Noniterative method to approximate the effective load carrying capability of a wind plant

The effective load carrying capability (ELCC) is considered the preferred metric to evaluate the capacity value of added wind generation. However, the classical method of computing this metric requires substantial reliability modeling and an iterative process that is quite computationally intensive. Consequently, a noniterative method of estimating a wind plant's ELCC is proposed in this paper. Inspired by Garver's approximation and derived based on well-known reliability concepts, the proposed method provides an excellent approximation while requiring only minimal reliability modeling and no computationally-intensive iterative process. It computes ELCC estimates from a single function using only the wind plant's multistate probabilistic representation and a graphically determined parameter that characterizes the existing power system. After presenting the complete mathematical derivation of this function, the method is applied to compute the ELCC estimates of various wind plants at different penetration levels. It is shown that the resultant ELCC estimates only slightly overestimate the classically computed values by relative errors of 2.5% or less. Furthermore, the proposed method yields more accurate ELCC estimates than the capacity factor approximation, which is commonly used to approximate the ELCC of a wind plant.