Load Frequency Control for an Interconnected Reheat Thermal Power Systems with Redox Flow Batteries using Beta Wavelet Neural Network Controller

This paper presents optimization of Proportional Integral controller gains of the two area interconnected thermal power system with the fast acting energy storaging devices. The energy storing device especially Redox Flow Batteries (RFB) can efficiently damp out electromechanical oscillations in the power system because of their efficient storage capacity in addition to the kinetic energy of the generator rotor, which can share the sudden changes in power requirements. The proposed controller is designed with the feasibility of applying a Beta Wavelet Neural Network (BWNN) approach for the automatic generation control and implemented in a two area interconnected thermal power system without and with RFB. The system was simulated and the frequency deviations in area 1 and area 2 and tie-line power deviations for 1% and 5% stepload disturbance in area 1 were obtained. The comparison of frequency deviations and tie-line power deviations for the two area interconnected thermal power system without and with RFB reveals that the system with RFB enhances a better stability than that of system without RFB.