CN110264375A - A kind of intermittent Multiple Time Scales of wind farm group power output quantify depicting method - Google Patents
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Abstract
The invention discloses a kind of intermittent Multiple Time Scales of wind farm group power output to quantify depicting method, described method includes following steps: one: defining wind power climbing duty ratio, consider the characteristic climbed up and down, obtains the time series of wind power climbing duty ratio using wind power plant actual measurement history wind power data；Two: establishing wind power climbing duty cycle time sequence statistic Regression Forecasting Model and forecast, complete intermittent forecast of contributing to the following wind farm group；Three: choosing multiple time intervals and repeat one, two to realize that the intermittent Multiple Time Scales of wind farm group power output are quantitatively portrayed.The present invention defines wind power climbing this index of duty ratio quantitatively to portray wind-powered electricity generation intermittence；Fully consider that climbing characteristic is different up and down；By carrying out Modeling and Prediction to parameter, risk assessment is carried out for electric system, rational management allowance is determined etc. decision support is provided, it is ensured that the stable operation of power system security after wind power integration；It takes Multiple Time Scales to portray, reduces the case where failing to report.
Description
Technical field
The present invention relates to a kind of method of the intermittent early warning of wind farm group power output, in particular to a kind of consideration Multiple Time Scales
The intermittent method quantitatively portrayed and forecast of wind farm group power output, to realize intermittent pre- to wind farm group power output
It is alert.
Background technique
Currently, understanding probabilistic to wind-powered electricity generation and grasp are to promote the safe and efficient consumption of the extensive renewable energy in China
With the key foundation problem of clean energy resource constructional transfer.Wherein, intermittence is the probabilistic important behaviour of wind-powered electricity generation.Wind-powered electricity generation
Intermittence makes the method for operation that original power grid is changed after wind-powered electricity generation large-scale grid connection, influences the stabilization and safe operation of power grid.
Therefore wind-powered electricity generation intermittence is studied, more detailed wind-powered electricity generation output characteristics can be provided for electric system, stabilize it to electricity
It is endangered caused by net.
Currently, the intermittent research achievement of wind-powered electricity generation has focused largely on qualitative description and how to stabilize elimination aspect, lack detailed
Quantitatively portray and describe to the greatest extent method.CN104463511B discloses a kind of wind speed interval based on blower unit time start and stop frequency
Property quantitative depicting method, refer to that wind speed is intermittent to be portrayed in this method；Meanwhile CN104598755B discloses one kind and is based on
The wind speed intermittence of wind speed abrupt change duty ratio quantifies depicting method, in this method that the spatial and temporal distributions of certain statistics of wind are uneven
Even property definition is wind speed intermittence and quantitatively portrays wind speed intermittence with wind speed abrupt change duty ratio.For wind power output interval
Quantifying for property is portrayed, and foreign scholar Milan et al. indicates the intermittence of wind power with the form of probability of wind power difference,
But this can only qualitative description wind power intervals, can not quantitative description it is intermittent.Gunturu et al. is based on wind power concentration
(WPD) conversion of the wind-resources between active and idle is defined as intermittence: when WPD is greater than or equal to 200W/m2When " to have
The available effective status of function "；And when WPD is less than 200W/m2When be " idle " invalid down state.Meanwhile he is big by WPD
In 200W/m2Above variation is known as fluctuation.
In addition, the climbing event of wind farm group power output is always emphasis that scholars pay close attention to, Zhang Dongying etc. is from definition, prediction
Method and the aspect of control strategy 3 be reviewed the Developments of wind-powered electricity generation climbing event: comparative analysis first is climbed
The common definition of slope event specifies its advantage and disadvantage and the scope of application；Secondly, the present Research of climbing prediction technique is summarized,
According to whether being divided into two class of DIRECT FORECASTING METHOD and indirect predictions method by the judgement of wind power prediction result, summarize common
Prediction technique evaluation index；Then basic thought, control method and the wind of the limited climbing control strategy of no energy storage are elaborated
The principle and progress of storage joint climbing control strategy；The primary study side in wind-powered electricity generation climbing event future is finally looked forward to
To；However, it, which is not referred to using the statistical parameter of wind-powered electricity generation climbing event, quantitatively portrays and describes intermittent method.
Summary of the invention
In order to solve the above problems existing in the present technology, the present invention provides a kind of wind farm group power output is intermittent more
Time scale quantifies depicting method.The present invention climbs statistical parameter to define climbing this parameter of duty ratio, in turn using wind-powered electricity generation
It realizes that wind farm group power output is intermittent quantitatively to portray and describe；Meanwhile fully considering that climbing characteristic is different up and down, is provided with not
Same threshold value.In addition, failing to report problem in order to avoid climbing event, contributed using Multiple Time Scales to following wind farm group
Intermittence is described, and realizes intermittent forecast by establishing statistical regression model.
