CN104135036A - Method for analyzing contribution of intermittent energy source based on time domain and constellation effect - Google Patents

Abstract

The invention discloses a method for analyzing the contribution of an intermittent energy source based on time domain and a constellation effect, belonging to the technical field of new energy source generation and grid connection. The method comprises the following steps of: counting real-time contribution data of an intermittent energy source wind power station, and performing volatility analysis on the contribution of the intermittent energy source wind power station from three levels of time scales; calculating the constellation effect of an intermittent energy source wind power station cluster; and determining relevance and complementary among the intermittent energy source wind power stations according to the constellation effect among the intermittent energy source wind power stations. According to the method, the volatility analysis is performed on the contribution from different levels of time scales, and an adjustment basis is provided for the wind power station; based on the running of levels of time scales, the current dispatching, pitch peak and spare capacity of a machine set are calculated according to six divided volatility types; and constellation effect indexes are overfitted by a hybrid Gaussian distribution method and introduced into a confidence interval, and the constellation effect intensities at different installed capacities are effectively calculated.

Description

A kind ofly analyze based on time domain and constellation effect the method that intermittent energy source is exerted oneself

Technical field

The invention belongs to generation of electricity by new energy interconnection technology field, particularly a kind ofly analyze based on time domain and constellation effect the method that intermittent energy source is exerted oneself.

Background technology

The regenerative resource such as wind-powered electricity generation and photovoltaic has intermittence, the feature of fluctuation and randomness, therefore their intermittent energy source that is otherwise known as.Because intermittence has determined regenerative resource and has had uncertain fluctuation, and this is the reason that intermittent energy source is accessed to electrical network and it is exerted an influence.In the time that the permeability of intermittent energy source arrives certain level, this power fluctuation that can not control will bring adverse influence to meritorious, the reactive balance of electrical network, both affect the voltage levvl of electrical network and stablizing of frequency, affected again the arrangement of for subsequent use and peak of the whole network.All the time owing to lacking comprehensively careful intermittent energy source fluction analysis, to such an extent as to the impact of the fluctuation that is difficult to hold intermittent energy source on electrical network, this is very disadvantageous for improving the dissolve ability of intermittent energy source of electrical network.

Because wind energy turbine set covering region is larger, the difference on the wind energy meeting Existential Space that in, different blower fans are accepted, the fluctuation of wind power is tending towards relaxing with the increase of spatial distribution yardstick, and this effect is called constellation effect.Constellation effect affects the output of whole electric field to electrical network.The constellation effect of effectively analyzing wind energy turbine set has great significance to fan-out capability and the fluctuation of holding wind energy turbine set.

At present the fluctuation analysis of intermittent energy source is focused mostly in the fluctuation analysis of long-term and short-term two aspects, draw the power fluctuation characteristic of long-term and short-term, but which kind of impact indefinite is this fluctuation wear to which side of power plant and electrical network, can say that purpose is not strong.And, ignore the impact of constellation effect on whole electric field output.

Summary of the invention

The problem existing for above-mentioned prior art, the present invention proposes a kind ofly to analyze based on time domain and constellation effect the method that intermittent energy source is exerted oneself, and it is characterized in that, and the method comprises:

Statistics intermittent energy source wind energy turbine set go out in real time force data, from three kinds of rank time scales, exerting oneself of intermittent energy source wind energy turbine set carried out to fluctuation analysis;

Calculate the constellation effect of intermittent energy source wind farm group;

For the constellation effect between intermittent energy source wind energy turbine set, determine correlation and complementarity between intermittent energy source wind energy turbine set.

Described three kinds of rank time scales are respectively planning rank time scale, runlevel time scale and control hierarchy time scale.

Describedly from three kinds of rank time scales, exerting oneself of intermittent energy source wind energy turbine set carried out to fluctuation analysis and is specially:

For planning rank time scale, analyze monthly, season of intermittent energy source wind energy turbine set and the fluctuation of exerting oneself in year;

The fluctuation of exerting oneself in monthly and season of described analysis intermittent energy source wind energy turbine set comprises statistics active power and capacity factor;

The fluctuation of exerting oneself in year of described analysis intermittent energy source wind energy turbine set comprises that calculating annual utilization hours, annual mean wind speed and annual exerts oneself;

For runlevel time scale, calculate the capacity factor of intermittent energy source wind energy turbine set, the fluctuation type of the daily output curve to intermittent energy source wind energy turbine set is added up, and determines the wave characteristic of intermittent energy source wind energy turbine set daily output;

For control hierarchy time scale, calculate the exert oneself probability distribution of undulate quantity of intermittent energy source wind energy turbine set level second, minute level and hour level, determine between the intermittent energy source output of wind electric field wave zone under different probability.

Described capacity factor is intermittent energy source output of wind electric field under mean wind speed and the ratio of its rated power.

The fluctuation type of described daily output curve is:

When intermittent energy source wind energy turbine set daily output per unit value is all less than capacity factor, fluctuation type is the interval Wave type of low value;

Intermittent energy source wind energy turbine set daily output curve is the rear downward trend that first rises, and fluctuation type is convex;

Intermittent energy source wind energy turbine set daily output curve is the trend that first declines and rise afterwards, and fluctuation type is spill;

Intermittent energy source wind energy turbine set daily output curve is totally in rising trend, and fluctuation type is ascending-type;

Intermittent energy source wind energy turbine set daily output curve is totally on a declining curve, and fluctuation type is down type;

In other situation, fluctuation type is the interval Wave type of high value.

