Cluster wind power grid connection modeling analysis method and system considering wind speed correlation
An analysis method and correlation technology, applied in wind power generation, electrical components, circuit devices, etc., can solve problems such as poor practicability, low modeling accuracy, and inability to describe tail correlation.
Inactive Publication Date: 2018-03-27
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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Problems solved by technology
For the problem of wind power correlation modeling, traditional modeling based on linear correlation coefficients, such as rank correlation coefficients to describe the nonlinear correlation of variables, cannot describe the strong tail correlation of wind power output, so the modeling accuracy is low , less practical
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[0053] In some embodiments, this step includes:
[0054] S301: Obtain model sampling points based on the wind speed multi-dimensional joint probability model;
[0055] S302: Obtain a correlated wind speed sampling sequence from the inverse function of the marginal distribution function based on the model sampling points.
[0056] S40: Predict the output of the wind farm based on the wind speed sampling sequence.
[0057] In some embodiments, in this step, a correction coefficient is introduced to reduce the prediction error. Among them, the correction coefficient is related to the wind speed, cut-in wind speed and rated wind speed of the wind farm.
[0058] In some embodiments, in this step, the system power flow distribution of cluster wind power grid-connected is calculated based on the predicted output of wind farms. Wherein, in step S40, the probability distribution characteristics of the system controlled variables are obtained according to the system power flow distribu...
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The invention discloses a cluster wind power grid connection modeling analysis method considering wind speed correlation. At least two cluster wind power grid connection related wind farms are provided. The method includes the following steps that: S10, the wind speed distribution of the cluster wind power grid connection related wind farms is acquired; S20, a wind speed multi-dimensional joint probability model is constructed based on the wind speed distribution; S30, a wind speed sampling sequence having correlation is obtained based on the wind speed multi-dimensional joint probability model; and S40, the output power of the wind farms is predicted based on the wind speed sampling sequence. In addition, the present invention also discloses a corresponding system. With the method and system of the invention adopted, modeling analysis can be performed accurately on cluster wind power grid connection; and the uncertainty of the output power of the wind farms, and the influence of correlations between the output power of the wind farms on power grids can be analyzed more accurately. The method and system have high operability and practicality and can provide great reference for theplanning and analysis of the power grid connection of large-scale cluster wind farms.
Description
technical field [0001] The present invention relates to wind power grid-connected modeling analysis, in particular to a cluster wind power grid-connected modeling analysis method and system. Background technique [0002] With the development and maturity of wind power generation technology, the scale of wind farms is becoming larger and clustered, and the development of onshore wind power has begun to shift to offshore wind power. The future planning of wind farms must be onshore wind power, large-scale clustering of offshore wind power, and phased development and utilization. my country is rich in offshore wind resources, and there are a large number of load centers in coastal areas. The development of offshore wind power can provide power for the load centers nearby. Therefore, the development of offshore wind resources has important practical significance. [0003] With the integration of wind power planned in the medium and long term, offshore wind power will become the...
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IPC IPC(8): H02J3/38G06Q10/04G06Q50/06G06F19/00
CPCG06Q10/04G06Q50/06G16Z99/00H02J3/386H02J2203/20Y02E10/76
Inventor 张梦瑶黄阮明郑秋宏庞磊韩蓓李国杰汪可友
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO