CN102192102B - Method for optimizing type-selecting of wind power generator set comprehensively - Google Patents

Abstract

The invention discloses a method for optimizing the type-selecting of a wind power generator set comprehensively in the technical field of wind power generation. The method disclosed by the invention is provided with two stages of preliminary type selecting and type selecting in detail; at the stage of preliminary type selecting, calculating a resource match index and a machine type cost index of each machine type to be selected respectively, and determining the selected machine type according to a comprehensive match index; and at the type selecting stage in detail, calculating the network access electric quantity per year of each selected machine type and the total service life cycle cost respectively, and determining a recommended proposal according to the comprehensive value index. The method provided by the invention has the advantages of less input parameters, is simple and convenient to operate, and the like, and is suitable for the type selection work of the wind power generator set in a wind power station engineering design.

Description

Wind power generating set complex optimum selection method

Technical field

The invention belongs to technical field of wind power generation, relate in particular to a kind of wind power generating set complex optimum selection method.

Background technique

Wind power generating set is the nucleus equipment in the wind energy turbine set project, and its investment accounts for 74% to 82% of whole wind energy turbine set gross investment.Except investment was huge, the match condition of unit and wind energy resources characteristic, operational reliability, maintainability etc. had significant impact for the economic benefit of wind energy turbine set life cycle management.

In recent years, in global installed capacity of wind-driven power rapid growth, the wind power generating set manufacturing industry also develops rapidly.Advance by leaps and bounds along with unit manufacturing enterprise is on the increase with R ﹠ D Level, technology path is different, the different type of performance parameter emerges in an endless stream, and has greatly expanded wind energy turbine set developer's Unit Selection scope.

Engineering design enterprise is continued to use the selection method that propose the nineties in last century more at present, namely relatively waits step to finish Unit Selection according to proposition candidate type, technical parameter comparison, theoretical generated energy comparison, Technological Economy.Through labor research, mainly there is following problem in above-mentioned Unit Selection method:

1. candidate's type scheme is limited, generally only has 5 ~ 10 kinds of schemes, has the risk of omitting optimal case.Proposing candidate's type scheme is the first step of Unit Selection, if the candidate's type neither one that proposes can with wind energy turbine set resource situation perfect matching, then Unit Selection work will be counted out.

Technological Economy relatively in, consider abundant not to project in the cost of investment in production and operation stage.The operation phase of wind energy turbine set is generally 20 years, because the technology path of different units is different, quality of product is different, and unit is also far from each other at the cost in production and operation stage, so should take into full account.

Summary of the invention

Not enough and cost of investment considered the shortcomings such as not enough for mentioning in the existing wind power generator group selection method candidate scheme in the above-mentioned background technology, the present invention proposes a kind of wind power generating set complex optimum selection method.

Technological scheme of the present invention is that wind power generating set complex optimum selection method is characterized in that the method may further comprise the steps:

Step 1: gather and plan to build the survey wind data of wind energy turbine set region, match obtains the wind speed profile function;

The formula of described wind speed profile function is:

$f\left(v\right)=\frac{k}{c}{\left(\frac{v}{c}\right)}^{k-1}\exp [-{\left(\frac{v}{c}\right)}^k]$

Wherein:

F (v) is the wind speed profile function;

V is wind speed;

K is form parameter;

C is dimensional parameters;

Step 2: gather the technical parameter of candidate wind power generating set type, set up power of the assembling unit curve characteristic function;

The formula of described power of the assembling unit curve characteristic function is:

$P\left(v\right)=\left\{\begin{array}{cc}0& (v<v_i)\\ \frac{v^2-{v_i}^2}{{v_r}^2-v_i}{P}_r& (v_i<v<v_r)\\ P_r& (v_r<v<v_f)\\ 0& (v>v_f)\end{array}\right.$

Wherein:

P (v) is power of the assembling unit curve characteristic function;

V is wind speed;

v _iBe the incision wind speed;

v _rBe rated wind speed;

v _fBe cut-out wind speed;

P _rBe rated power;

Step 3: computational resource match index on the basis of step 1 and step 2;

