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Hang Yin – Practical Application of Collocation Method in Power Flow Study of South Australia Grid
October 19 @ 4:35 pm - 5:00 pm
The stochastic collocation method is proposed to solve probabilistic power flow (PPF) model of South Australia (SA). And this model is based upon historical acquisition of power system data of SA. In SA, numbers of wind farms are installed and the variability of wind speed brings more uncertainties into the power system. The traditional deterministic power flow (DPF) computation does not consider the probabilistic nature of power system uncertainties, so PPF computation is imperative. However, as a commonly used PPF simulation method, Monte Carlo simulation (MCS) has a very high computation cost. Hence, sparse grid interpolation (SGI) is presented to accomplish PPF analysis with striking high computation efficiency. And an aggregated DC power flow model of SA is used to compare the computation efficiency of the SGI and MC.
Hang Yin received his B.E. (Electrical and Automation) and M.E. (Power Electronics and Power Drives) from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2005 and 2008, respectively. And after finishing his M.E. (Electrical and Electronic) in University of Adelaide, SA, Australia, in 2015, he is currently undertaking his PhD study in the School of Electrical and Electronic Engineering, University of Adelaide. His research interests include power system modeling, renewable energy generation modeling, probabilistic load flow computation, and power system security assessment.