The constellation effect of described calculating intermittent energy source wind farm group is specially:

Step 1: set up constellation effect index set S and calculate its distribution histogram;

Described constellation effect index set S is:

S＝{X ₁，X ₂，···，X _i’，···，X _n}；

Wherein, n represents number of days; X _{i '}=max{x _{t, i '}, 0<=t<24; x _{t, i '}represent the constellation effect desired value of t period in i' days, X _{i '}represent the maximum of i' days all period constellation effect desired values;

Step 2: utilize the regularity of distribution of mixed Gaussian method matching S, obtain probability density function;

Described probability density function is:

$f\left(x\right)=\underset{j=1}{\overset{n^{\&prime;}}{\mathrm{\&Sigma;}}}{\mathrm{\&alpha;}}_{j}N({\mathrm{\&mu;}}_j,{\mathrm{\&sigma;}}_j^2);$

Wherein, the number of n ' expression Gaussian function; α _jrepresent j the weight that Gaussian function is corresponding;

Step 3: introduce confidential interval R, calculate the constellation effect desired value in confidential interval, its computing formula is:

P(X _i′≤R)＝p；

Wherein, p is given probable value.

Described constellation effect index comprises maximum output ratio, maximum fluctuation ratio, peak value simultaneity factor and peak-valley difference ratio;

The computing formula of described maximum output ratio is:

The computing formula of described maximum fluctuation ratio is:

The computing formula of described peak value simultaneity factor is:

The computing formula of described peak-valley difference ratio is:

Wherein, V _pmrepresent maximum output ratio;

P _{Σ max}represent the total meritorious maximum of exerting oneself of intermittent energy source wind energy turbine set cluster;

Σ P _krepresent the rated power sum of all blower fans in intermittent energy source wind energy turbine set cluster;

P _krepresent the rated power of k blower fan in intermittent energy source wind energy turbine set cluster;

C _{Δ PS}represent maximum fluctuation ratio;

Δ P _maxrepresent the maximum of intermittent energy source wind energy turbine set cluster gross power undulate quantity;

C _oinrepresent peak value simultaneity factor;

Σ P _imaxrepresent each sub-electric field maximum output sum separately in intermittent energy source wind energy turbine set cluster;

P _imaxrepresent the maximum output of i sub-electric field in intermittent energy source wind energy turbine set cluster;

C _{Δ P}represent peak-valley difference ratio;

P _{Σ min}represent the total meritorious minimum value of exerting oneself of intermittent energy source wind energy turbine set cluster.

The computing formula of the correlation between described intermittent energy source wind energy turbine set is:

$C_r=\frac{\mathrm{\&Sigma;}(X-\stackrel{\&OverBar;}{X})(Y-\stackrel{\&OverBar;}{Y})}{\sqrt{\mathrm{\&Sigma;}{(X-\stackrel{\&OverBar;}{X})}^2}\sqrt{\mathrm{\&Sigma;}{(Y-\stackrel{\&OverBar;}{Y})}^2}};$

Wherein, C _rthe coefficient correlation that the wind-powered electricity generation of two sub-electric fields of intermittent energy source of expression is exerted oneself; X, Y represents that respectively the wind-powered electricity generation of two sub-electric fields of intermittent energy source exerts oneself, for the wind-powered electricity generation of two sub-electric fields of intermittent energy source in the statistical time range mean value of exerting oneself;

If C _r> 0 intermittent energy source has positive correlation, and total fluctuation that goes out increases; If C _r< 0 intermittent energy source has negative correlation, and total fluctuation that goes out reduces.

The beneficial effect of the invention: (1) the present invention is from three ranks (planning level, runtime class, controlled stage) time scale on intermittent energy source gone out to fluctuation analysis, determine its power producing characteristics, be the planning of intermittent energy source wind energy turbine set targetedly, operation and control plane provide adjustment foundation; (2) in runtime class time scale, to go out fluctuation and be divided into six kinds of Wave types, can give prominence to intuitively the interval that fluctuation tendency that intermittent energy source exerts oneself and peak-to-valley value thereof occur, making to find the anti-peak regulation period becomes more easy, can be targetedly according to different Wave types the exert oneself scheduling a few days ago of its unit of analysis and calculation and peak regulation and reserve capacity; (3) utilizing mixed Gaussian distribution matching constellation effect index, introduce confidential interval, effectively calculate the constellation effect intensity under different installed capacitys, is the dispatching of power netwoks after grid-connected, and power division provides more Data support.

