CN102609611B - A kind of Wind energy evaluation method based on effective wind speed - Google Patents

Abstract

The invention discloses a kind of Wind energy evaluation method based on effective wind speed, the method comprises: step 1: data acquisition; Step 2: tabling look-up of data processing obtains saturated steam partial pressure P _(sat); Step 3: the atmospheric density of data processing calculate; Step 4: for the atmospheric density historical data of wind energy turbine set, a selected value constant air density

Description

A kind of Wind energy evaluation method based on effective wind speed

Technical field

The present invention relates to a kind of Wind energy evaluation method, particularly relate to a kind of Wind energy evaluation method based on effective wind speed.

Background technology

The Construction and operation of wind energy turbine set is to occupy premised on abundant wind energy resources.Evaluation of Wind Energy Resources is great for the generated energy and economic benefit impact ensureing wind energy turbine set accurately.In wind farm siting process, need the meteorological record to location is over the years to investigate, and the wind speed in anemometer tower actual measurement field is set, obtained the wind power features of wind energy turbine set by statistics and analysis.

Generally speaking, for the various application of wind energy turbine set different phase, time span and the time interval of the wind power data of needs understanding are also different.In the operation process of wind energy turbine set, in order to formulate the long-term power generation planning of wind energy turbine set and reserve generation capacity plan, need the wind power data in the several years, the time interval of data point can reach a hour level; In order to meet the requirement of electric system energy scheduling, need the wind power data in several weeks, the time interval of data point is generally a minute level; And in the operation of Wind turbines controls, in order to protect Wind turbines not to be damaged, stabilize the rapid fluctuations of its output power, maintain the operation stability of electric system, often need the wind power transient characteristic in a few days, the time interval of data point can be as short as level second.

Wind power and wind speed closely related, therebetween in obvious nonlinear relationship.In traditional wind energy and wind power statistic, it is all carry out based on the mean wind speed in a period of time that all wind energies calculate.And this traditional conventional practice may bring very important error to wind energy statistics.An obvious adverse consequences is, by second level, wind energy difference that the mean wind speed of the Different time scales such as minute level and hour level calculates in the same amount of time that obtains is very large, cannot be consistent.

Summary of the invention

The object of the invention is the defect existed for above-mentioned background technology, a kind of Wind energy evaluation method based on effective wind speed is provided.

For achieving the above object, a kind of Wind energy evaluation method based on effective wind speed provided by the invention, the method comprises:

Step 1: data acquisition

The concrete data gathering wind energy turbine set are as follows: in certain hour section, evenly gathered the instant wind speed v in several same wind energy turbine set direction windward respectively by wind speed wind direction sensor simultaneously, instant wind speed v is the instant wind speed v in same wind energy turbine set windward on direction, and gathers several instant wind speed v, is evenly gathered the aerothermodynamics temperature T of several same wind energy turbine set by temperature sensor, evenly gathered the air humidity of several same wind energy turbine set by humidity sensor evenly gathered the soft air pressure P of several same wind energy turbine set by pressure transducer, gathered dry-bulb temperature t (d) of the soft air of several same wind energy turbine set by wet-and-dry bulb thermometer;

Step 2: tabling look-up of data processing obtains saturation vapor pressure P (sat)

Utilize dry-bulb temperature t (d) that wet-and-dry bulb thermometer measurement obtains, and try to achieve the wind energy turbine set saturation vapor pressure P (sat) corresponding to dry-bulb temperature t (d) by tabling look-up;

Step 3: the atmospheric density ρ of data processing calculates

The T gathered respectively according to temperature sensor, humidity sensor and pressure transducer, table look-up in P data and step 2 the saturation vapor pressure P (sat) obtained, and utilizes above-mentioned data and by atmospheric density ρ computing formula: calculate some corresponding atmospheric density ρ;

Step 4: for the atmospheric density historical data of wind energy turbine set, a selected value constant air density p _oas reference amount;

Step 5: several effective wind speeds in the minimum interval of data processing and average wind power density computation

According to atmospheric density ρ obtained some in step 3, utilize the law of physics of fluid and theorem of kinetic energy and by effective wind speed computing formula: calculate the effective wind speed for air density change in several minimum intervals, and pass through effective wind speed and the average wind power density formula in the some corresponding moment of gained: calculate all average wind power densities in corresponding moment in some minimum intervals, in formula, t ₀, t ₀+ T ₀be respectively the initial time and end time that gather instant wind speed v in wind energy turbine set;

