CN107798487A - Power industry carbon emission right distribution method combined with subjective and objective weight method - Google Patents
Power industry carbon emission right distribution method combined with subjective and objective weight method Download PDFInfo
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Abstract
The invention provides a method for distributing carbon emission rights in the power industry by combining an subjective and objective weight method, which is oriented to the distribution of the carbon emission rights in the power industry, fully combines an subjective and objective weight analysis method and provides a more reasonable scheme for distributing the carbon emission rights. Firstly, determining objective utility values of various indexes by adopting an improved entropy weight method; secondly, determining subjective utility values of all indexes by adopting an improved analytic hierarchy process; and finally, calculating the carbon emission right quota of the power industry of each region by combining the subjective and objective weights. The method can organically combine objective information transmitted by index sample data and experience and knowledge of a decision maker, can avoid subjective artificial interference, and fully embody the scientificity of a distribution scheme.
Description
Technical field
The present invention relates to power industry carbon permit allocation technical field, and subjective and objective power is combined more particularly, to one kind
The power industry carbon permit allocation method of weight method.
Background technology
Power industry is one of important foundation industry to involve the interests of the state and the people, the power producer operated as national economy,
Economic development and social stability to country have great significance.With the development of power industry, increasing coal, day
The fossil energies such as right gas are converted into electric energy, and power industry is while meeting that socio-economic development demand obtains a series of achievements
The discharge of the nitrogen oxides pollution such as huge destruction, especially carbon dioxide, sulfur dioxide thing is caused to environment and result in the whole world
The generation of a series of environmental problems such as climate warming, acid rain, haze.Power industry is both to clean the creator of high-grade energy,
It is primary energy consumption rich and influential family and disposal of pollutants rich and influential family, power industry wants to obtain long term growth, must just walk green, environmental protection
Sustainable development path, definitely can not be to sacrifice natural environment as cost.
Since new classical economists Marshall proposes the concept of " external effect ", economists agree unanimously environment
With negative external effect, it is the main reason for causing negative Externality, only that Coase theorem, which points out that determination of property rights is failed to understand, for pollution
Property right is clearly defined, by external cost internalization, could effectively solve negative Externality by the market behavior.Therefore, to control
The excess emissions of carbon dioxide processed, top priority are the right to use of the clear and definite enterprise to environmental resource, formulate rational carbon emission power
Allocative decision.
Influence carbon permit allocation factor have much how to determine each factor of influence weight be formulate carbon emission weigh
The key of allocative decision.The method of agriculture products weight mainly has two kinds at present：Subjective weighting method and objective weighted model.Subjectivity is assigned
Power method is a kind of method for qualitative analysis, the weight based on policymaker's subjective preferences or expertise agriculture products, such as step analysis
Method, Delphi method, efficiency coefficient method etc., its advantage is that operating process is simple and convenient, independent of sample data.And Objective Weight
Method is a kind of quantitative analysis method, according to the build-in attribute between sample data, transmits the related information of evaluation index.Such as entropy
Quan Fa, gray relative analysis method, regression coefficient method etc., because it is analyzed by real data, it can preferably reflect each finger
Inner link between mark, but shortcoming is to ignore the preference informations such as experience and the knowledge of policymaker it is determined that the importance of weight.
Therefore, the correct evaluation of weight should consider the subjective judgement of estimator and the objective information of index transmission, reach more public
Equal believable purpose.
The content of the invention
The present invention is to overcome at least one defect described in above-mentioned prior art, there is provided a kind of subjective and objective method of weighting of combination
Power industry carbon permit allocation method.
In order to solve the above technical problems, technical scheme is as follows：
A kind of power industry carbon permit allocation method of the subjective and objective method of weighting of combination, the described method comprises the following steps：
Step 1：The objective utility value of indices is determined using improved entropy assessment；
Step 2：The subjective utility value of indices is determined using improved H；
Step 3：Quota is weighed with reference to each regional power industry carbon emission of subjective and objective weight calculation.
