CN107833149A - A kind of power network development Development stage method and system based on more discriminant criterions - Google Patents

A kind of power network development Development stage method and system based on more discriminant criterions Download PDF

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CN107833149A
CN107833149A CN201711001710.6A CN201711001710A CN107833149A CN 107833149 A CN107833149 A CN 107833149A CN 201711001710 A CN201711001710 A CN 201711001710A CN 107833149 A CN107833149 A CN 107833149A
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CN107833149B (en
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韩丰
李晖
彭冬
薛雅玮
张鹏飞
龙望成
赵朗
李金超
李金颖
侍剑峰
李树林
徐谦
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State Grid Corp of China SGCC
State Grid Zhejiang Electric Power Co Ltd
North China Electric Power University
State Grid Economic and Technological Research Institute
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State Grid Corp of China SGCC
State Grid Zhejiang Electric Power Co Ltd
North China Electric Power University
State Grid Economic and Technological Research Institute
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Abstract

The present invention relates to a kind of power network development Development stage method and system based on more discriminant criterions, it is characterised in that comprises the following steps：1) obtain and include the power network initial data of discriminant criterion, wherein, power network initial data includes some national per capita household electricity consumption, per capita generated energy, per capita domestic load and the historical data of renewable energy power generation amount discriminant criterion per capita；2) power network initial data is handled using PCA, obtains power network development index；3) curve matching power network development index is used；4) evolution of power network development index is divided into by the geometrical property of curve by different developing periods.The present invention can ensure that power network has higher security and economy, and can make up the deficiency of power network development period between country quantitatively in terms of division, and reference frame is provided for the development plan and electric grid investment of power network.

Description

A kind of power network development Development stage method and system based on more discriminant criterions
Technical field
The present invention relates to a kind of power network development Development stage method and system, and more discriminant criterions are based on especially with regard to one kind Power network development Development stage method and system.
Background technology
As the basic industry of national economy, the development of China's power industry also enters the new rise period.By 2013, generating total amount in China's increased by 9.2% on a year-on-year basis, is sure to occupy the first in the world, per capita household electricity consumption 3596 up to 520,700,000,000 kilowatt hours Kilowatt hour, increase by 8.7% than last year, more than world average level.From the point of view of world wide, nineteen ninety, flourishing state Family's per capita household electricity consumption increasess slowly, and moves closer to or tends to saturation, and especially to after 2000, the level of economic development tends to be flat Surely, the growth rate of power consumption is slower, or even declining occurs in the power consumption of some developed countries.It can thus be seen that The power demand of one state can't be always maintained at growing trend, and power demand is likely to occur saturation and even decreased, therefore Power network as electric energy carrier will not also be always maintained at the state of high speed development, as socio-economic development tends to be steady and power network Infrastructure it is substantially perfect, the development of power network also can progressively tend to saturation.Although the power network development of various countries will be by national special The influence of different economy, society, environment, but the power network development of various countries still defers to basic power network development rule, therefore, has The course of necessity research various countries' power network development, vertical carding extract universal power network development rule, specify power network development and want The basic development period of experience and the feature within this developing period, so as to be offered reference for the development of China's power network, this will have Help improve to China's power network development rule and the understanding of future developing trend, contribute to relevant department according to national power network development Period carries out the work such as Electric Power Network Planning and investment work so that and related Electric Power Network Planning investment has more perspective and economy, Can preferably be the development service of social economy so as to ensure that power network has higher security and economy.
In terms of existing power network development Development stage method concentrates on qualitative analysis substantially, mainly pass through the development of electric power network technique Power network development is roughly divided into several periods by the connectedness of stage and regional power grid, can not clearly depict the hair of power network Open up rule.Although division methods existing for prior art also have the period that power network development has been divided using the method for quantitative analysis, But existing division methods only considered a kind of index related to power network development, it is impossible to more comprehensively depict power network Development level.
The content of the invention
In view of the above-mentioned problems, it is an object of the invention to provide a kind of power network development Development stage side based on more discriminant criterions It method and system, can not only ensure that power network has higher security and economy, and power network development between country can be made up The period quantitative deficiency in terms of division, reference frame is provided for the development plan and electric grid investment of power network.
To achieve the above object, the present invention takes following technical scheme：During a kind of power network development based on more discriminant criterions Phase division methods, it is characterised in that comprise the following steps：
1) the power network initial data for including discriminant criterion is obtained, wherein, power network initial data includes being used as discriminant criterion Some national per capita household electricity consumption, generated energy, per capita domestic load and the history number of renewable energy power generation amount per capita per capita According to；
2) power network initial data is handled using PCA, obtains power network development index；
3) curve matching power network development index is used；
4) evolution of power network development index is divided into by the geometrical property of curve by different developing periods.
