CN109325659B - Novel method for sequencing investment of power grid construction project - Google Patents
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Abstract
The invention discloses a new method for sequencing investment of power grid construction projects, which comprises the following steps: constructing a comprehensive evaluation index system of investment sequencing of each project to be built under the new electricity-transformation environment, wherein the comprehensive evaluation index system comprises qualitative indexes and quantitative indexes; quantifying the qualitative indexes by a fuzzy number method, describing the quantitative indexes by interval numbers and calculating; carrying out normalization processing on each index data by adopting 'rewarding, good and fine' linear transformation; determining an optimal and worst ideal scheme aiming at qualitative indexes and quantitative indexes; calculating the closeness degree of each index normalization value to an ideal point in the optimal and worst ideal schemes by adopting a grey correlation method; based on a prospect theory, determining a value function and a decision weight according to an optimal and worst ideal scheme, and calculating a comprehensive prospect value of each project to be built; and carrying out investment sequencing on each project to be built according to the comprehensive prospect value. Has the advantages that: the resolution precision of the indexes is greatly improved, the risk attitude of a decision maker can be taken into account by investment sequencing, and the decision result is more practical.
Description
Technical Field
The invention relates to an investment decision method, in particular to a novel method for sequencing investment of power grid construction projects, and belongs to the field of power grid construction project investment decision under the environment of new power change.
Background
Under the electric power market environment, there is uncertainty in price of power on the internet, electricity selling quantity, power supply cost, line loss rate, average price of power sold, price of power purchased, power supply reliability rate, etc. If a fixed value is adopted to describe the index attribute, the investment sorting of the project to be built may cause sorting deviation; meanwhile, all indexes in the power grid construction project index system are different in dimension and attribute, so that the investment sequencing of the power grid construction project belongs to the multi-attribute decision problem.
In the decision-making method, the existing method generally takes objective indexes as the eyepoints, and the subjective feeling of a decision-maker cannot be taken into account. However, the risk attitude of the decision maker under the uncertainty condition is crucial to the decision result.
Disclosure of Invention
The invention mainly aims to overcome the defects in the prior art and provide a novel method for ordering the investment of power grid construction projects, aiming at the multi-attribute problem of investment decision of the power grid construction projects, normalization is carried out according to the linear transformation of 'awarding, optimizing and punishing'; meanwhile, an optimal and a worst ideal scheme are obtained according to the method, and the ideal scheme is used for improving the value function and the decision weight in the existing prospect theory, so that the investment ranking can take the risk attitude of a decision maker into account, and the decision making result is more practical.
In order to achieve the purpose, the invention adopts the technical scheme that:
a new method for sequencing investment of power grid construction projects comprises the following steps:
step 1: constructing a comprehensive evaluation index system of investment sequencing of each project to be built under the new power transformation environment, wherein the comprehensive evaluation index system comprises qualitative indexes and quantitative indexes; the project to be built is a power grid planning project to be built;
step 2: quantifying qualitative indexes by a fuzzy number method, describing and calculating the quantitative indexes by interval numbers, and acquiring fuzzy index data obtained by quantification and interval index data obtained by calculation;
and step 3: carrying out normalization processing on each index data by adopting 'rewarding, good and punishment' linear transformation to obtain each index normalization value;
and 4, step 4: determining an optimal and worst ideal scheme aiming at qualitative indexes and quantitative indexes;
and 5: calculating the closeness degree of each index normalization value to an ideal point in the optimal and worst ideal schemes by adopting a grey correlation method;
step 6: based on a prospect theory, determining a value function and a decision weight according to an optimal and worst ideal scheme, and calculating a comprehensive prospect value of each project to be built;
and 7: and carrying out investment sequencing on each project to be built according to the comprehensive prospect value.
The invention is further configured to: the comprehensive evaluation index system in the step 1 adopts a three-layer index system which is respectively a target layer, a category layer and an index layer;
the target layer is a first layer, namely a target name, and specifically is a comprehensive evaluation index of investment sequencing of a power grid planning project; the category layer is a second layer, namely an index category which comprises a technical index, a benefit index, a project importance index and a project maturity index; the index layer is a third layer, namely indexes contained in each index category of the category layer, specifically technical indexes comprise network coordination, project technical innovation level, investment risk level and power supply reliability, benefit indexes comprise line loss rate, unit power grid investment and sales electricity quantity and investment revenue ratio, project importance indexes comprise the number of the heavy-load main transformers and the reduction number of heavy-load lines, and project maturity indexes comprise power grid project early-stage planning capacity, power grid project participation team management and control capacity and bid control capacity.