The formula of described resource matched index is:

$\mathrm{\&theta;}=\frac{{\&Integral;}_0^{\&infin;}f\left(v\right)P\left(v\right)\mathrm{dv}}{P_r}$

Wherein:

θ is resource matched index;

Step 4: each candidate's type cost index is calculated on the basis in step 2;

The formula of described type cost index is:

$\mathrm{\&sigma;}=\frac{0.00003\&CenterDot;{P_r}^2+0.37\&CenterDot;P_r+3.8\&CenterDot;H-140}{P_r}$

Wherein:

σ is the type cost index;

H is hub height;

Step 5: the comprehensive matching index is calculated on the basis in step 3 and step 4;

The formula of described comprehensive matching index is:

$\mathrm{\&lambda;}=\frac{\mathrm{\&theta;}}{\mathrm{\&sigma;}}$

Wherein:

λ is the comprehensive matching index;

Step 6: the comprehensive matching index of each type is sorted by descending order, select the specified quantity type as being shortlisted for type;

Step 7: the year electricity volume of calculating the type scheme of respectively being shortlisted for;

Step 8: the overall life cycle cost that calculates the type of respectively being shortlisted for;

The formula of described overall life cycle cost is:

LCC＝IC+OC+MC+FC+DC

Wherein:

LCC is overall life cycle cost;

IC is a cost of investment;

OC is operating cost;

MC is maintenance cost;

FC is failure cost;

DC is scrap cost;

Step 9: the comprehensive value index is calculated on the basis in step 7 and step 8;

The formula of described comprehensive value index is:

$V=\frac{E}{\mathrm{LCC}}$

Wherein:

V is the comprehensive value index;

E is a year electricity volume;

Step 10: the comprehensive value index V of the type of will respectively being shortlisted for sorts by descending order, and rank is final recommendation type at the type of setting the position.

" one takes turns " type selecting that the present invention will have now in the selection method is adjusted into " two-wheeled ", the whole types that can purchase on the preliminary type selecting stage can be with market compare, can be according to the thinking comprehensive assessment type cost of overall life cycle cost in the detailed type selecting stage.In addition, the present invention also possesses the advantages such as input parameter is few, easy and simple to handle, is convenient to promote employing at engineering field.

Description of drawings

Fig. 1 is the operational flowchart of wind power generating set complex optimum selection method;

Fig. 2 is resource matched index θ and year correlation analysis figure of electricity volume E;

Fig. 3 is the correlation analysis figure of type cost index σ and overall life cycle cost LCC.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that following explanation only is exemplary, rather than in order to limit the scope of the invention and to use.

The technical problem to be solved in the present invention is: for the problem that existing Unit Selection method exists, proposes a kind of, wind power generating set complex optimum selection method that computational process easy lower to the basic data requirement.

The target component that the present invention will embody generated energy is refined as two of the resource matched index θ of new definition and electricity volume E, and the target component that embodies cost is refined as two of the type cost index σ of new definition and overall life cycle cost LCC.

The present invention is converted into complex optimum evaluation index can be for Lectotype Decision Making the time with target component, has defined comprehensive matching index λ and two evaluation indexes of comprehensive value index V.

The present invention proposes the wind power generating set complex optimum selection method (Comprehensive Optimal Selection Method is called for short the COSM method) that comprises 2 stages, 10 steps.

The preliminary type selecting stage comprises 6 steps, is respectively: set up the dimensional parameters c and the form parameter k that plan to build wind farm wind velocity distribution function f (v), Weibull probability distribution; Collect each candidate type basic fundamental parameter and set up power of the assembling unit curve characteristic function P (v); Calculate the resource matched index θ of each candidate type; Calculate the type cost index σ of each candidate type; Calculate the comprehensive matching index λ of each candidate type; Enter the detailed type selecting stage according to the ordering of the comprehensive matching index λ type of determining to be shortlisted for.

The type selecting stage comprises 4 steps in detail, is respectively: utilize WAsP software and WindFarmer software to calculate the year electricity volume E of the type of respectively being shortlisted for; Calculate the overall life cycle cost LCC of the type of respectively being shortlisted for; Calculate the comprehensive value index V of the type of respectively being shortlisted for; Determine the final type of recommending according to the ordering of comprehensive value index V.