Further, the power network initial data of acquisition is represented using matrix：
X=(xij)m×n=(X1,X2,…,Xm)
In formula, matrix X is made up of value of the m index in n, xijRepresent value of i-th of index in jth year.
Further, the step 2) is handled power network initial data using PCA, obtains power network hair Exhibition index detailed process be：
2.1) power network initial data is standardized using Z-Score methods, the public affairs of Z-Score method standardizations Formula is：
In formula,The average and standard deviation of respectively i-th desired value；
Achievement data matrix after standardization is：Z=(zij)m×n=(Z1,Z2,…,Zm) meet：E(Zj)=0 and D (Zj) =1j=1,2 ..., m；
2.2) correlation matrix R=(r are solved using standardized index data matrixij)m×m, wherein, rijRepresent index ZiWith ZjBetween coefficient correlation, wherein, rijSolution formula it is as follows：
In formula, cov (Zi,Zj) it is ZiWith ZjCovariance；
2.3) correlation matrix R characteristic value and corresponding characteristic vector are solved, and obtained all features will be solved The corresponding characteristic vector of value is as principal component coefficient；
Because vectorial X is non-zero, so det (R- λ E)=0 be present, that is, determinant be present
| R- λ E |=0 (3)
Solution formula (3) can show that matrix R obtains all eigenvalue λs, be calculated further according to RX=λ X corresponding to characteristic root Characteristic vector；
Assuming that R has the k eigenvalue λs for being more than 01≥λ2≥…≥λk>=0, the characteristic vector corresponding to these characteristic values is A =(a1,a2,…,ak), A is considered as principal component coefficient；
Then k principal component can represent as follows：
Wherein, yiRepresent i-th of principal component, XiRepresent i-th of finger target value
2.4) each principal component y is calculatediContribution rate of the corresponding variance to population variance；
The variance contribution ratio of k principal component successively decreases one by one, then the accumulative variance contribution ratio of preceding t principal component represents For：
2.5) qualified principal component, and the principal component institute for passing through selection are chosen using the principal component selection standard of setting The calculation formula that power network development index f is calculated in corresponding principal component coefficient is as follows：
In formula, k is principal component number, and p is to meet the principal component number that principal component selection standard chooses condition.
Further, the step 3) use the detailed process of curve matching power network development index for：
3.1) it is Richards models to determine power network development exponential fitting model, and the mathematical expression of Richards models is such as Under：
In formula, c is the limiting value of variable, and a is the related parameter of and function initial value；B is rate of rise parameter；D is bent Wire shaped parameter；
3.2) Richards model parameters are determined as curve-fitting method using nonlinear least square method；
3.3) parameter for the Richards models being calculated is updated to Richards models, obtains power network development index Richards curves；
3.4) characteristic point of Richards curves is calculated.
Further, the step 3.2) determines Richards model parameters using L-M methods as curve-fitting method.
Further, the detailed process of the characteristic point of step 3.4) the calculating Richards curves is：
The characteristic point of Richards curves includes P '1、P′2With P '3, acceleration is in P '1Place is maximum, in P '2Place is zero, P′3Place is minimum, and the second dervative and three order derivatives that these three characteristic points pass through Richards functions are zero to draw, Richards letters Functional value and corresponding time point when number second dervative and three order derivatives are zero：
In formula, y1' and T1' it is characteristic point P1' functional value and corresponding time point, y2' and T2' it is characteristic point P2' function Value and corresponding time point, y3' and T3' it is characteristic point P3' functional value and corresponding time point.
Further, the evolution of power network development index is divided into not by the step 4) by the geometrical property of curve With the specific dividing condition of developing period be：Initial development 0~T of period1', accelerated development period T1'~T2', slow down development Period T2'~T3' and saturation developing period T3'~+∞.
To achieve the above object, the present invention takes following technical scheme：During a kind of power network development based on more discriminant criterions Phase dividing system, it is characterised in that the system includes：
One is used for the data acquisition module that acquisition includes the power network initial data of discriminant criterion, wherein, power network original number According to including some national per capita household electricity consumption as discriminant criterion, generated energy, per capita domestic load and renewable per capita per capita The historical data of energy generated energy；
One is used to handle power network initial data using PCA, at the data for obtaining power network development index Manage module；
One is used for the curve fitting module using curve matching power network development index；And
One is used to the evolution of power network development index be divided into different developing periods by the geometrical property of curve Division module.
