CN105552970A - Method and apparatus for improving accuracy of predicting power of wind power station - Google Patents
Method and apparatus for improving accuracy of predicting power of wind power station Download PDFInfo
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Abstract
The invention provides a method and an apparatus for improving accuracy of predicting power of a wind power station. The method comprises: acquiring a wind power station actual output value and a wind-power-station short-term power prediction curve; according to the wind power station actual output value, predicting a wind power output predicted value by adopting a linear extrapolation and moving smoothing method; according to the wind power output predicted value and the wind-power-station short-term power prediction curve, generating an energy storage system expected output value; and according to energy storage system residual capacity and SOC (System On Chip) operation interval constraints, correcting the energy storage system expected output value. According to the method and the apparatus which are provided by the invention, a small quantity of stored energy can be configured on the basis of excellent short-term power prediction accuracy, and the aim of improving the prediction accuracy to an excellent level is fulfilled, thereby reducing examination loss of the wind power station.
Description
Technical field
The present invention relates to wind energy turbine set power field, particularly relate to a kind of method and the device that improve wind farm power prediction accuracy.
Background technology
Under the overall background of global wind light generation high speed development, be limited to energy storage investment huge, domestic and international Large Copacity stored energy application mainly rests on demonstration phase, and the application scenarios of energy-storage system is also in exploration.Current existing stored energy application is divided into energy storage to be used alone and is used in combination two kinds with other generator units, when applying as separate unit, can be used for stabilizing load peak, peak load shifting etc., participate in frequency adjustment, black starting-up function is provided, also can be used for the energy requirement peak period transfer of user, thus utilize the difference electricity price of electricity market to reduce user's expenditure; The quality of power supply can be improved, strengthen power supply reliability etc.When energy storage and other generator units are used in combination, one is intermittence for the renewable energy power generation such as wind, light and unpredictability, the power stage curve of level and smooth renewable energy power generation unit; Two is the impacts that bring of prediction deviation can alleviating wind, light generating, coordinates auxiliary output, can improve the reliability that unit exports according to prediction case energy storage.Due to the fast development that wind power generation and photovoltaic generation are installed, Large Copacity energy-storage system can smoothly fluctuate by scene with it, regulates the advantages such as honourable output power curve, obtains and pays close attention to and develop.
In current great majority research, the control objectives of energy-storage system is the quality of power supply fluctuation or raising generation of electricity by new energy of smooth wind power, and has no in its examination be applied in wind energy turbine set short term power predictablity rate.
Summary of the invention
The present invention proposes a kind of method and the device that improve wind farm power prediction accuracy, by the energy-storage system of wind energy turbine set configuration certain capacity, to improve accuracy rate and the qualification rate of the prediction of wind energy turbine set short term power.
In order to achieve the above object, the embodiment of the present invention provides a kind of method improving wind farm power prediction accuracy, comprising: obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve; According to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction wind power output predicted value; According to described wind power output predicted value and wind energy turbine set short term power prediction curve, generate energy-storage system and expect force value; According to energy-storage system residual capacity and the constraint of SOC traffic coverage, expect force value correction to described energy-storage system.
Further, in one embodiment, obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve, be specially: obtain from the existing generator unit of wind energy turbine set described wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve.
Further, in one embodiment, according to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction generates wind power output predicted value, specifically comprise: according to described m-1 and the m-2 moment actual go out force value, adopt linear extrapolation recursion to obtain the wind power output value in m moment; Adopt the method for gliding smoothing, moving average process is carried out to the wind power output value in described m moment.
Further, in one embodiment, according to described wind power output predicted value and wind energy turbine set short term power prediction curve, generate energy-storage system and expect force value, also comprise: cubic spline interpolation process is carried out to described wind energy turbine set short term power prediction curve.
