CN102063575A - Method for analyzing influence of output power fluctuation of wind farm on power grid - Google Patents

Method for analyzing influence of output power fluctuation of wind farm on power grid Download PDF

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CN102063575A
CN102063575A CN2011100000031A CN201110000003A CN102063575A CN 102063575 A CN102063575 A CN 102063575A CN 2011100000031 A CN2011100000031 A CN 2011100000031A CN 201110000003 A CN201110000003 A CN 201110000003A CN 102063575 A CN102063575 A CN 102063575A
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power
wind power
fluctuation
grid
ace
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CN102063575B (en
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张磊
罗亚洲
栗向鑫
余有胜
郑贤福
翟志强
徐冲
周玲
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North China Grid Co Ltd
State Grid Electric Power Research Institute
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State Grid Electric Power Research Institute
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • 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
    • 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

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Abstract

The invention relates to a method for analyzing the influence of output power fluctuation of a wind farm on a power grid, which comprises the following steps of: calculating forecast ACE (Area Control Error fluctuation) of a next moment by using the wind power forecasting data of a single wind farm in an area power grid, the actual wind power data of the area power grid and the ACE fluctuation data of the area power grid, wherein the ACE is an error value formed according to the current load, power generation, power collection, frequency and other factors of the power grid, and reflects the power balance condition of an area;, comparing the ACE fluctuation with an ACE threshold, and giving out early warning. The method lays the foundation for large-scale wind power grid-connected access and scheduling, is favorable for improving the utilization efficiency of green energy and has obvious economic and social benefits.

