CN105427049A - Segmentation theory based power grid project pre-planning and operation and maintenance stage prewarning method - Google Patents
Segmentation theory based power grid project pre-planning and operation and maintenance stage prewarning method Download PDFInfo
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Abstract
The invention discloses an optimal segmentation theory based power grid project pre-planning and operation and maintenance stage investment prewarning method. The method comprises: firstly, for a fund plan and an actual condition of a power grid project pre-planning and operation and maintenance stage, establishing an investment monitoring point set; secondly, collecting investment monitoring point sample data and determining a preliminary prewarning threshold range by utilizing an optimal segmentation theory; thirdly, introducing judgment and analysis to correct the prewarning threshold range; and finally, according to an investment plan and an actual condition of an actual power grid project pre-planning and operation and maintenance stage, calculating monitoring data by substitution to obtain a prewarning situation, and performing dynamic monitoring until the total lifetime of a power grid project is up. According to the method, the investment risk can be effectively prewarned, so that the investment risk of the power grid project during the pre-planning and operation and maintenance stage can be prewarned in time and a certain foundation is provided for the research on investment risk control of the power grid project.
Description
Technical field
The invention belongs to Grid Construction Project management and control technical field.In particular to a kind of electricity power engineering preliminary planning based on segmentation theory and O&M stage method for early warning, for the investment supervision and control demand implementation phase of electricity power engineering specifically, adopt the method for extreme value theory, the investment implementation phase of electricity power engineering is dynamically followed the tracks of, weighs, deviation pre-alert, reach investment risk monitoring object.
Background technology
Important content in project management and key link are investment controls.When meeting progress and quality standard, by the control of investment of construction project in approval estimation limit category, and in time deviation being corrected, and then effectively guaranteeing that engineering project realizes the good investment objective.
In engineering life cycle management, there are itself singularity in preconsolidation stress and these two stages of later stage O&M, namely the preconsolidation stress of electricity power engineering determines the technology of whole engineering and cost trend, the controllability of longer and these two the stage costs of later stage O&M phases-time.Because power engineering industry internal competition is fierce, social credit mechanism is unsound, supervise unfavorable, lack the various factors such as sense of risk and legal conception, because the ineffective risk of project planning and operational management aspect is comparatively common, the effective Investment Premonition alarm method of research is very urgent.China at present for early warning and the management and control of electricity power engineering preliminary planning and the investment risk in O&M stage, complete, unripe method.
Summary of the invention
The object of the invention is to propose a kind of electricity power engineering preliminary planning based on segmentation theory and O&M stage method for early warning, it is characterized in that, comprise the steps:
(1) for electricity power engineering preliminary planning and the fund planning in O&M stage and actual conditions, the life cycle management of electricity power engineering is divided into different phase, sets up investment monitoring point set;
(2) collect investment monitoring point sample data, determine the interval optimum segmentation definite threshold of preliminary threshold value of warning;
(3) introduce discriminatory analysis, revise threshold value of warning interval;
(4) according to the actual preliminary planning of electricity power engineering project and the pogo plan in O&M stage and actual conditions, the data of monitoring are carried out substitution measuring and calculating, draw early warning situation, dynamic monitoring, until electricity power engineering total life cycle terminates.
The implementation step of described step (2) is as described below:
1) class diameter is defined
First according to index arrangement ordering C [p (n, k)], and p is established
*the a certain class of (n, k) is C [p (n, k)], and its mean vector is
P (n, 2): 1,2 ..., j-1}, j, j+1 ..., n} (formula 1)
Then definable class (x
1, x
2,x
n) diameter be
K≤j≤n (formula 2)
Wherein: n is the sum of achievement data; K is the classification quantity of achievement data; J is the order of data
Figure place; P (n, k) is a kind of method n ordered data being divided into k class; p
*(n, k's) is a certain class methods of p (n, k).
2) objective definition function
If p (n, k) is a kind of method n ordered data being divided into k class, wherein branch i
1=1<i
2< ... <i
k<i
k+1=n+1, then definable objective function is the summation of all kinds of deviation square,
Namely
(formula 3)
When C [p (n, k)] more hour, the quadratic sum between all kinds of is larger.Therefore, optimization is exactly division when making objective function reach minimum; The calculated value of sum of squares of deviations in the class that D (i, j) is such.
