CN103401273A - Power optimization distribution method for variable-pitch fans in wind power plant - Google Patents

Power optimization distribution method for variable-pitch fans in wind power plant Download PDF

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CN103401273A
CN103401273A CN2013103304841A CN201310330484A CN103401273A CN 103401273 A CN103401273 A CN 103401273A CN 2013103304841 A CN2013103304841 A CN 2013103304841A CN 201310330484 A CN201310330484 A CN 201310330484A CN 103401273 A CN103401273 A CN 103401273A
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power
wind
fan
pitch angle
historical data
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CN103401273B (en
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陈曦
付江
肖成刚
李敬
冯迎春
何轶斌
宋辉
孔斌
郭海滨
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The Ningxia Hui Autonomous Region Electric Power Design Institute Co., Ltd.
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NINGXIA HUI AUTONOMOUS REGION ELECTRIC POWER DESIGN INSTITUTE
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    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/70Wind energy
    • Y02E10/76Power conversion electric or electronic aspects
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70Smart grids as climate change mitigation technology in the energy generation sector
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a power optimization distribution method for variable-pitch fans in a wind power plant. The method comprises the following steps: counting the practical power history data, pitch angle change history data, fan power change rate history data and pitch angle change rate history data of each fan; receiving a scheduling power command, and acquiring the upper limit power value of the wind power plant; forecasting the total amount p wind energy which can be converted by each fan according to the practical power history data of each fan, and calculating the history accumulated value Eta of the wind power change rates of each fan and a current pitch angle change rate value b; calculating the power distribution coefficient S of each fan; distributing power to the fan of which the power distribution coefficient S is higher preferentially. According to the method, the influences of geographical environments and climate change on the power output of the wind power plant are considered to the maximum extent, and the influences are reflected to subsequent power distribution through a pitch angle.