Brief description of the drawings

Fig. 1 is the inventive method flow chart;

Fig. 2 is for judging intermittent energy source output of wind electric field Wave type flow chart;

Fig. 3 is geographical position and the relative distance schematic diagram of 5 wind energy turbine set in Hainan Region;

Fig. 4 is the monthly capacity factor of wind energy turbine set in 2011;

Fig. 5 be high climing, sense city, four more with Wenchang wind energy turbine set 24h wind-powered electricity generation capacity factor;

Fig. 6 be high climing, sense city, four more with Wenchang wind energy turbine set daily output fluctuation all kinds probability distribution;

Fig. 7 is the typical curve of the different fluctuation of wind-powered electricity generation type:

Fig. 8 is a) 30s interval wind energy turbine set power waves momentum;

Fig. 8 is b) 1min interval wind energy turbine set power waves momentum;

Fig. 8 is c) 15min interval wind energy turbine set power waves momentum;

Fig. 8 is d) 1 hour interval wind energy turbine set power waves momentum;

Fig. 9 is a) a day probability distribution histogram for maximum output ratio;

Fig. 9 is b) a day probability distribution histogram for maximum fluctuation ratio;

Fig. 9 is c) a day probability distribution histogram for peak value simultaneity factor;

Fig. 9 is d) a day probability distribution histogram for peak-valley difference ratio;

Figure 10 is a) a day mixed Gaussian distribution map for maximum output ratio;

Figure 10 is b) a day mixed Gaussian distribution map for maximum fluctuation ratio;

Figure 10 is c) a day mixed Gaussian distribution map for peak value simultaneity factor;

Figure 10 is d) a day mixed Gaussian distribution map for peak-valley difference ratio;

Figure 11 is the different units of high climing wind energy turbine set at the change curve of exerting oneself of a day;

Figure 12 is the more change curve of exerting oneself of two wind energy turbine set of Wenchang and four.

Embodiment

Below in conjunction with drawings and Examples, the inventive method is described further.

Traditional only starts with from Long-term Fluctuation and short-term fluctuation two aspects to the fluctuation analysis of intermittent energy source, purpose is not strong, and ignore the impact of constellation effect on whole electric field output, so what the present invention had considered different time domain aspect intermittent energy source goes out fluctuation and constellation effect, propose a kind ofly to analyze based on time domain and constellation effect the method that intermittent energy source is exerted oneself, as shown in Figure 1, the method comprises its flow process:

First, statistics intermittent energy source wind energy turbine set go out in real time force data, from three kinds of rank time scales, exerting oneself of intermittent energy source wind energy turbine set carried out to fluctuation analysis, be the planning of intermittent energy source wind energy turbine set targetedly, move and control plane provides adjustment foundation.

For planning rank time scale, analyze the fluctuation of exerting oneself in monthly and season of intermittent energy source wind energy turbine set, it comprises statistics active power and capacity factor; Analyze the fluctuation of exerting oneself in year of intermittent energy source wind energy turbine set, it comprises that calculating annual utilization hours, annual mean wind speed and annual exerts oneself, determine that annual mean wind speed and wind-powered electricity generation annual are exerted oneself and with the linear approximate relationship of annual utilization hours.

For runlevel time scale, calculate the capacity factor of intermittent energy source wind energy turbine set, the fluctuation type of the daily output curve to intermittent energy source wind energy turbine set is added up, and determines the wave characteristic of intermittent energy source wind energy turbine set daily output.

The inventive method has marked off six kinds of intermittent energy source and has gone out fluctuation type, makes to find the anti-peak regulation period to become more easy, can be targetedly according to different Wave types the exert oneself scheduling a few days ago of its unit of analysis and calculation and peak regulation and reserve capacity.Six kinds of intermittent energy source go out fluctuation type and are defined as:

What fluctuation was less exert oneself focuses mostly on below capacity factor, and therefore, what intermittent energy source wind energy turbine set daily output per unit value (relative value, unit is p.u.) was all less than to capacity factor is called the interval Wave type of low value.Wherein, capacity factor is intermittent energy source output of wind electric field under mean wind speed and the ratio of its rated power, due to mean wind speed bad calculation, so with " average power " approximate replacement " mean wind speed " calculated capacity factor.Because the mean wind speed under different stage time scale is different, so capacity factor is also different.

The daily output fluctuation that intermittent energy source wind energy turbine set daily output per unit value is distributed in more than capacity factor has obvious rule:

1) intermittent energy source wind energy turbine set daily output curve is the rear downward trend that first rises, and curve fluctuation type is called convex;

2) intermittent energy source wind energy turbine set daily output curve is the trend that first declines and rise afterwards, and curve fluctuation type is called matrix;

3) intermittent energy source wind energy turbine set daily output curve is totally in rising trend, and curve fluctuation type is called ascending-type;

4) intermittent energy source wind energy turbine set daily output curve is totally on a declining curve, and curve fluctuation type is called down type;

5) other, the higher and erratic wind-powered electricity generation fluctuation that fluctuates of intermittent energy source output of wind electric field is called the interval Wave type of high value.

The method of determining intermittent energy source output of wind electric field Wave type is as follows:

Adopt priority principle to judge it for the fluctuation type of arbitrary intermittent energy source output of wind electric field, that is: first, the type that fluctuates because low value is interval is exerted oneself lower, and fluctuation range is less and the most general, so judgement at first, priority is one-level; Secondly, because the curvilinear motion rule of convex, spill, down type and ascending-type is relatively obvious, there is feature separately, comparatively easily distinguish, so priority is secondary; Finally, because all the other curves of cyclical fluctuations are exerted oneself generally large and there is no an obvious fluctuating characteristic, for ensureing that fluctuation classification of change contains all curves, so be all summarized as the interval Wave type of high value, priority is three grades.