3) optimum segmentation is calculated
Use G
k-1={ j
k-1, j
k-1+ 1 ..., n} represents makes p (n, 2): 1,2 ..., j-1}, j, j+1 ..., n} reaches minimum classification.When two segmentations, so have
In like manner, as k≤j≤n, then available recurrence method asks objective function
Therefore, when observed data is split in order for n, first j can be found
kmake:
C [p
*(n, k)]=C [p
*(j
k-1, k-1)]+D (j, n) } (formula 6)
So obtain kth class G
k={ j
k, j
k+1..., n}, then looks for j
k-1, make it meet
C [p
*(j
k-1, k-1)]=C [p
*(j
k-1, k-2)]+D (j
k-1, n) } and (formula 7)
Obtain kth-1 class G
k-1={ j
k-1, j
k-1+ 1 ..., n}, continues successively, finally tries to achieve required optimum k and is divided into
P
*(n, k)=(G
1, G
2..., G
n) (formula 8);
4) comparatively optimal sorting hop count is determined
Determine that objective function changes function with piecewise function: C [p (n, k)]-k, the segments that the corner of this curve is corresponding is preferably segments, calculates this slope of a curve difference:
β (k)=| (C [p (n, k-1)]-C [p (n, k)])/(k-(k-1)) |-| (C [p (n, k)]-C [p (n, k+1)])/(k-(k-1)) | ... ... ... ... ... .... (formula 9)
Threshold value of warning interval is not continuous print, as shown in table 1
The preliminary threshold value of warning of table 1 is interval
Described step (3) introduces discriminatory analysis, revises threshold value of warning interval and comprises:
1) distance between new samples and class is defined
Due to the cluster principle of classical Fisher algorithm be ensure prerequisite that sequence is not destroyed under make sum of squares of deviations in class minimum, between class, sum of squares of deviations is maximum, so after being included into and should keeping forming new class equally of new samples, in new class, sum of squares of deviations is minimum, and between new class, sum of squares of deviations is maximum.Original cluster principle can be kept using square Euclidean distance as the distance metric between sample and class, and square Euclidean distance is for defining the distance used by class diameter in classical Fisher algorithm, so adopt square Euclidean distance to be rational as the distance between new samples and class.Definition squared euclidean distance is as follows
D (x, G
1)=(x-μ
1)
2(formula 10)
Wherein: G
1representation class, its average is μ
1, x is new samples.
2) discriminant function and decision rule is defined
W (x)=d (x, G
1)-d (x, G
2) (formula 11)
Decision rule: if W (x) is >0, then new samples is included into G
2class, otherwise be included into G
1class.Revise early warning
Threshold interval to make it continuous, as table 3 ?1,3 ?shown in 2 (wherein: c
i≤ 0, b
i>=0).
If the electricity power engineering investment monitoring node K0 implemented (K0 ∈ K1, K2 ..., Kn}) investment deviation value be that { c3 ~ c2}, then the alert of investing monitoring node K0 is " rectification " to p0, p0 ∈.
The final early warning of table 2 is interval
Table 3 ?1 preliminary planning multi-stage invest control point system
Table 3 ?2 O&M multi-stage invest control points
Beneficial effect of the present invention is that the present invention can carry out investment risk early warning effectively, thus making electricity power engineering project carry out early warning timely in preliminary planning and the investment risk in O&M stage, the research that the investment risk for electricity power engineering project controls provides certain basis.
Accompanying drawing explanation
Fig. 1 is electricity power engineering preliminary planning based on optimum segmentation theory and O&M multi-stage invest method for early warning workflow diagram.