Description

Wind energy turbine set feather type power of fan optimizing distribution method
Technical field:
The present invention relates to technical field of wind power generation, particularly a kind of wind energy turbine set feather type power of fan optimizing distribution method.
Background technology:
Electric power system is complicated dynamical system, and its safe and stable operation requires must constantly keep balance between generating and workload demand in essence.Imbalance of supply and demand if electric power system can not control effectively, occurs, the reliable electricity consumption of impact load even may be caused to the large-scale accident of system.
The wind energy fluctuation is strong, when power division is carried out in the large-scale wind power field, if can not carry out reasonable distribution, easily causes the power delivery fluctuation, easily reduces grid stability.In the past few years China has confirmed by to the wind energy turbine set power optimization, distributing to improve the importance of wind energy turbine set power stage stability more to the raising that the New-energy power system quality of power supply requires to the greatest extent.Because the wind energy turbine set power stage is unstable, increased commander's difficulty of dispatching, increased the unsettled risk of electrical network, reduced the quality of power supply, so just the stability of wind energy turbine set power stage has been had higher requirement.
In order to improve the ability of wind energy turbine set power stage stability, extensively adopt and install energy storage device additional in wind energy turbine set at present.But energy storage device is expensive, capacity is less, has increased the cost of electricity-generating of new forms of energy.
Summary of the invention:
Given this, be necessary to design a kind of wind energy turbine set feather type power of fan optimizing distribution method.
Factor on power of fan output impact is a lot, is mainly the uncontrollable factors such as geographical environment, climate change, therefore considers these factors, proposes the following methods step:
A kind of wind energy turbine set feather type power of fan optimizing distribution method comprises the following steps:
Figure 945790DEST_PATH_IMAGE001
Real power historical data, propeller pitch angle change histories data, power of fan rate of change historical data, the propeller pitch angle rate of change historical data sent out of statistics wind turbine, propeller pitch angle is large, and wind energy is higher, and wind speed has the leeway of release while changing; Wherein, the real power historical data P that sends out of blower fan i, propeller pitch angle change histories data a iStatistical method be: from current time, push away forward H hour, every M minute gets a value, n sampling point altogether, 1≤i≤n;
The real power historical data P that sends out of blower fan iAlgorithm be prior art, be not repeated.
Figure 406858DEST_PATH_IMAGE002
The receiving scheduling power instruction, obtain wind energy turbine set power upper limit value
Figure 836703DEST_PATH_IMAGE003
.
Figure 999700DEST_PATH_IMAGE004
According to the real power historical data of sending out of wind turbine, carry out power prediction, and according to the propeller pitch angle historical data, the prediction wind turbine can transform the total amount p of wind energy.
According to wind turbine power variation rate historical data, calculate the historical accumulated value η of wind turbine wind power variation rate,
Figure 540402DEST_PATH_IMAGE005
Calculate the current propeller pitch angle rate of change of wind turbine numerical value b,
Figure 121556DEST_PATH_IMAGE006
Figure 456723DEST_PATH_IMAGE007
Calculate the power partition coefficient S of wind turbine, utilize the unit that propeller pitch angle is larger, when wind energy changes among a small circle, can fall lower powered fluctuation like this
S=p×0.4+a n×0.3+h×0.2+b×0.1 。
Figure 372595DEST_PATH_IMAGE008
Preferential by power division to the large blower fan of power partition coefficient S, until wind energy turbine set power upper limit value
Figure 389093DEST_PATH_IMAGE003
Be assigned with.
Preferably, step
Figure 887070DEST_PATH_IMAGE008
In, on the basis that is distributed in S of power, according to the pro rate of each blower fan prediction energy output, when the apportioning cost of certain blower fan
Figure 580088DEST_PATH_IMAGE009
Less than it, regulate lower limit
Figure 796306DEST_PATH_IMAGE010
The time, apportioning cost is regulated lower limit for it , when greater than its installed capacity
Figure 968979DEST_PATH_IMAGE011
The time, be its installed capacity
Figure 101407DEST_PATH_IMAGE011
Mathematical Modeling is as follows:
Figure 477025DEST_PATH_IMAGE012
s.t.
Figure 897642DEST_PATH_IMAGE013
Figure 557162DEST_PATH_IMAGE014
The time,
Figure 405033DEST_PATH_IMAGE015
Figure 267946DEST_PATH_IMAGE016
The time,
Figure 492254DEST_PATH_IMAGE017
Wherein,
Figure 6281DEST_PATH_IMAGE018
Wind power prediction data for blower fan i within these regulation and control period,
Figure 228315DEST_PATH_IMAGE018
Available existing algorithm calculates, and N is the blower fan total amount.
The performance synthesis that the optimization of wind energy turbine set feather type power of fan distributes has been considered real power historical data, propeller pitch angle change histories data, power of fan rate of change historical data, the propeller pitch angle rate of change historical data sent out of wind turbine, from the result of statistics, judges the power stability of blower fan.This statistical method has been examined the impact on the wind energy turbine set power stage of geographical environment, climate change to greatest extent, and this impact is reacted in follow-up power division by propeller pitch angle.
Embodiment:
A kind of wind energy turbine set feather type power of fan optimizing distribution method comprises the following steps:
Figure 640842DEST_PATH_IMAGE001
Real power historical data, propeller pitch angle change histories data, power of fan rate of change historical data, the propeller pitch angle rate of change historical data sent out of statistics wind turbine; Wherein, the real power historical data P that sends out of blower fan i, propeller pitch angle change histories data a iStatistical method be: from current time, push away forward H hour, every M minute gets a value, n sampling point altogether, 1≤i≤n;
The real power historical data P that sends out of blower fan iAlgorithm be prior art, be not repeated.
Figure 590212DEST_PATH_IMAGE002
The receiving scheduling power instruction, obtain wind energy turbine set power upper limit value
Figure 709478DEST_PATH_IMAGE003
.
Figure 164730DEST_PATH_IMAGE004
According to the real power historical data of sending out of wind turbine, carry out power prediction, and according to the propeller pitch angle historical data, the prediction wind turbine can transform the total amount p of wind energy;
According to wind turbine power variation rate historical data, calculate the historical accumulated value η of wind turbine wind power variation rate,
Figure 272011DEST_PATH_IMAGE005
Calculate the current propeller pitch angle rate of change of wind turbine numerical value b,
Figure 838122DEST_PATH_IMAGE006
.
Figure 811894DEST_PATH_IMAGE007
Calculate the power partition coefficient S of wind turbine,
S=p×0.4+a n×0.3+h×0.2+b×0.1 。
Figure 438048DEST_PATH_IMAGE008
Preferential by power division to the large blower fan of power partition coefficient S, until wind energy turbine set power upper limit value
Figure 12117DEST_PATH_IMAGE003
Be assigned with.
Preferably, step In, on the basis that is distributed in S of power, according to the pro rate of each blower fan prediction energy output, when the apportioning cost of certain blower fan
Figure 210197DEST_PATH_IMAGE009
Less than it, regulate lower limit
Figure 194203DEST_PATH_IMAGE010
The time, apportioning cost is regulated lower limit for it
Figure 803039DEST_PATH_IMAGE010
, when greater than its installed capacity
Figure 914214DEST_PATH_IMAGE011
The time, be its installed capacity
Figure 924895DEST_PATH_IMAGE011
Mathematical Modeling is as follows:
Figure 79802DEST_PATH_IMAGE012
s.t.
Figure 113617DEST_PATH_IMAGE013
Figure 559642DEST_PATH_IMAGE014
The time,
Figure 880289DEST_PATH_IMAGE015
Figure 19147DEST_PATH_IMAGE016
The time,
Figure 540258DEST_PATH_IMAGE017
Wherein,
Figure 789974DEST_PATH_IMAGE018
Wind power prediction data for blower fan i within these regulation and control period,
Figure 962198DEST_PATH_IMAGE018
Available existing algorithm calculates, and N is the blower fan total amount.