Known one day intermittent energy source wind energy turbine set daily output curve, calculate 0:00～8:00,8:00～16:00, in tri-time periods of 16:00～24:00, the mean value of wind-powered electricity generation active power of output (being per unit value p.u.), is designated as respectively P1, P2, P3, capacity factor is made as δ, judges the step of its Wave type as shown in Figure 2, is specially:

If P1< δ and P2< δ and P3< δ, be judged to be low value interval fluctuation type (one-level);

If P1<P2 and P2>P3, be judged to be convex (secondary);

If P1<P2<P3, is judged to be ascending-type (secondary);

If P1>P2>P3, is judged to be down type (secondary);

If P1>P2 and P2<P3, be judged to be matrix (secondary);

Otherwise, be judged to be the high interval Wave type of value (three grades).

For control hierarchy time scale, calculate the exert oneself probability distribution of undulate quantity of intermittent energy source wind energy turbine set level second, minute level and hour level, determine between the intermittent energy source output of wind electric field wave zone under different probability.

Secondly, calculate the constellation effect of intermittent energy source wind farm group.

Step 1: set up constellation effect index set S and calculate its distribution histogram.

Constellation effect index comprises maximum output ratio, maximum fluctuation ratio, peak value simultaneity factor and peak-valley difference ratio.

The computing formula of maximum output ratio is:

The computing formula of maximum fluctuation ratio is:

The computing formula of peak value simultaneity factor is:

The computing formula of peak-valley difference ratio is:

V _pmrepresent maximum output ratio;

P _{Σ max}represent the total meritorious maximum of exerting oneself of intermittent energy source wind energy turbine set cluster;

Σ P _krepresent the rated power sum of all blower fans in intermittent energy source wind energy turbine set cluster, i.e. the rated power of whole wind energy turbine set cluster;

P _krepresent the rated power of k blower fan in intermittent energy source wind energy turbine set cluster;

C _{Δ PS}represent maximum fluctuation ratio;

Δ P _maxrepresent the maximum of intermittent energy source wind energy turbine set cluster gross power undulate quantity;

C _oinrepresent peak value simultaneity factor;

Σ P _imaxrepresent each sub-electric field maximum output sum separately in intermittent energy source wind energy turbine set cluster;

P _imaxrepresent the maximum output of i sub-electric field in intermittent energy source wind energy turbine set cluster;

C _{Δ P}represent peak-valley difference ratio;

P _{Σ min}represent the total meritorious minimum value of exerting oneself of intermittent energy source wind energy turbine set cluster, P _{Σ min}with P _{Σ max}to solve mode identical.

P _{Σ max}with Σ P _imaxaccount form difference, for example, every sub-wind energy turbine set has 24 data points (per hour), P _{Σ max}be first 24 data points of all sub-wind energy turbine set to be sued for peace separately, then the value after suing for peace separately compared, the maximum of obtaining is P _{Σ max}; And Σ P _imaxbe the maximum of first asking 24 data points in each sub-wind energy turbine set, then the maximum summation of all sub-wind energy turbine set be to Σ P _imax.

In the time calculating constellation effect index, the selected time period is one day, and maximum output ratio should be a day maximum output ratio, and in like manner, other corresponding indexs are a day maximum fluctuation ratio, day peak value simultaneity factor, day peak-valley difference ratio.

Constellation effect index set S is:

S＝{X ₁，X ₂，···，X _i’，···，X _n}；

Wherein, n represents number of days; X _{i '}=max{x _{t, i '}, 0<=t<24; x _{t, i '}represent the constellation effect desired value of t period in i' days, X _{i '}the maximum of (comprising a day maximum output ratio, day maximum fluctuation ratio, day peak value simultaneity factor and day peak-valley difference ratio) i' days all period constellation effect desired values of expression.

Step 2: utilize the regularity of distribution of mixed Gaussian method matching S, obtain probability density function, it changes and conform to the distribution histogram of constellation effect index set S.

Described probability density function is:

$f\left(x\right)=\underset{j=1}{\overset{n^{\&prime;}}{\mathrm{\&Sigma;}}}{\mathrm{\&alpha;}}_{j}N({\mathrm{\&mu;}}_j,{\mathrm{\&sigma;}}_j^2);$

Wherein, the number of n ' expression Gaussian function; α _jrepresent j the weight that Gaussian function is corresponding; Probability density function (being mixed Gaussian function) is the weighting of several Gaussian functions.By the discrete point X in step 1 _{i '}by the matching of mixed Gaussian method, obtain probability density function.

Step 3: above index can be used for weighing the size of wind-powered electricity generation constellation effect, but can not directly provide the Changing Pattern of wind-powered electricity generation constellation effect.For this reason, introduce confidential interval R, calculate the constellation effect desired value in confidential interval, its computing formula is:

P(X _i′≤R)＝p；

Wherein, p is given probable value; The concrete value of p can be determined according to Research Requirements.

P (X _{i '}≤ R) implication of=p is: the percentage that the number of samples that numerical value is less than R accounts for all sample numbers is p, tries to achieve by this probability density function the maximum sample value that numerical value is less than R.

Finally, for the constellation effect between intermittent energy source wind energy turbine set, determine correlation and complementarity between intermittent energy source wind energy turbine set.