The invention is further configured to: the qualitative indexes comprise project technical innovation level, investment risk level, power grid project early-stage planning capacity, power grid project participating team management and control capacity and bid inviting and bidding control capacity;
the quantitative indexes comprise network coordination, power supply reliability, line loss rate, unit power grid investment and sales electricity quantity increase, investment profit ratio, reduced number of heavy-load main transformers and reduced number of heavy-load lines.
The invention is further configured to: in the step 2, the qualitative indexes are quantified by a fuzzy number method, namely, the qualitative indexes are scored by experts and quantified according to triangular fuzzy numbers;
and r experts are provided to participate in the scoring, the final evaluation result of the j index of the ith project to be built by all experts is,
wherein the content of the first and second substances,
and
respectively are fuzzy attribute values of the jth index of the ith item to be built,
and respectively scoring the jth index of the ith project to be built for the kth expert.
The invention is further configured to: in the step 2, the quantitative index is described and calculated by the interval number, specifically,
setting the index value of the jth index of the ith project to be built as xij，
Described by the number of intervals, i.e. xijIn the interval of
Wherein the content of the first and second substances,
are respectively xijUpper and lower bounds.
The invention is further configured to: in the step 3, normalization processing is performed on each index data by adopting 'reward merit and penalty' linear transformation, specifically,
step 3 a: normalizing the interval type index data based on the principle of 'rewarding, good and bad';
order to
Wherein the content of the first and second substances,
is the mean value of interval type index data, m and n are the total number of the items to be built and the total number of the indexes respectively, i and j are the secondi items to be built and the jth index,
are respectively xijUpper and lower bounds of (2), xijAn index value of the jth index of the ith project to be built;
for the benefit type index, there are
For cost type index, there are
Wherein, the first and the second end of the pipe are connected with each other,
and
respectively an upper bound and a lower bound of the ith item to be built after the linear transformation of the jth index;
due to the fact that
And
the value of (A) is greater than 1 or less than-1, in order to be in the interval [ -1, 1]In (1),
by adopting a normalization formula, the method adopts the following steps,
wherein the content of the first and second substances,
and
respectively an upper bound and a lower bound of the jth index of the ith project to be built after normalization by a prize-giving and good-penalty principleA boundary;
and step 3 b: performing normalization processing on the fuzzy index data based on a principle of 'rewarding, good and bad';
is provided with
Wherein v isjIs the average of the ambiguity index data,
and
fuzzy attribute values of jth indexes of ith project to be built are respectively obtained;
for the benefit type index, then
For cost type index, then
Wherein the content of the first and second substances,
and
respectively the triangular fuzzy attribute values of the jth index of the ith project to be built after normalization by the principle of 'rewarding, good and bad',
the evaluation matrix A formed by each index data is changed into (x) by linear transformation of' reward merit and penaltyij)m×nNormalized to index interval of [ -1, 1]Is (E) is given as the normalization matrix E ═ Eij)m×n，eijAnd the normalized value is the j index of the ith project to be built.