Claims (2)

1. a wind energy turbine set feather type power of fan optimizing distribution method, is characterized in that, comprises the following steps:
Figure 777938DEST_PATH_IMAGE001
Real power historical data, propeller pitch angle change histories data, power of fan rate of change historical data, the propeller pitch angle rate of change historical data sent out of statistics wind turbine; Wherein, the real power historical data P that sends out of blower fan i, propeller pitch angle change histories data a iStatistical method be: from current time, push away forward H hour, every M minute gets a value, n sampling point altogether, 1≤i≤n;
The receiving scheduling power instruction, obtain wind energy turbine set power upper limit value
Figure 26703DEST_PATH_IMAGE003
Figure 804166DEST_PATH_IMAGE004
According to the real power historical data of sending out of wind turbine, carry out power prediction, and according to the propeller pitch angle historical data, the prediction wind turbine can transform the total amount p of wind energy;
According to wind turbine power variation rate historical data, calculate the historical accumulated value η of wind turbine wind power variation rate,
Figure 474706DEST_PATH_IMAGE005
Calculate the current propeller pitch angle rate of change of wind turbine numerical value b,
Figure 704830DEST_PATH_IMAGE006
Figure 748878DEST_PATH_IMAGE007
Calculate the power partition coefficient S of wind turbine,
S=p×0.4+a n×0.3+h×0.2+b×0.1 ;
Figure 380848DEST_PATH_IMAGE008
Preferential by power division to the large blower fan of power partition coefficient S, until wind energy turbine set power upper limit value Be assigned with.
2. wind energy turbine set feather type power of fan optimizing distribution method as claimed in claim 1, is characterized in that step
Figure 202359DEST_PATH_IMAGE008
In, on the basis that is distributed in S of power, according to the pro rate of each blower fan prediction energy output, when the apportioning cost of certain blower fan
Figure 784519DEST_PATH_IMAGE009
Less than it, regulate lower limit
Figure 270996DEST_PATH_IMAGE010
The time, apportioning cost is regulated lower limit for it , when greater than its installed capacity
Figure 747775DEST_PATH_IMAGE011
The time, be its installed capacity
Figure 868046DEST_PATH_IMAGE011
Mathematical Modeling is as follows:
Figure 474608DEST_PATH_IMAGE012
s.t.
Figure 733551DEST_PATH_IMAGE013
Figure 409252DEST_PATH_IMAGE014
The time,
Figure 349526DEST_PATH_IMAGE015
The time,
Figure 224127DEST_PATH_IMAGE017
Wherein,
Figure 403436DEST_PATH_IMAGE018
Wind power prediction data for blower fan i within these regulation and control period, N is the blower fan total amount.
CN201310330484.1A 2013-08-01 2013-08-01 Wind energy turbine set feather type power of fan optimizing distribution method Active CN103401273B (en)

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Cited By (1)

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Publication number Priority date Publication date Assignee Title
CN109973301A (en) * 2017-12-28 2019-07-05 新疆金风科技股份有限公司 The method and apparatus of wind generating set pitch control are controlled under extreme turbulent flow wind regime

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109973301A (en) * 2017-12-28 2019-07-05 新疆金风科技股份有限公司 The method and apparatus of wind generating set pitch control are controlled under extreme turbulent flow wind regime
CN109973301B (en) * 2017-12-28 2020-07-24 新疆金风科技股份有限公司 Method and device for controlling pitch variation of wind generating set under extreme turbulent wind condition
US11208984B2 (en) 2017-12-28 2021-12-28 Xinjiang Gold Wind Science & Technology Co., Ltd. Method and apparatus for controlling pitch of wind turbine in extreme turbulence wind conditions

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Address after: No. 3120, Dalian Road, Jinfeng District, Yinchuan, the Ningxia Hui Autonomous Region

Patentee after: The Ningxia Hui Autonomous Region Electric Power Design Institute Co., Ltd.

Address before: 750001 East Road, the Great Wall, Yinchuan, Yinchuan, the Ningxia Hui Autonomous Region

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