Performance analysis and optimization of a multilevel power flow controller using Ann

With the increase in power demand power generated has also increased as a result, some transmission lines are heavily loaded and thus the system stability has become the power transfer limiting factor. The various power system steady state problems are solved by using Flexible AC Transmission Systems (FACTS). Interline Power Flow Controller (IPFC) is a versatile device that is used to control the power flow in multiline substation and it is analyzed in a developed two area system. Real and reactive power developed in both the system is given to load, if the real power delivered to the load is minimized then the power is shared between the two systems. Neural network concepts are employed to optimize the controlled parameter of a multiline system. A Simulink model of an IPFC based multi-machine system along with neural network is developed and the results obtained were compared with the conventional system with and without IPFC, thus the effectiveness of the proposed controller is confirmed. The main objective is to enhance the power flow in generation side and to share the load during power demand using IPFC along with the neural network.