Further, in one embodiment, according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expect force value correction to described energy-storage system, comprise: SOC range set of being exerted oneself by rated power is [10%, 90%], SOC range set of maximum power being exerted oneself is [40%, 60%], to judge whether described energy-storage system residual capacity meets described energy-storage system and expect force value, as meet then by as described in energy-storage system desired value exert oneself, if meet then according to as described in energy-storage system residual capacity exert oneself.
In order to achieve the above object, the embodiment of the present invention also provides a kind of device improving wind farm power prediction accuracy, comprising: acquiring unit, for obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve; Wind power output predicted value generating means, for according to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction wind power output predicted value; Energy-storage system is expected force value generation unit, for according to described wind power output predicted value and wind energy turbine set short term power prediction curve, generates energy-storage system and expects force value; Amending unit, for according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expects force value correction to described energy-storage system.
Further, in one embodiment, described acquiring unit be used for obtain from the existing generator unit of wind energy turbine set described wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve.
Further, in one embodiment, described wind power output predicted value generating means specifically comprises: linear extrapolation module, for according to described m-1 and the m-2 moment actual go out force value, adopt linear extrapolation recursion to obtain the wind power output value in m moment; Smoothly exerting oneself module, for adopting the method for gliding smoothing, moving average process being carried out to the wind power output value in described m moment.
Further, in one embodiment, described energy-storage system expects that force value generation unit comprises: interpolation processing module, for carrying out cubic spline interpolation process to described wind energy turbine set short term power prediction curve.
Further, in one embodiment, described amending unit specifically for: SOC range set of being exerted oneself by rated power is [10%, 90%], SOC range set of maximum power being exerted oneself is [40%, 60%], to judge whether described energy-storage system residual capacity meets described energy-storage system and expect force value, as meet then by as described in energy-storage system desired value exert oneself, if meet then according to as described in energy-storage system residual capacity exert oneself.
The method of the raising wind farm power prediction accuracy of the embodiment of the present invention and device, to improve wind energy turbine set short term power predictablity rate and qualification rate for target, by configuring the energy-storage system of certain capacity to wind energy turbine set, integrated application linear extrapolation and gliding smoothing method fast prediction wind energy turbine set are exerted oneself in real time, consider the capacity in energy-storage system range of safety operation and different SOC interval simultaneously, control energy-storage system is exerted oneself, that is: wind energy turbine set can on good short term power predictablity rate basis, configure a small amount of energy storage, reach object prediction accuracy being increased to superior level, use and reduce wind energy turbine set examination loss.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those skilled in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the process chart of the method for the raising wind farm power prediction accuracy of the embodiment of the present invention;
Fig. 2 is the method flow diagram that the design energy-storage system desired value of the embodiment of the present invention exports;
Fig. 3 is the energy-storage system operational factor schematic diagram of the embodiment of the present invention;
Fig. 4 is the process chart of the energy-storage system capacity feedback of the embodiment of the present invention;
Fig. 5 is the structural representation of the device of the raising wind farm power prediction accuracy of the embodiment of the present invention;
Fig. 6 is the structural representation of the wind power output predicted value generating means 102 of the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
At present, the influencing factor mainly accuracy of numerical weather forecast and the precision of prediction algorithm of wind energy turbine set short term power predictablity rate, the present invention supposes that the predictablity rate that this algorithm can reach is determined, on this basis, joins energy storage device improve predictablity rate further by adding.Wherein, the performance assessment criteria to Power Output for Wind Power Field prediction in the computing reference national grid company standard of wind energy turbine set short term power predictablity rate " wind farm power prediction forecast management Tentative Measures ", day wind power predictablity rate:
Wherein: p
mkfor the actual average power in k moment, p
pkfor the prediction average power in k moment, N is total prediction data number, and general computing cycle is 24 hours, and predict frequency is 15 minutes points, totally 96 points, and Cap is that wind field runs installed capacity.