Step 6: the effective wind speed in the minimum interval of data processing is to the conversion of the effective wind speed in arbitrary larger time interval

By the effective wind speed v in several minimum intervals of calculating in step 5 _eas the different effective wind speed v calculated in arbitrary larger time interval _{e (i+1)}, and by effective wind speed conversion formula:

$v_{e\left(i+1\right)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\left(k-1\right)N+j\right)}{N}},k=1,2,\mathrm{...},\[\frac{M}{N}\]$

Calculate the effective wind speed in the larger time interval, in formula, i is natural number, and i-th layer of effective wind speed sequence is: v _{e (i)}(k), k=1,2 ..., M, the time span that each data point occupies is T _(i); The i-th+1 layer effective wind speed sequence is: the time span that each data point occupies is T _(i+1)=NT _(i);

Step 7: the wind energy assessment in the arbitrary larger time interval of data processing

According to calculating average wind power density, the effective wind speed in the larger time interval that in the effective wind speed of minimum interval, minimum interval, each effective wind speed is corresponding in step 5 and step 6, and pass through

${\stackrel{\‾}{p}}_{e(i+1)}=\frac{1}{2}{\mathrm{\ρ}}_o{v}_{e(i+1)}^3$

$E_{(i+1)}\left(k\right)={\stackrel{\‾}{p}}_{e(i+1)}\left(k\right)T_{(i+1)}=\underset{j=1}{\overset{N}{\Σ}}{E}_{\left(i\right)}((k-1)N+j)$

And $v_{e\left(i+1\right)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\left(k-1\right)N+j\right)}{N}},k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Combined calculation draws the wind energy based on effective wind speed in arbitrary larger time interval, and in formula, i is natural number.

In sum, a kind of Wind energy evaluation method based on effective wind speed of the present invention is applicable to the wind energy turbine set wind energy assessment of atmospheric density ρ change in certain time, not only can assess the wind energy of wind energy turbine set exactly, and when carrying out wind energy assessment, result is not by the impact of time period length.

Embodiment

By describing technology contents of the present invention, structural attitude in detail, being reached object and effect, be hereby explained in detail below.

When assessing the wind energy of wind energy turbine set, atmospheric density ρ change is one of them critical factor to affect on wind energy assessment impact, but the change of atmospheric density ρ is again by the impact of the factors such as environment temperature, air humidity, air pressure, and the moment is in the middle of variation; Simultaneously, the wind speed of wind energy turbine set is to being in the middle of variation as another crucial factor to the assessment of wind energy also moment, two assessments of the key influencing factor changed at any time to wind energy turbine set wind energy cause larger difficulty, and how utilizing the mathematical model of simplification and principle to carry out assessment effectively accurately to wind energy situation is a great problem in the assessment of current wind energy

A kind of Wind energy evaluation method based on effective wind speed of the present invention is applicable to atmospheric density ρ and the assessment of wind farm wind velocity moment change wind energy turbine set wind energy, and the method specifically comprises the following steps:

Step 1: data acquisition

The concrete data gathering wind energy turbine set are as follows: in certain hour section, evenly gathered the instant wind speed v in several same wind energy turbine set direction windward respectively by wind speed wind direction sensor simultaneously, instant wind speed v is the instant wind speed v in same wind energy turbine set windward on direction, and gathers several instant wind speed v, is evenly gathered the aerothermodynamics temperature T of several same wind energy turbine set by temperature sensor, evenly gathered the air humidity of several same wind energy turbine set of wind energy turbine set by humidity sensor evenly gathered the soft air pressure P of several same wind energy turbine set by pressure transducer, gathered dry-bulb temperature t (d) of the soft air of several same wind energy turbine set by wet-and-dry bulb thermometer.

In this specific embodiment, wind speed wind direction sensor gathers the wind energy turbine set instant wind speed v in direction, the aerothermodynamics temperature T of the wind energy turbine set of temperature sensor collection, the wind energy turbine set air humidity of humidity sensor collection windward the wind energy turbine set pressure P of pressure transducer collection and the soft air of wet-and-dry bulb thermometer collection dry is asked temperature t (d) to be synchronization and is gathered simultaneously, and above-mentioned v, T, p and t (d) sample frequency is 1 second 1 time.

