Impact of Stochastic Generation in Power Systems Contingency Analysis

A new methodology is proposed for the contingency analysis of power systems with a high penetration of stochastic generation. The essence of the proposed technique is the use of a probabilistic risk measure for the security assessment of the N subsystems deriving from the application of the N-1 criterion. This measure, namely the stochastic stress of the system, corresponds to the concurrent behavior of the stochastic system inputs (loads and stochastic generators) that are situated in the lower voltage levels of the system. In the context of Monte Carlo simulation, this problem is equivalent to the sampling of a large number of non-trivial dependent random variables (stochastic power injections). The modeling procedure is split in two independent tasks: modeling the marginal distributions and modeling the stochastic dependence structure. The second part is the most cumbersome modeling problem. For this, a two-step method is used. First, clusters of positively correlated variables are defined and are modeled based on the concepts of perfect correlation (comonotonicity). Then, the exact correlations between these clusters are modeled based on the joint normal transform methodology. This powerful computational method can be easily applied to large systems with a high number of stochastic generators. The application of the method for the contingency analysis of the 5-bus/7-branch test system (Hale network) with a high penetration of wind generation is presented in the paper