The principle that the present invention is based on is: be input as that wind energy turbine set is actual exerts oneself and wind energy turbine set short term power prediction curve, adopt the method for linear extrapolation and rolling average, the wind power output power of prediction subsequent time (level second), difference is done with short term power predicted value, show that energy-storage system is exerted oneself desired value, consider the restriction of energy-storage system residual capacity and SOC traffic coverage, synthesis exports energy-storage system and to exert oneself instruction, namely by energy-storage system to compensate the precision of wind energy turbine set short-term forecast power, with improve wind energy turbine set short term power prediction accuracy rate.
Therefore, based on above-mentioned general principle, in the present invention, crucial step accurately calculates energy-storage system to expect to exert oneself, and according to energy-storage system capacity to expecting that force value retrains.
Fig. 1 is the process chart of the method for the raising wind farm power prediction accuracy of the embodiment of the present invention.As shown in Figure 1, the method for the present embodiment comprises: step S101, obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve; Step S102, according to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction wind power output predicted value; Step S103, according to described wind power output predicted value and wind energy turbine set short term power prediction curve, generates energy-storage system and expects force value; Step S104, according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expects force value correction to described energy-storage system.
In the present embodiment, in step S101, can obtain from the existing generator unit of wind energy turbine set described wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve.
In step s 102, this step to be exerted oneself in real time history value prediction subsequent time wind power output according to wind energy turbine set.The present invention utilizes linear extrapolation to predict, and uses gliding smoothing method to be optimized.
Linear extrapolation refers to that the historical trend utilizing curve infers future trend, and the present invention utilizes the measured power composition straight line in m-1 and m-2 moment in wind-powered electricity generation history run curve, and the slope of calculated line, utilizes this slope recursion m moment wind power output.The straight slope k of measured power group in m-1 and m-2 moment can be calculated according to formula (2), (3)
m-1, m-2.
y
m＝y
m-1+k
m-1,m-2×Δt(2)
The wherein minimum interval of the desirable wind power output Real-time Collection of Δ t; y
m-1and y
m-2that the actual measurement in wind energy turbine set m-1 moment and m-2 moment goes out activity of force respectively.
Adopt the data accuracy of linear extrapolation method prediction subsequent time higher, can engineer applied be met, but when larger fluctuation occurs data or variation tendency is become decline from rising or had decline to become rising, time delay and the sudden change of stepwise predict data can be caused.Therefore the present invention carries out moving average process to the real time data that linear extrapolation is predicted, such as formula (4), dopes activity of force y to the wind-powered electricity generation m moment calculated through linear extrapolation
mand y
mn number of historical data is before averaged, the result y obtained
m' as y
moptimal value, substitute y
m.
Wherein, N is the number of the history real time data obtained after adopting linear extrapolation prediction and rolling average, y
m-i, i=0,1 ..., N is the history real time data obtained after adopting linear extrapolation prediction and rolling average, and choosing of N can to y
m' prediction accuracy have an impact.
The present invention, on rolling average length of window Selecting research, adopts the method for statistics, calculates the prediction data of many days.Result proves as sliding window length N=3, and precision of prediction is the highest, and following table 1 lists the result of calculation of any three days.
Table 1 rolling average length of window is on the impact of accuracy rate
And, because general wind energy turbine set short term power prediction curve is 15min point, therefore need to be treated as the identical curve of data sampling of exerting oneself in real time with wind-powered electricity generation, consider that short-term forecast curve is comparatively level and smooth, therefore adopt cubic spline interpolation process wind energy turbine set short term power prediction curve.
According to said method, design the method flow diagram of energy-storage system desired value output as shown in Figure 2:
Step S201, obtains wind-powered electricity generation and goes out force data in real time;
Step S202, reads wind-powered electricity generation and goes out two nearest some P of force data in real time
m-2, P
m-1;
Step S203, asks 2 slope k formed;
Step S204, with slope k linear extrapolation subsequent time wind power output P
m;
Step S205, uses predicted value P
mupgrade predicted value with historical data moving average, in the present embodiment, the length adopting sliding window is 3, namely asks P
m-2, P
m-1, P
maverage value P
m';
Step S206, obtains wind-powered electricity generation short term power prediction curve;
Step S207, does cubic spline interpolation process to this wind-powered electricity generation short term power prediction curve;
Step S208, reads the wind power output predicted value P in m moment
a;
Step S209, by the wind power output predicted value P after renewal
m' predict the predicted value P of corresponding point with short term power
adifference to exert oneself desired value P as energy-storage system
bat, i.e. P
bat=P
m'-P
a.