For the present invention due to taking above technical scheme, it has advantages below：1st, the method that the present invention passes through quantitative description Developing period has been divided for the development of power network so that the division of developing period definitely, with more operability, is advantageous to be directed to The different power network development stages formulates different strategic decisions, improves investment decision precision and efficiency, avoids investment hysteresis from restricting Economic development or the generation of the advanced problem such as cause asset utilization ratio low of investment, have very significant directly or indirectly benefit. 2nd, the present invention is electric into power network development index, then foundation by the horizontal indicator combination of multiple sign power network developments by principal component analysis Net development index divides developing period to power network development, avoids relying on generation caused by single index division power network development period The drawbacks of table is not strong.3rd, the present invention ensure that well using Richards curves as model of fit, its excellent adaptability Fitting effect, be ensure that using L-M methods as curve-fitting method, its excellent optimizing performance and faster convergence rate Higher fitting precision.To sum up, the present invention can ensure that power network has higher security and economy, and can make up state The power network development period quantitative deficiency in terms of division, reference frame is provided for the development plan and electric grid investment of power network between family.
Brief description of the drawings
Fig. 1 is the flow chart of the power network development Development stage method based on more discriminant criterions of the present invention；
Fig. 2 is the Richards curves of the present invention；
Fig. 3 is the corresponding Richards curves of the China Power Grids development index of the present invention.
Embodiment
Come to carry out the present invention detailed description below in conjunction with accompanying drawing.It should be appreciated, however, that accompanying drawing has been provided only more Understand the present invention well, they should not be interpreted as limitation of the present invention.
As shown in figure 1, the power network development Development stage method provided by the invention based on more discriminant criterions, including following step Suddenly：
1st, the power network initial data for including discriminant criterion is obtained, power network initial data includes the electricity consumption per capita of some country Amount, per capita generated energy, per capita domestic load and the per capita historical data of these discriminant criterions of renewable energy power generation amount, and will The power network initial data of acquisition is represented using matrix：
X=(xij)m×n=(X1,X2,…,Xm)
In formula, matrix X is made up of value of the m index in n, xijRepresent value of i-th of index in jth year.
2nd, power network initial data is handled using PCA, obtains power network development index, detailed process is：
2.1) power network initial data is standardized, obtains standardized index data matrix.
Because power network initial data has the different orders of magnitude, it is impossible to be directly used in principal component analysis.Therefore the present invention adopts Power network initial data is standardized with Z-Score methods, so as to eliminate the magnitude differences between power network initial data, So that the full detail of packet initial data containing power network after processing.Wherein, the formula of Z-Score methods standardization is：
In formula,The average and standard deviation of respectively i-th desired value.
Achievement data matrix after standardization is：Z=(zij)m×n=(Z1,Z2,…,Zm) meet：E(Zj)=0 and D (Zj) =1 (j=1,2 ..., m).
2.2) correlation matrix is solved using standardized index data matrix.
Normalized achievement data matrix Z correlation matrix R=(rij)m×m, wherein, rijRepresent index ZiWith Zj Between coefficient correlation, wherein, rijSolution formula it is as follows：
In formula, cov (Zi,Zj) it is ZiWith ZjCovariance.Due to D (Zj)=1, so correlation matrix is equal to association side Poor matrix.Again because of E (Zj)=0, then correlation matrix can represent as follows：
2.3) correlation matrix R characteristic value and corresponding characteristic vector are solved, and obtained all features will be solved The corresponding characteristic vector of value is as principal component coefficient.
For m × m rank matrix R, cause RX=λ X if there is several λ and m dimensions non-vanishing vector X, then claim number λ to be square formation R Characteristic value, non-vanishing vector X are the characteristic vectors of the square formation R corresponding to λ.Because vectorial X is non-zero, so det (R- λ be present E)=0, that is, determinant be present
| R- λ E |=0 (4)
Solution formula (4) can show that matrix R obtains all eigenvalue λs, and it is right to calculate characteristic root institute further according to RX=λ X The feature vector, X answered.
Assuming that R has the k eigenvalue λs for being more than 01≥λ2≥…≥λk>=0, the characteristic vector corresponding to these characteristic values is A =(a1,a2,…,ak), A is considered as principal component coefficient by the present invention.
Then k principal component can represent as follows：
Wherein, yiRepresent i-th of principal component, XiI-th of finger target value is represented, is expressed as matrix form：
Y=ATX (6)
2.4) contribution rate of the variance corresponding to each principal component to population variance is calculated.
Due to being orthogonal, and i-th of principal component y between each principal componentiCorresponding eigenvalue λiBe this it is main into Point variance, then principal component yiCorresponding variance is expressed as to the contribution rate of population variance：
Variance contribution ratio wiPrincipal component y is reactediTo the utilization rate of power network primary data information (pdi).
