An analytical approach for probabilistic evaluation of transient stability of a power system incorporating a wind farm is presented in this study. Based on the fact that the boundary of practical dynamic security region (PDSR) of a power system with double fed induction generators (DFIG) can be approximated by one or few hyper-planes in nodal power injection space, transient stability criterion for given configurations of pre-fault, fault-on and post-fault of a power system is to be expressed by certain expressions of linear combination of nodal injection vector and the transient stability probability (TSP) is further obtained with a much more simplified expression than the complex integral. Furthermore, considering uncertainties of nodal injection power including wind power and load, TSP is calculated analytically by Cornish-Fisher expansion, which can provide reliable evaluation results with high accuracy and much less computing time compared with Monte Carlo simulation. TSP and its visualization can further help operators and planners be aware of the degree of stability or instability and find critical components to monitor and reinforce. Test results on the New England 10-generators and 39-buses power system show the method’s effectiveness and significance for probabilistic security assessment.

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practical dynamic security region pdsr probabilistic evaluation of transient stability of postfault load tsp cornishfisher expansion prefault faulton england 10generators and 39buses power system integral double fed induction generators hyperplanes monte carlo simulation tsp analytical approach transient stability probability tsp probabilistic security assessment linear combination of nodal injection vector boundary

YiXin Yu,YanLi Liu,.Transient stability probability of a power system incorporating a wind farm. 59 (6),973-979.

YiXin Yu,YanLi Liu,"Transient stability probability of a power system incorporating a wind farm" 59

YiXin Yu,YanLi Liu,"Transient stability probability of a power system incorporating a wind farm"