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Wind power plant cluster scheduling method with consideration of prediction error distribution characteristics

A technology of wind farm group and prediction error, which is applied in the direction of prediction, instrumentation, data processing application, etc.

Inactive Publication Date: 2013-09-11
高文忠
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a wind farm cluster scheduling method considering the distribution characteristics of prediction errors for the wind farm cluster scheduling problem

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  • Wind power plant cluster scheduling method with consideration of prediction error distribution characteristics
  • Wind power plant cluster scheduling method with consideration of prediction error distribution characteristics
  • Wind power plant cluster scheduling method with consideration of prediction error distribution characteristics

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Embodiment Construction

[0034] The data used in the calculation example of the method of the present invention come from an actual wind farm cluster in Gansu area. The wind farm cluster contains four wind farms. Among them, the capacity of WF1 and WF3 is 200MW, and that of WF2 and WF4 is 150MW.

[0035] The process of the present invention is as figure 1 As shown, the measured output active power data set y of the wind farm group within 300 days i , the predicted output active power data set y i ', so as to obtain the wind farm group active power prediction error data sample set e i =y i '-y i .

[0036] Set h as the window width of historical error statistics, that is, divide the statistical range into n equal parts of size h when performing error statistics. The smaller the window width, the higher the accuracy of the error probability distribution, the more complex the probability distribution model, and the more time-consuming the subsequent scheduling algorithm. Therefore, it should be se...

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Abstract

The invention discloses a wind power plant cluster scheduling method with consideration of prediction error distribution characteristics. The wind power plant cluster scheduling method is specifically used for scheduling a wind power plant cluster. The wind power plant cluster scheduling method has the advantages that historical error probability distribution characteristics are analyzed by a statistical process on the basis of historical predicted wind power data, and an optimization objective includes minimizing the sum of values of mathematical expectation of shortage of wind power outputted by various wind power plants after active power instructions are issued by the wind power plant cluster, so that active power instructions which are issued by a system to the wind power plant cluster can be completed to the greatest extent; by the method, power difference caused by the fact that active power outputted by existing wind power plants cannot meet cluster scheduling requirements due to wind power active prediction errors can be reduced, system scheduling participation ability of the wind power plants is improved, and accordingly the system scheduling pressure is relieved.

Description

technical field [0001] The invention relates to a cluster scheduling method of wind farms, in particular to a cluster scheduling method of wind farms considering the distribution characteristics of prediction errors, and belongs to the technical field of wind power generation. Background technique [0002] In recent years, with the increase of wind power grid-connected capacity and the improvement of access voltage level, the impact of large-scale wind power centralized grid-connected on the power grid dispatching system is increasing. In order to deal with the impact of the randomness and volatility of wind power on the active power balance of the system, it is inevitable to incorporate wind power prediction information into the daily dispatching operation of the power system. However, the existing dispatching system's dispatching method for wind power active power is too simple, resulting in low annual average utilization hours of wind power generation and poor completion ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 高文忠
Owner 高文忠
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