CN109993402A - A kind of power grid project risk determines method - Google Patents
A kind of power grid project risk determines method Download PDFInfo
- Publication number
- CN109993402A CN109993402A CN201910126138.9A CN201910126138A CN109993402A CN 109993402 A CN109993402 A CN 109993402A CN 201910126138 A CN201910126138 A CN 201910126138A CN 109993402 A CN109993402 A CN 109993402A
- Authority
- CN
- China
- Prior art keywords
- index
- project
- power grid
- fuzzy
- investment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000013139 quantization Methods 0.000 claims abstract description 11
- 230000005611 electricity Effects 0.000 claims description 28
- 239000011159 matrix material Substances 0.000 claims description 19
- 230000009467 reduction Effects 0.000 claims description 10
- 238000005516 engineering process Methods 0.000 claims description 8
- 230000009466 transformation Effects 0.000 claims description 8
- 238000010606 normalization Methods 0.000 claims description 7
- 238000013210 evaluation model Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 4
- 230000008901 benefit Effects 0.000 claims description 3
- 238000013459 approach Methods 0.000 claims description 2
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 230000005540 biological transmission Effects 0.000 description 8
- 238000010276 construction Methods 0.000 description 6
- 238000012502 risk assessment Methods 0.000 description 5
- 238000007726 management method Methods 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000010348 incorporation Methods 0.000 description 2
- FGRBYDKOBBBPOI-UHFFFAOYSA-N 10,10-dioxo-2-[4-(N-phenylanilino)phenyl]thioxanthen-9-one Chemical compound O=C1c2ccccc2S(=O)(=O)c2ccc(cc12)-c1ccc(cc1)N(c1ccccc1)c1ccccc1 FGRBYDKOBBBPOI-UHFFFAOYSA-N 0.000 description 1
- FNMKZDDKPDBYJM-UHFFFAOYSA-N 3-(1,3-benzodioxol-5-yl)-7-(3-methylbut-2-enoxy)chromen-4-one Chemical compound C1=C2OCOC2=CC(C2=COC=3C(C2=O)=CC=C(C=3)OCC=C(C)C)=C1 FNMKZDDKPDBYJM-UHFFFAOYSA-N 0.000 description 1
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Method is determined the invention discloses a kind of power grid project risk, including building electric grid investment project risk confirms index system, and index system is from top to bottom divided into destination layer, classification layer and three layers of indicator layer；Quantitative target and qualitative index in quantizating index layer；Each quantitative, qualitative index obtained after quantization is normalized；Determine the weight of each index after normalizing；Power grid project risk is confirmed according to the index after determining weight.
Description
Technical field
The invention belongs to power grid project risks to determine technical field, in particular to a kind of electric grid investment Project Risk Assessment is new
Method.
Background technique
New electricity changes under environment, and electric grid investment faces huge uncertainty, such as rate for incorporation into the power network, electricity sales amount, power supply cost, line
Loss rate, average rate of electricity sold, power purchase valence and power supply reliability etc. need to be counted in the presence of uncertainty, therefore when electric grid investment assessment and wind
Danger.
Power grid enterprises assess after often laying particular emphasis on when assessing investment at present, which generally uses certainty side
Method.Right electricity changes the uncertainty of power grid enterprises under environment, and risk assessment need to be carried out before investment, need to be retouched using uncertain method
It states.On method of investment appraisal, since electric grid investment belongs to Multiple Attribute Decision Problems.
Summary of the invention
Of the existing technology in order to solve the problems, such as, the present invention provides a kind of power grid project risk and determines method, Neng Gougen
Comprehensive descision is carried out according to a variety of uncertain factors, so that judging power grid project risk degree closer to practical.
The technical problem to be solved by the present invention is to what is be achieved through the following technical solutions:
A kind of power grid project risk determines method, including
It constructs electric grid investment project risk and confirms index system, and index system is from top to bottom divided into destination layer, classification
Layer and three layers of indicator layer；
Quantitative target and qualitative index in quantizating index layer；
Each quantitative, qualitative index obtained after quantization is normalized；Specifically:
For quantitative target, quantitative target is normalized based on " rewarding the good and punishing the bad " principle, specifically:
It enables
Wherein,For the mean value (mean value for referring to all j-th of indexs of m project) of interval type achievement data, m and n difference
For project total number yet to be built and index total number,Respectively xijLower bound and the upper bound, xijFor i-th of project jth yet to be built
The index value of a index；
For profit evaluation model index therein, have
For cost type index therein, have
Wherein,WithLower bound and the upper bound after the linear transformation of respectively i-th j-th of index of project yet to be built；
For qualitative index, qualitative index is normalized based on " rewarding the good and punishing the bad " principle, specifically:
If
Wherein, n is index total number, vjFor the mean value of fuzzy targets data,Respectively i-th to
Build fuzzy payoff of j-th of the index of project when the Triangular Fuzzy Number upper bound, lower bound and degree of membership are 1；
For profit evaluation model index therein, have
For cost type index therein, have
Wherein,Respectively i-th j-th of index of project yet to be built " is rewarded the good and punished the bad " after principle normalization
Fuzzy payoff when the Triangular Fuzzy Number upper bound, lower bound and degree of membership are 1, For the maximum value in all items at the Triangular Fuzzy Number upper bound and lower bound；
By " rewarding the good and punishing the bad " linear transformation, the evaluations matrix A=(x that each achievement data is constitutedij)m×nIt is normalized to refer to
Mark the Standard Process E=(e that section is [- 1,1]ij)m×n, eijFor the normalized value of i-th of j-th of index of project yet to be built.
