| Wind power has strong fluctuation that makes it span multiple states in a short period of time,which brings great challenges to the safety and stability of the power system.In addition,the power system has a complex and large-scale structure,which requires high timeliness of operation risk assessment.Therefore,to achieve rapid and accurate operation risk assessment for power system containing wind power is extremely important for improving the ability of power system risk prevention.Based on this problem,the work done in this paper is as follows:Firstly,considering that wind power fluctuation is correlated with time and wind speed,this paper uses probability distribution function to fit the wind power fluctuation rate at each longitudinal moment,and a Markov model of wind power fluctuation rate based on wind speed is established,which describes the differences of wind power fluctuation at different times and wind speed conditions.Through the simulation analysis of actual wind power data,it is verified that the wind power fluctuation model can better reflect the distribution law of wind power fluctuation at each longitudinal moment and the transition law between longitudinal times.Secondly,in order to improve the computational efficiency of the traditional risk assessment method,from the perspective of improving the efficiency of system state sampling and system state analysis,a method for rapid risk assessment with the combination of improved adaptive importance sampling method and load shedding model based on power flow tracing theory is proposed.On the one hand,the adaptive importance sampling method is combined with LHS(Latin Hypercube Sampling)method,the component probability distribution function modified by the adaptive importance sampling method is sampled by the LHS method,thus it can avoid sampling of a large number of repeated states and improve the sampling efficiency.On the other hand,a load shedding model is established to screen out the most effective set of control nodes by power flow tracing theory,turning global optimization into local optimization.The accuracy and effectiveness of the proposed model are verified by the analysis of IEEE-RTS79 system and actual power grid.Finally,in order to reflect the impact of wind power fluctuation on the overall operation risk of the power system in the future time periods,this paper established three-layer assessment indicators with a progressive relationship based on the value at risk theory.The assessment indicators at each wind power forecast moment such as the load shedding risk indicator,the line overload risk indicator and the voltage violation risk indicator are calculated based on the real-time outage model of wind turbines,conventional generators,and transmission lines,and they are used as the first layer indicators.Synthesizing the results of the first layer assessment indicators at all moments and using the logistic distribution and exponential distribution to describe the probability distribution of each indicator,the value at risk theory is introduced to calculate the second layer indicators such as load shedding risk change indicator,line overload risk change indicator,and voltage violation risk change indicator.The comprehensive risk indicators that are used as the third layer indicators are introduced to comprehensively evaluate the power system operation risks.The rationality of the proposed model and method is verified with the analysis in the IEEE-RTS79 system and actual power grid.This paper further analyzes the impact of different wind farm access nodes,access capacities,wind farm centralized access and decentralized access on power system operation risks. |
