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 PDFInfo
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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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- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS 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
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems 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
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:
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.
The receiving scheduling power instruction, obtain wind energy turbine set power upper limit value
.
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,
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 。
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.
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
Less than it, regulate lower limit
The time, apportioning cost is regulated lower limit for it
, when greater than its installed capacity
The time, be its installed capacity
Mathematical Modeling is as follows:
Wherein,
Wind power prediction data for blower fan i within these regulation and control period,
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:
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.
The receiving scheduling power instruction, obtain wind energy turbine set power upper limit value
.
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,
S=p×0.4+a
n×0.3+h×0.2+b×0.1 。
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.
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
Less than it, regulate lower limit
The time, apportioning cost is regulated lower limit for it
, when greater than its installed capacity
The time, be its installed capacity
Mathematical Modeling is as follows:
Claims (2)
1. a wind energy turbine set feather type power of fan optimizing distribution method, is characterized in that, comprises the following steps:
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;
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,
S=p×0.4+a
n×0.3+h×0.2+b×0.1 ;
2. wind energy turbine set feather type power of fan optimizing distribution method as claimed in claim 1, is characterized in that 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
Less than it, regulate lower limit
The time, apportioning cost is regulated lower limit for it
, when greater than its installed capacity
The time, be its installed capacity
Mathematical Modeling is as follows:
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Cited By (1)
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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)
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 Patentee before: Ningxia Hui Autonomous Region Electric Power Design Institute |
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