access icon free Using probabilistic collocation method for neighbouring wind farms modelling and power flow computation of South Australia grid

In this study, the probabilistic collocation method (PCM) is proposed to construct a stochastic correlation model of wind speeds at neighbouring wind farms and solve probabilistic power flow (PPF) of South Australia (SA) grid. Based on the historical sampled wind source data, the model is developed to reduce the number of uncertain parameters of the power system model by considering the spatial correlation of wind speeds between neighbouring wind farms. Furthermore, this model aims to increase the computational efficiency of PCM when dealing with PPF simulation. Finally, the computation efficiency and accuracy of the PCM, compared with traditional Monte Carlo simulation method, are validated by the simulation results of aggregated power flow model of SA case studies.

Inspec keywords: wind power plants; probability; correlation theory; power grids; stochastic processes; load flow

Other keywords: historical sampled wind source data; spatial correlation; PCM; wind speeds; power flow computation; South Australia grid; probabilistic power flow; PPF simulation; stochastic correlation model; Monte Carlo simulation method; neighbouring wind farms modelling; probabilistic collocation method; power system model

Subjects: Wind power plants; Other topics in statistics

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