Identification Of Fragile Nodes And Evolution Of Self-organized Criticality State In Power Systems Considering The Influence Of Photovoltaics

The cascading failure caused by a single fault in the power system is the main reason for the frequent occurrence of blackouts.From the failure of a single component to the collapse of the entire network caused by the cascading failure,it is often only a moment,and dispatchers have no time to take effective control measures to suppress the propagation of faults.Therefore,grasping the operating status of the power grid and taking protective measures in advance,identifying and locating the vulnerable links in the power grid are effective means to avoid cascading failures and ensure the safe and stable operation of the power system.Firstly,based on the structural vulnerability and state vulnerability of power network,a comprehensive vulnerability assessment index system is constructed,which includes five indexes,namely,network cohesion,network efficiency change rate,node electrical betweenness,node power flow impact entropy and node minimum singular value change rate.In addition,this thesis constructs a comprehensive evaluation model based on G1-anti-entropy optimal combination weighting method to evaluate the vulnerability of nodes.The combination of the G1-anti-entropy method effectively combines the knowledge of the decision-makers with the objective distribution characteristics of the data,which increases the robustness of the evaluation model.The IEEE 39 standard node example verifies the effectiveness of the proposed method.The integration of clean energy such as photovoltaics has brought new challenges to the vulnerability assessment of the power grid.Therefore,this thesis proposes a method for identifying vulnerable nodes of the power grid that takes into account the volatility of photovoltaic output and the randomness of the load.First by Latin hypercube sampling method simulating photovoltaic power and load fluctuations,then,proposing the node failure risks factor to improve the node vulnerability assessment index system.Finally,in view of the shortcomings of the traditional two-parameter interval number sorting method,a three-parameter interval number sorting method based on a Boolean matrix is proposed to determine the vulnerable nodes in the power grid.The IEEE 39 standard node calculation example after photovoltaic access verifies the effectiveness of the proposed method.In addition,this thesis analyzes the influence of the uneven distribution of fragile nodes in the power network on the self-organized criticality of the system.Based on this,a weighted distribution entropy index is proposed,which can automatically track the changes of the power network organization structure and operating state,and dynamically characterize the evolution trend of the criticality state of the power grid.The simulation result of the IEEE 39-bus system shows that with the increase in the weighted distribution entropy while keeping the average load rate of the system unchanged,the risk of a system blackout increases,which proves that this indicator can better reveal the self-organized criticality state of the system.Finally,the influence of photovoltaic access on the evolution of the self-organized criticality state of the grid is studied through simulation.