques—fuzzy-PI, PSO-PI and fuzzy PSO-PI, provides voltage compensation in the DFIG-based grid-connected wind power system in five test cases, namely simultaneous occurrence of step change (drop) in wind speed and dip in grid voltage, single-line-to-ground (SLG) fault, line-to-line (LL) fault, double-line-to-ground (DLG) fault and sudden increase in load by more than a thousand times. A performance comparison regarding the amount of voltage compensation offered is done among all the three artificial intelligence-based STATCOM control techniques in all the five test cases.