Description

Method for analyzing influence of output power fluctuation of wind power plant on power grid
Technical Field
The invention belongs to the technical field of wind power generation and distribution, and relates to a method for analyzing influence of output power fluctuation of a wind power plant on a power grid.
Background
In recent years, the grid-connected wind power in China is rapidly developed, the total installed capacity of the wind power in China reaches 2580.5 kilowatts (21581 wind power generation units) by the end of 2009, the wind power is second in the world, and the installed capacity of the wind power in China with four provincial power grids exceeds 200 kilowatts by 9 months in 2010, and the total installed capacity of the wind power is expected to reach 1.5 hundred million kilowatts by 2020, so that 7 million kilowatt-level super-large-scale wind power bases are built. The uncertainty of wind resources and the operating characteristics of a wind power generation set enable the output power of a wind power plant to have intermittency and volatility, large-scale grid connection of wind power brings difficulty to safe and stable operation of a power system, the technical problem, operation difficulty and bottleneck of wind power grid connection are gradually shown, and the wind power grid connection difficulty becomes a focus of attention. The influence of the output power of the wind power plant on the power grid is quantitatively analyzed, and a basis can be provided for correcting the power generation plan of a power grid dispatching department in real time, so that a basis is provided for guaranteeing the safety and stability of the power grid and improving the utilization efficiency of green energy such as wind power and the like to the maximum extent.
The method comprises the steps of using single wind power plant wind power prediction data in a regional power grid, regional power grid wind power actual power data and regional power grid ACE (Area Control Error, which is an offset value formed according to factors such as current load, power generation, power receiving and frequency of the power grid and reflects the power balance condition of the region) fluctuation data, calculating prediction ACE fluctuation at the next moment, comparing the prediction ACE fluctuation with an ACE threshold value, and giving early warning, and is an effective method for analyzing the influence of wind power plant output power fluctuation on the power grid.
Disclosure of Invention
The invention aims to provide a method for analyzing the influence of output power fluctuation of a wind power plant on a power grid, which provides reference for wind power integration and dispatching and ensures safe and stable operation of the power grid.
In order to achieve the above object, the present invention adopts the following technical solutions.
The method comprises the following steps of analyzing the influence of the output power fluctuation of the wind power station on the power grid by combining the ACE fluctuation data of the regional power grid according to the single wind power station wind power prediction data and the actual wind power output data of the regional power grid in the regional power grid, wherein the method comprises the following steps:
collecting the predicted power of each grid-connected wind power plant from the wind power prediction system of each grid-connected wind power plant of the regional power grid, performing compilation according to time, summing the predicted power of the wind power plants at the same time point, and calculating to obtain the total predicted wind power of the regional power grid (the predicted wind power is 15 minutes and 1 data point):
Figure 878165DEST_PATH_IMAGE001
in the formula: n represents the number of grid-connected wind power plants of the regional power grid,
Figure 892388DEST_PATH_IMAGE002
representing the predicted power of a single wind farm,
Figure 475816DEST_PATH_IMAGE003
and representing the wind power prediction total power of the regional power grid.
Acquiring the actual output power of each grid-connected wind power plant of the regional power grid from the regional power grid data acquisition and monitoring system, performing marshalling according to time, summing the actual output power of the wind power plants at the same time point, and calculating to obtain the actual output total power of the wind power of the regional power grid:
Figure 660285DEST_PATH_IMAGE004
in the formula: n represents the number of grid-connected wind power plants of the regional power grid,
Figure 645559DEST_PATH_IMAGE005
representing the actual output power of a single wind farm,
Figure 955318DEST_PATH_IMAGE006
and representing the actual wind power output total power of the regional power grid.
And acquiring ACE fluctuation data of the regional power grid from a regional power grid data acquisition and monitoring system.
According to the actual total wind power at the current moment and the predicted total wind power nearest after the current moment, calculating the predicted wind power fluctuation at the analysis moment:
Figure 963725DEST_PATH_IMAGE007
（
Figure 954815DEST_PATH_IMAGE008
<
Figure 794595DEST_PATH_IMAGE009
）
in the formula:
Figure 212938DEST_PATH_IMAGE009
representing the time length from the nearest wind power prediction total power at the current moment,
Figure 505379DEST_PATH_IMAGE008
indicating the time duration from the current time of day to the analysis time of day,
Figure 300159DEST_PATH_IMAGE010
representing the actual total power of wind power at the current moment，
Figure 994446DEST_PATH_IMAGE011
To represent
Figure 459056DEST_PATH_IMAGE009
The total power of the wind power is predicted at the moment,
Figure 504373DEST_PATH_IMAGE012
and the wind power fluctuation is predicted at the analysis moment.