Embodiment
The present invention proposes a kind of electricity power engineering preliminary planning based on segmentation theory and O&M stage method for early warning, is explained below in conjunction with drawings and Examples.Concrete steps are as shown in Figure 1 as follows:
The first step: drop into projected conditions for the fund using plan in the implementation phase of electricity power engineering with actual, set up investment monitoring point set;
Second step: investment monitoring point data gathers
Described in the first step, choosing of electricity power engineering preconsolidation stress decision phase investment monitoring point is contract bag based on occurring in engineering practice mid-early stage planning process, each contract bag is exactly a point to be monitored, present case adopts main equipment installation work contract bag as control point, be designated as K1, select the investment deviation ratio of this monitoring node, be set to A0.Again according to history engineering record choose 2013 ?2014 liang of years 10 similar projects investment estimation data, what need to illustrate is again, so-called similar projects refers to that with wanting the new construction of early warning the same be all mini engineering, at utmost can ensure the feasibility adopting the data of history engineering for purpose project early warning like this.Calculate monitoring node K1 investment over-expense than data, concrete form is as shown in table 4, and because electrical network main equipment installation work technology reaches its maturity, industry standard is specification comparatively, and also reducing appears in over-expense situation thereupon.
Table 4 history similar projects detection node over-expense table
3rd step: data optimum segmentation
Described in optimum segmentation basic theory, K1 node unit over-expense in each history similar projects shown in table 4 is sorted from small to large than data, forms a vector, this mean vector input optimum segmentation theory calculate device is calculated data as shown in table 5.The vector wherein formed is as follows:
(0.01％,0.32％,1.56％,3.12％,3.78％,4.56％,4.89％,6.44％,7.32％,9.65％)，
Table 5 optimum segmentation basic theory result of calculation
Table 3 ?in 6, k represents segmentation hop count, C [p (n, k)] represent deviation total sum of squares in class when being divided into k class, k is larger, then C [p (n, k)] less, represent all kinds of between quadratic sum larger, in the class that now data rows separates, all kinds of interior data are more concentrated, and all kinds of are at utmost separated.As mentioned before, in order to seek optimal classes, construct β (k), the k corresponding when β (k) reaches maximum is optimal segmentation number.Visible, in present case, be optimal segmentation when segments is 4 sections.At k=4 place, there is flex point in function C [p (n, k)]-k.So, optimum segmentation be 1 ?3}, 4 ?7}{8 ?9}, { 10}.Thus corresponding threshold range can be obtained, as shown in table 6.
Table 6 substation project cost warp rate threshold value of warning
According to arrears alert theory system part, based on the theoretical defects of optimum segmentation basic theory, be the indispensable part of this system to the optimization of this basic theory, illustrate how discriminant analysis theory solves this defect problem by case below.Such as, according to the result that optimum segmentation basic theory obtains, 5% in the class that optimal segmentation obtains, and this just needs differentiation 5% which kind of to belong to actually.For this reason, according to optimum theory above, introduce discriminant analysis theory and sort out 5%.
Differentiate which kind of these data belong to, introduce discriminant function W (x)=d (x, G
1)-d (x, G
2), because 2.2% belongs to data between the 1st class and the 2nd class class, therefore G1 is the 1st class, and G2 is the 2nd class.Calculate these data according to discriminant analysis theory and belong to the 1st class, the data between other classes process equally.
According to the research of the applicability problem to minus deviation data, equally minus deviation data are processed, finally obtain complete early warning interval as shown in table 7.Interval according to final early warning, if the investment estimation deviation ratio of monitoring point " main production engineering expense " is 6% in newly-built power transformation engineering project, then the early warning result of this investment deviation is stopped work.
The final early warning of table 7 is interval
4th step: analyze
According to case computation process, this case computation process is made up of two large divisions, first optimum segmentation basic theory result of calculation forms an original early warning interval, secondly discriminatory analysis optimizes this basic theory, compensate for the defect of optimum segmentation theory in theory, make early warning interval more complete, and be convenient to early warning personnel and directly draw early warning result.
In addition, in the computation process of case, choose the systematic error problem that unit project amount investment deviation ratio more can be avoided as monitoring index causing because project scale is different; Minus deviation data rows is done the same process of same overgauge data and minus deviation problem can be made to be resolved by computation process.
Due to the disunity of the standard of reconstruction and extension project cost, cause construction investment early warning variable factor more, so do not do early warning analysis to the investment of reconstruction and extension project, namely this pre-alarming system is only applicable to new construction.In addition, in construction costs reality, power transmission engineering and power transformation engineering cost have separability feature, so the investment early warning of power transmission engineering and power transformation engineering separated, early warning respectively.
