Equivalent modeling and optimal control method of wind field based on fuzzy c-means clustering algorithm

Abstract

The invention discloses a wind field equivalent modeling and optimization control method based on a fuzzy c-means clustering algorithm, comprising: determining the number c of clusters in the clustering algorithm; selecting the average output power and output power standard of a wind turbine The difference, inertial time constant, longitude, latitude and height are analyzed as the clustering elements in the clustering algorithm; the above parameters are preprocessed to obtain the characteristic matrix of the wind turbine; the clustering distance and the objective function are determined; the wind field is fuzzy c means clustering algorithm to obtain the wind field equivalent model; perform parameter aggregation on the virtual wind turbine in the wind field equivalent model; optimize the output power of the virtual wind turbine; repeat the above steps every preset time, update the parameters, and The output power of the virtual fan is optimized according to the updated parameters. The invention can accurately reflect the actual running state of the wind field while simplifying the wind field model, and the calculation process is relatively simple and easy to implement.

Description

technical field [0001] The invention relates to the technical field of wind power generation, in particular to a wind field equivalent modeling and optimization control method based on a fuzzy c-means clustering algorithm. Background technique [0002] With the continuous development of the energy market, more and more new energy has been paid attention to. As a clean and efficient new energy, wind energy is also developing its related technologies. One of the features brought about by the development of wind power technology is the ever-increasing scale of grid-connected wind farms. In the process of modeling the wind field, generally due to the large scale of the wind field, if each unit is modeled, it will not only increase the scale of the model, but also increase the complexity of calculation, analysis and simulation. Very cumbersome. Therefore, in order to reduce the amount of calculation and simulation time, it is necessary to use the method of equivalent modeling t...

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Problems solved by technology

[0006] In order to solve the above-mentioned problems existing in the prior art, the present invention proposes a wind field equivalent modeling and optimization control method based on the fuzzy c-means clustering algorithm, to solve the existing wind farm equivalent clustering algorithm. The equivalence method cannot accurately reflect the actual operating status of the wind farm in the study of large-scale wind farms, and the grouping index considered by the multi-machine equivalence method is relatively single or the calculation is too complex and difficult to realize.

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