The computing formula of correlation is:

$C_r=\frac{\mathrm{\&Sigma;}(X-\stackrel{\&OverBar;}{X})(Y-\stackrel{\&OverBar;}{Y})}{\sqrt{\mathrm{\&Sigma;}{(X-\stackrel{\&OverBar;}{X})}^2}\sqrt{\mathrm{\&Sigma;}{(Y-\stackrel{\&OverBar;}{Y})}^2}};$

Wherein, C _rthe coefficient correlation that the wind-powered electricity generation of two sub-wind energy turbine set of intermittent energy source of expression is exerted oneself; X, Y represents that respectively the wind-powered electricity generation of two sub-wind energy turbine set of intermittent energy source exerts oneself, for the wind-powered electricity generation of two sub-wind energy turbine set of intermittent energy source in the statistical time range mean value of exerting oneself;

If C _r> 0, intermittent energy source has positive correlation, and total fluctuation that goes out increases; If C _r< 0, intermittent energy source has negative correlation, and total fluctuation that goes out reduces.

Embodiment

One, wind-powered electricity generation fluctuation in Hainan is analyzed

Based on the actual operating data of the main wind energy turbine set in Hainan Region, the Changing Pattern of constellation effect is analyzed and researched.The geographical position of 5 wind energy turbine set and relative distance are as shown in Figure 3.It is coastal that Wenchang wind energy turbine set (WF1) is positioned at northeast, and high climing wind-powered electricity generation first phase, second phase (WF2 and WF3) be adjacent, and to be positioned at the northwestward coastal, and WF1 and WF2 are at a distance of 200km; Four more lay respectively on southwestern coastal Liang Ge town with sense city wind energy turbine set (WF4 and WF5), and WF3 and WF4 are at a distance of 120km; WF1 and WF5 are at a distance of 300km.The rated capacity of each wind energy turbine set is 49.5 megawatts (MW).The data that use in research are the power data at 2011～2012 years 5min intervals.

(1) the planning rank time scale fluctuation of wind energy turbine set

(11) annual fluctuation

Wind-powered electricity generation annual utilization hours, represent the annual energy output of generating equipment in this generating equipment with needed hourage under rated power, i.e. the ratio of the annual actual power generation of wind power equipment and this generating equipment rated power.

Add up respectively the annual utilization hours of the each wind energy turbine set in Hainan between 2011 and 2012, as shown in table 1.

Table 1 wind energy turbine set annual utilization hours

Annual utilization hours (h)	2011	2012
			Wenchang	2339.9	1757.22
Four more	2341.51	1807.76
			Sense city	1935.97	1895.64
High climing	1947.79	1473.24

Wind-powered electricity generation annual utilization hours can be evaluated the height of the utilization ratio of wind energy turbine set, and Hainan wind-powered electricity generation installation is less, does not consider to limit wind, and the height of the wind energy turbine set hourage of different year has reflected the relative size of different year wind speed from the side.The mean wind speed that therefrom can find out 2011 is greater than 2012, and wind energy turbine set electricity is also more.

Between the same year, the variation of annual utilization hours is not mainly subject to long-term weather influence, Hainan annual utilization hours of 2011 and 2012 on average differs 400h, maximum exceedes 500h, and fluctuating range is very violent, and this may be relevant with the Activity Effects of Hainan Region tropical cyclone.For single wind energy turbine set, wind speed changes with theoretical energy output, utilizes the variation of hourage to be linear approximate relationship, and the every variation of mean wind speed 0.1m/s, utilizes hourage to change about 50h～60h.

(12) monthly, season fluctuation of wind-powered electricity generation

Respectively 2011 and exerting oneself of 4 wind energy turbine set in Hainan in 2012 are added up, selecting statistical indicator is active power and capacity factor.As shown in table 2 is monthly average active power

Table 2 monthly average active power (unit: MW)

As can be seen from Table 2, wind-powered electricity generation exerts oneself that maximum appears at November, December, January, and average wind-force is larger in the winter time; In summer, about June, also there will be large wind; Spring and autumn, general wind-force was less.

Fig. 4 shown Wenchang, high climing, sense city and four more 4 wind energy turbine set each month wind-powered electricity generation capacity factor (its value is 0.2) in 2011.In the winter time, exerting oneself of each wind energy turbine set all reached the peak value in a year, spring and autumn wind-powered electricity generation exert oneself lower, and in summer, the different Changing Pattern of exerting oneself of different wind energy turbine set.Four more approach with sense wind energy turbine set position, two, city, in west side, Hainan Island, have the similar wind-powered electricity generation fluctuation pattern of exerting oneself, and whole curve presents double-peak feature, and Wenchang and high climing wind energy turbine set are all in north side, island, and curve has unimodal feature.

(2) runlevel time scale (day) fluctuation of wind-powered electricity generation

Be illustrated in figure 5 the per day power curve of certain day, after being averaged, per day power curve tries to achieve capacity factor, the capacity factor of finding four wind energy turbine set had identical regularity in 24 hours: in one day, night and the morning wind-powered electricity generation to go out force level lower, and change little, afternoon wind-powered electricity generation goes out force level constantly to be increased, and peak value generally appears at 14:00～18:00; Area, Wenchang, wind-powered electricity generation is exerted oneself did not have obvious increasing law in 24 hours, and the day part size of exerting oneself is substantially equal.