The invention is further configured to: the step 4 determines the optimal and worst ideal schemes for the qualitative index and the quantitative index, specifically,
step 4 a: for the interval type index data, a definition is given,
definition of
Record the corresponding interval attribute value as
Balance
The optimal ideal point of interval index data is obtained;
definition of
Record the corresponding interval attribute value as
Balance
The point is the worst ideal point of interval index data;
and 4 b: and the definition is given to the fuzzy index data,
definition of
Record the corresponding fuzzy attribute value as
Balance
The optimal ideal point of the fuzzy index data is obtained;
definition of
Record the corresponding fuzzy attribute value as
Balance
Is the worst ideal point of the fuzzy index data;
and 4 c: respectively constructing the optimal ideal point set and the worst ideal point set of each index data into attribute values of an optimal ideal scheme and a worst ideal scheme;
the optimal ideal scheme is expressed as
The worst ideal scheme is expressed as
The invention is further configured to: in the step 5, the degree of closeness of each index normalized value to the ideal point in the optimal and worst ideal schemes is calculated, specifically,
setting the index set of the ith project to be built as si＝(ei1,ei2,…,ein) The best ideal scheme and the worst ideal scheme are known as
And
the association coefficients of the project index set with the optimal ideal point and the worst ideal point are,
wherein rho is a resolution coefficient and belongs to (0, 1);
if eijIs the interval type index data, and the interval type index data,
then there is
If eijIn order to obtain the fuzzy index data,
then there is
According to the project index set and the calculation formula of the correlation coefficients of the optimal ideal point and the worst ideal point, the positive correlation coefficient matrix xi can be obtained+And negative correlation coefficient matrix xi-Are respectively as
The invention is further configured to: in the step 6, the comprehensive foreground value of each project to be built is calculated, specifically,
step 6 a: determining a cost function;
recording the normalized value of the jth index of the ith project to be built as eijIf the reference point is
The decision maker will face the benefit; if the reference point is
The decision maker will face the loss;
e is thenijThe cost of return and loss function of (a) is,
wherein v is+(eij) And v-(eij) Positive foreground values brought to revenue and negative foreground values brought to loss, respectively; alpha and beta respectively represent the concave-convex degree of the value power function of the profit and loss region, the sensitivity degree of a decision maker to the profit and the loss is reflected, the value alpha is obtained, and the value beta is less than or equal to 1; theta is damage to decision makerThe value theta is larger than 1;
and 6 b: determining a decision weight;
the index decision weight calculation formula of the profit and loss of the ideal scheme is as follows,
wherein the index j represents the j-th index, pjIs the weight of the j index, w+(pj) And w-(pj) Deciding weights for the jth index profit and loss respectively; gamma + and gamma-respectively represent the risk attitude of the decision maker facing the income and the loss, and reflect the bending degree of the decision weight function;
step 6 c: solving a comprehensive foreground value;
the comprehensive prospect value of the project is determined by the value function and the index decision weight together, the calculation formula of the comprehensive prospect value V is as follows,
wherein, w (p)j) Determining weights for the indices, v (x)j) Is a value function, and the two are values formed by subjective feelings of decision makers; x is the number ofjThe index value of the jth index;
the comprehensive foreground value of the ith project to be built is the sum of the positive foreground value and the negative foreground value and the decision weight corresponding to the positive foreground value and the negative foreground value, the calculation formula is,
wherein, ViAnd the comprehensive foreground value of the ith project to be built is obtained.
The invention is further configured to: and 7, the investment sequencing of the projects to be built in the step is carried out from good to bad according to the principle that the projects with large comprehensive prospect value are investment-first.
Compared with the prior art, the invention has the beneficial effects that:
according to the novel method for sorting the investment of the power grid construction project, provided by the invention, aiming at the multi-attribute problem of the investment decision of the power grid construction project, the data range of the investment sorting is determined through the construction of a comprehensive evaluation index system, and the decision accuracy is improved; normalization processing is carried out on each index data based on a 'reward and punishment' principle, and the resolution precision of each index is greatly improved; based on the normalized optimal and worst ideal schemes, a value function and decision weight in a prospect theory are improved, a comprehensive prospect value of each project to be built is calculated, the investment decision can be realized, and the risk preference of a decision maker can be calculated, so that the decision result is more in line with the reality and has higher reliability, and meanwhile, the investment risk of a power grid enterprise is favorably reduced.
The foregoing is only an overview of the technical solutions of the present invention, and in order to more clearly understand the technical solutions of the present invention, the present invention is further described below with reference to the accompanying drawings.
Drawings
FIG. 1 is a flow chart of a new method for ordering investment of power grid construction projects according to the present invention;
FIG. 2 is a schematic diagram of a comprehensive evaluation index system constructed in accordance with the present invention;
fig. 3 is a schematic diagram of an RTS-79 node system according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the accompanying drawings.
The invention provides a new method for sequencing investment of power grid construction projects, which comprises the following steps as shown in figure 1:
step 1: constructing a comprehensive evaluation index system of investment sequencing of each project to be built under the new power transformation environment, wherein the comprehensive evaluation index system comprises qualitative indexes and quantitative indexes; and the project to be built is a power grid planning project to be built.
As shown in fig. 2, the comprehensive evaluation index system adopts a three-layer index system, which is a target layer, a category layer and an index layer.
