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Wind power unit commitment contained modeling method considering predication error timing sequence distribution

A prediction error, wind turbine technology, applied in wind power generation, data processing applications, instruments, etc., can solve the problem of not giving selection basis risk value size, unconfidence level and the corresponding relationship between spinning reserve and other problems

Inactive Publication Date: 2016-02-10
SHANDONG UNIV
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AI Technical Summary

Problems solved by technology

[0008] In terms of confidence level selection, the traditional chance constraint gives the confidence level, but does not give the selection basis and the risk value corresponding to the corresponding confidence level; Explain the corresponding relationship between

Method used

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  • Wind power unit commitment contained modeling method considering predication error timing sequence distribution
  • Wind power unit commitment contained modeling method considering predication error timing sequence distribution
  • Wind power unit commitment contained modeling method considering predication error timing sequence distribution

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Embodiment Construction

[0051] The present invention is described in detail below in conjunction with accompanying drawing:

[0052] The invention provides a method for establishing a combined model including wind turbines considering the time series distribution of prediction errors, which includes the following steps:

[0053] (1) Extracting the measured wind power data within the set time period of the wind farm to be measured;

[0054] (2) Carry out day-ahead prediction (power prediction 24 hours in advance) to the data, and obtain the trend of prediction error variation under different prediction periods;

[0055] (3) Fitting the prediction error by using the time series segmented fitting method which is fitted separately at different time periods, to obtain the fitting curves of the prediction error at different time periods;

[0056] (4) Classify the backup cost of wind power, and correspond to different confidence level intervals in the forecast error fitting curve distribution of each type of...

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Abstract

The invention discloses a wind power unit commitment contained modeling method considering predication error timing sequence distribution. A predication error segmentation fitting method under a timing sequence based on error characteristic analysis is proposed; fitting is performed based on t location-scale distribution to reduce a heavy-tail effect and improve the fitting precision, and the fitting method can be matched with a UC decision in timing sequence; next, a dual-quantile type UC decision model capable of taking conventional cost, extra standby cost and risk cost into considerations is established; the selection of confidence levels can be balanced through the restrictive relations among different costs; the standby classification can be guided by the division of the different confidence levels; the error timing sequence segmentation distribution is adapted by time varying confidence levels, so that the model is more economical, targeted and applicable; and finally, an improved hybrid particle swarm algorithm with a heuristic searching principle is adopted to solve a multi-variable mixed integer programming model of a text, and the effectiveness of the method is verified by example results.

Description

technical field [0001] The invention relates to the technical field of unit combination model establishment, in particular to a method for establishing a combination model including wind turbines considering the time series distribution of prediction errors. Background technique [0002] The large-scale grid-connection of uncertain wind power brings huge challenges to the operation and dispatch of traditional power grids. How to make it reasonable and efficient to participate in large-scale grid dispatching is necessary and urgent. [0003] Unit Combination (UC for short) is an important part of day-ahead dispatching. It is mainly based on the load forecast value to formulate the power generation plan of the unit in the future period (usually 24 hours), so as to minimize the cost of power generation. Compared with traditional load, wind power has stronger randomness and intermittency, and its relative forecast error is significantly larger than traditional load forecast. Th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/38G06Q50/06
CPCY02E10/76
Inventor 王成福王利平梁军
Owner SHANDONG UNIV
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