According to the fluctuation of the ACE at the current moment, wind power fluctuation prediction is predicted at the analysis moment, and the fluctuation of the ACE predicted at the analysis moment is calculated:
Figure 834336DEST_PATH_IMAGE013
in the formula:indicating that the analysis moment predicts the ACE fluctuation,
Figure 408853DEST_PATH_IMAGE015
which indicates that the current moment in time ACE fluctuates,
Figure 613570DEST_PATH_IMAGE012
and the wind power fluctuation is predicted at the analysis moment.
And comparing the calculated predicted ACE fluctuation at the analysis moment with an ACE fluctuation threshold value, and giving an early warning if the calculated predicted ACE fluctuation exceeds the threshold value.
The method for analyzing the influence of the output power fluctuation of the wind power plant on the power grid has the advantages that the quantitative analysis method is provided based on the actual wind power data of the regional power grid, the single wind power plant wind power prediction data in the regional power grid and the ACE fluctuation data of the regional power grid, and the influence of the output power fluctuation of the wind power plant on the power grid is analyzed. The method has the core that the wind power prediction technology and the SCADA technology are integrated, the influence of wind power fluctuation on a power grid is early warned, a basis is provided for large-scale grid-connected access and scheduling of wind power, the utilization efficiency of green energy is improved, and the method has obvious economic benefits and social benefits.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The method for analyzing the influence of the output power fluctuation of the wind power plant on the power grid mainly aims to quantitatively analyze the influence of the wind power output power fluctuation of a region on the ACE fluctuation of the region power grid, and comprises three links: basic data acquisition, calculation, limit value comparison and early warning, wherein the process is shown in figure 1.
1) Basic data collection
Step1：Method for collecting predicted power of each grid-connected wind power plant from wind power prediction system of each grid-connected wind power plant of North China power grid
Figure 812470DEST_PATH_IMAGE002
And predicting power of certain two wind farms in North China power grid from 12 months, 01 days and 00 to 12 hours in 2010.
Step2：Performing compilation according to time, summing the predicted power of the wind power plant at the same time point, and calculating the total power according to a formula
Figure 215769DEST_PATH_IMAGE001
Calculating to obtain the total predicted power of the wind power of the North China power grid
Figure 412396DEST_PATH_IMAGE003
For example, in 2010, in 12 months and 01 Rihua, North electric networkAnd predicting total power data of the wind power.
Step3：Collecting actual output power of each grid-connected wind power plant in Huabei power grid
Figure 166725DEST_PATH_IMAGE005
And actually outputting power of two wind power plants of the North China power grid from 00 to 48 minutes at 08 hours of 12 months and 01 days in 2010.
Step4：Performing reorganization according to time, summing actual output power of each grid-connected wind power plant at the same time point, and calculating the sum according to a formula
Figure 841420DEST_PATH_IMAGE004
Calculating to obtain the actual total wind power output power of the North China power grid
Figure 364805DEST_PATH_IMAGE006
And e.g. 00-48 minutes of 2010, 12 months, 01 days and 08 hours, and wind power actual total output power data of the North China power grid.
Step 5: collecting ACE fluctuation data of the North China power grid, such as 00-30 minutes of 2010, 12 months and 01 days of 08.
2) Computing
Step1：The current time is 30 minutes at 2010, 12 months, 01 days and 08 hours, and the actual total power of the wind power of the power grid in North China at the time
Figure 794649DEST_PATH_IMAGE010
The predicted total power of the wind power of the North China power grid closest to the moment is 3724MW
Figure 708379DEST_PATH_IMAGE011
3920MW at 45 points of 2010, 12 months, 01 days and 08 hours
Figure 249082DEST_PATH_IMAGE009
15min, 31 minutes at the analysis time of 2010, 12 months, 01 days and 08 days, and then
Figure 830236DEST_PATH_IMAGE008
Is 1min, according to the formula:
Figure 165402DEST_PATH_IMAGE007
，
wind power fluctuation predicted by calculating time prediction
Figure 894324DEST_PATH_IMAGE012
It was 13.07 MW.
Step2：Taking 30 minutes at the current moment of 2010, 12 months, 01 days and 08 hours, wherein the ACE fluctuation of the North China power grid at the moment is 24MW, and according to a formula:
Figure 910821DEST_PATH_IMAGE013
is calculated to obtain
Figure 408799DEST_PATH_IMAGE008
Temporal prediction of ACE fluctuation
Figure 849620DEST_PATH_IMAGE014
It was 37.07 MW.
3) Comparing the limit values and giving early warning
Step1：Taking 30 minutes of current time of 12 month, 1 day and 08 hours in 2010 and 31 minutes of analysis time of 12 month, 01 days and 08 hours in 2010, and calculating to obtain analysis time forecast ACE fluctuation
Figure 65837DEST_PATH_IMAGE014
The ACE fluctuation threshold value is 30MW, and compared with the ACE fluctuation threshold value, the ACE fluctuation threshold value is 7.07MW, and an early warning is given.
According to the process, 30 days 08 at 12 months and 1 days in 2010, a central office dispatcher on duty of a North China power grid can timely respond to a situation that 31 minutes 31 days of Jingjin Tang ACE fluctuation exceeds a threshold value of 7.07MW when wind power fluctuation possibly causes 08 hours, and adjust operation modes of other types of power supplies, so that adverse effects on safe and stable operation of the power grid due to wind power fluctuation are avoided.