The early warning of preliminary planning multi-stage invest control point is interval, according to the investment Early-warning Model in preliminary planning stage, each control point has a final early warning interval, and the interval data construct according to control point same in similar projects in history in the past of this early warning forms.Improve with described in applied research about optimum segmentation theory in conjunction with a upper joint, then copy the case analysis of this section Part II, little according to state's network mark standard, in, that heavy construction builds the final early warning of preconsolidation stress stage all investment monitorings point is respectively interval.
1) mini engineering early warning: accurate according to state network mark, below electric pressure 110Kv and design length is less than 250Km is small grids engineering; Described in last joint, because more than 70% of electricity power engineering construction project total cost produces (" Grid Construction Project Control and administration of Construction Cost ") due to equipment and Master Cost, same electric pressure and the little transmission distance of difference just define the qualitative rank of equipment and material, and therefore this is also the essence reason dividing large, medium and small type engineering.The difference of similar electricity power engineering project investment total value is mainly based on the difference of amount, i.e. circuit mileage, so just can take into account the impact of construction investment total value.Based on this reason, think that in same class electricity power engineering project, even if the contract price of same monitoring point is different, but the same deviation ratio of same monitoring node just has same alert.Finally, copy the case analysis of this section Part II to calculate the early warning interval of each investment monitoring point of small grids engineering preliminary planning stage, final early warning interval is in table 8.
The early warning of table 8 preliminary planning multi-stage invest control point is interval
2) medium-sized forewarning on engineering failure: accurate according to state's network mark, electric pressure is 220Kv or 110Kv, and circuit long design more than 250Km is medium-sized electricity power engineering.Similar with mini engineering early warning, think that in same class electricity power engineering project, even if the contract price of same monitoring point is different, but the same deviation ratio of same monitoring node just has same alert.Finally, the case analysis of this section Part II is copied to calculate the early warning interval of each investment monitoring point of medium-sized electricity power engineering preliminary planning stage.
3) heavy construction early warning: accurate according to state's network mark, electric pressure is more than 330Kv is large-scale power grid engineering.Similar with small-sized and medium-sized forewarning on engineering failure, think that in same class electricity power engineering project, even if the contract price of same monitoring point is different, but the same deviation ratio of same monitoring node just has same alert.Finally, the case analysis of this section Part II is copied to calculate the early warning interval of each investment monitoring point of large-scale power grid engineering preliminary planning stage.
Described in above, choosing of electricity power engineering operation and maintenance stage investment monitoring point is contract bag based on occurring in operation maintenance process in engineering practice, and each contract bag is exactly a point to be monitored.According to the investment Early-warning Model in O&M stage, each control point has a final early warning interval, and the interval data construct according to control point same in similar projects in history in the past of this early warning forms; Copy case analysis above, can the final early warning of structure O&M stage all investment monitorings point interval.
5th step: according between above-mentioned electricity power engineering preliminary planning and the Investment Premonition police region in O&M stage etc., carries out the early warning of dynamic investment risk for the preliminary planning of electricity power engineering project and O&M stage.
Claims (3)
1., based on electricity power engineering preliminary planning and the O&M stage method for early warning of segmentation theory, it is characterized in that, comprise the steps:
(1) for electricity power engineering preliminary planning and the fund planning in O&M stage and actual conditions, the life cycle management of electricity power engineering is divided into different phase, sets up investment monitoring point set;
(2) collect investment monitoring point sample data, determine the interval optimum segmentation definite threshold of preliminary threshold value of warning
(3) introduce discriminatory analysis, revise threshold value of warning interval;
(4) according to the actual preliminary planning of electricity power engineering project and the pogo plan in O&M stage and actual conditions, the data of monitoring are carried out substitution measuring and calculating, draw early warning situation, dynamic monitoring, until electricity power engineering total life cycle terminates.