The target layer is a first layer, namely a target name, and specifically is a comprehensive evaluation index of investment sequencing of a power grid planning project; the category layer is a second layer, namely an index category which comprises a technical index, a benefit index, a project importance index and a project maturity index; the index layer is a third layer, namely indexes included in each index category of the category layer, and specifically comprises the following steps: the technical indexes comprise network coordination, project technical innovation level, investment risk level and power supply reliability, the benefit indexes comprise line loss rate, unit power grid investment and sales electricity quantity and investment revenue ratio, the project importance indexes comprise the number of the heavy-load main transformers and the reduction number of heavy-load lines, and the project maturity indexes comprise power grid project early-stage planning capacity, power grid project participation team control capacity and bidding control capacity.
Classifying specific indexes in the comprehensive evaluation index system into qualitative indexes and quantitative indexes, wherein the qualitative indexes comprise project technical innovation level, investment risk level, power grid project early-stage planning capacity, power grid project participation team management and control capacity and bid inviting and bidding control capacity; the quantitative indexes comprise network coordination, power supply reliability, line loss rate, unit power grid investment and sales electricity quantity increase, investment profit ratio, reduced number of heavy-load main transformers and reduced number of heavy-load lines.
Step 2: and quantizing the qualitative indexes by a fuzzy number method, describing the quantitative indexes by interval numbers, and calculating to obtain quantized fuzzy index data and calculated interval index data.
Quantifying qualitative indexes by a fuzzy number method, namely scoring by experts and quantifying according to a triangular fuzzy number method; the blur levels used and the corresponding triangular blur numbers are shown in table 1.
| Fuzzy language | Triangular fuzzy number |
| Extremely low | (0,0,0.1) |
| Is very low | (0,0.1,0.2) |
| Is low in | (0.1,0.2,0.3) |
| Is lower than | (0.2,0.3,0.4) |
| Is a little lower | (0.3,0.4,0.5) |
| In general | (0.4,0.5,0.6) |
| Is a little higher | (0.5,0.6,0.7) |
| Is higher than | (0.6,0.7,0.8) |
| Height of | (0.7,0.8,0.9) |
| Is very high | (0.8,0.9,1.0) |
| Super high | (0.9,1.0,1.0) |
TABLE 1
R experts are set to participate in scoring, the final evaluation result of j indexes of the ith project to be built by all experts is as follows,
wherein the content of the first and second substances,
and
respectively are fuzzy attribute values of the jth index of the ith item to be built,
and respectively scoring the jth index of the ith project to be built for the kth expert.
Describing and calculating the quantitative index through the interval number, specifically,
setting the index value of the jth index of the ith project to be built as xijDescribed by the number of intervals, i.e. xijIn the interval of
Wherein the content of the first and second substances,
are respectively xijUpper and lower bounds.
The original index data acquisition of the embodiment of the invention adopts an RTS-79 node system as shown in FIG. 3, and if the transmission line is overloaded due to the increase of regional load, the transmission line needs to be newly added, and the capacity expansion or replacement of corresponding transformation equipment is carried out. The planning projects (1,2,3,4) are shown in dashed lines in FIG. 3; the marketability value is 0.3.
Item 1: the load at the bus 6 is increased by 136MW, a loop of transmission line with the length of 25.76km is newly erected between the node 6 and the node 10, and an 80MVA transformer is added. The construction cost of the transmission line is 140 ten thousand yuan/km, the construction cost of the transformer is 40 ten thousand yuan/MVA, the total planned investment is 6886 ten thousand yuan, the project construction period is 2 years, and the annual investment is 3443 ten thousand yuan; the equipment is retired after 18 years of operation, and the annual operation cost is 500 ten thousand yuan.
Item 2: since the load at the bus 4 is increased from 74MW to 285MW, a new 44km transmission line is planned to be erected between the node 4 and the node 9, and the corresponding transformer is simultaneously expanded from the original 240MVA to 300 MVA. The various construction expenses refer to the unit price of the project 1, the total planned investment is 8080 ten thousand yuan, and the annual operation cost is 590 ten thousand yuan per year.
Item 3: as the load at the bus 5 is increased from 71MW to 300MW, a transmission line with the length of 36km is newly erected between the node 1 and the node 5, and meanwhile, the phase transformer is expanded from the original 120MVA to 320 MVA. The total investment of each type of construction cost reference project 1 is 13040 ten thousand yuan, and the annual operation cost is 520 ten thousand yuan/year.