Certainly, in the present embodiment, the order of step S206-S208 does not also mean that after step S201-S205, and both can carry out simultaneously, or the order of S206-S208 is before step S201-S205.
In step S104 embodiment illustrated in fig. 1, according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expect force value correction to described energy-storage system, comprise: SOC range set of being exerted oneself by rated power is [10%, 90%], SOC range set of maximum power being exerted oneself is [40%, 60%], to judge whether described energy-storage system residual capacity meets described energy-storage system and expect force value, as meet then by as described in energy-storage system desired value exert oneself, if meet then according to as described in energy-storage system residual capacity exert oneself.
SOC traffic coverage, when considering energy-storage system units limits, has been carried out more careful segmentation by the present invention.That is: exert oneself interval, rated power of maximum power is divided in SOC interval to exert oneself interval and dangerous interval of exerting oneself.Energy-storage system rated power, rated capacity and SOC range of operation is considered in each interval.
Energy-storage system operational factor designed by the present invention as shown in Figure 3, exert oneself rated power P by energy-storage system
n, the rated capacity of its correspondence is Q
n; Maximum output power (being generally limited to current transformer) P
max, its correspondence rated capacity be Q
max; For protection battery extends energy-storage system useful life, avoid energy-storage system to be operated in SOC two ends, SOC range set of being exerted oneself by rated power is [10%, 90%], maximum power is exerted oneself, and SOC range set is [40%, 60%].
Fig. 4 is the process chart of the energy-storage system capacity feedback of the embodiment of the present invention.As shown in Figure 4:
Step S401, the initial condition of setting energy-storage system;
Step S402, judges the SOC in m-1 moment;
Step S403, according to the current SOC state of energy-storage system, judge that whether energy-storage system is in SOC safe operation interval [10%, 90%], if operate in security interval [10%, 90%], then enter step S405, if do not operate in security interval [10%, 90%], then enter step S404;
Step S404, exceeds safe range, and energy-storage system is exerted oneself P
bbe 0, wait for that next discharge and recharge switch instant judges again;
Step S405, judges whether the traffic coverage [40%, 60%] of exerting oneself at permission 1.5 times of rated power, if allowed, then enters step S406, does not allow, enter step S409;
Step S406, judges residual capacity P
maxwhether meet energy storage to expect force value P
bkif, i.e. P
bk>=P
max, then step S407 is entered, if P
bk≤ P
max, enter step S408;
Step S407, according to residual capacity P
maxexert oneself, i.e. P
b=P
max;
Step S408, by desired value P
bkexert oneself, i.e. P
b=P
bk;
Step S409, if exceed traffic coverage [40%, 60%], but at security interval [10%, 90%], and if energy storage expect force value P
bk>=0, then enter step S410 and step S411 respectively;
Step S410, when SOC is near 0.1, judges whether the current lower limit of exerting oneself of the stored energy capacitance of energy-storage system is greater than energy storage and expects to exert oneself P
bk, if so, then enter step S412, expect force value P according to energy storage
bkexert oneself, i.e. P
b=P
bk, if not, then enter step S413, exert oneself according to the stored energy capacitance of energy-storage system, namely
Step S411, when SOC is near 0.9, judges whether the current lower limit of exerting oneself of the stored energy capacitance of energy-storage system is greater than energy storage and expects to exert oneself P
bk, if so, then enter step S414, expect force value P according to energy storage
bkexert oneself, i.e. P
b=P
bk, if not, then enter step S415, exert oneself according to the stored energy capacitance of energy-storage system, namely
At SOC borderline region, may occur that residual capacity can not maintain and exert oneself with rated power next second, therefore can the present invention consider residual capacity simultaneously and meet energy-storage system with desired value continuous output.