The purpose of the present invention is what is be achieved through the following technical solutions:
A kind of intermittent Multiple Time Scales of wind farm group power output quantify depicting method, include the following steps:
Step 1: wind power climbing duty ratio is defined, considers the characteristic climbed up and down, surveys history wind function using wind power plant
Rate data obtain the time series of wind power climbing duty ratio, and the time series of the climbing duty ratio is divided into climbing duty ratio
With the time series of lower climbing duty ratio；
Step 2: according to step 1 as a result, establishing wind power climbing duty ratio using SVR (support vector regression method)
Time series statistical regression forecasting model is forecast, intermittent forecast of contributing to the following wind farm group is completed；
Step 3: for reduce be likely to occur fail to report situation, choose multiple time intervals and repeat Step 1: two realize wind
The intermittent Multiple Time Scales of electric field group power output are quantitatively portrayed.
Compared with the prior art, the present invention has the advantage that
1, it proposes and defines wind power climbing this index of duty ratio quantitatively to portray wind-powered electricity generation intermittence.
2, fully consider that climbing characteristic is different up and down.
3, by carrying out Modeling and Prediction to parameter, risk assessment is carried out for electric system, rational management allowance is determined etc. and mentions
For decision support, it is ensured that the stable operation of power system security after wind power integration.
4, it takes Multiple Time Scales to portray, reduces the case where failing to report.
Detailed description of the invention
Fig. 1 is the flow diagram of the method for the present invention；
Fig. 2 is the wind field power climbing duty ratio timing diagram at 1 month interval 15min；
Fig. 3 is the wind field power climbing duty ratio timing diagram at 1 month interval 30min；
Fig. 4 is the wind field power climbing duty ratio timing diagram at 1 month interval 60min；
Fig. 5 is timing diagram of climbing on the wind field power at the interval 15min；
Fig. 6 is timing diagram of climbing under the wind field power at the interval 15min；
Fig. 7 is wind power plant climbing duty ratio SVR forecast result.
Specific embodiment
Further description of the technical solution of the present invention with reference to the accompanying drawing, and however, it is not limited to this, all to this
Inventive technique scheme is modified or replaced equivalently, and without departing from the spirit and scope of the technical solution of the present invention, should all be covered
Within the protection scope of the present invention.
The present invention provides a kind of intermittent Multiple Time Scales of wind farm group power output to quantify depicting method, mentality of designing
It is as follows: to define the concept of wind power climbing duty ratio first, on the basis of wind power plant surveys historical data, obtain wind power and climb
The time series of slope duty ratio；The difference for fully considering climbing with lower climbing simultaneously, respectively obtains wind power using this method
The abrupt change duty cycle time sequence climbed above and below；Wind power climbing duty ratio statistical regression forecasting model is established on this basis,
Wind power climbing duty ratio is forecast, and is realized using multi-scale method to the intermittent essence of following wind farm group power output
The amount of determination is portrayed.As shown in Figure 1, specifically comprising the following steps:
Step 1: wind power climbing duty ratio is defined, considers the characteristic climbed up and down, surveys history wind function using wind power plant
Rate data obtain wind power climbing duty ratio time series, can be divided into detail climbing duty ratio and it is lower climbing duty ratio when
Between sequence.
In this step, wind power climbing duty ratio is defined as follows:
The wind power of note t moment and t+ Δ t be respectively P (t) and P (t+ Δ t), then in Δ t time interval wind power change
Change amount Δ P (t)=P (t+ Δ t)-P (t).For wind power variation, combines on the basis of existing document and climb not up and down
With the threshold value P for providing climbing eventth1With the threshold value P of lower climbing eventth2, as Δ P (t) > Pth1When, show that wind power occurs
Upper climbing event；As Δ P (t) < Pth2When, show that lower climbing event has occurred in wind power.Cycle T is taken (to can be 1 hour
Or 1 day) in wind power sequence, calculate the wind power variation sequence { Δ P (t) } at given time interval Δ t, together
When statistic period T in wind power occur on climb event and lower climbing event number, be denoted as N respectively1And N2, the climbing of wind power
The total degree of event is N (N=N1+N2), on this basis, wind power climbing duty ratio λ is defined as follows:
Likewise, climbing duty ratio λ on wind power can also be definedupWith the duty ratio λ that climbs under wind powerdown:
Wind power climbing duty ratio actually indicates that ratio shared by climbing event occurs for wind power in a period of time, takes
Being worth range is [0,1].λ is bigger, shows that wind power climbing duration is longer in a period of time, then wind power in the period
Intermittence it is stronger；Otherwise λ is smaller, shows that wind power time of climb is short in a period of time, wind power in the period
It is intermittent weaker.Thus we can realize the quantitative quarter to wind power intervals with wind power climbing this parameter of duty ratio
It draws.