Item 4: as the load of the bus 8 is increased from 171MV to 270MV, a power transmission line with the length of 26km is newly erected between the nodes 7 and 8, and meanwhile, the phase transformer is expanded from the original 200MVA to 300 MVA. The construction cost reference project 1 of various types plans total investment of 7640 ten thousand yuan, and the annual operation cost is 500 ten thousand yuan/year. The construction cost of the transmission line is 140 ten thousand yuan/km, and the construction cost of the transformer is 40 ten thousand yuan/MVA.
The results of the quantization and calculation of the index data in each of items 1 to 4 are shown in table 2.
TABLE 2
And step 3: and (3) carrying out normalization processing on each index data by adopting 'rewarding, upgrading and degrading' linear transformation to obtain each index normalization value.
In particular, the method comprises the following steps of,
step 3 a: normalizing the interval type index data based on the principle of 'rewarding, good and bad';
order to
Wherein the content of the first and second substances,
is the average value of interval type index data, m and n are the total number of items to be built and the total number of indexes respectively, i and j are the ith item to be built and the jth index respectively,
are respectively xijUpper and lower bounds of (2), xijAn index value of the jth index of the ith project to be built;
for the benefit type index, there are
For cost type index, there are
Wherein the content of the first and second substances,
and
respectively an upper bound and a lower bound of the ith item to be built after the linear transformation of the jth index;
due to the fact that
And
the value of (b) is greater than 1 or less than-1, in order to be in the interval [ -1, 1]In (1),
by adopting a normalization formula, the method adopts the following steps,
wherein the content of the first and second substances,
and
respectively an upper bound and a lower bound of the jth index of the ith project to be built after normalization by a prize-giving, good-selling and bad-selling principle;
and step 3 b: performing normalization processing on the fuzzy index data based on a principle of 'rewarding, good and bad';
is provided with
Wherein v isjIs the mean value of the ambiguity index data,
and
fuzzy attribute values of jth indexes of ith project to be built are respectively obtained;
for the benefit type index, then
For cost type index, then
Wherein, the first and the second end of the pipe are connected with each other,
and
respectively the triangular fuzzy attribute values of the jth index of the ith project to be built after normalization by the principle of 'rewarding, good and bad',
the evaluation matrix A formed by each index data is changed into (x) by 'reward merit and penalty' linear transformationij)m×nNormalized to index interval of [ -1, 1]Normalized matrix E ═ (E)ij)m×n，eijAnd the normalized value is the j index of the ith project to be built. The results obtained by normalizing the index data based on the "reward-benefit-penalty" principle are shown in table 3.
| Index (I) | Item 1 | Item 2 | Item 3 | Item 4 |
| Network coordination | (-0.4511,1) | (-0.6917,-0.2124) | (-0.6128,0.3365) | (-0.2914,0.9211) |
| Reliability of power supply | (-0.3768,1) | (-0.3768,0.1594) | (-0.3913,-0.3333) | (-0.2899,0.3043) |
| Line loss rate reduction | (-0.5578,-0.4389) | (0.8284,1) | (0.0231,0.4851) | (-0.7558,-0.5842) |
| Unit electric network investment increase selling electric quantity | (-0.1403,1) | (-0.9844,-0.2502) | (0.0538,0.7054) | (-0.5401,0.1559) |
| Investment to income ratio | (0.6605,0.9796) | (-1,0.0495) | (-0.8957,-0.2924) | (-0.3292,0.3824) |
| Reducing the number of heavy-duty transformers | (-0.5555,0.3334) | (-1,-0.1090) | (0.3334,0.7776) | (0.5555,0.7776) |
| Reducing the number of heavy load lines | (-0.2411,0.5237) | (-0.6189,0.1429) | (0.1429,0.9047) | (-1,0.1429) |
| Novelty of project | (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 class | (0.1236,0.4831,0.8427) | (-0.5506,-0.1910,0.1685) | (-1,-0.6404,0.2809) | (-0.0112,0.3483,0.7079) |
| Project pre-planning capability | (-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 team management and control capability | (0.1903,0.5345,1) | (-0.4676,-0.0628,0.3421) | (-0.5688,-0.1640,0.2409) | (-0.7713,-0.3664,0.0385) |
| Project bid control capability | (-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
And 4, step 4: and determining the optimal and worst ideal schemes according to the qualitative indexes and the quantitative indexes.