The variance contribution ratio of k principal component successively decreases one by one, then the accumulative variance contribution ratio of preceding t principal component represents For：
2.5) qualified principal component, and the principal component institute for passing through selection are chosen using the principal component selection standard of setting Power network development index is calculated in corresponding principal component coefficient.
4 horizontal indexs of power network development will be weighed to represent using k principal component, and phase is not present between these principal components Guan Xing, avoid the multicollinearity of initial data.When calculating power network development index, p accumulative variance tributes before can choosing Offer principal component of the rate more than 85%, then calculated by them power network development index f calculation formula it is as follows：
The power network development index f now drawn is time series data, and most of letter with power network initial data Breath, the development level of power network can be symbolized more fully hereinafter.
3rd, it is specific as follows using Richards curve matching power network development indexes：
3.1) it is Richards models to determine power network development exponential fitting model
Power network development index f initial gain amount is smaller, but it has progressed into one quickly over time In growth period, then speedup eases up once again, and finally stablizes in a total amount, this development course be similar to one elongation Sigmoid curve.The species of sigmoid curve is more, and conventional has Logistic curves, Verhulstt curves, Bertalanffy curves With Richards curves etc., wherein, Richards curves have the advantage that other curves hardly match, i.e. Richards curves can Other sigmoid curves are transformed into the change by profile shape parameter, this advantage causes it to retouch diversity growth It is wider to state scope, descriptive power is stronger.Therefore the present invention uses model of fit of the Richards models as power network development index. The mathematical expression of Richards models is as follows：
In formula, c is the limiting value of variable, and a is the related parameter of and function initial value；B is rate of rise parameter；D is bent Wire shaped parameter.The curve of Richards functions is the sigmoid curve using c as asymptote.
3.2) Richards model parameters are determined.
Because Richards models are curves, the present invention is using nonlinear least square method as curve-fitting method. In conventional nonlinear least square method, L-M methods (Levenberg-Marquardt) have the excellent of gradient method and Newton method Point, and there is faster convergence rate, therefore the present invention uses calculation method of parameters of the L-M methods as Richards models, Parameter is calculated and can drawn using existing Matlab program calculations, will not be repeated here.
3.3) parameter for the Richards models being calculated is updated to Richards models, obtains power network development index Richards curves.
3.4) characteristic point of Richards curves is calculated.
Richards curves can be described variable partitions developing period by its different growth acceleration, and it is different Growth acceleration be can be by 3 characteristic point (P '1、P′2、P′3) come what is distinguished, wherein, the acceleration of Richards curves In P '1Place is maximum, in P '2Place is zero, in P '3Place is minimum.This 3 characteristic points can by the second dervatives of Richards functions and Three order derivatives are zero to draw.
Functional value and corresponding time point when Richards functions second dervative given below and three order derivatives are zero：
In formula, y1' and T1' it is characteristic point P1' functional value and corresponding time point, y2' and T2' it is characteristic point P2' function Value and corresponding time point, y3' and T3' it is characteristic point P3' functional value and corresponding time point.
4th, the evolution of power network development index is divided into by the geometrical property of Richards curves by different development Period.
Richards curve quantitatively characterizings the phased development process of power network development index, power network development index experienced Slowly the development course of-fast-slow-saturation, and this development course growth rate specific with Richards curves and curvature phase It is corresponding, therefore developing period can be divided for the evolution of power network development index by the geometrical property of Richards curves, And then the development level of clear and definite national grid.The present invention makees the functional value corresponding to the second dervative zero point of Richards functions For the critical point (P of power network development exponential increase2'), the growth acceleration of power network development index is a=0 at this feature point, this When power network development index speedup it is most fast；The present invention distinguishes the functional value corresponding to three derivative zeros of Richards functions Acceleration point (P as power network development exponential increase1') and clinkering point (P3'), in acceleration point (P1') place's power network development index plus Speed reaches maximum, and now the amplification of power network development index speedup is maximum；In clinkering point (P3') place's power network development index plus Speed reaches minimum value, now the biggest drop of power network development index speedup.Correspondingly, according to the development rail of power network development index Mark and characteristic point, the development course of power network development index can be divided into four developing periods, i.e. initial development period, acceleration Developing period, slow down developing period and saturation developing period.Each developing period it is detailed dividing condition it is as follows：
Initial development period (0~T1′)：Accelerated development is presented in the period in power network development index, but due to primary quantity Relatively low, the amplification of power network development index is less than other developing periods.Constantly accelerate in the development speed of the period power network, and speed Amplification also progressively increase.
Accelerated development period (T1'~T2′)：Accelerated growth, but the increasing of speed are still presented in the period for power network development index Width gradually reduces, until amplification drops to 0.Due to the accumulative effect of development early stage, the power network development in this period is fastest, but The amplification of development speed is gradually reduced.