Exerting oneself of wind energy turbine set has different fluctuation modes, therefore wind-powered electricity generation is carried out to simple classification in the fluctuation mode of 24h, as shown in table 3 and Fig. 6, taking Wenchang wind energy turbine set as example: wherein the appearance situation of the interval Wave type of low value is maximum, account for 40% to 50% of all statistics number of days, this type represents the morning, noon and evening output of wind electric field mean value be all no more than 20% of installation, secondly be the interval Wave type of high value, convex, down type, ascending-type and matrix.

Table 3 wind energy turbine set daily output fluctuation all kinds probability distribution

Type	Convex	Matrix	Down type	Ascending-type	Low value interval type	High value interval type
							Wenchang	0.087079	0.036517	0.122191	0.098315	0.449438202	0.206461
Four more	0.202247	0.032303	0.067416	0.099719	0.401685393	0.196629
							Sense city	0.102528	0.026685	0.110955	0.09691	0.484550562	0.178371
High climing	0.126404	0.032303	0.071629	0.136236	0.463483146	0.169944

Statistics has distribution at 6 kinds of wind-powered electricity generation power curves, gets the mean value of all types of wind-powered electricity generation power curves, is regarded as all types of typical curves, as shown in Figure 7.

(3) the control hierarchy time scale fluctuation of wind-powered electricity generation

Select 2011～2012 years actual measurement power output data of high climing wind energy turbine set (33 units of first phase, specified installed capacity 49.5MW), the power fluctuation characteristic of wind energy turbine set is analyzed.The time scale of wind power fluctuation characteristic quantity research is got respectively 30 seconds (s), 1 point (min), 2min, 5min, 10min, 20min, 30min, 1 hour (h), 2h, 6h, and the probability statistics data of wind power undulate quantity are as shown in table 4.The time interval be 30s, 1min, 15min and 1h wind energy turbine set power waves momentum as Fig. 8 a)～8d) as shown in.

The probability statistics of table 4 wind power undulate quantity

Table 4 and Fig. 8 a)～8d) shown the curve of cyclical fluctuations and the probability distribution situation of wind power undulate quantity in different intervals under different time yardstick.Can find out: under 99.9% probability, be less than ± 0.05p.u. of 30s sampling interval wind power undulate quantity, be less than ± 0.10p.u. of 2min sampling interval wind power undulate quantity, be less than ± 0.15p.u. of 5min sampling interval wind power undulate quantity, be less than ± 0.30p.u. of 10min sampling interval wind power undulate quantity, be less than ± 0.50p.u. of 30min sampling interval wind power undulate quantity.With the increase in sampling time, wind power fluctuating range increases, and the distributed area of undulate quantity will more extensive, and the time interval exceeded after one hour, and wind-powered electricity generation fluctuates has distribution substantially on the ± whole sampling interval of 1.0p.u..

Two, constellation effect analysis

Based on the actual operating data of the main wind energy turbine set in Hainan Region, the Changing Pattern of constellation effect is analyzed and researched.

(1) wind-powered electricity generation constellation effect probability distribution

Calculate the probability distribution of constellation effect index for the wind energy turbine set cluster in whole region, its probability distribution histogram as Fig. 9 a)～9d) as shown in.

For different constellation effect indexs, adopt mixed Gauss model fitting result as Figure 10 a)～10d) as shown in, wherein day maximum output ratio, day maximum fluctuation ratio, a day peak value simultaneity factor meet two component Gaussian Profile, and a day peak-valley difference ratio meets simple Gaussian Profile.As can be seen from the figure, application mix Gauss model can obtain good fitting effect.Fitting parameter is as shown in table 5:

Table 5 mixed Gaussian fitting of distribution parameter

Fitting parameter	Day maximum output ratio	Day maximum fluctuation ratio	Day peak value simultaneity factor	Day peak-valley difference ratio
					α1	0.0492	0.1337	-0.0432	0.0834
μ1	0.4167	0.0654	0.7316	0.2939
					σ1	0.3405	0.0305	0.0080	0.2134
α2	0.0187	0.0612	0.0625	——
					μ2	0.188	0.0885	0.7807	——
σ2	0.0996	0.0944	0.2	——

Get formula P (X _{i '}≤ R) p is that 95% (being that confidence level is 95%) is example in=p, calculates under 95% confidence level under different installed capacitys the constellation effect desired value of wind energy turbine set as shown in table 6:

The constellation effect index of wind energy turbine set under different installed capacitys under table 6 95% confidence level

Because the installed capacity of Hainan Power Grid wind energy turbine set is all 50MW, installed capacity and wind energy turbine set number have corresponding relation m=C/50, and (C is installed capacity, m is wind-powered electricity generation number of fields), can obtain the constellation effect desired value of the wind energy turbine set of different numbers, as shown in table 7.

The constellation effect desired value of the wind energy turbine set of the different numbers of table 7

As can be seen from Table 7, along with the increase of m, constellation effect index is the trend of decay.