By the definition of above-mentioned wind power climbing duty ratio it can be seen that it has with the number of climbing and lower climbing on wind power
It closes, and the judgement of climbing event and the threshold value P given in advance occur for wind powerth1And Pth2It is related, so needing to provide threshold value
Determine method.In the present invention, the two threshold values are provided using the method for rated power percentage.And the selection of threshold value and when
Between interval of delta t it is related, correspond to situation it is as shown in table 1.
The time interval and its corresponding threshold value of 1 catastrophic event of table
PRRepresent the rated power of wind power plant.
On the basis of the above, it is based on true wind power data, calculates climbing duty ratio.All wind function in the present invention
The sampling interval of rate data is 5s, and electric system is dispatched a few days ago was formulated as unit of hour, therefore time at this time
Interval of delta t is selected as 1h, and period T is taken as 1 day.
Step 2: according to step 1 as a result, establishing wind power climbing duty cycle time sequence statistic Regression Forecasting Model
It is forecast, completes intermittent forecast of contributing to the following wind farm group.
Statistical regression methods utilize data statistics principle, carry out Mathematical treatment to a large amount of statistical data, and determine dependent variable
With the correlativity of certain independents variable, the regression equation (function expression) of a good relationship is established, and is extrapolated, is used
In the analysis method of the variation of the dependent variable of prediction from now on.The linear recurrence of currently used method, ridge regression, supporting vector are returned
Return (SVM) and BP neural network method etc..
This step establishes statistical regression forecasting model to wind function on the basis that analysis wind power climbing duty ratio can be forecast
Rate climbing duty ratio is forecast that completion is intermittent to following wind farm group power output quantitatively to portray.It is forecast using statistical regression
Model forecasts 1 hour in advance, in advance 2 hours and 3 hours in advance wind power climbing duty ratio, to following wind-powered electricity generation
Field group's power output intermittence is quantitatively described.It equally can also be to duty ratio of climbing under climb on wind power duty ratio and wind power
It is forecast.
Step 3: for reduce be likely to occur fail to report situation, choose multiple time intervals and repeat Step 1: two realize wind
The intermittent Multiple Time Scales of electric field group power output are quantitatively portrayed.
Actually climbing prediction in, if threshold value choose it is excessive if easily fail to report, and will cause it is excessive when real-time control, in turn
Large effect can be caused to electric network active balance and frequency stabilization.Therefore, the present invention is quantitatively portrayed using Multiple Time Scales
Wind farm group power output is intermittent.Specific step is as follows:
On the basis of step 1, it successively is divided into 15min, 30min and 60min between access time, is determined according to table 1 corresponding
Threshold value, the corresponding period is chosen for 1h, 1h and 1 day.Repeat step 1 later portrays work, obtains corresponding wind function
Rate climbing duty cycle time sequence, repeats the prediction work of step 2, takes their union as final result.So far, complete
Depicting method is quantified at the intermittent Multiple Time Scales of wind farm group power output.
Electric system can formulate the operation plan of more reasonable economy according to the forecast result of wind power climbing duty ratio,
More spare capacity is provided in the wind power intervals stronger period, and it is reserved in the wind power intervals weaker period
Less spare capacity.
Step 1: three result is as shown in figs. 1 to 6, Fig. 1~3 be followed successively by between access time be divided into 15min, 30min,
The timing diagram of climbing duty ratio in 1 month of 60min, it can be seen that with the increase of time interval, the width for duty ratio of climbing
Value and frequency can reduce, this is because the selection of time interval influences the size of threshold value, selected time interval is bigger, corresponding threshold
It is worth bigger.Multiple time intervals are chosen, corresponding abrupt change duty ratio timing diagram is integrated, it is possible to prevente effectively from because using single
A time interval, which is portrayed, leads to the case where omitting.Climbing duty ratio timing diagram is as shown in Figure 5 and Figure 6 up and down, it can be seen that
Lower climbing duty ratio is climbed on the Amplitude Ration in timing diagram, and duty ratio is big, and the frequency of generation is more.This is because climbing is special up and down
Property it is different so that the selection of threshold value is different, the threshold value of lower climbing is lower than upper climbing.Consider the difference climbed up and down, can keep away
Exempt from accidentally generation by normal event as upper climbing event or by lower climbing event as normal event, improve portray it is accurate
Property.The example of step 2 is as shown in Figure 7, it can be seen that the overall effect of forecast is preferable.
