Probabilistic Analysis of Small-Signal Stability of Power Systems Affected by Wind Power Generation Uncertainties Considering Wake Effects

Most existing studies on probabilistic analysis of small-signal stability (PASS) of power systems affected by wind power generations ignore the intrinsic phenomenon in wind farms (WFs), i.e., wake effect (WE). This will result in inaccurate results of PASS. Therefore, this paper proposes an approach for PASS considering the WEs of WFs. Firstly, an improved WE model is proposed to characterize the shape transition of wind speed deficits in different wake areas. It can reflect WEs more realistically and accurately. Also, since the calculation results of the proposed improved WE model can be directly used by the power system model, it can be easily integrated into the power system model without modifications and is suitable for PASS due to its limited computational time. Then, a generic sparse stochastic spectral embedding (GSSSE) approach for PASS is proposed, which can tackle arbitrary uncertainties with arbitrary correlations in a time-saving and accurate manner. Moreover, based on GSSSE, a framework of PASS is designed. It contains not only the PASS results included in existing PASS frameworks but also the visualization of small-signal stability risk regions, thereby efficiently and accurately conducting more comprehensive PASS. Finally, case studies are conducted to reveal the necessity of considering the WEs of WFs in PASS and verify the effectiveness of the proposed improved WE model and PASS approach.