Studies On Controlled Splitting Strategy In Power Systems

With the rapid development of power system and the formation of large-scale interconnected power grid,the security of power system has been paid more and more attention.How to prevent the propagation of system failure and avoid chain failure are key problems to be considered.Controlled splitting is a kind of emergency control measures with real-time dynamic information in a given power system appropriately employed.Implementation of timely and appropriate controlled splitting for a given power system under large disturbance can block the propagation of faults,and system collapse possibly caused by malfunctioning of protection devices can be avoided to some extent,and hence rapid restoration of the whole power system can be attained.At present,researches on controlled splitting mainly focus on three aspects:when to split,where to split and how to control.In this thesis,a complete set of controlled splitting strategy is proposed to solve the three key problems above,and the effectiveness of the proposed strategy is verified by simulation examples.The main work of this thesis is summarized as follows:Regarding the splitting time,a method for determining controlled splitting time based on wide area measurement system(WAMS)and combined linear prediction algorithm is proposed,and both power angles and operating frequencies of generators are taken into account.In this method,WAMS is utilized to collect the power angles and operating frequencies of generators in real time,and the combined linear prediction algorithm is employed to forecast the disturbed trajectory of generators,hence the system can be islanded before operating frequencies of generators beyond the limit.Thus the emergency shutdown of generators can be avoided and the security of the power system can be ensured.Moreover,aiming at the shortcomings of traditional prediction algorithms,a combined linear prediction algorithm is presented to improve the prediction performance by combining the auto-regressive moving-average algorithm and the Kalman filter algorithm.Finally,effectiveness of the proposed algorithm are validated by simulation results of the IEEE 39-bus test system.Regarding the splitting location,a method for searching controlled splitting sections quickly based on constraint spectrum clustering algorithm is proposed.First,an improved version is presented for the spectral clustering algorithm developed in the field of machine learning,and a constrained spectral clustering algorithm proposed to account for the coherent constraints of generators.The problem of searching splitting sections is then transformed into the one of finding generalized eigenvalues.Furthermore,in order to avoid the drawbacks of the traditional k-medoids algorithm that the clustering result is sensitive to the specified initial cluster centers and the search procedure is inefficient,an improved k-medoids algorithm is proposed and employed with the constrained spectral clustering algorithm to search the optimal splitting sections.Finally,the IEEE 118-bus test system and the actual power system are employed to demonstrate the feasibility and effectiveness of the proposed method.Regarding the control problem,an optimal adjustment strategy for isolated island combining node adjustment domain and power flow tracing algorithm is proposed based on the principle of proximity and importance.Firstly,the node adjustment domain is defined based on the node degree theory,and the relative distance between the isolated island node and the splitting point is calculated by using the breadth-first search algorithm to determine the adjustment range.Next,the power flow tracing algorithm is adopted to calculate the utilization coefficient of the splitting sections for nodes in the node adjustment domain,then the adjustment object and the adjustment sequence can be determined.Furthermore,the bidirectional flow tracing algorithm is adopted on the splitting sections to determine the adjustment amount.Finally,the IEEE 118-bus test system and the actual power system are employed to demonstrate the effectiveness of the proposed method.Finally,the research work of this thesis is summarized,and future research directions in relevant research fields highlighted.