The quantization of quantitative target specifically:
If the index value of j-th of index of i-th of project yet to be built is xij, set xijSection, i.e. xijSection beWherein,Respectively xijUpper and lower bound.The setting in section is according to the maximum value of each index and most
Small value defines.Maximin is rule of thumb set；
The quantization of qualitative index are as follows:
It is given a mark by expert to each qualitative index, and the index after marking is further quantified by Triangular Fuzzy Number, measured
Change result to be shown below:
Wherein, n is to participate in marking expert's number,Respectively i-th j-th of index of project yet to be built is three
Fuzzy payoff when the angle fuzzy number upper bound, lower bound and degree of membership are 1,Respectively k-th of expert couple
Marking value of i-th of j-th of index of project yet to be built when the Triangular Fuzzy Number upper bound, lower bound and degree of membership are 1.Every expert adopts
The project indicator is described with fuzzy language, corresponding with fuzzy language is fuzzy number, the present invention using Triangular Fuzzy Number come
Quantify qualitative index, the corresponding Triangular Fuzzy Number of fuzzy language is made of three numbers, is denoted asWithU, L, M points
When not correspond to the upper bound, lower bound and degree of membership of the fuzzy number again in fuzzy set be 1.
Determine the weight of each index after normalizing；Specifically:
Each index weights are confirmed using Fuzzy AHP,
Firstly, establishing the consistent judgment matrix A of fuzzy hierarchy, the consistent judgment matrix A of fuzzy hierarchy is the matrix of m × m, wherein
M is index sum, and each element value is as follows in matrix:
I, j, γ=1,2 ..., m
Then, the corresponding index weights w of index is sought according to fuzzy consistent judgment matrix, calculated as follows:
ρ is the resolution parameter for determining weight in formula, and value is to take elIf current computation layer is classification layer, l is current
The index number of layer；If current computation layer is indicator layer, l is the index number that layer of all categories includes.
Power grid project risk is confirmed according to the index after determining weight, specifically:
The optimal case and Worst scheme for first seeking each index, further according to scheme at a distance from optimal case and Worst scheme
The approximation ratio for seeking scheme and ideal solution carries out planned project according to the big project investment preferential principle of approximation ratio
Investment sequence, specifically:
When asking the optimal of quantitative target and most bad ideal scheme
It enablesCorresponding attribute value is denoted asAt this timeFor the optimal ideal point of quantitative target；
It enablesCorresponding attribute value is denoted asAt this timeFor the most bad ideal point of quantitative target；
When asking the optimal of qualitative index and most bad ideal scheme
It enablesCorresponding fuzzy payoff is denoted asClaimTo obscure type
The optimal ideal point of index；
It enablesCorresponding fuzzy payoff is denoted asClaimTo obscure type
The most bad ideal point of index；
The optimal ideal point set of each index and most bad ideal point set respectively constitute the category of optimal case and Worst scheme
Property value is as follows:
Optimum attributes value vector isIfThen for quantitative targetIf qualitative finger
Mark is then
Most bad attribute value vector isIfThen for quantitative targetIf qualitative index
Then
Scheme and optimal case and it is most bad at a distance from are as follows:
If eijFor quantitative target, then have:
If eijFor qualitative index, then have:
Forcing for investment project and ideal solution is calculated accordingly
Short range degree are as follows:Finally further according to the degree of closeness according to each capital project and ideal solution, invested
Assessment sequence.
Further, the destination layer is power grid project risk index；Power grid project risk index is divided into skill by classification layer
Art index, performance indicator, project different degree index and project mature indicator.
