Economic Risk Assessment of Power Generation and Transmission Systems with Wind Power
In order to evaluate the economic risk of large-scale wind power generation and transmission systems after grid-connected,a combined sampling algorithm based on ECM algorithm and slice sampling algorithm combined with Latin hypercube sampling algorithm was proposed,and a Markov chain Monte Carlo(MCMC)simulation method based on combined sampling algorithm was proposed.Firstly,the weighted Gaussian mixture distribution is used to establish the wind farm output probability model,and the ECM algorithm is used to estimate the parameters.Secondly,the slice sampling algorithm is used to sample the wind farm model to obtain the initial sample space,and then the Latin hypercube sampling algorithm is used to process the initial sample to obtain the final sample space.Thirdly,the economic risk assessment model of grid-connected wind power generation and transmission system is established and the economic risk index is given.Finally,with IEEE-RTS79 system as a standard example,the effectiveness and accuracy of the proposed algorithm are verified by simulation,and the economic risk assessment of grid-connected wind power generation and transmission system is carried out by MCMC method.The simulation results show that the weighted Gaussian mixture distribution determined by ECM algorithm can accurately fit the probability distribution characteristics of wind farm output fluctuations,and the combined sampling algorithm can reduce the sample size and improve the computational efficiency under the condition of meeting the accuracy requirements.The result of risk assessment shows that the economic risk of power generation and transmission system can be reduced by proper capacity and reasonable location of wind power grid connection.
wind power grid connectiongeneration and transmission systemMarkov chain Monte Carlo simulationvombinatorial sampling algorithmeconomic risk assessment
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