Coordinated Design Of PSS And SVC Damping Controller Based On Hybrid Intelligence Algorithm

With the expansion of the scale of interconnected power system,widely used of high magnification fast excitation technology,and the influence of external and various internal environment condition,Low frequency oscillation has become one of the most important factors that endanger the safe operation of the power grid and restrict the transmission capacity of the power grid.At present,the system can effectively suppress low frequency oscillation by means of the power system stabilizer and the static var compensator,and it has been widely used so far.The combination of power system stabilizer(PSS)and the static var compensator(SVC)with additional control can effectively damp the low frequency oscillation and improve the dynamic stability of the power system.However,the uncoordinated design between PSS and SVC will often cause the instability of power system.Given the nonlinear of power system,this paper presents a chaos cross mutation particle swarm optimization algorithm for the coordination of PSS and SVC parameters.Based on the optimal control theory,the algorithm uses the characteristics of non repetition random of the chaotic variable to initialize the particle swarm to increase the diversity of particles.In the late stage of the algorithm,the crossover mutation operation is carried out,avoiding the local optimum and balancing the global searching ability and local improving ability of the PSO algorithm.The control performance of SVC and PSS is considered.The coordinated design problem is formulated as an optimization problem.And the control target is the ability of the system output to track a given value according to the minimum error.The simulation of four machine two area system on the example shows that CCMPSO has a good performance under different disturbances comparing with PSO.It can effectively suppress the low frequency oscillation,improve the transient stability of power system,and reduce the voltage fluctuation.