Operating process of the present invention is described in detail below in conjunction with the type selecting example as shown in Figure 1:

A. preliminary type selecting stage

B. detailed type selecting stage

Comprise among the above-mentioned steps A:

A1. gather and plan to build the survey wind data of wind energy turbine set region, match obtains wind speed profile function f (v), dimensional parameters c and form parameter k according to the Weibull probability density characteristics, and f (v) representation is as follows:

$f\left(v\right)=\frac{k}{c}{\left(\frac{v}{c}\right)}^{k-1}\exp [-{\left(\frac{v}{c}\right)}^k]$

The dimensional parameters c of 70 meters height of example wind energy turbine set is 7.5, and form parameter k is 1.83.

A2. gather candidate wind power generating set type basic fundamental parameter (incision wind speed v _i, rated wind speed v _r, cut-out wind speed v _f, wind speed v, rated power P _rWith hub height H), it is as follows to set up power of the assembling unit curve characteristic function P (v):

$P\left(v\right)=\left\{\begin{array}{cc}0& (v<v_i)\\ \frac{v^2-{v_i}^2}{{v_r}^2-v_i}{P}_r& (v_i<v<v_r)\\ P_r& (v_r<v<v_f)\\ 0& (v>v_f)\end{array}\right.$

Collected 293 kinds of types of present 36 main flow wind power generating set manufacturing enterprises in the example wind energy turbine set, with WTG001 to WTG293 above-mentioned type has been numbered.

A3. it is as follows that calculating book is invented defined resource matched index θ:

$\mathrm{\&theta;}=\frac{{\&Integral;}_0^{\&infin;}f\left(v\right)P\left(v\right)\mathrm{dv}}{P_r}=\frac{1}{4(v_i+v_r)}[\mathrm{\&xi;}\left(v_i\right)+3\mathrm{\&xi;}\left(\frac{v_i+2v_r}{3}\right)+3\mathrm{\&xi;}\left(\frac{v_r+2v_i}{3}\right)+\mathrm{\&xi;}\left(v_r\right)]-\frac{\mathrm{\&xi;}\left(v_f\right)}{v_f}$

Wherein: $\mathrm{\&xi;}\left(v\right)=v[1-C\left(v\right)]=v\&CenterDot;\exp [-{\left(\frac{v}{c}\right)}^k].$

Front 10 type of rank is as shown in table 1 from high to low for resource matched index θ in the example wind energy turbine set.

The resource matched index θ list of table 1 candidate type

A4. it is as follows that calculating book is invented defined type cost index σ:

$\mathrm{\&sigma;}=\frac{0.00003\&CenterDot;{P_r}^2+0.37\&CenterDot;P_r+3.8\&CenterDot;H-140}{P_r}$

Front 10 type of rank is as shown in table 2 from low to high for type cost index σ in the example wind energy turbine set.

The type cost index σ list of table 2 candidate type

A5. it is as follows that calculating book is invented defined comprehensive matching index λ:

$\mathrm{\&lambda;}=\frac{\mathrm{\&theta;}}{\mathrm{\&sigma;}}$

Front 10 type of rank is as shown in table 3 from high to low for comprehensive matching index λ in the example wind energy turbine set.

The comprehensive matching index λ list of table 3 candidate type

A6. the comprehensive matching index λ with different type of machines sorts by descending order, and eliminating does not meet the type of wind energy turbine set location construction condition and the safety conditions such as extreme wind speeds, turbulence intensity, final ranking can be used as the type of being shortlisted at front 10 candidate's type, enters the detailed type selecting stage.The concrete quantity of type of being shortlisted for can take the circumstances into consideration to adjust.

Through the analysis to example wind energy turbine set wind energy resources and construction condition, the safety class of the applicable wind power generating set of example wind energy turbine set should be not less than IEC III-B, this wind energy turbine set zone does not have specific (special) requirements at aspects such as weather conditions, conditions of transportation, construction conditions substantially to the wind power generating set type selecting.Front 10 the type design safety grades of comprehensive matching index λ rank all are not less than IEC III-B, namely all meet safety requirement.According to comprehensive matching index λ rank determine to be shortlisted for type and the type of being shortlisted for renumberd, as shown in table 4.

