The intelligent optimal sieving method for control of FACTS devices in multi-machine systems

This paper presents a multi-target oriented optimal control strategy for FACTS devices installed in multi-machine power systems, named the intelligent optimal sieving control (IOSC) method. This novel method divides the FACTS device output region into several parts and selects one typical value to form each part, which is called output candidate. Then, an intelligent optimal sieve is constructed, which predicts the impacts of each output candidate on a power system and selects an optimal output from all candidates. The artificial neural network technologies and fuzzy methods are applied to build the intelligent sieve. Finally, the real control signal of FACTS devices is calculated according to the selected optimal output through inverse system method. Simulation has been done on a three-machine power system and the results show that the IOSC controller can effectively attenuate system oscillations and enhance the power system transient stability