Abstract
With the deepening penetration of renewable resources worldwide, power system operators are faced with emerging challenges, e.g., the increase of operating risks due to the volatility and uncertainty of wind and solar power. To efficiently identify the operational limit violations, a switch from deterministic to stochastic framework for assessing the system security, which could manage various types of uncertainties, has been advocated in this paper. The established model is based on an improved probabilistic load flow, which is adapted to incorporate the steady-state behavior of frequency regulation. An efficient importance sampling (IS) technique is also developed to speed up the crude Monte Carlo (MC) simulation in estimating the low probability of violations of security constraints. Extensive computational experiments on both the IEEE 14-bus test case and a simplified regional system show that the proposed IS estimator makes significant enhancement to the crude MC in the computational efficiency and has better numerical performance as compared with other IS schemes.
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