Step 2: tabling look-up of data processing obtains saturation vapor pressure P (sat)

Utilize dry-bulb temperature t (d) that wet-and-dry bulb thermometer measurement obtains, and try to achieve the wind energy turbine set saturation vapor pressure P (sat) corresponding to dry-bulb temperature t (d) by tabling look-up.

Step 3: the atmospheric density ρ of data processing calculates

The T gathered respectively according to temperature sensor, humidity sensor and pressure transducer, table look-up in P data and step 2 the saturation vapor pressure P (sat) obtained, and utilizes above-mentioned data and by atmospheric density ρ computing formula: calculate corresponding atmospheric density ρ.

Because of T, p and t (d) is by several data and these data amount checks are equal, thus can calculate several identical numbers correspond to the corresponding collection point moment T, namely the atmospheric density ρ of P and P (sat), also atmospheric density ρ occurs with the form of one group of data and these group data and instant wind speed have relation one to one.

The concrete derivation of atmospheric density ρ is as follows:

According to atmospheric density ρ by dry air with soft air is two-part forms, therefore such atmospheric density ρ is 1m ³in contained dry air density and density of moist air sum; That is:

ρ＝ρ(da)+ρ(v)①

In formula, ρ (da), ρ (v) are respectively the density of dry air density and water vapor, and unit is: Kg/m ³.

Because dry air can be considered ideal gas, be present in water vapor in air because dividing potential drop is very low, density is very little, also can be considered ideal gas.Therefore the air of dry air and water vapor composition, can represent with the imperial formula of carat uncle equally:

PV＝RT②

In formula, P-soft air pressure, unit: Pa;

Volume shared by V-air, unit: m ³;

T-thermodynamic temperature, unit: (273.16+t) ° K.

By Dalton's law, the general pressure of soft air equals the partial pressure of dry air and the partial pressure sum of water vapor, that is:

P＝P(da)+P(v)③

And

In formula, relative humidity in air, unit: %;

P (sat)-corresponding to the saturation vapor pressure of dry-bulb temperature t, unit: Pa.

Can be obtained by equation of gaseous state:

ρ＝1/V＝P/RT

When standard state, Po=760mm mercury slug=760 × 13.596 × 9.81 ≈ 101366.3Pa, To=273.16 ° of K, dry air density p: ρ=1.293Kg/m ³, water-vapour density ρ (vo): ρ (vo)=18/22.4=0.80357Kg/m ³

The gas law constant of dry air:

R(da)＝Po/Toρ＝101366.3/273.16×1.293＝286.997≈287J/(Kg·K)

The gas law constant of water vapor:

R(v)＝Po/Toρ(vo)＝101366.3/273.16×0.80357＝461.799≈462J/(Kg·K)

Finally can go out the computing formula of density of moist air:

Step 4: for the atmospheric density historical data of wind energy turbine set, a selected value constant air density p _oas reference amount

Value constant air density p in this step 4 _oatmospheric density data preferably for wind energy turbine set location are calculated by average mode.

The atmospheric density ρ that the value discussed in this patented technology file is constant _oobtain manner do not restrict other better obtain manners.

In other embodiments, before step 4 can be placed in step 1, step 2 and step 3.Relation accordingly between front 4 steps will do corresponding adjustment, not repeat them here.

Step 5: several effective wind speeds in the minimum interval of data processing and average wind power density computation

According to the atmospheric density ρ obtained in step 3, utilize the law of physics of fluid and theorem of kinetic energy and by effective wind speed computing formula: calculate the effective wind speed for air density change in several minimum intervals, and pass through effective wind speed and the average wind power density formula in the some corresponding moment of gained: calculate all average wind power densities in corresponding moment in some minimum intervals, in formula, t ₀, t ₀+ T ₀be respectively the initial time and end time that gather instant wind speed v in wind energy turbine set.