Claims (1)

1. A method for analyzing influence of output power fluctuation of a wind power plant on a power grid is characterized by comprising the following steps:
1) collecting the predicted power of each grid-connected wind power plant from the wind power prediction system of each grid-connected wind power plant of the regional power grid, performing marshalling according to time, summing the predicted power of the wind power plants at the same time point, and calculating the sum through a formula
Figure 243437DEST_PATH_IMAGE001
And calculating to obtain the total predicted power of the regional power grid wind power, wherein: n represents the number of grid-connected wind power plants of the regional power grid,
Figure 362703DEST_PATH_IMAGE002
representing the predicted power of a single wind farm,
Figure 552376DEST_PATH_IMAGE003
representing the total predicted power of wind power of a regional power grid;
2) acquiring the actual output power of each grid-connected wind power plant of the regional power grid from the regional power grid data acquisition and monitoring system, performing marshalling according to time, summing the actual output power of the wind power plants at the same time point, and calculating the sum according to a formula
Figure 389882DEST_PATH_IMAGE004
Calculating to obtain the total power of the wind power actual output of the regional power grid, wherein: n represents the number of grid-connected wind power plants of the regional power grid,
Figure 955992DEST_PATH_IMAGE005
representing the actual output power of a single wind power plant and representing the actual output total power of the wind power of a regional power grid;
3) acquiring ACE fluctuation data of a regional power grid from a regional power grid data acquisition and monitoring system;
according to the actual output total power of the regional power grid wind power at the current moment, predicting the total power of the nearest regional power grid wind power after the current moment, and calculating the total power of the regional power grid wind power through a formula
Figure 192414DEST_PATH_IMAGE006
Calculating and analyzing the predicted wind power fluctuation at the moment, wherein:
Figure 490671DEST_PATH_IMAGE007
representing the time length from the nearest wind power prediction total power at the current moment,indicating the time duration from the current time of day to the analysis time of day,
Figure 185275DEST_PATH_IMAGE009
the actual total power of the wind power at the current moment is represented,
Figure 75870DEST_PATH_IMAGE010
to represent
Figure 810608DEST_PATH_IMAGE007
The total power of the wind power is predicted at the moment,
Figure 419444DEST_PATH_IMAGE011
representing the wind power fluctuation predicted at the analysis moment; wherein,
Figure 530620DEST_PATH_IMAGE008
<
Figure 541301DEST_PATH_IMAGE007
；
4) analyzing the forecast wind power fluctuation forecast at the moment according to the ACE fluctuation at the current moment, and obtaining the forecast wind power fluctuation forecast through a formula
Figure 446940DEST_PATH_IMAGE012
Calculating to obtain the predicted ACE fluctuation at the analysis time, wherein:
Figure 543072DEST_PATH_IMAGE014
the method comprises the steps of expressing prediction ACE fluctuation at an analysis moment, expressing the ACE fluctuation at the current moment and expressing prediction wind power fluctuation at the analysis moment;
5) predicting ACE fluctuation of the calculated analysis time
Figure 192359DEST_PATH_IMAGE013
And comparing the ACE fluctuation threshold value, and giving an early warning if the ACE fluctuation threshold value is exceeded.
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WO2012088915A1 (en) * 2011-01-01 2012-07-05 国网电力科学研究院 Method for analyzing influence of fluctuation in output power of wind farm on power grid
CN103280830A (en) * 2013-04-27 2013-09-04 南京南瑞集团公司 Overload control method suitable for large-scale wind power centralized access
CN103296679A (en) * 2013-05-20 2013-09-11 国家电网公司 Modeling method for medium and long-term wind power output model of power system capable of optimally running for medium and long terms
CN103997068A (en) * 2014-04-30 2014-08-20 国家电网公司 Interconnected power grid automatic power generation control performance evaluation method under concentrated wind power access
CN105701590A (en) * 2014-11-28 2016-06-22 国家电网公司 Wind power fluctuation probability distribution description method based on great likelihood estimation
CN109217378A (en) * 2018-10-12 2019-01-15 许昌许继软件技术有限公司 Power swing adjusting method and device suitable for new energy
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WO2012088915A1 (en) * 2011-01-01 2012-07-05 国网电力科学研究院 Method for analyzing influence of fluctuation in output power of wind farm on power grid
CN103280830A (en) * 2013-04-27 2013-09-04 南京南瑞集团公司 Overload control method suitable for large-scale wind power centralized access
CN103296679A (en) * 2013-05-20 2013-09-11 国家电网公司 Modeling method for medium and long-term wind power output model of power system capable of optimally running for medium and long terms
CN103296679B (en) * 2013-05-20 2016-08-17 国家电网公司 The medium-term and long-term long-term wind power run that optimizes of power system is exerted oneself model modelling approach
CN103997068A (en) * 2014-04-30 2014-08-20 国家电网公司 Interconnected power grid automatic power generation control performance evaluation method under concentrated wind power access
CN105701590A (en) * 2014-11-28 2016-06-22 国家电网公司 Wind power fluctuation probability distribution description method based on great likelihood estimation
CN109217378A (en) * 2018-10-12 2019-01-15 许昌许继软件技术有限公司 Power swing adjusting method and device suitable for new energy
CN109217378B (en) * 2018-10-12 2020-10-30 许昌许继软件技术有限公司 Power fluctuation adjusting method and device suitable for new energy
CN110571866A (en) * 2019-09-12 2019-12-13 珠海格力电器股份有限公司 Energy scheduling method, device and system based on load prediction

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