Based on same design, the embodiment of the present invention also provides a kind of device improving wind farm power prediction accuracy, as shown in Figure 5, comprising: acquiring unit 101, for obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve; Wind power output predicted value generating means 102, for according to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction wind power output predicted value; Energy-storage system is expected force value generation unit 103, for according to described wind power output predicted value and wind energy turbine set short term power prediction curve, generates energy-storage system and expects force value; Amending unit 104, for according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expects force value correction to described energy-storage system.
Concrete, described acquiring unit 101 for obtain from the existing generator unit of wind energy turbine set described wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve.
Concrete, as shown in Figure 6, described wind power output predicted value generating means 102 specifically comprises: linear extrapolation module 1021, for according to described m-1 and the m-2 moment actual go out force value, adopt linear extrapolation recursion to obtain the wind power output value in m moment; Smoothly exerting oneself module 1022, for adopting the method for gliding smoothing, moving average process being carried out to the wind power output value in described m moment.
Concrete, described energy-storage system expects that force value 103 generation unit comprises: interpolation processing module, for carrying out cubic spline interpolation process to described wind energy turbine set short term power prediction curve.
Concrete, described amending unit 104 specifically for: SOC range set of being exerted oneself by rated power is [10%, 90%], SOC range set of maximum power being exerted oneself is [40%, 60%], to judge whether described energy-storage system residual capacity meets described energy-storage system and expect force value, as meet then by as described in energy-storage system desired value exert oneself, if meet then according to as described in energy-storage system residual capacity exert oneself.
The present invention is to improve wind energy turbine set short term power predictablity rate and qualification rate for target, and by wind energy turbine set configuration certain capacity energy-storage system, research energy-storage system is exerted oneself control strategy.Integrated application linear extrapolation and gliding smoothing method fast prediction wind energy turbine set are exerted oneself in real time, consider the capacity in energy-storage system range of safety operation and different SOC interval simultaneously, control energy-storage system is exerted oneself, can ensure that energy-storage system is operated in area of safety operaton, and not exceed the upper limit of exerting oneself in different SOC interval.Meanwhile, wind energy turbine set short term power predictablity rate and qualification rate can be improved, reduce wind energy turbine set examination loss.
Those skilled in the art should understand, embodiments of the invention can be provided as method, system or computer program.Therefore, the present invention can adopt the form of complete hardware embodiment, completely software implementation or the embodiment in conjunction with software and hardware aspect.And the present invention can adopt in one or more form wherein including the upper computer program implemented of computer-usable storage medium (including but not limited to magnetic disc store, CD-ROM, optical memory etc.) of computer usable program code.
The present invention describes with reference to according to the flow chart of the method for the embodiment of the present invention, equipment (system) and computer program and/or block diagram.Should understand can by the combination of the flow process in each flow process in computer program instructions realization flow figure and/or block diagram and/or square frame and flow chart and/or block diagram and/or square frame.These computer program instructions can being provided to the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing device to produce a machine, making the instruction performed by the processor of computer or other programmable data processing device produce device for realizing the function of specifying in flow chart flow process or multiple flow process and/or block diagram square frame or multiple square frame.
These computer program instructions also can be stored in can in the computer-readable memory that works in a specific way of vectoring computer or other programmable data processing device, the instruction making to be stored in this computer-readable memory produces the manufacture comprising command device, and this command device realizes the function of specifying in flow chart flow process or multiple flow process and/or block diagram square frame or multiple square frame.
These computer program instructions also can be loaded in computer or other programmable data processing device, make on computer or other programmable devices, to perform sequence of operations step to produce computer implemented process, thus the instruction performed on computer or other programmable devices is provided for the step realizing the function of specifying in flow chart flow process or multiple flow process and/or block diagram square frame or multiple square frame.