Preferably, in step 1, improved entropy assessment determines that the process of the objective utility value of indices is：
Step 201：Determined to influence the larger index of power industry carbon emission amount according to index decomposition method, and according to each finger
Relation between mark and emission reduction responsibility, is divided into profit evaluation model index and cost type index, as shown in table 1 by each index：
Table 1
Step 202：N items index is ranked up in the way of significance level is not added with：
D1≥D2≥…≥Dj≥…≥Dn, index matrix is established,
xijFor i-th of regional jth item index, a shared m regional n items indexs；
Normalization is carried out to index using deviation standard law, when index is profit evaluation model index：
When index is cost type index：
The implication of each symbol is as shown in table 2：
Table 2
| Symbol | Implication |
| xI, j | I-th of regional jth item index |
| xMin, j | The minimum value of jth item index in all regions |
| xMax, j | The maximum of jth item index in all regions |
| rI, j | I-th of regional jth item index after normalization |
rI, jAlso it is m row n column matrix；
Step 203：Calculate the comentropy d of jth item indexj：
Wherein
Work as yi,jFor 0 when, lnyi,j=0；
Step 204：Improved entropy assessment calculates the objective weight value of jth item index：
It is determined that the objective weight value based on i-th of regional carbon emission quota for improving entropy assessment：
Preferably, in the step 2, improved H determines that the process of the subjective utility value of indices is：
Step 301：According to expertise or experience to adjacent two indices DjWith Dj+1(j=1,2 ..., n-1)
Importance degree is compared, importance reduced value and implication such as table 3：
Table 3
| Importance reduced value δj | Implication |
| 1 | DjWith Dj+1It is of equal importance |
| 2 | DjCompare Dj+1It is slightly important |
| 3 | DjCompare Dj+1It is more important |
| 4 | DjCompare Dj+1It is obvious important |
| 5 | DjCompare Dj+1It is absolutely essential |
If DjImportance degree be pj(j=1,2 ..., n-1), due toThen
Make DnImportance degree pn=1, then DjImportance degree
Step 302：Calculate the subjective weighted value t of indicesj：
Then the subjective weighted value of i-th of regional carbon emission quota is：
Preferably, in the step 3, calculating the process that each regional power industry carbon emission weighs quota is,
Step 401：Calculate i-th of regional carbon emission quota comprehensive weight：
Step 402：Calculate i-th of regional carbon emission quota：
Qi=ωi*Q。
Compared with prior art, the beneficial effect of technical solution of the present invention is：The present invention provides a kind of with reference to subjective and objective power
The power industry carbon permit allocation method of weight method, towards power industry carbon permit allocation, fully combine subjective and objective weight point
Analysis method, provide a kind of relatively reasonable carbon permit allocation scheme.First, indices are determined using improved entropy assessment
Objective utility value；Secondly, the subjective utility value of indices is determined using improved H；Finally, with reference to subjective and objective
The each regional power industry carbon emission power quota of weight calculation.The objective letter that this method can transmit index sample data itself
The experience of breath and policymaker combine with knowledge, can avoid the artificial disturbance of subjectivity, fully demonstrate allocative decision
Science.
Brief description of the drawings
Fig. 1 is the step block diagram for the power industry carbon permit allocation method that the present invention combines the subjective and objective method of weighting.
Embodiment
Technical scheme is described further with reference to the accompanying drawings and examples.
Embodiment 1
As shown in figure 1, a kind of power industry carbon permit allocation method of the subjective and objective method of weighting of combination, methods described include
Following steps：
Step 1：The objective utility value of indices is determined using improved entropy assessment；
Step 2：The subjective utility value of indices is determined using improved H；
Step 3：Quota is weighed with reference to each regional power industry carbon emission of subjective and objective weight calculation.
In step 1, improved entropy assessment determines that the process of the objective utility value of indices is：
Step 201：Determined to influence the larger index of power industry carbon emission amount according to index decomposition method, and according to each finger
Relation between mark and emission reduction responsibility, is divided into profit evaluation model index and cost type index, as shown in table 1 by each index：
Table 1
Step 202：N items index is ranked up in the way of significance level is not added with：
D1≥D2≥…≥Dj≥…≥Dn, index matrix is established,
xijFor i-th of regional jth item index, a shared m regional n items indexs；
Normalization is carried out to index using deviation standard law, when index is profit evaluation model index：
When index is cost type index：
The implication of each symbol is as shown in table 2：
Table 2
| Symbol | Implication |
| xI, j | I-th of regional jth item index |
| xMin, j | The minimum value of jth item index in all regions |
| xMax, j | The maximum of jth item index in all regions |
| rI, j | I-th of regional jth item index after normalization |
rI, jAlso it is m row n column matrix；
Step 203：Calculate the comentropy d of jth item indexj：
Wherein
Work as yi,jFor 0 when, lnyi,j=0；