The concrete derivation of effective wind speed formula is as follows:

According to the law of physics of fluid, at certain moment t, the wind power P perpendicular through a section S is:

$P=\frac{dE}{dt}$ ①

Wherein, dE is the kinetic energy in element of volume d Ω=Svdt apoplexy, and the normal direction of S is consistent with the direction of wind speed v.Atmospheric density is ρ, then elementary mass dm=ρ d Ω, and infinitesimal kinetic energy can be expressed as:

$dE=\frac{1}{2}\left(dm\right)v^2=\frac{1}{2}\left(\mathrm{\ρ}Svdt\right)v^2=\frac{1}{2}{\mathrm{\ρSv}}^{3}dt$

Obtaining wind power function is thus:

$P=\frac{1}{2}{\mathrm{\ρSv}}^3$ ②

1. this step 5 Chinese style illustrates, wind power is directly proportional to atmospheric density ρ and wind sweeping area S, and becomes with wind speed v cube to compare relation.From this step 5 Chinese style 1. further, pass perpendicularly through the wind power of unit area, namely wind power concentration p is:

$p=\frac{1}{2}{\mathrm{\ρv}}^3$

At a period of time [t ₀, t ₀+ T ₀] in, the wind energy passing perpendicularly through unit area is:

$E={\∫}_{t_0}^{t_0+T_0}pdt=\frac{\mathrm{\ρ}}{2}{\∫}_{t_0}^{t_0+T_0}{v}^{3}dt$ ③

Average wind power density in this period should meet:

$E=\stackrel{\‾}{p}\·T_0=\frac{\mathrm{\ρ}}{2}{\∫}_{t_0}^{t_0+T_0}{v}^{3}dt$

Thus: $\stackrel{\‾}{p}=\frac{\mathrm{\ρ}}{2T}{\∫}_{t_0}^{t_0+T_0}{v}^{3}dt$ ④

With reference to formula 2., by the average wind power density in a period of time be expressed as corresponding equivalent wind speed v _ecube than function:

$\stackrel{\‾}{p}=\frac{1}{2}{\mathrm{\ρv}}_e^3$ ⑤

By this step 5 Chinese style 4. with formula 5., for the situation that atmospheric density ρ is constant, definition is by the effective wind speed v of atmospheric density ρ variable effect _efor:

$v_E=\sqrt[3]{\frac{1}{T}{\∫}_{t_0}^{t_0+T_0}{v}^{3}dt}$ ⑥

Utilize this step be 5. averaged the calculating of wind power concentration time, atmospheric density ρ is because being in the middle of variation at any time, and atmospheric density ρ rather unstable, in addition effective wind speed v _ealso be a variable, therefore average wind power density cannot be calculated accurately and effectively.

Cause is at same a period of time [t ₀, t ₀+ T ₀] in, also there is an integration to the time in atmospheric density ρ, now atmospheric density ρ also can be expressed as further equally:

A kind of Wind energy evaluation method based on effective wind speed of this method, for reducing operand and ensureing validity and the correctness of operation result, for the reference quantity atmospheric density ρ in step 4 _o, the atmospheric density ρ certainty that wind energy turbine set measured data calculates and ρ _obetween ratio have following relation: if for calculate atmospheric density ρ four parameter T, enough hour of the acquisition time interval of P and P (sat), therefore can be considered atmospheric density ρ relative constancy, in the present embodiment, at [t ₀, t ₀+ T ₀] in the time period, four parameter T, p and P (sat) samples at synchronization, frequency is 1 second 1 time, also can be considered atmospheric density ρ relative constancy, but, when the altering a great deal of time interval of 2 sampling instant points comparatively large and atmospheric density ρ, when atmospheric density ρ forms very large impact to wind energy assessment assessment, 7. the formula below addressed will meet the appearance of this kind of situation well.

By this step 4 Chinese style 4. with formula 5., for the situation of atmospheric density ρ change, definition is by the effective wind speed v of atmospheric density ρ variable effect _efor:

$\begin{array}{cc}{v}_e=\sqrt[3]{\frac{1}{{\mathrm{\ρ}}_o{T}^2}{\∫}_{t_0}^{t_0+T}{\mathrm{\ρdtv}}^{3}dt}& v_e=\sqrt[3]{\frac{1}{{\mathrm{\ρ}}_o{T}^2}{\∫}_{t_0}^{t_0+T_0}{\mathrm{\ρdtv}}^{3}dt}\end{array}$

Multiple because having according to the atmospheric density ρ calculating gained in step 3, and with the sampling instant point of the instant wind speed of wind energy turbine set with calculate four parameter T that atmospheric density ρ needs to gather, the sampling instant point of P and P (sat) has consistance, therefore by effective wind speed computing formula calculate some effective wind speed v of gained _ewith some atmospheric density ρ, there is relation corresponding to meaning.