Slow down developing period (T2'~T3′)：Power network development index is still in growing trend in the period, but due to growth Acceleration is already less than 0, and the growth rate of power network development index constantly reduces, and fall constantly expands, growth now Situation is that the deceleration that growth rate constantly reduces increases.The power network development speed in this period has dropped compared to accelerated development period It is low, but speedup is still very fast.
Saturation developing period (T3'~+∞)：Power network development index is still presented growth trend in the period, and speedup The range of decrease is also gradually reduced, but due to early stage slow down cumulative effect, the speedup in the period is smaller, and is also constantly declining, until Speedup will be 0.The development speed of the power network in this period is slow, is provided with the characteristic of ripe power network substantially.
To sum up, because power network can embody different development characteristic in different developing stage.In initial development period, electricity The scale is smaller of net and build slow, the speedup of power transformation capacity and transmission line length is relatively low, and correspondingly electric grid investment demand is just It is few.After power network enters accelerated development period, power network scale is expanded rapidly, and power transformation capacity and transmission line length quickly increase, phase Ground electric grid investment demand is answered also can quickly to increase.In deceleration developing stage, power network already has more huge scale, and Power network scale also is continuing to increase, but speedup is slowing down, and now the power transformation capacity of power network and the speedup of transmission line of electricity are also begun to down Drop, but still remains faster speedup, and now the investment demand of power network is still higher, due to power network now had compared with Big scale, expending the expense in terms of operation of power networks and maintenance is also increasing.After power network enters saturation stage, the rule of power network Although mould is also being expanded, its rate of expansion is slowing down, and the speedup of power transformation capacity and transmission line length is also gradually reducing, this When electric grid investment also across peak value, start year by year to decline, and finally stablize in a less value, but now power network Operation and maintenance cost reach highest level, but also may proceed to rise.As can be seen here, the change of electric grid investment demand and electricity The residing developing stage of net it is closely related, specify the current developing stage of power network and be advantageous to power grid enterprises and determine suitable power network Scale of investment so that power network can be with appropriate advance in the development of national economy, so as to be preferably community service.In addition, power network Different stages of development there is different Electric Power Network Plannings, construction, operation, maintenance and management task, grasp residing for power network development Stage is advantageous to power grid enterprises and adjusts focus in good time, holds operative orientation.Accordingly, it is determined that developing stage and its rank of power network Duan Tedian, to ensureing that the sustainable development of China's power network is significant.
The present invention also provides a kind of power network development Development stage system based on more discriminant criterions, and the system includes：
One is used for the data acquisition module that acquisition includes the power network initial data of discriminant criterion, wherein, power network original number According to including some national per capita household electricity consumption as discriminant criterion, generated energy, per capita domestic load and renewable per capita per capita The historical data of energy generated energy；
One is used to handle power network initial data using PCA, at the data for obtaining power network development index Manage module；
One is used for the curve fitting module using curve matching power network development index；And
One is used to the evolution of power network development index be divided into different developing periods by the geometrical property of curve Division module.Describe the power network development Development stage based on more discriminant criterions of the present invention in detail below by specific embodiment The detailed process of method, the embodiment of the present invention choose the power network of China as research object, its power network development period are drawn Point.
The present embodiment chooses China in the per capita household electricity consumption of 1960~2014 years, per capita generated energy, per capita domestic load Renewable energy power generation amount composition power network raw data matrix X=(x per capitaij)4×44=(X1,X2,X3,X4)。
Power network raw data matrix X is standardized using Z-Score methods first, so as to obtain standardized index Data matrix Z=(zij)4×44=(Z1,Z2,Z3,Z4)。
Then normalized achievement data matrix Z correlation matrix R, and solve R characteristic value and characteristic vector. Learn that correlation matrix R there are 4 characteristic values by calculating, therefore R has 4 principal components, but corresponding to first characteristic value First principal component variance contribution ratio w1Reach 94.21%, using the principal component selection standard higher than 85%, therefore this reality Example selection first principal component is applied to represent power network initial data, the principal component coefficient corresponding to first principal component is as shown in table 1 below：