In particular, the method comprises the following steps of,
step 4 a: for the interval type index data, a definition is given,
definition of
Record the corresponding interval attribute value as
Balance
The optimal ideal point of interval index data is obtained;
definition of
Record the corresponding interval attribute value as
Balance
The point is the worst ideal point of interval index data;
and 4 b: and defining the fuzzy index data,
definition of
Record the corresponding fuzzy attribute value as
Balance
The optimal ideal point of the fuzzy index data is obtained;
definition of
Record the corresponding fuzzy attribute value as
Balance with scale
Is the worst ideal point of the fuzzy index data;
and 4 c: respectively constructing the optimal ideal point set and the worst ideal point set of each index data into attribute values of an optimal ideal scheme and a worst ideal scheme;
the optimal ideal scheme is expressed as
The worst ideal scheme is expressed as
And 5: and (3) calculating the closeness degree of each index normalization value to the ideal point in the optimal and worst ideal schemes by adopting a grey correlation method.
In particular, the method comprises the following steps of,
setting the index set of the ith project to be built as si＝(ei1,ei2,…,ein) The best ideal scheme and the worst ideal scheme are known as
And
the association coefficients of the project index set with the optimal ideal point and the worst ideal point are,
where ρ is a resolution coefficient, ρ belongs to (0,1), and ρ is generally 0.5;
if eijIs the interval type index data, and the interval type index data,
then there is
If eijIn order to obtain the fuzzy index data,
then there is
According to the project index set and the calculation formula of the correlation coefficients of the optimal ideal point and the worst ideal point, the positive correlation coefficient matrix xi can be obtained+And negative correlation coefficient matrix xi-Are respectively as
The calculation results of the positive and negative correlation coefficient matrices of items 1-4 are as follows:
step 6: based on the prospect theory, determining a value function and a decision weight according to the optimal and worst ideal schemes, and calculating the comprehensive prospect value of each project to be built.
In particular, the method comprises the following steps of,
step 6 a: determining a cost function;
recording the normalized value of the jth index of the ith project to be built as eijIf the reference point is
The decision maker will face the benefit; if the reference point is
The decision maker will face the loss;
e is thenijThe cost of return and loss function of (a) is,
wherein v is+(eij) And v-(eij) Positive foreground values brought to revenue and negative foreground values brought to loss, respectively; alpha and beta represent the concave power function of the profit and loss regions respectivelyThe convexity reflects the sensitivity of a decision maker to the income and loss, and the value of alpha is less than or equal to 1; theta is the aversion degree of the decision maker to the loss, and the value theta is more than 1;
step 6 b: determining a decision weight;
the index decision weight calculation formula of the profit and loss of the ideal scheme is as follows,
wherein the index j represents the j-th index, pjWeight of the j-th index, w+(pj) And w-(pj) Deciding weights for the jth index profit and loss respectively; gamma + and gamma-respectively represent the risk attitude of the decision maker facing the income and the loss, and reflect the bending degree of the decision weight function;
step 6 c: solving a comprehensive foreground value;
the comprehensive prospect value of the project is determined by the value function and the index decision weight together, the calculation formula of the comprehensive prospect value V is as follows,
wherein, w (p)j) Determining weights for the indices, v (x)j) Is a value function, and the two are values formed by subjective feelings of decision makers; x is the number ofjThe index value of the jth index;
the comprehensive foreground value of the ith project to be built is the sum of the positive foreground value and the negative foreground value and the decision weight corresponding to the positive foreground value and the negative foreground value, the calculation formula is,
wherein, ViAnd the comprehensive foreground value of the ith project to be built is obtained.
And 7: and carrying out investment sequencing on each project to be built according to the comprehensive prospect value.
And (4) carrying out investment sequencing on each project to be built, wherein the sequencing is from good to bad according to the principle that the investment of the project with a large comprehensive prospect value is prior.