For ease of describing and describing the problem, the time interval length of the instant wind speed v of regulation wind speed wind direction sensor collection is as the foundation judged in time scale, the time interval the shortest person is minimum interval/basal latency interval, level effective wind speed data based on some effective wind speeds that the instant wind speed v correspondence gathered by minimum interval/basal latency interval calculates.The time interval comparatively elder be larger the time interval/the more high-level time interval, by calculate based on base level effective wind speed data obtain larger the time interval/some effective wind speed data in the more high-level time interval are as more high-level effective wind speed data.

Therefore each effective wind speed in minimum interval can with general formula show, in like manner, each average wind power density calculated in the minimum interval of gained by effective wind speed and atmospheric density also can with general formula show, and v _{e (1)}, data amount check equal and there is relation one to one.It is important to note that as i=1, v _{e (1)}, represent all average wind power datas in the effective wind speed data in all different minimum intervals, minimum interval respectively.In this specific embodiment: use v _e, represent respectively in order to represent all effective wind speed data in minimum interval and average wind power intensity data.Computing formula after simplification: for calculating each effective wind speed in minimum interval, for calculating each average wind power density in minimum interval.Therefore v _e, the equal and one_to_one corresponding of data amount check.

Measured in different time scales for making effective wind speed, the Wind energy evaluation method that the present invention is based on effective wind speed adopts the form of data hierarchy to carry out the statistics of effective wind speed, and the foundation divided using the length of sampling time interval as different layers stage layered, measure in same time section

In preferred embodiment, anemoclinograph gathers instant wind speed v to be less than or equal to 1 second time interval usually.

In this specific embodiment, with the time interval be 1 second, sample frequency be within 1 time/1 second, gather several instant wind speed v and in utilizing this step formula 7. for atmospheric density ρ change effective wind speed computing formula obtain base level effective wind speed data; Be greater than the time interval of 1 second using the time and utilize relevant effective wind speed recurrence relation to derive the effective wind speed data of some effective wind speeds as higher levels.

The Wind energy evaluation method that the present invention is based on effective wind speed at least comprises two level time intervals, namely at least comprises the base level had in minimum interval and higher levels two levels with the larger time interval.Below only illustrate accordingly to exemplify form, but be not limited to following form in a specific embodiment, as adopted second, minute, hour ... as the time scale that different level divides, wherein, layer effective wind speed data based on the effective wind speed calculated are gathered using second as the time interval, the basis of base level effective wind speed data can be calculated by relevant effective wind speed recurrence relation the effective wind speed data of higher levels respectively, as higher levels be minute level effective wind speed data, more high-level is hour level effective wind speed data

It needs to be noted, when sample frequency reaches 1 second 1 time or 1 second more than 1 time, change because of wind speed is enough little and the time interval is extremely short, therefore the instant wind speed of wind speed wind direction sensor collection and a kind of effective wind speed approximately equal calculated based on the Wind energy evaluation method of effective wind speed of the present invention.

The effective wind speed of more high-level can be converted by the effective wind speed of base level and calculate corresponding wind energy thus.

In addition, there is following derivation relation in the effective wind speed between adjacent lower-level i-th layer and higher levels the i-th+1 layer:

Describe the problem for ease of describing, ad hoc fixed i-th layer of lower effective wind speed sequence is: v _{e (i)}(k), k=1,2 ..., M, the time span that each data point occupies is T _(i).

The i-th+1 layer higher effective wind speed sequence is: the time span that each data point occupies is T _(i+1)=NT _(i).

Adjacent two layers effective wind speed can be extrapolated and there is following recurrence Relation:

$v_{e\left(i+1\right)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\left(k-1\right)N+j\right)}{N}},k=1,2,\mathrm{...},\[\frac{M}{N}\]$ ⑧

From above-mentioned conclusion, a data point of the i-th+1 layer is corresponding to the N number of data point in i-th layer, and the time span that they occupy is identical.And the effective wind speed of upper layer data point is the equal cubic root of the multiple data point effective wind speed of lower floor's correspondence.At T _(i+1)in time period, the wind energy calculated by the i-th+1 number of plies strong point always equals the wind energy calculated by the N number of corresponding data point in i-th layer.