The principal component coefficient of table 1
Show that the power network development index f of China is as shown in table 2 below according to formula (9)：
The power network development index of table 2
Time 1971 1972 1973 1974 1975 1976 1977 1978 1979
f 234.64 251.87 269.33 264.17 304.25 311.81 339.31 388.08 420.24
Time 1980 1981 1982 1983 1984 1985 1986 1987 1988
f 424.26 428.65 445.86 468.73 499.28 538.12 582.66 636.40 688.07
Time 1989 1990 1991 1992 1993 1994 1995 1996 1997
f 726.33 759.57 822.46 908.09 994.37 1083.01 155.94 1218.81 1279.19
Time 1998 1999 2000 2001 2002 2003 2004 2005 2006
f 1304.41 1378.69 1496.28 1630.27 1808.84 2078.25 2386.76 2681.74 3068.79
Time 2007 2008 2009 2010 2011 2012 2013 2014
f 3501.09 3666.20 3916.34 4384.88 4936.22 5155.67 5604.66 5767.04
After the power network development index for drawing China, with power network development exponential fitting Richards curves, approximating method Using L-M algorithms, specific fit procedure is programmed by Matlab and completed.Show Richards models to data by fitting result Goodness of fit R2=0.9891, show that Richards models are preferable to the fitting effect of data.In addition, the limiting value c of function =10044, initial parameter a=8.2899, rate of rise b=0.1759, profile shape parameter d=1.7834, it can thus be concluded that going out The Richards models of China Power Grids development index, and draw out corresponding Richards curves.China Power Grids development index is intended The Richards curves closed out are as shown in Figure 3.According to the Richards model parameters drawn, formula (11-12) is being combined, can be with Draw each characteristic point of division China Power Grids developing period, the time of each characteristic point and its appearance is as shown in table 3 below：
3 each characteristic point of table and its time of occurrence
Characteristic point P′1 P′2 P′3
y' 2904.4 5657.2 8347.8
T' 2005 2014 2023
As shown in Table 3, before 2005, Chinese power network development is in initial development period；Between 2005-2014 The power network development of China is in accelerated development period；Chinese power network development is in developing period of slowing down between 2014-2023； After 2023, Chinese power network development is in saturation developing period.
In summary, the present invention will characterize the horizontal multiple characteristic indexs of power network development using principal component analysis and be combined into electricity Net development index so that power network development index can more characterize the development level of a national grid than single features index；This hair It is bright using model of the Richards curves as power network development exponential fitting, and with L-M algorithms as pattern fitting method, energy Access the preferable goodness of fit, the model fitted also can reflected well power network development level and development trend.
The various embodiments described above are merely to illustrate the present invention, and wherein each implementation steps of method etc. are all to be varied from , every equivalents carried out on the basis of technical solution of the present invention and improvement, it should not exclude the protection in the present invention Outside scope.

Claims (8)

  1. A kind of 1. power network development Development stage method based on more discriminant criterions, it is characterised in that comprise the following steps：
    1) the power network initial data for including discriminant criterion is obtained, wherein, power network initial data includes certain as discriminant criterion Individual national per capita household electricity consumption, per capita generated energy, per capita domestic load and the per capita historical data of renewable energy power generation amount；
    2) power network initial data is handled using PCA, obtains power network development index；
    3) curve matching power network development index is used；
    4) evolution of power network development index is divided into by the geometrical property of curve by different developing periods.
  2. 2. a kind of power network development Development stage method based on more discriminant criterions as claimed in claim 1, it is characterised in that will The power network initial data of acquisition is represented using matrix：
    X=(xij)m×n=(X1,X2,…,Xm)
    In formula, matrix X is made up of value of the m index in n, xijRepresent value of i-th of index in jth year.
  3. A kind of 3. power network development Development stage method based on more discriminant criterions as claimed in claim 2, it is characterised in that institute State step 2) to handle power network initial data using PCA, the detailed process for obtaining power network development index is：
    2.1) power network initial data is standardized using Z-Score methods, the formula of Z-Score method standardizations For：
    <mrow> <msub> <mi>z</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mover> <mi>x</mi> <mo>&amp;OverBar;</mo> </mover> <mi>i</mi> </msub> </mrow> <msub> <mover> <mi>s</mi> <mo>&amp;OverBar;</mo> </mover> <mi>i</mi> </msub> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
    In formula,The average and standard deviation of respectively i-th desired value；
    Achievement data matrix after standardization is：Z=(zij)m×n=(Z1,Z2,…,Zm) meet：E(Zj)=0 and D (Zj)=1j =1,2 ..., m；
    2.2) correlation matrix R=(r are solved using standardized index data matrixij)m×m, wherein, rijRepresent index ZiWith Zj Between coefficient correlation, wherein, rijSolution formula it is as follows：
    <mrow> <msub> <mi>r</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <mi>cov</mi> <mrow> <mo>(</mo> <msub> <mi>Z</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>Z</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <msqrt> <mrow> <mi>D</mi> <mrow> <mo>(</mo> <msub> <mi>Z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow> </msqrt> <msqrt> <mrow> <mi>D</mi> <mrow> <mo>(</mo> <msub> <mi>Z</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> </mrow> </msqrt> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>
