| Wind power is renewable and clean energy, which plays a extremely important role in alleviating the energy crisis and ensuring the sustainable development of the whole society. However, with the large-scale wind power bringing to the power grid, the randomness and the uncertainty of wind power have great influence on the safe operation of power system, especially the transient stability of the po wer system. How to evaluate this impact effectively and accurately is an urgent problem to be solved, so in this paper, the problem is focused and the transient stability of power system with large scale wind power is studied from the perspective of risk.Firstly, aiming at the wind speed uncertainty, the risk index for assessing transient stability of power system based on the risk theory is proposed. Three aspects, the probability distribution of wind speed, lines failure probability modeland the severity of the consequences caused by accidents, are taken into account so that transient stability of power system with large scale wind power can be characterized accurately. In computing the severity of the consequences caused by accidents, power system transient stability margin is proposed to characterize the severity. At the same time, the K-means clustering analysis is applied to the risk assessment in this paper, and the risk is classified effectively. Simulation analysis for risk indicators are finished, the result proves that the risk assessment methods in this paper can effectively reflect the transient stability of power system with large scale wind farms. It’s more accurate to reflect the actual situation compared with the previous transient stability analysis method which only considers the transient consequence.Secondly, the effect of the correlation of wind speed on the transient stability of power system is studied. The Copula theory is applied to the correlation study of wind speed, the correlation model of wind speed and the probability distribution model of wind speed correlation are established based on the Copula function. Firstly, the wind is converted from the Weibull distribution space into uniform distribution space, and then it is converted from the wind speed edge distribution(uniform spatial distribution) to the joint distribution space based on Copula function. Given by the correlation coefficient, the marginal distribution of each wind farm is calculated. Finally the correlation wind speed sequences are obtained using the inverse Weibull distribution function. Based on the transient stability risk index of the single wind, the transient risk index of the all system is established. The simulation result shows that the system risk index increases with the increase of the correlation coefficient. At the same time, the influence of correlation of wind speed on the transient stability of the system is growing with the increase of wind power penetration.Finally, aiming at the risk for transient stability of the system, the system risk is reduced by adjusting the conventional units’ mechanical power to prevent and control system. In the process of looking for adjustment of the amount of application, the trajectory sensitivity technique is applied to transient stability analysis, the sensitivity of the risk index to every conventional unit’s mechanical power is established, and every adjustment is computed rapidly by the sign and magnitude o f the sensitivity by positive and negative sensitivity and size. The trajectory sensitivity equations of the system, which compose of system equations with the original differential algebraic equations together, are established by this method. The trajectory sensitivities of angular velocities and angles are obtained by time-domain simulation, finally the risk trajectory sensitivity is calculated. The simulation verifies the effectiveness of adjusting conventional units’ mechanical power rapidly through the risk sensitivity. |
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