Apply specific embodiment in the present invention to set forth principle of the present invention and execution mode, the explanation of above embodiment just understands method of the present invention and core concept thereof for helping; Meanwhile, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (10)
1. improve a method for wind farm power prediction accuracy, it is characterized in that, comprising:
Obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve;
According to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction wind power output predicted value;
According to described wind power output predicted value and wind energy turbine set short term power prediction curve, generate energy-storage system and expect force value;
According to energy-storage system residual capacity and the constraint of SOC traffic coverage, expect force value correction to described energy-storage system.
2. the method for raising wind farm power prediction accuracy according to claim 1, is characterized in that, obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve, be specially:
Obtain from the existing generator unit of wind energy turbine set described wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve.
3. the method for raising wind farm power prediction accuracy according to claim 1, is characterized in that, according to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction generates wind power output predicted value, specifically comprises:
According to described m-1 and the m-2 moment actual go out force value, adopt linear extrapolation recursion to obtain the wind power output value in m moment;
Adopt the method for gliding smoothing, moving average process is carried out to the wind power output value in described m moment.
4. the method for raising wind farm power prediction accuracy according to claim 3, is characterized in that, according to described wind power output predicted value and wind energy turbine set short term power prediction curve, generates energy-storage system and expects force value, also comprise:
Cubic spline interpolation process is carried out to described wind energy turbine set short term power prediction curve.
5. the method for raising wind farm power prediction accuracy according to claim 1, is characterized in that, according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expects force value correction, comprising described energy-storage system:
SOC range set of being exerted oneself by rated power is [10%, 90%], SOC range set of maximum power being exerted oneself is [40%, 60%], to judge whether described energy-storage system residual capacity meets described energy-storage system and expect force value, as meet then by as described in energy-storage system desired value exert oneself, if meet then according to as described in energy-storage system residual capacity exert oneself.
6. improve a device for wind farm power prediction accuracy, it is characterized in that, comprising:
Acquiring unit, for obtain wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve;
Wind power output predicted value generating means, for according to described wind energy turbine set actual go out force value, adopt the method for linear extrapolation and gliding smoothing, prediction wind power output predicted value;
Energy-storage system is expected force value generation unit, for according to described wind power output predicted value and wind energy turbine set short term power prediction curve, generates energy-storage system and expects force value;
Amending unit, for according to energy-storage system residual capacity and the constraint of SOC traffic coverage, expects force value correction to described energy-storage system.
7. the device of raising wind farm power prediction accuracy according to claim 6, is characterized in that, described acquiring unit be used for obtain from the existing generator unit of wind energy turbine set described wind energy turbine set actual go out force value and wind energy turbine set short term power prediction curve.
8. the device of raising wind farm power prediction accuracy according to claim 6, is characterized in that, described wind power output predicted value generating means specifically comprises:
Linear extrapolation module, for according to described m-1 and the m-2 moment actual go out force value, adopt linear extrapolation recursion to obtain the wind power output value in m moment;
Smoothly exerting oneself module, for adopting the method for gliding smoothing, moving average process being carried out to the wind power output value in described m moment.
9. the device of raising wind farm power prediction accuracy according to claim 8, is characterized in that, described energy-storage system expects that force value generation unit comprises:
Interpolation processing module, for carrying out cubic spline interpolation process to described wind energy turbine set short term power prediction curve.
10. the device of raising wind farm power prediction accuracy according to claim 6, is characterized in that, described amending unit specifically for:
SOC range set of being exerted oneself by rated power is [10%, 90%], SOC range set of maximum power being exerted oneself is [40%, 60%], to judge whether described energy-storage system residual capacity meets described energy-storage system and expect force value, as meet then by as described in energy-storage system desired value exert oneself, if meet then according to as described in energy-storage system residual capacity exert oneself.
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