Further, the technical indicator include the network coordination, item technology innovation horizontal, investment risk grade and
Power supply reliability；Performance indicator includes line loss per unit, unit electric grid investment increasing electricity sales amount, investment return ratio；Project different degree index
Number of units and heavy-haul line including heavily loaded main transformer reduction reduce number；Project mature indicator includes power grid project's earlier stage plan
Ability, power grid project is drawn to take part in building troop's control ability and bidding control ability.
Further, the qualitative index includes item technology innovation level, investment risk grade, power grid project's earlier stage plan
Ability, power grid project is drawn to take part in building troop control ability, bidding control ability；
The quantitative target includes the network coordination, power supply reliability, line loss per unit, unit electric grid investment increasing electricity sales amount, throws
It provides income and reduces number than, the number of units of heavily loaded main transformer reduction and heavy-haul line.
The utility model has the advantages that a kind of power grid project risk provided by the invention determines method, based on " rewards and punishments are penalized bad " principle to each
Achievement data is normalized, and improves the resolving accuracy of each index；For more categories of electric grid investment project risk judgement
Property problem, proposes that the project risk of similarity to ideal solution determines method, effectively reduces the investment risk of power grid enterprises.
Detailed description of the invention
Fig. 1 is RTS-79 node system schematic diagram used in the embodiment of the present invention；
Fig. 2 is flow chart of the method for the present invention；
Fig. 3 is the schematic diagram for the System of Comprehensive Evaluation that the present invention constructs.
Specific embodiment
In order to further describe technical characterstic and effect of the invention, below in conjunction with the drawings and specific embodiments to this hair
It is bright to be described further.
As shown, Fig. 1-3, a kind of power grid project risk determines method,
The initial data of the embodiment of the present invention uses RTS-79 node system as shown in Figure 1.If due to regional load
Growth causes transmission line of electricity to overload, and needs to newly establish transmission line of electricity, and carry out dilatation or replacement to corresponding transformer equipment.Planning
Project (1,2,3,4) is as shown in the dotted line in Fig. 1.Market rate value is 0.3.
Project 1: load increases 136MW at bus 6, intends the new frame one between node 6 and node 10 to return length being 25.76km
Transmission line of electricity, while the transformer of a newly-increased 80MVA.Work transmission line cost is 1,400,000 yuan/km, transformer engineering
Cost is 400,000 yuan/MVA, and 68,860,000 yuan of total investment quota, the project construction phase 2 years, annual investment was 34,430,000 yuan；Equipment operation
18 years retired, and annual operating cost is 5,000,000 yuan.
Project 2: since load by 74MW increases to 285MW at bus 4, intend newly setting up between node 4 and node 9 one time
The transmission line of electricity of 44km, while to corresponding transformer from former 240MVA dilatation to 300MVA.All kinds of construction costs are with reference to 1 project
Unit price, 80,800,000 yuan of total investment quota, annual operating and maintenance cost is 5,900,000 yuan/year.
Project 3: since load by 71MW increases to 300MW at bus 5, intend newly setting up between node 1 and node 5 one time
Length is the transmission line of electricity of 36km, while by corresponding transformer from former 120MVA dilatation to 320MVA.All kinds of construction cost references
Project 1,130,400,000 yuan of total investment quota, annual operating and maintenance cost is 5,200,000 yuan/year.
Project 4: since the load of bus 8 increases to 270MV by 171MV, intend newly setting up between node 7 and 8 one time long
Degree is the transmission line of electricity of 26km, while by corresponding transformer from former 200MVA dilatation to 300MVA.All kinds of construction cost reference items
Mesh 1,76,400,000 yuan of total investment quota, annual operating and maintenance cost is 5,000,000 yuan/year.Work transmission line cost is 1,400,000 yuan/km, is become
Depressor project cost is 400,000 yuan/MVA.
The present invention provides a kind of electric grid investment project risk and determines method.As shown in Figure 1, comprising the following steps:
Step 1: building electric grid investment Project Risk Assessment index system, which includes qualitative index and quantitative finger
Mark.
As shown in figure 3, evaluation index system uses three layers of index system, respectively destination layer, classification layer and indicator layer.
Wherein, destination layer is first layer, i.e. target designation, specially electric grid investment Project Risk Assessment index；Classification layer
For the second layer, i.e. index classification, including technical indicator, performance indicator, project different degree index and project mature indicator；Index
Layer is third layer, i.e. each index classification of classification layer index for being included, and specially technical indicator includes the network coordination, project skill
Art innovation level, investment risk grade and power supply reliability, performance indicator include line loss per unit, unit electric grid investment increase electricity sales amount and
Investment return ratio, project different degree index includes the number of units of heavily loaded main transformer reduction and heavy-haul line reduces number, and project is mature
Degree index includes that power grid early project planning ability, power grid project are taken part in building troop's control ability and bidding control ability.