Step 204：Improved entropy assessment calculates the objective weight value of jth item index：
It is determined that the objective weight value based on i-th of regional carbon emission quota for improving entropy assessment：
In step 2, improved H determines that the process of the subjective utility value of indices is：
Step 301：According to expertise or experience to adjacent two indices DjWith Dj+1(j=1,2 ..., n-1)
Importance degree is compared, importance reduced value and implication such as table 3：
Table 3
If DjImportance degree be pj(j=1,2 ..., n-1), due toThen
Make DnImportance degree pn=1, then DjImportance degree
Step 302：Calculate the subjective weighted value t of indicesj：
Then the subjective weighted value of i-th of regional carbon emission quota is：
In step 3, calculating the process that each regional power industry carbon emission weighs quota is,
Step 401：Calculate i-th of regional carbon emission quota comprehensive weight：
Step 402：Calculate i-th of regional carbon emission quota：
Qi=ωi*Q。
Illustrate carbon permit allocation scheme proposed by the present invention below by the example of a reality, it is each regional each
Desired value is as shown in table 4：
Table 4
One shares 5 areas, 7 indexs, Ci、Ci、Si、Ii、LiFor cost type index, MiWith E 'iFor profit evaluation model index.Root
According to expertise and knowledge, each index is not added with being ordered as by importance：History carbon emission amount (E 'i), thermal power generation standard coal consumption
Measure (Ii), thermal power generation accounting (Si), spontaneous electricity take up an area area own demand ratio Mi, per GDP power consumption (Ci), single site network
Damage (Li) and the horizontal G of regional economic developmenti。
According to expertise or experience to adjacent two indices DjWith Dj+1The importance journey of (j=1,2 ..., n-1)
Degree is compared, and importance reduced value is as shown in table 5：
Table 5
| δj | Importance reduced value | Implication |
| δ1 | 3 | E′iCompare IiIt is more important |
| δ2 | 2 | IiCompare SiIt is slightly important |
| δ3 | 1 | SiWith MiIt is of equal importance |
| δ4 | 4 | MiCompare CiIt is obvious important |
| δ5 | 2 | CiCompare LiIt is slightly important |
| δ6 | 3 | LiCompare GiIt is more important |
Assuming that the total carbon emission available for distribution is 500,000,000 tons, proposed using the present invention based on the electric power for improving entropy assessment
The allocation result that industry carbon permit allocation scheme obtains is as shown in table 6：
Table 6
From the point of view of area 1 is by objective weight, the level of economic development is higher, should bear larger emission reduction responsibility, but in view of special
Family experience, it is believed that the scale of history carbon emission amount is most important, and the history carbon emission amount of this area is larger, thus subjective weight compared with
Greatly.With reference to subjective and objective weight, carbon emission power comprehensive weight is 0.3351.
Regional 2 thermal power generation account for it is smaller, it is most of to be generated electricity for clean energy resource, generated electricity for A clear guidance clean energy resource, should
Carbon permit allocation volume is properly increased, its objective weight is larger, and because its history carbon emission amount is smaller, subjective weight is smaller.It is comprehensive
Close and consider, last carbon permit allocation ratio is 0.2070.
It is 20 that 3 spontaneous electricity of area, which takes up an area area's own demand ratio, and most of electricity outwards conveys, and contributes to other ground
Area, its emission reduction responsibility should be reduced, therefore the allocation of more carbon emission power should be distributed, objective weight is larger.Come from subjective weight
See, history carbon emission amount is largest, but its thermal power generation standard coal consumption is also larger, therefore subjective weight is not maximum.Balance master
Objective weight, last carbon permit allocation ratio are 0.2398.
Regional 4 thermal power generation norm-coal consumptions are maximum, are 366 (g/kWh), to guide and accelerating poorly efficient highly energy-consuming generator
Eliminating for group, should reduce its carbon permit allocation, therefore its objective weight is minimum, and its subjective weight is also minimum, therefore comprehensive weight is most
It is small, it is 0.0824.
Regional 5 levels of economic development are relatively low, and larger to the electricity of other area conveyings, history carbon emission amount is smaller, comprehensive
Consider that the carbon emission amount of distribution is smaller, comprehensive weight 0.1358.
In summary, for the allocative decision of power industry carbon emission power, the subjective and objective power of combination proposed by the present invention is used
The objective information and the warp of policymaker that the power industry carbon permit allocation scheme of weight method can transmit index sample data itself
Test and combined with knowledge, fully demonstrate the science of allocative decision.With simple dependence objective weight or subjective weight
Allocative decision is compared, and is had and is significantly improved effect of optimization.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the scope of the present invention.It is all
Any modification, equivalent substitution and improvements made within the spirit and principles in the present invention etc., are all contained in protection scope of the present invention
It is interior.