The table 4 type statistical form of being shortlisted for

Comprise among the above-mentioned steps B:

B1. utilize WAsP software and WindFarmer software, and by the electric weight reduction, calculate the year electricity volume E of the type scheme of respectively being shortlisted for.

10 sections of type year electricity volume E that are shortlisted for are more as shown in table 5 for the example wind energy turbine set.

The table 5 type electricity volume E comparison sheet of being shortlisted for

Accompanying drawing 2 is resource matched index θ and year correlation analysis figure of electricity volume E.Figure can find out thus, and the coherence between resource matched index θ and the electricity volume E is fine, and correlation coefficient is near 0.837.This figure has proved the rationality of the defined resource matched index θ computational methods of the present invention.

B2. calculate respectively be shortlisted for type corresponding cost of investment IC, an operating cost OC, maintenance cost MC, failure cost FC, scrap cost DC etc., and calculate overall life cycle cost LCC.

The computational methods of above-mentioned cost and the application in the type selecting example see for details hereinafter.

B3. it is as follows that calculating book is invented defined comprehensive value index V:

$V=\frac{E}{\mathrm{LCC}}$

V is more as shown in table 6 for 10 sections of type comprehensive value indexes of being shortlisted for of example wind energy turbine set.

The table 6 type comprehensive value index V comparison sheet of being shortlisted for

B4. the comprehensive value index V of type of will respectively being shortlisted for sorts by descending order, and rank is at the final recommendation type of being of front three, and the type that wherein ranks the first is " cost performance " the highest type.Under the prerequisite of not purchasing other restrictive conditions such as environment, transportation, installation, recommend preferentially to select.

The example wind energy turbine set is shortlisted for type comprehensive value index V relatively, and it is as shown in table 7 to draw suggested design.

Table 7 wind power generating set shaping recommendation scheme table

Also comprise among the above-mentioned steps B2:

B21. according to existing Unit Selection method, calculate a cost of investment IC of the type of respectively being shortlisted for.A cost of investment IC is more as shown in table 8 for 10 sections of types of being shortlisted for of example wind energy turbine set.

Table 8 a cost of investment IC of the type comparison sheet of being shortlisted for

B22. calculate the operating cost OC of the type of respectively being shortlisted for.Suppose as follows: wind energy turbine set operations staff is 20 people, and employee's wage is 40,000 yuan/year, and the welfare rate is 41%, and the every annual premium of project is 0.15% of a cost of investment, and the riding material expense is about 20 yuan/kW, and other correlative charges are 10 yuan/kW.

OC is more as shown in table 9 for 10 sections of type operating costs of being shortlisted for of example wind energy turbine set.

The table 9 type operating cost OC comparison sheet unit that is shortlisted for: ten thousand yuan

B23. calculate the maintenance cost MC of the type of respectively being shortlisted for.Suppose as follows: the preventive maintenance rate in wind energy turbine set every year is about 10 yuan/kW, the whole overhaul life be 4 years once, the expense of each overhaul be single wind generator form this 30%.

MC is more as shown in table 10 for 10 sections of type maintenance costs of being shortlisted for of example wind energy turbine set.

The table 10 type maintenance cost MC comparison sheet unit that is shortlisted for: ten thousand yuan

B24. calculate the failure cost FC of the type of respectively being shortlisted for.Suppose as follows: rate for incorporation into the power network is 0.61 yuan/kWh, and the electric quantity loss rate is 3% of year electricity volume E, year fault repair expense be in the wind energy turbine set wind power generating set overall cost 0.5%.

FC is more as shown in table 11 for 10 sections of type failure costs of being shortlisted for of example wind energy turbine set.

The table 11 type failure cost FC comparison sheet of being shortlisted for

B25. calculate the scrap cost DC of the type of respectively being shortlisted for.Suppose as follows: the salvage value rate of wind power generating set is 5% in the wind energy turbine set, and residual value counts by negative value.