Specific targets in risk assessment index are classified as quantitative target and qualitative index, the quantitative target includes net
Network harmony, power supply reliability, line loss per unit, unit electric grid investment increase electricity sales amount, investment return is reduced than, heavily loaded main transformer
Number of units and heavy-haul line reduce number；Before the qualitative index includes item technology innovation level, investment risk grade, power grid project
Phase ability to architect plans and strategies, power grid project are taken part in building troop's control ability and bidding control ability.
Step 2: quantitative target being described and calculated by interval number, qualitative index is carried out by fuzzy counting method
Quantization obtains and calculates resulting interval type achievement data and the resulting fuzzy type achievement data of quantization.
Quantitative target is calculated using section counting method.Under market environment, rate for incorporation into the power network, electricity sales amount, power supply cost, line loss
Rate, average rate of electricity sold, power purchase valence and power supply reliability etc. exist it is uncertain, therefore each index be also it is probabilistic, here
The uncertainty of each index is described using interval number method.If xijSection beWhereinRespectively xijLower limit
And the upper limit.
1. the network coordination
The network coordination mainly considers the harmony of route, and the harmony of route is weighed with the standard deviation of line load rate
Amount, is embodied as:Wherein, LiFor the load factor on i-th line road,For line load rate
Average value, NLFor route sum.
2. power supply reliability
Rate of load condensate is lost by computing system to describe power supply reliability.It is based on Monte-carlo Simulation Method, computational item herein
Mesh implements the difference of the mistake rate of load condensate of front and back, to indicate the variation of power supply reliability.System is lost rate of load condensate formula and is indicated are as follows:In formula: N is total frequency in sampling, FLOLP(ti) it is system in state tiUnder cutting load state, 1
Indicate cutting load, 0 indicates that cutting load does not occur.
3. the reduction of line loss per unit, the reduction of heavily loaded transformer number of units and the reduction of heavy-loaded line number
According to the operating parameter of system to be studied, the trend that planned project implements front and back is calculated, seeks planned project accordingly
Implement the variation of the line loss per unit of front and back system, and counts the heavily loaded transformer number and heavy-loaded line number of reduction.
4. unit electric grid investment increases electricity sales amount
According to historical data and local economic development, week prediction life-cycle is carried out to These parameters using grey forecasting model
Then the increasing electricity sales amount of phase the first two years is increased later increasing electricity sales amount with 6% ratio, according to previous experiences, operation 14
Electricity consumption reaches saturation after year.
5. investment return ratio
All kinds of project investment volumes are calculated using the method based on life cycle management and income, specific calculating process are as follows:
If general item investment is T0,Wherein, n indicates life cycle management, n=n1+n2。n1It indicates
Construction period, n2Indicate the cycle of operation, TjIndicate the investment in jth year, i is discount rate.
The income R of planned project based on life cycle management calculates as follows:
In formula: P1j、P2jAnd P3jThe respectively average purchase electricity price in jth year, average sale of electricity electricity price and average T-D tariff,
QjFor total electricity sales amount in jth year, λ is market rate, βjFor the line loss per unit in jth year, Δ βjFor the decreasing value of the line loss per unit in jth year,
ΔωjFor the raising amount of the power supply reliability in jth year, μ is that line loss appraises and decides coefficient, rule of thumb generally takes 0.5.
Project investment income ratio P, P=R/T based on life cycle management0。
Qualitative index is quantified by expert estimation and according to Triangular Fuzzy Number.The fuzzy class of use and its corresponding
Triangular Fuzzy Number is as shown in table 1.
| Fuzzy language | Triangular Fuzzy Number |
| It is extremely low | (0,0,0.1) |
| It is very low | (0,0.1,0.2) |
| It is low | (0.1,0.2,0.3) |
| It is lower | (0.2,0.3,0.4) |
| It is slightly lower | (0.3,0.4,0.5) |
| Generally | (0.4,0.5,0.6) |
| It is slightly higher | (0.5,0.6,0.7) |
| It is higher | (0.6,0.7,0.8) |
| It is high | (0.7,0.8,0.9) |
| It is very high | (0.8,0.9,1.0) |
| It is high | (0.9,1.0,1.0) |
Table 1
Marking is participated in equipped with n experts, all experts see below formula to the final appraisal results of i-th of project, j-th of index:
Wherein,Respectively i-th j-th of index of project yet to be built the Triangular Fuzzy Number upper bound, lower bound with
And degree of membership be 1 when fuzzy payoff,Respectively k-th of expert is to i-th j-th of project yet to be built
Marking value of the index when the Triangular Fuzzy Number upper bound, lower bound and degree of membership are 1.
