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

作者：Yin Hang^*; Zivanovic Rastko

来源：IET Generation Transmission & Distribution, 2017, 11(14): 3568-3575.

DOI：10.1049/iet-gtd.2017.0162

• load flow
• probability
• wind power plants
• stochastic processes
• correlation theory
• power grids
• probabilistic collocation method
• neighbouring wind farms modelling
• power flow computation
• South Australia grid
• PCM
• stochastic correlation model
• wind speeds
• probabilistic power flow
• historical sampled wind source data
• power system model
• spatial correlation
• PPF simulation
• Monte Carlo simulation method

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.

• 出版日期2017-9-28