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Wind energy penetration in power system has been increased very fast and large amount of capitals invested for wind farms all around the world. Meanwhile, in power systems with Wind Turbine Generators (WTGs), the value of AVAILABLE TRANSFER CAPABILITY (ATC) is influenced by the probabilistic nature of the wind power. The Mont Carlo Simulation (MCS) is the most common method to model the uncertainty of WTG. However, the MCS method suffers from low convergence rate. To overcome this shortcoming, the proposed technique in this paper uses a new formulation for solving ATC problem analytically. This lowers the computational burden of the ATC computation and hence results in increased convergence rate of the MCS. Using the proposed method, ATC is calculated based on one step computations while numerous steps is required for ATC calculation in iterative computational methods. Using this fast technique to evaluate the ATC, wind generation and load correlation is required to get into modeling. A numerical method is presented to consider load and wind correlation. The proposed method is tested on the modified IEEE 118 bus to analyze the impacts of the WTGs on the ATC. The obtained results show that wind generation capacity and its correlation with system load has significant impacts on the network transfer capability. It is shown descriptively that a complex and nonlinear relation exist among ATC distribution function, WTG capacity and network topography.

A Fast Calculation Method for Analyzing the Effect of Wind Generation on ATC