Each achievement data in Fig. 1 example in project 1- project 4 is quantified and the result that is calculated is shown in table 2.
Table 2
Step 3: by " rewarding the good and punishing the bad " linear transformation, each index is normalized, specifically,
Step 3a: it to interval type quantitative target, is normalized based on " rewarding the good and punishing the bad " principle；
It enablesWherein,For the mean value of interval type achievement data, m and
N is respectively project total number and index total number yet to be built, and i and j are respectively i-th of project yet to be built and j-th of index,Point
It Wei not xijLower bound and the upper bound, xijFor the index value of i-th of j-th of index of project yet to be built.For profit evaluation model index therein,
HaveFor cost type index therein, haveWherein,WithRespectively i-th item yet to be built
Lower bound and the upper bound after the linear transformation of j-th of index of mesh；
Due toWithValue exist greater than 1 or be less than -1 the case where, for its value to be in section [- 1,1], adopt
With normalization formula,Wherein,WithRespectively i-th j-th of index of project yet to be built is through " prize is excellent
Penalize bad " principle normalization after lower bound and the lower upper bound；
Step 3b: it to fuzzy type qualitative index, is normalized based on " rewarding the good and punishing the bad " principle；
IfWherein, vjFor the mean value of fuzzy targets data,WithThe fuzzy payoff of respectively i-th j-th of index of project yet to be built.For profit evaluation model index therein, haveFor cost type index therein, haveWherein, Respectively i-th j-th of index of project yet to be built " rewarded the good and punished the bad " principle normalization after in Triangular Fuzzy Number
The fuzzy payoff when upper bound, lower bound and degree of membership are 1,
By " rewarding the good and punishing the bad " linear transformation, the evaluations matrix A=(x that each achievement data is constitutedij)m×nIt is normalized to refer to
Mark the Standard Process E=(e that section is [- 1,1]ij)m×n, eijFor the normalized value of i-th of j-th of index of project yet to be built.
According to above-mentioned calculation method, the normalization of each index can be calculated as a result, being shown in Table 3:
| Index/project | Project 1 | Project 2 | Project 3 | Project 4 |
| Network coordination degree | (-0.4511,1) | (-0.6917,-0.2124) | (-0.6128,0.3365) | (-0.2914,0.9211) |
| Power supply reliability | (-0.3768,1) | (-0.3768,0.1594) | (-0.3913,-0.3333) | (-0.2899,0.3043) |
| Line loss per unit reduces | (-0.5578,-0.4389) | (0.8284,1) | (0.0231,0.4851) | (-0.7558,-0.5842) |
| Unit electric grid investment increases electricity sales amount | (-0.1403,1) | (-0.9844,-0.2502) | (0.0538,0.7054) | (-0.5401,0.1559) |
| Investment income ratio | (0.6605,0.9796) | (-1,0.0495) | (-0.8957,-0.2924) | (-0.3292,0.3824) |
| Reduce heavily loaded transformer number | (-0.5555,0.3334) | (-1,-0.1090) | (0.3334,0.7776) | (0.5555,0.7776) |
| Reduce heavy-loaded line number | (-0.2411,0.5237) | (-0.6189,0.1429) | (0.1429,0.9047) | (-1,0.1429) |
| Project innovation | (0.1868,0.5385,0.8901) | (-1,-0.6484,-0.2967) | (-0.4725,-0.1209,0.2308) | (-0.1209,0.2308,0.5824) |
| Investment risk grade | (0.1236,0.4831,0.8427) | (-0.5506,-0.1910,0.1685) | (-1,-0.6404,0.2809) | (-0.0112,0.3483,0.7079) |
| Early project planning ability | (-0.4510,-0.1373,0.1765) | (-0.8431,-0.5294,-0.2157) | (0.3725,0.6863,1) | (-0.3333,-0.0196,0.2941) |
| Project construction troop manages ability | (0.1903,0.5345,1) | (-0.4676,-0.0628,0.3421) | (-0.5688,-0.1640,0.2409) | (-0.7713,-0.3664,0.0385) |
| Project bidding control ability | (-0.7222,-0.2778,0.1667) | (01,-0.5556,-0.1111) | (-0.1111,0.3333,0.7778) | (0.0556,0.5,0.9444) |
Table 3
Step 4: according to the consistent judgment matrix of fuzzy hierarchy, calculating the weight of each index accordingly.Specifically,
Step 4a: fuzzy consistent judgment matrix A is the matrix of m × m, and wherein m is index sum, each element value in matrix
It is as follows:
I, j, γ=1,2 ..., m
Step 4b: the corresponding index weights w of index is sought according to fuzzy consistent judgment matrix, is calculated as follows:
ρ is the resolution parameter for determining weight in formula, and value is to take elIt (is classification layer if current computation layer, then l is class
Other layer index number；If current computation layer is indicator layer, l is the index number that layer of all categories includes).
