Frequency Control in Power System Including Wind- Farm

Abstract

Conservation of climate and to reduce CO2 emission is the main motive to integrate more Renewable Energy Sources with existing electrical power network. The growing penetration of wind power may threat frequency stability issues with existing conventional energy sources as it reduces overall inertia of the system due to decoupling from the AC power grid using power electronic converters. Recent advertence has been identified as method of controlling stored kinetic energy in DFIG to retain frequency stability during transient event and hence it is more important to consider participation of wind-farm in such circumstances for desired support in the event of system frequency disturbance. In the present work detailed survey of certain advanced techniques for inertial control are suggested. The proposed approach is based on a modified inertial control scheme which includes the favour of fast response capability with wind energy conversion system which allows the kinetic energy stored by rotational masses to be partly and transiently released in order to provide fast frequency support and hence DFIGs have the ability to reduce speed instantly and release the stored kinetic energy to support conventional generators in regulating system frequency. Further the different architecture of controller based on conventional techniques i.e. PID controller are designed for two area interconnected energy system having capability of DFIG during load disturbance to improve frequency profile of the power system. The performance of such system depends upon the optimal selection of controller gains and hence the different control techniques such as Classic PID, Pessen Integral Rule, Some Overshoot, No Overshoot and Ziegler{Nichols method are proposed and comparative analysis of the various system controls are evaluated for 1% change in one of the control areas. In addition to above, the control design based on the concept of the fuzzy logic effectively trained with the help of artificial neural system is proposed for the above considered system. The system performance is assessed for 1% change in load demand and the application results are compared with conventional design in order to show the effectiveness and power of ANFIS based control for conventional system with DFIG as compared to that obtained through conventional control.