The comprehensive foreground value calculation results of the projects 1 to 4 and the investment ranking of 4 projects to be built are shown in the following table 4.
| Item | 1 | 2 | 3 | 4 |
| Integrated foreground value | 0.1554 | -1.8594 | -0.7078 | -0.5704 |
| Sorting | ① | ④ | ③ | ② |
TABLE 4
From Table 4, it can be seen that the 4 projects to be created are ranked from good to bad in the investment ranking of project 1 to project 4 as {1,4,3,2 }.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (3)
1. A new method for sequencing investment of power grid construction projects is characterized by comprising the following steps:
step 1: constructing a comprehensive evaluation index system of investment sequencing of each project to be built under the new power transformation environment, wherein the comprehensive evaluation index system comprises qualitative indexes and quantitative indexes; the project to be built is a power grid planning project to be built;
step 2: quantifying qualitative indexes by a fuzzy number method, describing and calculating the quantitative indexes by interval numbers, and acquiring fuzzy index data obtained by quantification and interval index data obtained by calculation;
and step 3: carrying out normalization processing on each index data by adopting 'rewarding, good and punishment' linear transformation to obtain each index normalization value;
and 4, step 4: determining an optimal and worst ideal scheme aiming at qualitative indexes and quantitative indexes;
and 5: calculating the closeness degree of each index normalization value to an ideal point in the optimal and worst ideal schemes by adopting a grey correlation method;
step 6: determining a value function and a decision weight in a foreground theory according to the optimal and worst ideal schemes, and calculating a comprehensive foreground value of each project to be built;
and 7: according to the comprehensive prospect value, carrying out investment sequencing on each project to be built;
in the step 3, normalization processing is performed on each index data by adopting 'reward merit and penalty' linear transformation, specifically,
step 3 a: normalizing the interval type index data based on the principle of 'rewarding, good and bad';
order to
Wherein the content of the first and second substances,
is the average value of interval index data, m and n are the total number of the project to be built and the total number of the indexes respectively, i and j are the ith project to be built and the jth index respectively,
are each xijUpper and lower bounds of (2), xijAn index value of the jth index of the ith project to be built;
for the benefit type index, there are
For cost type index, there are
Wherein the content of the first and second substances,
and
respectively an upper bound and a lower bound of the ith item to be built after the linear transformation of the jth index;
due to the fact that
And
the value of (A) is greater than 1 or less than-1, in order to be in the interval [ -1, 1]In (1),
by adopting a normalization formula, the method adopts the following steps,
wherein the content of the first and second substances,
and
respectively an upper bound and a lower bound of the jth index of the ith project to be built after normalization by a prize-giving, good-selling and bad-selling principle;
and step 3 b: performing normalization processing on the fuzzy index data based on a principle of 'rewarding, good and bad';
is provided with
Wherein v isjIs the mean value of the ambiguity index data,
and
fuzzy attribute values of jth indexes of ith project to be built are respectively obtained;
for the benefit type index, then
For cost type index, then
Wherein the content of the first and second substances,
and
respectively is the jth index of the ith project to be built "The triangle fuzzy attribute value after normalization by the principle of rewarding, good and bad,
the evaluation matrix A formed by each index data is changed into (x) by linear transformation of' reward merit and penaltyij)m×nNormalized to index interval of [ -1, 1]Is (E) is given as the normalization matrix E ═ Eij)m×n，eijThe normalized value of the jth index of the ith project to be built is obtained;
the step 4 of determining the optimal and worst ideal schemes for the qualitative index and the quantitative index, specifically,
step 4 a: for the interval type index data, a definition is given,
definition of
Record the corresponding interval attribute value as
Balance
The optimal ideal point of interval index data is obtained;
definition of
Record the corresponding interval attribute value as
Balance with scale
The point is the worst ideal point of interval index data;
and 4 b: and defining the fuzzy index data,
definition of
Record the corresponding fuzzy attribute value as
Balance
The optimal ideal point of the fuzzy index data is obtained;
definition of
Record the corresponding fuzzy attribute value as
Balance
Is the worst ideal point of the fuzzy index data;
and 4 c: respectively constructing the optimal ideal point set and the worst ideal point set of each index data into attribute values of an optimal ideal scheme and a worst ideal scheme;
the optimal ideal scheme is expressed as
The worst ideal scheme is expressed as
In the step 5, the degree of closeness of each index normalized value to the ideal point in the optimal and worst ideal schemes is calculated, specifically,
setting the index set of the ith project to be built as si＝(ei1,ei2,…,ein) The best ideal scheme and the worst ideal scheme are known as
And
the association coefficients of the project index set with the optimal ideal point and the worst ideal point are,
wherein rho is a resolution coefficient and belongs to (0, 1);
if eijIs the interval type index data, and the interval type index data,