$\begin{array}{c}{E}_{\left(i+1\right)}\left(k\right)={\stackrel{\‾}{p}}_{\left(i+1\right)}\left(k\right)T_{\left(i+1\right)}\\ =\frac{\mathrm{\ρ}}{2}{v}_{e\left(i+1\right)}^3\left(k\right)T_{\left(i+1\right)}\\ =\frac{{\mathrm{\ρT}}_{\left(i\right)}}{2}\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\left(k-1\right)N+j\right)\\ =\underset{j=1}{\overset{N}{\Σ}}{\stackrel{\‾}{p}}_{\left(i\right)}\left(\left(k-1\right)N+j\right)T_{\left(i\right)}\\ =\underset{j=1}{\overset{N}{\Σ}}{E}_{\left(i\right)}\left(\left(k-1\right)N+j\right)\end{array}$ ⑨

Shown by above formula, between different layers, the recurrence method of effective wind speed can ensure each layer wind energy result of calculation with actual wind energy consistance.

Although 8. the recurrence Relation of effective wind speed only illustrates the recurrence relation of effective wind speed between two adjacent layer levels between this two rank, but in fact, as long as the effective wind speed data one of base level or lower-level determine the effective wind speed all 8. calculating more any high-level by level effective wind speed recurrence Relation.In the present embodiment, the effective wind speed of all higher levels higher than base level all can be calculated by the effective wind speed based on base level, and goes with the corresponding effective wind speed obtained the assessment carrying out wind energy.Unique difference is that the number of each effective wind speed of the base level corresponding to the time span data point of different higher levels each effective wind speed data point is different.Namely, more the effective wind speed data point of the base level required for an effective wind speed data point of high-level is more, also namely, the time more corresponding to high-level effective wind speed data point is longer, and the more basal layer effective wind speed data point of corresponding needs just can corresponding calculating.

Step 6: the effective wind speed in the minimum interval of data processing is to the conversion of the effective wind speed in arbitrary larger time interval

By the effective wind speed v in several minimum intervals of calculating in step 5 _eas the different effective wind speed v calculated in arbitrary larger time interval _{e (i+1)}basis, and by effective wind speed conversion formula:

$v_{e\left(i+1\right)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\left(k-1\right)N+j\right)}{N}},k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Calculate the effective wind speed in the larger time interval, in formula, i is natural number, and i-th layer of effective wind speed sequence is: v _{e (i)}(k), k=1,2 ..., M, the time span that each data point occupies is T _(i); The i-th+1 layer effective wind speed sequence is: the time span that each data point occupies is T _(i+1)=NT _(i).

Step 7: the wind energy assessment between the arbitrary larger time of data processing in interval

According to average wind power density corresponding to effective wind speed each in the effective wind speed calculated in step 5 and step 6 in minimum interval, minimum interval, effective wind speed in the larger time interval, and pass through

${\stackrel{\‾}{p}}_{e(i+1)}=\frac{1}{2}{\mathrm{\ρ}}_o{v}_{e(i+1)}^3$

$E_{(i+1)}\left(k\right)={\stackrel{\‾}{p}}_{e(i+1)}\left(k\right)T_{(i+1)}=\underset{j=1}{\overset{N}{\Σ}}{E}_{\left(i\right)}((k-1)N+j)$

And $v_{e\left(i+1\right)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\left(k-1\right)N+j\right)}{N}},k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Combined calculation draws the wind energy based on effective wind speed in arbitrary larger time interval, and in formula, i is natural number.

In sum, a kind of Wind energy evaluation method based on effective wind speed of the present invention is applicable to the wind energy turbine set wind energy assessment of the change of atmospheric density ρ, not only can assess the wind energy of wind energy turbine set exactly, and carry out wind energy assessment result not by the impact of time period length.

Above-described technical scheme is only the preferred embodiment of a kind of Wind energy evaluation method based on effective wind speed of the present invention, is anyly included within the scope of the claim of this patent at a kind of equivalent transformation based on the Wind energy evaluation method basis of effective wind speed is done of the present invention or replacement.