According to the above method, the fuzzy consistent judgment matrix of classification layer is obtained are as follows:
Since the index of classification layer is 4, so resolution parameter ρ=e4, the index weights of layer of all categories can be obtained, are shown in Table 4；
Each layer index weights of weight coefficient of the available each indicator layer of same method, wherein table 5 is technical indicator weight, and table 6 is imitated
Beneficial index weights, 7 power grid project different degree index weights of table, 8 power grid project mature indicator weight of table.It is specific as follows:
| Index | Technology | Benefit | Different degree | Maturity |
| Weight | 0.2644 | 0.3945 | 0.1959 | 0.1452 |
Table 4
| Index | The network coordination | Item technology innovation is horizontal | Investment risk grade | Power supply reliability |
| Weight | 0.1895 | 0.1404 | 0.2885 | 0.3816 |
Table 5
| Index | The reduction of line loss per unit | Unit electric grid investment increases income electricity | Investment return ratio |
| Weight | 0.1912 | 0.4605 | 0.3483 |
Table 6
| Index | Reduce heavily loaded number transformer | Reduce heavy-haul line quantity |
| Weight | 0.5 | 0.5 |
Table 7
| Index | Power grid early project planning ability | Power grid project take part in building troop control ability | Bidding control ability |
| Weight | 0.4573 | 0.2984 | 0.2443 |
Table 8
Step 5: the optimal case and Worst scheme of each index are first sought, further according to scheme and optimal case and Worst scheme
Distance seek the approximation ratio of scheme and ideal solution.According to the big project investment preferential principle of approximation ratio, to plan item
Mesh carries out investment sequence.
Specific step is as follows:
Step 5a: the optimal and most bad ideal scheme of quantitative target
DefinitionCorresponding attribute value is denoted asClaimFor the optimal ideal point of interval type index.
DefinitionCorresponding attribute value is denoted asClaimFor the most bad ideal point of interval type index.
Step 5b: the optimal and most bad ideal scheme of fuzzy type index
DefinitionCorresponding fuzzy payoff is denoted asClaimIt is fuzzy
The optimal ideal point of type index.
DefinitionCorresponding fuzzy payoff is denoted asClaimIt is fuzzy
The most bad ideal point of type index.
The optimal ideal point set of each index and most bad ideal point set respectively constitute the category of optimal case and Worst scheme
Property value is as follows:
Optimum attributes value vector isIfThen for interval type indexIf fuzzy
Type index is then
Most bad attribute value vector isIfThen for interval type indexIf fuzzy type
Index is then
Step 5c: scheme is at a distance from optimal case and Worst schemeI=1,2 ..., m,
J=1,2 ..., n.If eijFor quantitative target, then haveIf eijFor qualitative finger
Mark, thenIt the results are shown in Table 9.
| Distance | Scheme 1 | Scheme 2 | Scheme 3 | Scheme 4 |
| With optimal case distance | 0.6081 | 1.0047 | 0.6341 | 0.7121 |
| With Worst scheme distance | 0.8443 | 0.4776 | 0.8325 | 0.7674 |
Table 9
Calculate the approximation ratio of investment project and ideal solutionIt is shown in Table 10.
| Scheme | Scheme 1 | Scheme 2 | Scheme 3 | Scheme 4 |
| With the approach degree of ideal solution | 0.5813 | 0.3222 | 0.5677 | 0.5187 |
Table 10
According to the degree of closeness of 10 each capital project and ideal solution of table, investment appraisal sequence is carried out, ranking results are scheme
1, scheme 3, scheme 4, scheme 2.
Above-described embodiment does not limit the present invention in any form, and all forms for taking equivalent substitution or equivalent transformation are obtained
Technical solution, be within the scope of the present invention.
Claims (9)
1. a kind of power grid project risk determines method characterized by comprising
Construct electric grid investment project risk and confirm index system, and index system is from top to bottom divided into destination layer, classification layer and
Three layers of indicator layer；
Quantitative target and qualitative index in quantizating index layer；
Each quantitative, qualitative index obtained after quantization is normalized；
Determine the weight of each index after normalizing；
Power grid project risk is confirmed according to the index after determining weight.
2. a kind of power grid project risk according to claim 1 determines method, it is characterised in that: the destination layer is power grid
Project risk index；Classification layer by power grid project risk index be divided into technical indicator, performance indicator, project different degree index and
Project mature indicator.