    In formula, cov (Zi,Zj) it is ZiWith ZjCovariance；
    2.3) correlation matrix R characteristic value and corresponding characteristic vector are solved, and obtained all characteristic value institutes will be solved Corresponding characteristic vector is as principal component coefficient；
    Because vectorial X is non-zero, so det (R- λ E)=0 be present, that is, determinant be present
    | R- λ E |=0 (3)
    Solution formula (3) can show that matrix R obtains all eigenvalue λs, and the feature corresponding to characteristic root is calculated further according to RX=λ X Vector；
    Assuming that R has the k eigenvalue λs for being more than 01≥λ2≥…≥λk>=0, the characteristic vector corresponding to these characteristic values is A= (a1,a2,…,ak), A is considered as principal component coefficient；
    Then k principal component can represent as follows：
    <mrow> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>y</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>y</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>y</mi> <mi>k</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>a</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>a</mi> <mn>21</mn> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>a</mi> <mrow> <mi>m</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>a</mi> <mn>12</mn> </msub> </mtd> <mtd> <msub> <mi>a</mi> <mn>22</mn> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>a</mi> <mrow> <mi>m</mi> <mn>2</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mrow></mrow> </mtd> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mrow></mrow> </mtd> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> <mtd> <mo>.</mo> </mtd> <mtd> <mrow></mrow> </mtd> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>a</mi> <mrow> <mn>1</mn> <mi>k</mi> </mrow> </msub> </mtd> <mtd> <msub> <mi>a</mi> <mrow> <mn>2</mn> <mi>k</mi> </mrow> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>a</mi> <mrow> <mi>m</mi> <mi>k</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>X</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>X</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>X</mi> <mi>m</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
    Wherein, yiRepresent i-th of principal component, XiRepresent i-th of finger target value
    2.4) each principal component y is calculatediContribution rate of the corresponding variance to population variance；
    <mrow> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>k</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>j</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>
    The variance contribution ratio of k principal component successively decreases one by one, then the accumulative variance contribution ratio of preceding t principal component is expressed as：
    <mrow> <mi>&amp;rho;</mi> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>t</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>k</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>j</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow>
    2.5) qualified principal component is chosen using the principal component selection standard of setting, and by corresponding to the principal component of selection Principal component coefficient be calculated power network development index f calculation formula it is as follows：
    <mrow> <mi>f</mi> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <msub> <mi>w</mi> <mn>1</mn> </msub> <msub> <mi>y</mi> <mn>1</mn> </msub> <mo>+</mo> <msub> <mi>w</mi> <mn>2</mn> </msub> <msub> <mi>y</mi> <mn>2</mn> </msub> <mo>+</mo> <mo>...</mo> <mo>+</mo> <msub> <mi>w</mi> <mi>p</mi> </msub> <msub> <mi>y</mi> <mi>p</mi> </msub> <mo>)</mo> <mo>&amp;times;</mo> <mn>100</mn> </mrow> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>p</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>k</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>j</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>
    In formula, k is principal component number, and p is to meet the principal component number that principal component selection standard chooses condition.
  4. A kind of 4. power network development Development stage method based on more discriminant criterions as claimed in claim 3, it is characterised in that institute State step 3) use the detailed process of curve matching power network development index for：
    3.1) it is Richards models to determine power network development exponential fitting model, and the mathematical expression of Richards models is as follows：
    <mrow> <msub> <mi>y</mi> <mn>3</mn> </msub> <mo>=</mo> <mfrac> <mi>c</mi> <msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <msup> <mi>e</mi> <mrow> <mi>a</mi> <mo>-</mo> <mi>b</mi> <mi>t</mi> </mrow> </msup> <mo>)</mo> </mrow> <mrow> <mn>1</mn> <mo>/</mo> <mi>d</mi> </mrow> </msup> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow>
    In formula, c is the limiting value of variable, and a is the related parameter of and function initial value；B is rate of rise parameter；D is shaped form Shape parameter；
    3.2) Richards model parameters are determined as curve-fitting method using nonlinear least square method；
    3.3) parameter for the Richards models being calculated is updated to Richards models, obtains power network development index Richards curves；
    3.4) characteristic point of Richards curves is calculated.
  5. A kind of 5. power network development Development stage method based on more discriminant criterions as claimed in claim 4, it is characterised in that institute State step 3.2) and Richards model parameters are determined as curve-fitting method using L-M methods.