Claims (9)

1., based on a Wind energy evaluation method for effective wind speed, it is characterized in that:

Step 1: data acquisition

The concrete data gathering wind energy turbine set are as follows: in certain hour section, evenly gathered the instant wind speed v in several same wind energy turbine set direction windward respectively by wind speed wind direction sensor simultaneously, instant wind speed v is the instant wind speed v in same wind energy turbine set windward on direction, and gathers several instant wind speed v, is evenly gathered the aerothermodynamics temperature T of several same wind energy turbine set by temperature sensor, evenly gathered the air humidity of several same wind energy turbine set by humidity sensor evenly gathered the soft air pressure P of several same wind energy turbine set by pressure transducer, evenly gathered dry-bulb temperature t (d) of the soft air of some same wind energy turbine set by wet-and-dry bulb thermometer;

Step 2: tabling look-up of data processing obtains saturation vapor pressure P (sat)

Utilize dry-bulb temperature t (d) that wet-and-dry bulb thermometer measurement obtains, and try to achieve the wind energy turbine set saturation vapor pressure P (sat) corresponding to dry-bulb temperature t (d) by tabling look-up;

Step 3: the atmospheric density ρ of data processing calculates

The T gathered respectively according to temperature sensor, humidity sensor and pressure transducer, table look-up in P data and step 2 the saturation vapor pressure P (sat) obtained, and utilizes above-mentioned data and by atmospheric density ρ computing formula: calculate some corresponding atmospheric density ρ;

Step 4: for the atmospheric density historical data of wind energy turbine set, a selected value constant air density p _oas reference amount;

Step 5: several effective wind speeds in the minimum interval of data processing and average wind power density computation

According to atmospheric density ρ obtained some in step 3, utilize the law of physics of fluid and theorem of kinetic energy and by effective wind speed computing formula: calculate the effective wind speed for air density change in several minimum intervals, and pass through effective wind speed and the average wind power density formula in the some corresponding moment of gained: calculate all average wind power densities in corresponding moment in some minimum intervals, in formula, t ₀, t ₀+ T ₀be respectively the initial time and end time that gather instant wind speed v in wind energy turbine set;

Step 6: the effective wind speed in the minimum interval of data processing is to the conversion of the effective wind speed in arbitrary larger time interval

By the effective wind speed v in several minimum intervals of calculating in step 5 _eas the different effective wind speed v calculated in arbitrary larger time interval _{e (i+1)}basis, and by effective wind speed conversion formula:

$v_{e(i+1)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\right(k-1)N+j)}{N}},$ $k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Calculate the effective wind speed in the larger time interval, in formula, i is natural number, and i-th layer of effective wind speed sequence is: v _{e (i)}(k), k=1,2 ..., M, the time span that each data point occupies is T _(i); The i-th+1 layer effective wind speed sequence is: the time span that each data point occupies is T _(i+1)=NT _(i);

Step 7: the wind energy assessment in the arbitrary larger time interval of data processing

The average wind power density corresponding according to effective wind speed each in the effective wind speed calculated in step 5 and step 6 in minimum interval, minimum interval, the effective wind speed in the larger time interval, and pass through

${\stackrel{\‾}{p}}_{e(i+1)}=\frac{1}{2}{\mathrm{\ρ}}_o{v}_{e(i+1)}^3$

$E_{(i+1)}\left(k\right)={\stackrel{\‾}{p}}_{e(i+1)}\left(k\right)T_{(i+1)}=\underset{j=1}{\overset{N}{\Σ}}{E}_{\left(i\right)}\left(\right(k-1)N+j)$

And $v_{e(i+1)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\right(k-1)N+j)}{N}},$ $k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Combined calculation draws the wind energy based on effective wind speed in arbitrary larger time interval, and in formula, i is natural number.

2. the Wind energy evaluation method based on effective wind speed according to claim 1, is characterized in that: wind speed wind direction sensor gathers to obtain instantaneous wind speed instant wind speed to be less than or equal to 1 second time interval.

3. the Wind energy evaluation method based on effective wind speed according to claim 1, is characterized in that: the sample frequency that wind speed wind direction sensor gathers the wind energy turbine set instant wind speed v in direction is windward 1 second 1 time.

4. the Wind energy evaluation method based on effective wind speed according to claim 1, is characterized in that: adopt the form of data hierarchy to carry out the statistics of wind speed.

5. the Wind energy evaluation method based on effective wind speed according to claim 4, is characterized in that: the foundation that sampling time interval length divides as different layers stage layered.

6. the Wind energy evaluation method based on effective wind speed according to claim 5, it is characterized in that, it is characterized in that: at least comprise two level time intervals, namely at least comprise the base level with minimum interval and high-level two levels with the larger time interval.

7. the Wind energy evaluation method based on effective wind speed according to claim 1, is characterized in that: v _{e (1)}, data amount check equal and there is relation one to one, also i.e. v _e, the equal and one_to_one corresponding of data amount check.