3. a kind of power grid project risk according to claim 2 determines method, which is characterized in that the technical indicator includes
The network coordination, item technology innovation level, investment risk grade and power supply reliability；Performance indicator includes line loss per unit, list
Position electric grid investment increases electricity sales amount, investment return ratio；Project different degree index includes the number of units and again of heavily loaded main transformer reduction
It carries route and reduces number；Project mature indicator includes that power grid early project planning ability, power grid project are taken part in building troop's control ability
And bidding control ability.
4. a kind of power grid project risk according to claim 3 determines method, it is characterised in that: the qualitative index includes
Item technology innovation level, investment risk grade, power grid early project planning ability, power grid project take part in building troop control ability,
Bidding control ability；
The quantitative target includes the network coordination, power supply reliability, line loss per unit, unit electric grid investment increases electricity sales amount, investment is received
Benefit ratio, the number of units of heavily loaded main transformer reduction and heavy-haul line reduce number.
5. a kind of power grid project risk according to claim 1 determines method, which is characterized in that the quantization of quantitative target has
Body are as follows:
If the index value of j-th of index of i-th of project yet to be built is xij, set xijSection, i.e. xijSection be
Wherein,Respectively xijLower and upper limit.
6. a kind of power grid project risk according to claim 1 determines method, which is characterized in that the quantization of qualitative index
Are as follows:
It is given a mark by expert to each qualitative index, and the index after marking is further quantified by Triangular Fuzzy Number, quantization knot
Fruit is shown below:
Wherein, n is to participate in marking expert's number,Respectively i-th j-th of index of project yet to be built is in triangle
Fuzzy payoff when the fuzzy number upper bound, lower bound and degree of membership are 1,Respectively k-th of expert is to i-th
Marking value of a j-th of index of project yet to be built when the Triangular Fuzzy Number upper bound, lower bound and degree of membership are 1.
7. a kind of power grid project risk according to claim 1 determines method, which is characterized in that obtained after described pair of quantization
Each quantitative, qualitative index be normalized, specifically:
For quantitative target, quantitative target is normalized based on " rewarding the good and punishing the bad " principle, specifically:
It enables
Wherein,For the mean value of interval type achievement data, m and n are respectively project total number and index total number yet to be built,
Respectively xijLower bound and the upper bound, xijFor the index value of i-th of j-th of index of project yet to be built；
For profit evaluation model index therein, have
For cost type index therein, have
Wherein,WithLower bound and the upper bound after the linear transformation of respectively i-th j-th of index of project yet to be built；
For qualitative index, qualitative index is normalized based on " rewarding the good and punishing the bad " principle, specifically:
If
Wherein, n is index total number, vjFor the mean value of fuzzy targets data,Respectively i-th item yet to be built
Fuzzy payoff of j-th of the index of mesh when the Triangular Fuzzy Number upper bound, lower bound and degree of membership are 1；
For profit evaluation model index therein, have
For cost type index therein, have
Wherein,Respectively i-th j-th of index of project yet to be built " rewarded the good and punished the bad " principle normalization after three
Fuzzy payoff when the angle fuzzy number upper bound, lower bound and degree of membership are 1, For the maximum value in all items at the Triangular Fuzzy Number upper bound and lower bound；
By " rewarding the good and punishing the bad " linear transformation, the evaluations matrix A=(x that each achievement data is constitutedij)m×nIt is normalized to Index areas
Between be [- 1,1] Standard Process E=(eij)m×n, eijFor the normalized value of i-th of j-th of index of project yet to be built.
8. a kind of power grid project risk according to claim 7 determines method, which is characterized in that after the determining normalization
The acquisition of each index weights, specifically: each index weights are confirmed using Fuzzy AHP,
Firstly, establishing the consistent judgment matrix A of fuzzy hierarchy, the consistent judgment matrix A of fuzzy hierarchy is the matrix of m × m, and wherein m is
Index is total, and each element value is as follows in matrix:
Then, the corresponding index weights w of index is sought according to fuzzy consistent judgment matrix, calculated as follows:
ρ is the resolution parameter for determining weight in formula, and value is to take elIf current computation layer is classification layer, l is current layer
Index number；If current computation layer is indicator layer, l is the index number that layer of all categories includes.