Claims (6)
1. a kind of wind farm group is contributed, intermittent Multiple Time Scales quantify depicting method, it is characterised in that the method includes such as
Lower step:
Step 1: wind power climbing duty ratio is defined, considers the characteristic climbed up and down, surveys history wind power number using wind power plant
According to the time series of wind power climbing duty ratio is obtained, the time series of the climbing duty ratio is divided into climbing duty ratio under
The time series for duty ratio of climbing；
Step 2: according to step 1 as a result, establishing wind power climbing duty cycle time sequence statistic using SVR returns forecast mould
Type is forecast, intermittent forecast of contributing to the following wind farm group is completed；
Step 3: for reduce be likely to occur fail to report situation, choose multiple time intervals and repeat Step 1: two realize wind power plant
The intermittent Multiple Time Scales of group's power output are quantitatively portrayed.
2. wind farm group according to claim 1 is contributed, intermittent Multiple Time Scales quantify depicting method, and feature exists
It is as follows in the method for defining wind power climbing duty ratio:
The wind power of note t moment and t+ Δ t be respectively P (t) and P (t+ Δ t), then in Δ t time interval wind power variable quantity
Δ P (t)=P (t+ Δ t)-P (t)；
For wind power variation, the threshold value P of climbing event is providedth1With the threshold value P of lower climbing eventth2, as Δ P (t) >
Pth1When, show that climbing event has occurred in wind power；As Δ P (t) < Pth2When, show that lower climbing event has occurred in wind power；
The wind power sequence in cycle T is taken, wind power variation sequence { the Δ P at given time interval Δ t is calculated
(t) }, while in statistic period T wind power occur on climb the number of event and lower climbing event, be denoted as N respectively1And N2, wind function
The total degree of rate climbing event is N, N=N1+N2, on this basis, wind power climbing duty ratio λ is defined as follows:
3. wind farm group according to claim 1 is contributed, intermittent Multiple Time Scales quantify depicting method, and feature exists
In the threshold value P of the upper climbing eventth1With the threshold value P of lower climbing eventth2It is carried out using the method for rated power percentage true
It is fixed.
4. wind farm group according to claim 1 or 3 is contributed, intermittent Multiple Time Scales quantify depicting method, feature
It is the threshold value P of the upper climbing eventth1With the threshold value P of lower climbing eventth2Selection it is related with time interval Δ t, it is right
Answer situation as shown in table 1:
The time interval and its corresponding threshold value of 1 catastrophic event of table
PRRepresent the rated power of wind power plant.
5. wind farm group according to claim 1 is contributed, intermittent Multiple Time Scales quantify depicting method, and feature exists
In the step 2, the wind power using statistical regression forecasting model to 1 hour in advance, in advance 2 hours and 3 hours in advance is climbed
Slope duty ratio is forecast, following wind farm group power output intermittence is quantitatively described.
6. wind farm group according to claim 4 is contributed, intermittent Multiple Time Scales quantify depicting method, and feature exists
In the step 3, specific step is as follows:
On the basis of step 1, it successively is divided into 15min, 30min and 60min between access time, corresponding threshold is determined according to table 1
Value, corresponding period are chosen for 1h, 1h and 1 day；Repeat step 1 later portrays work, obtains corresponding wind power and climbs
Slope duty cycle time sequence, repeats the prediction work of step 2, takes their union as final result, so far, completes wind
The intermittent Multiple Time Scales of electric field group power output quantify depicting method.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111582557A (en) * | 2020-04-20 | 2020-08-25 | 哈尔滨工业大学 | Wind power climbing event multi-stage early warning method based on variation function |
| CN111952969A (en) * | 2020-08-14 | 2020-11-17 | 哈尔滨工业大学 | Wind power climbing event direct forecasting method combining generalized source-network-load information |
| CN114254805A (en) * | 2021-11-22 | 2022-03-29 | 华北电力大学 | Time window identification method, device, equipment and storage medium for climbing event |
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Cited By (4)
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| CN111582557A (en) * | 2020-04-20 | 2020-08-25 | 哈尔滨工业大学 | Wind power climbing event multi-stage early warning method based on variation function |
| CN111952969A (en) * | 2020-08-14 | 2020-11-17 | 哈尔滨工业大学 | Wind power climbing event direct forecasting method combining generalized source-network-load information |
| CN111952969B (en) * | 2020-08-14 | 2022-06-10 | 哈尔滨工业大学 | Wind power climbing event direct forecasting method combining generalized source-network-load information |
| CN114254805A (en) * | 2021-11-22 | 2022-03-29 | 华北电力大学 | Time window identification method, device, equipment and storage medium for climbing event |
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Application publication date: 20190920 |