Data in his-and-hers watches 7 are carried out power exponent matching, can obtain the Changing Pattern of constellation effect index with wind energy turbine set number, thereby obtain the functional relation of wind-powered electricity generation number of fields and constellation effect index, and then after estimating that wind energy turbine set is built in enlarging or increasing, the impact that wind farm group is exerted oneself.Power exponent formula is:

R(m)＝a×m ^b；

Wherein, R (m) is constellation effect desired value; A, b is power exponent parameter.

Power exponent fitting parameter value is as shown in table 8:

Table 8 power exponent fitting parameter

Parameter	Day maximum output ratio	Day maximum fluctuation is than (15min)	Day peak value simultaneity factor	Day peak-valley difference ratio
					a	0.592	0.591	1.010	0.9616

b

-0.3024

-0.6708

-0.0421

-0.2625

To divide exactly the correlation of Long-term Fluctuation and the complementarity of short-term fluctuation to analyze for the constellation effect analysis in the time domain of wind farm group.The correlation of Long-term Fluctuation can be calculated by formula, but the complementarity of short-term fluctuation can only be used theory analysis, reaches a conclusion by curve comparison.The complementarity that proposes short-term fluctuation is for making analytical method more comprehensive.

(2) correlation of Long-term Fluctuation

The long-term mobility of wind-powered electricity generation depends on seasonal climate type and the variation of wind between year, and the scope of these factors impacts is generally very large, and the wind energy fluctuation under same climatic environment has obviously similar trend.

According to 2011～2012 years meritorious exerting oneself of each monthly average, the relative coefficient of each output of wind electric field was as shown in table 9:

The monthly coefficient correlation of exerting oneself of table 9 Hainan wind-powered electricity generation

Relative coefficient	Wenchang	Four more	Sense city	High climing
					Wenchang	1	——	——	——
Four more	0.4209	1	——	——
					Sense city	-0.2781	0.5163	1	——
High climing	0.9170	0.6322	-0.2174	1

The absolute value of relative coefficient, the closer to 1, represents that correlation is stronger.The coefficient correlation of Wenchang and high climing two output of wind electric field reaches 0.9170, belongs to strong correlation, and four more climingly belong to general relevant with high to sense city, four, sense city and Wenchang, feel city and high climing correlation a little less than.Relevant with the factor such as geographic distance, latitude as Relativity, geographic distance is nearer, and the probability that runs into identical weather is larger, and the wind speed of wind energy turbine set, the correlation of exerting oneself are stronger.

(3) complementarity of short-term fluctuation

Under controlled stage time scale, wind-powered electricity generation is exerted oneself and is had complementarity, mainly comprises 2 aspects:

(31) complementarity of wind energy turbine set inside.On the one hand, under the effect of moment of inertia and active power control strategy, wind-powered electricity generation unit can effectively stabilize second level time scale meritorious go out fluctuation; On the other hand, because the randomness of fluctuations in wind speed and Feng Feng, wind valley are different the time of advent, there is certain complementarity in different wind-powered electricity generation unit in wind energy turbine set, can suppress several minutes following time scales meritorious go out fluctuation.

(32) the local position distribution effect between wind energy turbine set in region.The wind peak of diverse location wind energy turbine set is different the time of advent with wind valley, and maximum output rate of change goes out now can be not identical yet, thereby realizes complementation, has reduced the rate of change of exerting oneself in wind-powered electricity generation base.Because the distance between wind energy turbine set is limited, this complementarity is embodied within the scope of the time scale hour below level.

Figure 11 and Figure 12 represent respectively the exert oneself relation of the different units of wind energy turbine set between the relation of exerting oneself and the different wind energy turbine set of one day.Can find out, under short-term conditions, different unit/output of wind electric field curves have different, the smoothly fluctuation of the wind-powered electricity generation under short-term yardstick to a certain extent, but in long-term trend, their the obvious correlation of having exerted oneself.

The suffered influencing factor of power fluctuation of large-scale wind power is numerous, and it is common decision of fluctuation by long-term tendency and short-term.Between the wind energy turbine set of same climatic province, under long time scale, power fluctuation has obvious correlation; Short time yardstick has very large complementary effect, and this two aspect has formed the constellation effect of wind-powered electricity generation jointly.

The above; only for preferably embodiment of the present invention, but protection scope of the present invention is not limited to this, is anyly familiar with in technical scope that those skilled in the art disclose in the present invention; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (8)

1. analyze based on time domain and constellation effect the method that intermittent energy source is exerted oneself, it is characterized in that, the method comprises:

Statistics intermittent energy source wind energy turbine set go out in real time force data, from three kinds of rank time scales, exerting oneself of intermittent energy source wind energy turbine set carried out to fluctuation analysis;

Calculate the constellation effect of intermittent energy source wind farm group;

For the constellation effect between intermittent energy source wind energy turbine set, determine correlation and complementarity between intermittent energy source wind energy turbine set.

2. method according to claim 1, is characterized in that, described three kinds of rank time scales are respectively planning rank time scale, runlevel time scale and control hierarchy time scale.

