Analysis model construction method for typical characteristics of wind power output

Abstract

The invention discloses an analysis model construction method for typical characteristics of the wind power output. Original data are obtained and data pretreatment is carried out, the data are normalized by using multi-temporal-scale wind power volatility and simultaneous rate valuation indexes, and segmented aggregation is carried out to reduce the dimension; on the basis of an improved adaptivefuzzy clustering algorithm, an adaptive function alpha (c) is calculated and an optimal cluster number c is determined, and wind power output characteristics are classified; a variation dispersion coefficient betai is introduced and wind-power output distortion data are rejected; and a partition weighted median probability estimation method is put forward and a wind-power output daily typical characteristic curve/zone band is identified and extracted. According to the invention, the multi-space-scale large-scale wind power output characteristics and monthly, quarterly or yearly multi-time-scale wind-power output characteristics are analyzed and calculated and the wind-power output daily typical characteristic curve/zone band is extracted, so that the power operation staff can master the wind-power output rule well and a technical reference is provided for real-time scheduling of a power system, scheduling plan arrangement, wind farm planning and system backup configuration.

Description

technical field [0001] The invention relates to the technical field of electric power system control, in particular to a method for constructing a wind farm output daily typical characteristic curve / interval band analysis model. Background technique [0002] With the development of wind power technology, wind power is currently the fastest growing renewable energy in the world, and the proportion of installed capacity in the power grid is increasing day by day. Due to the characteristics of peak shaving, the impact of large-scale wind power grid connection on the grid is becoming more and more obvious, such as the impact on grid security and stability, wind power transmission, frequency peak shaving, power quality, backup arrangements, many operating units, and coordination difficulties. , not only affects the safe operation of the power grid, but also limits the ability of the power grid to accept wind power, leading to a further increase in the amount of abandoned wind, re...

AI Technical Summary

Problems solved by technology

[0002] With the development of wind power technology, wind power is currently the fastest growing renewable energy in the world, and the proportion of installed capacity in the power grid is increasing day by day. Due to the characteristics of peak shaving, the impact of large-scale wind power grid connection on the grid is becoming more and more obvious, such as the impact on grid security and stability, wind power transmission, frequency peak shaving, power quality, backup arrangements, many operating units, and coordination difficulties. , not only affects the safe operation of the power grid, but also limits the ability of the power grid to accept wind power, leading to a further increase in the amount of abandoned wind, resulting in energy waste

[0003] Due to the intermittent uncertainty of wind power output, the characteristics of wind power output are different from the load demand, and it is difficult to obtain intuitively b

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