9. a kind of power grid project risk according to claim 8 determines method, which is characterized in that after determining weight
Index confirms power grid project risk are as follows:
The optimal case and Worst scheme for first seeking each index are sought at a distance from optimal case and Worst scheme further according to scheme
The approximation ratio of scheme and ideal solution invests planned project according to the big project investment preferential principle of approximation ratio
Sequence, specifically:
When asking the optimal of quantitative target and most bad ideal scheme
It enablesCorresponding attribute value is denoted asAt this timeFor
The optimal ideal point of quantitative target；
It enablesCorresponding attribute value is denoted asAt this timeIt is fixed
The most bad ideal point of figureofmerit；
When asking the optimal of qualitative index and most bad ideal scheme
It enablesCorresponding fuzzy payoff is denoted asClaimTo obscure type index
Optimal ideal point；
It enablesCorresponding fuzzy payoff is denoted asClaimTo obscure type index
Most bad ideal point；
The optimal ideal point set of each index and most bad ideal point set respectively constitute the attribute value of optimal case and Worst scheme,
It is as follows:
Optimum attributes value vector isIfFor quantitative target, thenThen if qualitative index
Most bad attribute value vector isIfFor quantitative target, thenThen if qualitative index
Scheme is at a distance from optimal case and Worst scheme are as follows:
If eijFor quantitative target, then have:
If eijFor qualitative index, then have:
Calculate investment project and ideal solution accordingly approaches journey
Degree are as follows:Finally further according to the degree of closeness according to each capital project and ideal solution, investment appraisal is carried out
Sequence.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910126138.9A CN109993402A (en) | 2019-02-20 | 2019-02-20 | A kind of power grid project risk determines method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910126138.9A CN109993402A (en) | 2019-02-20 | 2019-02-20 | A kind of power grid project risk determines method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109993402A true CN109993402A (en) | 2019-07-09 |
Family
ID=67130085
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910126138.9A Pending CN109993402A (en) | 2019-02-20 | 2019-02-20 | A kind of power grid project risk determines method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109993402A (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109165809A (en) * | 2018-07-18 | 2019-01-08 | 国网江苏省电力有限公司 | A kind of new electricity changes Electric Power Network Planning project investment Ranking evaluation method under environment |
| CN109325659A (en) * | 2018-08-20 | 2019-02-12 | 国网江苏省电力有限公司 | A kind of power network construction project investment sequence new method |
-
2019
- 2019-02-20 CN CN201910126138.9A patent/CN109993402A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109165809A (en) * | 2018-07-18 | 2019-01-08 | 国网江苏省电力有限公司 | A kind of new electricity changes Electric Power Network Planning project investment Ranking evaluation method under environment |
| CN109325659A (en) * | 2018-08-20 | 2019-02-12 | 国网江苏省电力有限公司 | A kind of power network construction project investment sequence new method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Henderson | The sizes and types of cities | |
| Knetsch | The influence of reservoir projects on land values | |
| CN109325659B (en) | Novel method for sequencing investment of power grid construction project | |
| Rothenberg | Transport infrastructure and firm location choice in equilibrium: evidence from Indonesia’s highways | |
| CN109165809B (en) | Power grid planning project investment sequencing assessment method under new electricity-to-electricity environment | |
| CN110458374A (en) | A kind of business electrical maximum demand prediction technique based on ARIMA and SVM | |
| CN107766976A (en) | A kind of active demand response platform of electric power market | |
| CN109428344A (en) | More generator investment planning method and apparatus containing wind power plant | |
| CN106097140B (en) | Electricity sales amount distribution method and system | |
| CN107103441A (en) | Power Material sorting technique based on Self-Organizing Feature Maps | |
| CN108876487A (en) | A kind of industrial plot estimation method based on big data and intelligent decision mechanism | |
| CN113240272A (en) | Enterprise ESG index determination method and related product | |
| Wang et al. | Performance based regulation of the electricity supply industry in Hong Kong: An empirical efficiency analysis approach | |
| CN104240040A (en) | City smart power grid planning method on basis of land conversion risk | |
| CN107545378A (en) | A kind of appraisal procedure of technological value, device, equipment and readable storage medium storing program for executing | |
| CN110264007A (en) | Stock exchange control method and device | |
| CN108921425A (en) | A kind of method, system and the server of asset item classifcation of investment | |
| CN110322121A (en) | A kind of power supply enterprise's customer satisfaction appraisal procedure | |
| CN103839176A (en) | New energy enterprise value assessment model based on analytic hierarchy process | |
| Mathew et al. | Demand forecasting for economic order quantity in inventory management | |
| CN109993402A (en) | A kind of power grid project risk determines method | |
| CN107862476A (en) | A kind of metering table demand computational methods based on data analysis | |
| CN109034458A (en) | It is a kind of to guarantee to permit taking in acquired electric grid investment planing method | |
| Barry et al. | Changing time attitudes in intertemporal analysis | |
| CN108898322A (en) | A kind of electric grid investment strategy benefit integrated evaluating method based on FCM algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190709 |