Security Region-Based Probabilistic Stability Analysis of Sub/Super-Synchronous Oscillation in Wind Power Integrated Power Systems

The stability of sub/super- synchronous oscillation (SSO) is dependent on system operating conditions. However, the existing stability analysis methods mostly investigate the SSO stability under a specific condition, which cannot reflect the real SSO risk. To address the issue, this paper proposes a security region (SR)-based probabilistic stability analysis method. Firstly, an efficient high-dimensional SR construction method is proposed based on the predictor-corrector technique. And several hyperplanes are adopted to fit the SR boundary. Then based on the SR, the probabilistic stability coefficient and stability margin index is established, so that the SSO risk under uncertain operating conditions can be evaluated and the dominant oscillation mode as well as sensitive nodes can be identified. This will provide significance guidance on the planning and operation of the system. Finally, the proposed method is conducted on a practical wind power system. The influence of the number of WTGs, wind speed distribution parameters as well as correlation on SSO probabilistic stability is studied. Compared with the traditional Monte-Carlo simulation method, the computational efficiency is improved by over 20 times. Thus verifies the effectiveness of the proposed method.