Additional Control Of SVC To Suppress Low Frequency Oscillations Of Power Grid

With the interconnection of regional communication system and widely using of high magnificationquick excitation system, low frequency oscillation damp of system presents weakening trend and it iseasy to cause low frequency oscillation. It limits the interconnection transmission power and affects thesecurity of power system. Accompanied by large scale wind power access, wind power has an largeinfluence on the stability of the system.Therefore, how to restrain the low frequency oscillationeffectively has become the focus of current research. As an example, this paper studied the additionaldamping controller for low frequency oscillation suppression effect based on SVC, analyzed theinteraction of control loops on SVC, put forward a coordination optimization method of control links anddamping controllers based on improved genetic algorithm which embedded neural network。And thispaper has designed the SVC wide-area additional damping controller and studied the delay stability.This paper firstly studied mutual influence of SVC control links,which proved the interaction of thelink of SVC damping control and voltage regulation，and put forward a coordination optimizationmethod of control links which based on improved genetic algorithm with BP neural network. At thesame time，the algorithm has the advantages of saving computing time and wide applicable scope, whichprovides an effective solution to the sort of question called for optimization calculation of the complexcalculation.In order to improve the dynamic stability of power grid as a whole, this paper put forward acoordination optimization method of PSS and SVC damping controller based on improved geneticalgorithm which embedded Adaboost-BP neural network.And the neural network is optimized andisolated the small disturbance eigenvalue analysis by the method of knowledge learning process ofmedium, so as to improved the efficiency of optimization calculation of the genetic algorithm. Thesimulation verified the effectiveness and superiority of the method based on the two area with fourmachine system and a region of large interconnected power grid.This paper selected the input signal of SVC additional wide-area damping controller based on theanalysis of Prony and primary modulus ratio, and optimized SVC parameters by the method of improvedgenetic algorithm which embedded Adaboost-BP neural network. Using the subspace identificationmethod, it established wide-area power system model considered delay in two area with four machinesystem. The stability of wide-area system was studied by delay stability criterion based on linear matrixinequality and got the delay stability margin.