2., according to claim 1 based on electricity power engineering preliminary planning and the O&M stage method for early warning of segmentation theory, it is characterized in that, the implementation step of described step (2) is as described below:
1) class diameter is defined
First according to index arrangement ordering C [p (n, k)], and p is established
*the a certain class of (n, k) is C [p (n, k)], and its mean vector is
P (n, 2): 1,2 ..., j-1}, j, j+1 ..., n} (formula 1)
Then definable class (x
1, x
2... x
n) diameter be
K≤j≤n (formula 2)
Wherein: n is the sum of achievement data; K is the classification quantity of achievement data; J is the order figure place of data; P (n, k) is a kind of method n ordered data being divided into k class; p
*(n, k's) is a certain class methods of p (n, k);
2) objective definition function
If p (n, k) is a kind of method n ordered data being divided into k class, wherein branch i
1=1<i
2< ... <i
k<i
k+1=n+1, then definable objective function is the summation of all kinds of deviation square, namely
Then when C [p (n, k)] more hour, the quadratic sum between all kinds of is larger, and therefore, optimization is exactly division when making objective function reach minimum; The calculated value of sum of squares of deviations in the class that D (i, j) is such;
3) optimum segmentation is calculated
Use G
k-1={ j
k-1, j
k-1+ 1 ..., n} represents makes p (n, 2): 1,2 ..., j-1}, j, j+1 ..., n} reaches minimum classification;
When two segmentations, so have
In like manner, as k≤j≤n, then available recurrence method asks objective function
Therefore, when observed data is split in order for n, first j can be found
kmake:
C [p
*(n, k)]=C [p
*(j
k-1, k-1)]+D (j, n) } (formula 6)
So obtain kth class G
k={ j
k, j
k+1..., n}, then looks for j
k-1, make it meet
C [p
*(j
k-1, k-1)]=C [p
*(j
k-1, k-2)]+D (j
k-1, n) } and (formula 7)
Obtain kth-1 class G
k-1={ j
k-1, j
k-1+ 1 ..., n}, continues successively, finally tries to achieve required optimum k and is divided into
P
*(n, k)=(G
1, G
2..., G
n) (formula 8)
4) comparatively optimal sorting hop count is determined
Determine that objective function changes function with piecewise function: C [p (n, k)]-k, the segments that the corner of this curve is corresponding is preferably segments, calculates this slope of a curve difference:
β (k)=| (C [p (n, k-1)]-C [p (n, k)])/(k-(k-1)) |-| (C [p (n, k)]-C [p (n, k+1)])/(k-(k-1)) | (formula 9)
Threshold value of warning interval is not continuous print, as shown in table 1
The preliminary threshold value of warning of table 1 is interval
3. according to claim 1 based on electricity power engineering preliminary planning and the O&M stage method for early warning of segmentation theory, it is characterized in that, described step (3) introduces discriminatory analysis, revises threshold value of warning interval and comprises:
1) distance between new samples and class is defined
Due to the cluster principle of classical Fisher algorithm be ensure prerequisite that sequence is not destroyed under make sum of squares of deviations in class minimum, between class, sum of squares of deviations is maximum, so after being included into and should keeping forming new class equally of new samples, in new class, sum of squares of deviations is minimum, between new class, sum of squares of deviations is maximum, original cluster principle can be kept using square Euclidean distance as the distance metric between sample and class, and square Euclidean distance is for defining the distance used by class diameter in classical Fisher algorithm, so adopt square Euclidean distance to be rational as the distance between new samples and class, definition squared euclidean distance is as follows
D (x, G
1)=(x-μ
1)
2(formula 10)
Wherein: G
1representation class, its average is μ
1, x is new samples;
2) discriminant function and decision rule is defined
W (x)=d (x, G
1)-d (x, G
2) (formula 11)
Decision rule: if W (x) is >0, then new samples is included into G
2class, otherwise be included into G
1class;
Revise threshold value of warning interval to make it continuous, as shown in table 3-1,3-2 (wherein: c
i≤ 0, b
i>=0), if the electricity power engineering investment monitoring node K0 implemented (K0 ∈ K1, K2 ..., Kn}) investment deviation value be p0, p0 ∈ c3 ~ c2}, then the alert of investing monitoring node K0 is " rectification ";
The final early warning of table 2 is interval
Table 3-1 preliminary planning multi-stage invest control point system
Table 3-2 O&M multi-stage invest control point
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110445149A (en) * | 2019-08-15 | 2019-11-12 | 国网湖南省电力有限公司 | A kind of not equal capacity group technology of substation's parallel capacitor group |
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2015
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110445149A (en) * | 2019-08-15 | 2019-11-12 | 国网湖南省电力有限公司 | A kind of not equal capacity group technology of substation's parallel capacitor group |
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