8. the Wind energy evaluation method based on effective wind speed according to claim 1, is characterized in that: the atmospheric density ρ that in step 4, value is constant _oatmospheric density data for wind energy turbine set location are calculated by the mode of arithmetic mean.

9., based on a Wind energy evaluation method for effective wind speed, it is characterized in that:

Step 1: for the atmospheric density historical data of wind energy turbine set, a selected value constant air density p _oas reference amount;

Step 2: data acquisition

The concrete data gathering wind energy turbine set are as follows: in certain hour section, evenly gathered the instant wind speed v in several same wind energy turbine set direction windward respectively by wind speed wind direction sensor simultaneously, instant wind speed v is the instant wind speed v in same wind energy turbine set windward on direction, and gathers several instant wind speed v, is evenly gathered the aerothermodynamics temperature T of several same wind energy turbine set by temperature sensor, evenly gathered the air humidity of several same wind energy turbine set by humidity sensor evenly gathered the soft air pressure P of several same wind energy turbine set by pressure transducer, evenly gathered dry-bulb temperature t (d) of the soft air of several same wind energy turbine set by wet-and-dry bulb thermometer;

Step 3: tabling look-up of data processing obtains saturation vapor pressure P (sat)

Utilize dry-bulb temperature t (d) that wet-and-dry bulb thermometer measurement obtains, and try to achieve the wind energy turbine set saturation vapor pressure P (sat) corresponding to dry-bulb temperature t (d) by tabling look-up;

Step 4: the atmospheric density ρ of data processing calculates

The T gathered respectively according to temperature sensor, humidity sensor and pressure transducer, table look-up in P data and step 3 the saturation vapor pressure P (sat) obtained, and utilizes above-mentioned data and by atmospheric density ρ computing formula: calculate some corresponding atmospheric density ρ;

Step 5: several effective wind speeds in the minimum interval of data processing and average wind power density computation

According to atmospheric density ρ obtained some in step 4, utilize the law of physics of fluid and theorem of kinetic energy and by effective wind speed computing formula: calculate the effective wind speed for air density change of several minimum intervals, and pass through effective wind speed and the average wind power density formula in the some corresponding moment of gained: calculate all average wind power densities corresponding in some minimum intervals, in formula, t ₀, t ₀+ T ₀be respectively the initial time and end time that gather instant wind speed v in wind energy turbine set;

Step 6: the effective wind speed in the minimum interval of data processing is to the conversion of the effective wind speed in arbitrary larger time interval

By the effective wind speed v in several minimum intervals of calculating in step 5 _eas the different effective wind speed v calculated in arbitrary larger time interval _{e (i+1)}basis, and by effective wind speed conversion formula:

$v_{e(i+1)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\right(k-1)N+j)}{N}},$ $k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Calculate the effective wind speed in the larger time interval, in formula, i is natural number, and i-th layer of effective wind speed sequence is: v _{e (i)}(k), k=1,2 ..., M, the time span that each data point occupies is T _(i); The i-th+1 layer effective wind speed sequence is: $v_{e(i+1)}\left(k\right),k=1,2,\mathrm{...},\[\frac{M}{N}\],$ The time span that each data point occupies is T _(i+1)=NT _(i);

Step 7: the wind energy assessment in the arbitrary larger time interval of data processing

The average wind power density corresponding according to effective wind speed each in the effective wind speed calculated in step 5 and step 6 in minimum interval, minimum interval, the effective wind speed in the larger time interval, and pass through

${\stackrel{\‾}{p}}_{e(i+1)}=\frac{1}{2}{\mathrm{\ρ}}_o{v}_{e(i+1)}^3$

$E_{(i+1)}\left(k\right)={\stackrel{\‾}{p}}_{e(i+1)}\left(k\right)T_{(i+1)}=\underset{j=1}{\overset{N}{\Σ}}{E}_{\left(i\right)}\left(\right(k-1)N+j)$

And $v_{e(i+1)}\left(k\right)=\sqrt[3]{\frac{\underset{j=1}{\overset{N}{\Σ}}{v}_{e\left(i\right)}^3\left(\right(k-1)N+j)}{N}},$ $k=1,2,\mathrm{...},\[\frac{M}{N}\]$ Combined calculation draws the wind energy based on effective wind speed in arbitrary larger time interval, and in formula, i is natural number.