  6. A kind of 6. power network development Development stage method based on more discriminant criterions as claimed in claim 4, it is characterised in that institute State step 3.4) and calculate the detailed processes of characteristic point of Richards curves and be：
    The characteristic point of Richards curves includes P1'、P2' and P3', acceleration is in P1' place's maximum, in P2' place is zero, in P3' place Minimum, the second dervative and three order derivatives that these three characteristic points pass through Richards functions are zero to draw, Richards functions two Functional value and corresponding time point when order derivative and three order derivatives are zero：
    <mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msup> <msub> <mi>y</mi> <mn>1</mn> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mfrac> <mi>c</mi> <msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <mfrac> <mrow> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>3</mn> <mi>d</mi> <mo>-</mo> <msqrt> <mrow> <msup> <mi>d</mi> <mn>4</mn> </msup> <mo>+</mo> <mn>5</mn> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>6</mn> <msup> <mi>d</mi> <mn>3</mn> </msup> </mrow> </msqrt> </mrow> <mn>2</mn> </mfrac> <mo>)</mo> </mrow> <mfrac> <mn>1</mn> <mi>d</mi> </mfrac> </msup> </mfrac> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msup> <msub> <mi>y</mi> <mn>2</mn> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mfrac> <mi>c</mi> <msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <mi>d</mi> <mo>)</mo> </mrow> <mfrac> <mn>1</mn> <mi>d</mi> </mfrac> </msup> </mfrac> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msup> <msub> <mi>y</mi> <mn>3</mn> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mfrac> <mi>c</mi> <msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <mfrac> <mrow> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>3</mn> <mi>d</mi> <mo>+</mo> <msqrt> <mrow> <msup> <mi>d</mi> <mn>4</mn> </msup> <mo>+</mo> <mn>5</mn> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>6</mn> <msup> <mi>d</mi> <mn>3</mn> </msup> </mrow> </msqrt> </mrow> <mn>2</mn> </mfrac> <mo>)</mo> </mrow> <mfrac> <mn>1</mn> <mi>d</mi> </mfrac> </msup> </mfrac> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow>
    <mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msup> <msub> <mi>T</mi> <mn>1</mn> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mo>-</mo> <mfrac> <mrow> <mi>l</mi> <mi>n</mi> <mrow> <mo>(</mo> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>3</mn> <mi>d</mi> <mo>-</mo> <msqrt> <mrow> <msup> <mi>d</mi> <mn>4</mn> </msup> <mo>+</mo> <mn>5</mn> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>6</mn> <msup> <mi>d</mi> <mn>3</mn> </msup> </mrow> </msqrt> <mo>)</mo> </mrow> <mo>-</mo> <mi>l</mi> <mi>n</mi> <mn>2</mn> <mi>a</mi> </mrow> <mi>b</mi> </mfrac> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msup> <msub> <mi>T</mi> <mn>2</mn> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mo>-</mo> <mfrac> <mrow> <mi>l</mi> <mi>n</mi> <mfrac> <mi>d</mi> <mi>a</mi> </mfrac> </mrow> <mi>b</mi> </mfrac> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msup> <msub> <mi>T</mi> <mn>3</mn> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mo>-</mo> <mfrac> <mrow> <mi>l</mi> <mi>n</mi> <mrow> <mo>(</mo> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>3</mn> <mi>d</mi> <mo>+</mo> <msqrt> <mrow> <msup> <mi>d</mi> <mn>4</mn> </msup> <mo>+</mo> <mn>5</mn> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <mn>6</mn> <msup> <mi>d</mi> <mn>3</mn> </msup> </mrow> </msqrt> <mo>)</mo> </mrow> <mo>-</mo> <mi>l</mi> <mi>n</mi> <mn>2</mn> <mi>a</mi> </mrow> <mi>b</mi> </mfrac> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> </mrow>
    In formula, y1' and T1' it is characteristic point P1' functional value and corresponding time point, y2' and T2' it is characteristic point P2' functional value and Corresponding time point, y3' and T3' it is characteristic point P3' functional value and corresponding time point.
  7. A kind of 7. power network development Development stage method based on more discriminant criterions as claimed in claim 6, it is characterised in that institute State step 4) and the evolution of power network development index is divided into by the geometrical property of curve by the specific of different developing periods Dividing condition is：Initial development 0~T of period1', accelerated development period T1'~T2', slow down developing period T2'~T3' and saturation Developing period T3'~+∞.
  8. 8. a kind of power network development Development stage system based on more discriminant criterions, it is characterised in that the system includes：
    One is used for the data acquisition module that acquisition includes the power network initial data of discriminant criterion, wherein, power network raw data packets Include as some national per capita household electricity consumption of discriminant criterion, generated energy, per capita domestic load and regenerative resource per capita per capita The historical data of generated energy；
    One is used to handle power network initial data using PCA, obtains the data processing mould of power network development index Block；
    One is used for the curve fitting module using curve matching power network development index；And
    One is used to the evolution of power network development index be divided into drawing for different developing periods by the geometrical property of curve Sub-module.
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