Fast Unscented Transformation-Based Transient Stability Margin Estimation Incorporating Uncertainty of Wind Generation


Intermittent generation from wind farms results in fluctuating Power System operating conditions pushing the steadiness margin to its limits. The ancient means of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative answer. This paper proposes a quick estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is employed to produce linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the ancient Monte Carlo (MC) methodology and also the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE fourteen generator Australian dynamic system. This methodology will aid grid operators to perform quick on-line calculations to estimate TSM distribution of an influence system with high levels of intermittent wind generation.

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