Study On The Operation And Planning Of Power System With Large-scale Wind Farms

Large-scale wind power generation has become the mainstream of today's global power industry. The integration of large-scale wind farms will impact on many aspects of the power system and present new challenges to the traditional power system analysis methods. As wind power is variable, intermittent and uncontrollable, the traditional power system analysis methods couldn't properly handle the effects of the volatility of large-scale renewable energy like wind power. Therefore, the research on the power system analysis methods that takes into account the effects brought by the integration of renewable energy generation systems like large-scale wind farms is of great theoretical and practical significance. In allusion to the effects brought by the wind power volatility on the power grid in different time scales, and from the view point of operation and planning, this paper studies problems of power system operation and planning including the probabilistic load flow analysis, dynamic economic dispatch with wind farms, and the power system transmission network expansion planning considering the uncertainties of both the load demand and the wind power output from large-scale wind farms.(1) In allusion to the correlation among the random factors such as loads and power output of renewable energy generation systems like wind farms, this paper proposes a novel probabilistic power flow method which is a combination of Nataf transformation and Latin hypercube sampling. This method is able to handle the correlation between the input random variables, and has the advantages of Latin hypercube sampling. It has a good prospect of engineering application. This paper provides an effective method to tackle the probabilistic power flow problem with correlated input random variables.(2) This paper proposes a novel hybrid intelligent optimization method to solve the traditional dynamic economic dispatch model with valve-point effect and the dynamic economic dispatch model with wind farms. The algorithm consists of the Sobol sequences, the improved hybrid leapfrog algorithm (ISFLA), and sequential quadratic programming (SQP). The results of test examples fully demonstrate that the proposed method is of high efficiency, and can attain high quality results. This paper proposes an effective new method to solve the dynamic economic dispatch problem with or without wind farms considering valve-point effects.(3) This paper applies the robust linear optimization theory to study the minimum load-shedding problem for transmission network planning with multiple wind farms. The model can give the most secure load-shedding scheme. In addition, it can give some eclectic load-shedding schemes from the viewpoint of economy and robustness. The proposed model is flexible. Based on the robust linear optimization theory, this paper proposes a flexible transmission network expansion planning method. The proposed method can tackle the uncertainties of both the load demand and the wind power output from large-scale wind farms. The proposed method is flexible, efficient and effective. With this method not only the most robust planning scheme within economic constraint can be obtained if existed but also a number of eclectic planning schemes can be given from the viewpoint of economy and robustness. It can provide planners with comprehensive and useful information for making decisions.