Improving Transient Stability of Power Systems using Nonlinear Control of TCSC and Neural Networks

AbstractIn order to solve the problems of power system stability, which has always been considered by electrical engineers, by increasing the efficiency of operation and adding new lines to the system to meet the load demand in an interconnected power system and have satisfactory reliability and stability can be Overcame such problems. However, with the increase in the problems of constructing new transmission lines, such a solution will not be practical. At the same time, these new lines should be used based on their economic conditions. Therefore, the present study aimed to provide a method to increase the transient stability of power systems using nonlinear control TCSC and neural networks. This paper uses a thyristor-controlled series capacitor (TCSC), which is of particular interest today, to improve the transient stability of power systems. Therefore, a nonlinear control method called direct feedback linearization (DFL) is used to control and change the TCSC reactance so that fluctuations caused by an error are damped as quickly as possible. The proposed method is successfully implemented on a multi-machine test system and the results of the simulations performed are also analyzed. A comparison is made between the results obtained from the proposed controller (DFL). Finally, the results of temporal simulation of a SMIB power system including TCSC with DFL control and its comparison with Bang-Bang control method showed that the system power fluctuations using the DFL control method are well damped and the stability of the power system using the controller. The proposal has a significant improvement

کلیدواژه ها:

ent stability ، TCSC nonlinear control ، neural network.