then there is
If eijIn order to obtain the fuzzy index data,
then there is
According to the project index set and the calculation formula of the correlation coefficients of the optimal ideal point and the worst ideal point, the positive correlation coefficient matrix xi can be obtained+And negative correlation coefficient matrix xi-Are respectively as
The comprehensive evaluation index system in the step 1 adopts a three-layer index system which is respectively a target layer, a category layer and an index layer;
the target layer is a first layer, namely a target name, and specifically is a comprehensive evaluation index of investment sequencing of a power grid planning project; the category layer is a second layer, namely an index category which comprises a technical index, a benefit index, a project importance index and a project maturity index; the index layer is a third layer, namely indexes included in each index category of the category layer, and specifically comprises the following steps: the technical indexes comprise network coordination, project technical innovation level, investment risk level and power supply reliability, the benefit indexes comprise line loss rate, unit power grid investment and sales electricity quantity and investment revenue ratio, the project importance indexes comprise the number of the heavy-load main transformers and the reduction number of heavy-load lines, and the project maturity indexes comprise power grid project early-stage planning capacity, power grid project participation team management and control capacity and bidding control capacity;
the qualitative indexes comprise project technical innovation level, investment risk level, power grid project early-stage planning capacity, power grid project participating team management and control capacity and bid inviting and bidding control capacity;
the quantitative indexes comprise network coordination, power supply reliability, line loss rate, unit power grid investment and sales electricity quantity increase, investment profit ratio, reduced number of heavy-load main transformers and reduced number of heavy-load lines;
in the step 2, the qualitative indexes are quantified by a fuzzy number method, namely, the qualitative indexes are scored by experts and quantified according to triangular fuzzy numbers;
and r experts are provided to participate in the scoring, the final evaluation result of the j index of the ith project to be built by all experts is,
wherein the content of the first and second substances,
and
respectively are fuzzy attribute values of the jth index of the ith item to be built,
respectively scoring the jth index of the ith project to be built for the kth expert;
in the step 2, the quantitative index is described and calculated by the interval number, specifically,
setting the index value of the jth index of the ith project to be built as xij，
Described by the number of intervals, i.e. xijIn the interval of
Wherein the content of the first and second substances,
are respectively xijUpper and lower bounds.
2. The new investment ranking method for power grid construction projects according to claim 1, characterized in that: in the step 6, the comprehensive foreground value of each project to be built is calculated, specifically,
step 6 a: determining a cost function;
recording the normalized value of the jth index of the ith project to be built as eijIf the reference point is
The decision maker will face the benefit; if the reference point is
The decision maker will face the loss;
e is thenijThe cost of return and loss function of (a) is,
wherein v is+(eij) And v-(eij) Positive foreground values brought to revenue and negative foreground values brought to loss, respectively; alpha and beta respectively represent the concave-convex degree of the value power function of the profit and loss area, the sensitivity degree of a decision maker to the profit and the loss is reflected, the value alpha is selected, and the value beta is less than or equal to 1; theta is the aversion degree of the decision maker to the loss, and the value theta is taken>1；
Step 6 b: determining a decision weight;
the index decision weight calculation formula of the profit and loss of the ideal scheme is as follows,
wherein the index j represents the j-th index, pjIs the weight of the j index, w+(pj) And w-(pj) Deciding weights for the jth index profit and loss respectively; gamma + and gamma-respectively represent the risk attitude of the decision maker facing the income and the loss, and reflect the bending degree of the decision weight function;
step 6 c: solving a comprehensive foreground value;
the comprehensive prospect value of the project is determined by the value function and the index decision weight together, the calculation formula of the comprehensive prospect value V is as follows,
wherein, w (p)j) Determining weights for the indices, v (x)j) Is a value function, and the two are values formed by subjective feelings of decision makers; x is the number ofjThe index value of the jth index;
the comprehensive foreground value of the ith project to be built is the sum of the positive foreground value and the negative foreground value and the decision weight corresponding to the positive foreground value and the negative foreground value, the calculation formula is as follows,
wherein, ViAnd the comprehensive foreground value of the ith project to be built is obtained.
3. The new investment ranking method for power grid construction projects according to claim 1, characterized in that: and 7, the investment sequencing of the projects to be built in the step is carried out from good to bad according to the principle that the projects with large comprehensive prospect value are investment-first.
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