Power System Stability Enhancement Using Fuzzy Logic Controller

The common remedy for inadequate damping is to utilize additional excitation control by means of power system stabilizers (PSS).Nonlinear load has a considerable effect on system performance and has to be taken into consideration when designing the PSS.Although reducing the number of membership functions of the inputs and respectively reducing number of rules will introduce an error in output gains but it still recommended to use FLCPSS instead of fixed gains one even with small number ofMFs.The study has demonstrated the need for accurate modeling of loads. A static representation of loads that in reality exhibit significant dynamic behavior can give very misleading results.FLC has been developed for tuning a proportional integral power system stabilizer (PIPSS). The FLC receives active load model parameter (np) which characterize the nonlinear load model, active and reactive power which characterize the dynamic load model, at its inputs and provides the desired gain settings (Kp, Ki) of the PIPSS at its output.Simulation results show that PIPSS with its gain settings updated in real time by the FLC can provide good damping for the power system over a wide range of load models and significantly improve the dynamic performance of the system. On the other hand, PIPSS with fixed gain settings can only provide a good damping for the system under some particular points.The proposed fuzzy logic based controller doesn’t require model identification, is very simple for practical implementation since the decentralized output iedback control law developed in this thesis requires only local measurements.Overdoing PSS results in system instability due to their contribution to negative Umping in the system interaction modes.Future work:Regarding practical implantation is recommended. Also, comparison with other artificial intelligent method such as ANN in designing such controllers is needed.