DC is more as shown in table 12 for 10 sections of type scrap cost of being shortlisted for of example wind energy turbine set.

The table 12 type scrap cost DC comparison sheet unit that is shortlisted for: ten thousand yuan

B26. the overall life cycle cost LCC that calculates the type of respectively being shortlisted for is as follows:

LCC＝IC+OC+MC+FC+DC

LCC is more as shown in table 13 for 10 sections of type overall life cycle costs of being shortlisted for of example wind energy turbine set.

The table 13 type overall life cycle cost LCC comparison sheet of being shortlisted for

Accompanying drawing 3 is the correlation analysis figure of type cost index σ and overall life cycle cost LCC.Figure can find out thus, the good relationship between type cost index σ and the overall life cycle cost LCC, correlation coefficient about 0.652.This figure has proved the rationality of the defined type cost index of the present invention σ computational methods.

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

Claims (1)

1. wind power generating set complex optimum selection method is characterized in that the method may further comprise the steps:

Step 1: gather and plan to build the survey wind data of wind energy turbine set region, match obtains the wind speed profile function;

The formula of described wind speed profile function is:

$f\left(v\right)=\frac{k}{c}{\left(\frac{v}{c}\right)}^{k-1}\exp [-{\left(\frac{v}{c}\right)}^k]$

Wherein:

F (v) is the wind speed profile function;

V is wind speed;

K is form parameter;

C is dimensional parameters;

Step 2: gather the technical parameter of candidate wind power generating set type, set up power of the assembling unit curve characteristic function;

The formula of described power of the assembling unit curve characteristic function is:

$P\left(v\right)=\left\{\begin{array}{cc}0& (v<v_i)\\ \frac{v^2-{v_i}^2}{{v_r}^2-v_i}{P}_r& (v_i<v<v_r)\\ P_r& (v_r<v<v_f)\\ 0& (v>v_f)\end{array}\right.$

Wherein:

P (v) is power of the assembling unit curve characteristic function;

V is wind speed;

v _iBe the incision wind speed;

v _rBe rated wind speed;

v _fBe cut-out wind speed;

P _rBe rated power;

Step 3: computational resource match index on the basis of step 1 and step 2;

The formula of described resource matched index is:

$\mathrm{\&theta;}=\frac{{\&Integral;}_0^{\&infin;}f\left(v\right)P\left(v\right)\mathrm{dv}}{P_r}$

Wherein:

θ is resource matched index;

Step 4: each candidate's type cost index is calculated on the basis in step 2;

The formula of described type cost index is:

$\mathrm{\&sigma;}=\frac{0.00003\&CenterDot;{P_r}^2+0.37\&CenterDot;P_r+3.8\&CenterDot;H-140}{P_r}$

Wherein:

σ is the type cost index;

H is hub height;

Step 5: the comprehensive matching index is calculated on the basis in step 3 and step 4;

The formula of described comprehensive matching index is:

$\mathrm{\&lambda;}=\frac{\mathrm{\&theta;}}{\mathrm{\&sigma;}}$

Wherein:

λ is the comprehensive matching index;

Step 6: the comprehensive matching index of each type is sorted by descending order, select the specified quantity type as being shortlisted for type;

Step 7: the year electricity volume of calculating the type scheme of respectively being shortlisted for;

Step 8: the overall life cycle cost that calculates the type of respectively being shortlisted for;

The formula of described overall life cycle cost is:

LCC＝IC+OC+MC+FC+DC

Wherein:

LCC is overall life cycle cost;

IC is a cost of investment;

OC is operating cost;

MC is maintenance cost;

FC is failure cost;

DC is scrap cost;

Step 9: the comprehensive value index is calculated on the basis in step 7 and step 8;

The formula of described comprehensive value index is:

$V=\frac{E}{\mathrm{LCC}}$

Wherein:

V is the comprehensive value index;

E is a year electricity volume;

Step 10: the comprehensive value index of the type of will respectively being shortlisted for sorts by descending order, and rank is final recommendation type at the type of setting the position.

Images