3. method according to claim 2, is characterized in that, describedly from three kinds of rank time scales, exerting oneself of intermittent energy source wind energy turbine set is carried out to fluctuation analysis and is specially:

For planning rank time scale, analyze monthly, season of intermittent energy source wind energy turbine set and the fluctuation of exerting oneself in year;

The fluctuation of exerting oneself in monthly and season of described analysis intermittent energy source wind energy turbine set comprises statistics active power and capacity factor;

The fluctuation of exerting oneself in year of described analysis intermittent energy source wind energy turbine set comprises that calculating annual utilization hours, annual mean wind speed and annual exerts oneself;

For runlevel time scale, calculate the capacity factor of intermittent energy source wind energy turbine set, the fluctuation type of the daily output curve to intermittent energy source wind energy turbine set is added up, and determines the wave characteristic of intermittent energy source wind energy turbine set daily output;

For control hierarchy time scale, calculate the exert oneself probability distribution of undulate quantity of intermittent energy source wind energy turbine set level second, minute level and hour level, determine between the intermittent energy source output of wind electric field wave zone under different probability.

4. method according to claim 3, is characterized in that, described capacity factor is intermittent energy source output of wind electric field under mean wind speed and the ratio of its rated power.

5. method according to claim 4, is characterized in that, the fluctuation type of described daily output curve is:

When intermittent energy source wind energy turbine set daily output per unit value is all less than capacity factor, fluctuation type is the interval Wave type of low value;

Intermittent energy source wind energy turbine set daily output curve is the rear downward trend that first rises, and fluctuation type is convex;

Intermittent energy source wind energy turbine set daily output curve is the trend that first declines and rise afterwards, and fluctuation type is spill;

Intermittent energy source wind energy turbine set daily output curve is totally in rising trend, and fluctuation type is ascending-type;

Intermittent energy source wind energy turbine set daily output curve is totally on a declining curve, and fluctuation type is down type;

In other situation, fluctuation type is the interval Wave type of high value.

6. method according to claim 1, is characterized in that, the constellation effect of described calculating intermittent energy source wind farm group is specially:

Step 1: set up constellation effect index set S and calculate its distribution histogram;

Described constellation effect index set S is:

S＝{X ₁，X ₂，···，X _i’，···，X _n}；

Wherein, n represents number of days; X _{i '}=max{x _{t, i '}, 0<=t<24; x _{t, i '}represent the constellation effect desired value of t period in i' days, X _{i '}represent the maximum of i' days all period constellation effect desired values;

Step 2: utilize the regularity of distribution of mixed Gaussian method matching S, obtain probability density function;

Described probability density function is:

$f\left(x\right)=\underset{j=1}{\overset{n^{\&prime;}}{\mathrm{\&Sigma;}}}{\mathrm{\&alpha;}}_{j}N({\mathrm{\&mu;}}_j,{\mathrm{\&sigma;}}_j^2);$

Wherein, the number of n ' expression Gaussian function; α _jrepresent j the weight that Gaussian function is corresponding;

Step 3: introduce confidential interval R, calculate the constellation effect desired value in confidential interval, its computing formula is:

P(X _i′≤R)＝p；

Wherein, p is given probable value.

7. method according to claim 6, is characterized in that, described constellation effect index comprises maximum output ratio, maximum fluctuation ratio, peak value simultaneity factor and peak-valley difference ratio;

The computing formula of described maximum output ratio is:

The computing formula of described maximum fluctuation ratio is:

The computing formula of described peak value simultaneity factor is:

The computing formula of described peak-valley difference ratio is:

Wherein, V _pmrepresent maximum output ratio;

P _{Σ max}represent the total meritorious maximum of exerting oneself of intermittent energy source wind energy turbine set cluster;

Σ P _krepresent the rated power sum of all blower fans in intermittent energy source wind energy turbine set cluster;

P _krepresent the rated power of k blower fan in intermittent energy source wind energy turbine set cluster;

C _{Δ PS}represent maximum fluctuation ratio;

Δ P _maxrepresent the maximum of intermittent energy source wind energy turbine set cluster gross power undulate quantity;

C _oinrepresent peak value simultaneity factor;

Σ P _imaxrepresent each sub-electric field maximum output sum separately in intermittent energy source wind energy turbine set cluster;

P _imaxrepresent the maximum output of i sub-electric field in intermittent energy source wind energy turbine set cluster;

C _{Δ P}represent peak-valley difference ratio;

P _{Σ min}represent the total meritorious minimum value of exerting oneself of intermittent energy source wind energy turbine set cluster.

8. method according to claim 1, is characterized in that, the computing formula of the correlation between described intermittent energy source wind energy turbine set is:

$C_r=\frac{\mathrm{\&Sigma;}(X-\stackrel{\&OverBar;}{X})(Y-\stackrel{\&OverBar;}{Y})}{\sqrt{\mathrm{\&Sigma;}{(X-\stackrel{\&OverBar;}{X})}^2}\sqrt{\mathrm{\&Sigma;}{(Y-\stackrel{\&OverBar;}{Y})}^2}};$

Wherein, C _rthe coefficient correlation that the wind-powered electricity generation of two sub-electric fields of intermittent energy source of expression is exerted oneself; X, Y represents that respectively the wind-powered electricity generation of two sub-electric fields of intermittent energy source exerts oneself, for the wind-powered electricity generation of two sub-electric fields of intermittent energy source in the statistical time range mean value of exerting oneself;

If C _r> 0 intermittent energy source has positive correlation, and total fluctuation that goes out increases; If C _r< 0 intermittent energy source has negative correlation, and total fluctuation that goes out reduces.