Claims (4)
- A kind of 1. power industry carbon permit allocation method of the subjective and objective method of weighting of combination, it is characterised in that methods described includes Following steps：Step 1：The objective utility value of indices is determined using improved entropy assessment；Step 2：The subjective utility value of indices is determined using improved H；Step 3：Quota is weighed with reference to each regional power industry carbon emission of subjective and objective weight calculation.
- 2. the power industry carbon permit allocation method of the subjective and objective method of weighting of combination according to claim 1, its feature exist In in step 1, improved entropy assessment determines that the process of the objective utility value of indices is：Step 201：Determine to influence the larger index of power industry carbon emission amount according to index decomposition method, and according to each index with Relation between emission reduction responsibility, each index is divided into profit evaluation model index and cost type index, as shown in table 1：Table 1Step 202：N items index is ranked up in the way of significance level is not added with：D1≥D2≥…≥Dj≥…≥Dn, index matrix is established,xijFor i-th of regional jth item index, a shared m regional n items indexs；Normalization is carried out to index using deviation standard law, when index is profit evaluation model index：<mrow> <msub> <mi>r</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>x</mi> <mrow> <mi>min</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </mrow> <mrow> <msub> <mi>x</mi> <mrow> <mi>max</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>x</mi> <mrow> <mi>min</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </mrow> </mfrac> </mrow>When index is cost type index：<mrow> <msub> <mi>r</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>x</mi> <mrow> <mi>max</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </mrow> <mrow> <msub> <mi>x</mi> <mrow> <mi>max</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>x</mi> <mrow> <mi>min</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </mrow> </mfrac> </mrow>The implication of each symbol is as shown in table 2：Table 2
Symbol Implication xi,j I-th of regional jth item index xmin,j The minimum value of jth item index in all regions xmax,j The maximum of jth item index in all regions ri,j I-th of regional jth item index after normalization ri,jAlso it is m row n column matrix；Step 203：Calculate the comentropy d of jth item indexj：<mrow> <msub> <mi>d</mi> <mi>j</mi> </msub> <mo>=</mo> <mo>-</mo> <mfrac> <mn>1</mn> <mrow> <mi>ln</mi> <mi> </mi> <mi>m</mi> </mrow> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>y</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>*</mo> <mi>ln</mi> <mi> </mi> <msub> <mi>y</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow>Wherein<mrow> <msub> <mi>y</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msub> <mi>r</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>r</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </mrow> </mfrac> </mrow>Work as yi,jFor 0 when, ln yi,j=0；Step 204：Improved entropy assessment calculates the objective weight value of jth item index：<mrow> <msub> <mi>&lambda;</mi> <mi>j</mi> </msub> <mo>=</mo> <mfrac> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>d</mi> <mi>k</mi> </msub> <mo>+</mo> <mn>1</mn> <mo>-</mo> <mn>2</mn> <msub> <mi>d</mi> <mi>j</mi> </msub> </mrow> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mrow> <mo>(</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>d</mi> <mi>k</mi> </msub> <mo>+</mo> <mn>1</mn> <mo>-</mo> <mn>2</mn> <msub> <mi>d</mi> <mi>l</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow>It is determined that the objective weight value based on i-th of regional carbon emission quota for improving entropy assessment：<mrow> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>y</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>*</mo> <msub> <mi>&lambda;</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mo>.</mo> </mrow> - 3. the power industry carbon permit allocation method of the subjective and objective method of weighting of combination according to claim 2, its feature exist In in step 2, improved H determines that the process of the subjective utility value of indices is：Step 301：According to expertise or experience to adjacent two indices DjWith Dj+1The importance of (j=1,2 ..., n-1) Degree is compared, importance reduced value and implication such as table 3：Table 3
Importance reduced value δj Implication 1 DjWith Dj+1It is of equal importance 2 DjCompare Dj+1It is slightly important 3 DjCompare Dj+1It is more important 4 DjCompare Dj+1It is obvious important 5 DjCompare Dj+1It is absolutely essential If DjImportance degree be pj(j=1,2 ..., n-1), due toThenMake DnImportance degree pn=1, then DjImportance degreeStep 302：Calculate the subjective weighted value t of indicesj：<mrow> <msub> <mi>t</mi> <mi>j</mi> </msub> <mo>=</mo> <mfrac> <msub> <mi>p</mi> <mi>j</mi> </msub> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>p</mi> <mi>j</mi> </msub> </mrow> </mfrac> <mo>;</mo> </mrow>Then the subjective weighted value of i-th of regional carbon emission quota is：<mrow> <msub> <mi>&beta;</mi> <mi>i</mi> </msub> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>y</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>*</mo> <msub> <mi>t</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mo>.</mo> </mrow> - 4. the power industry carbon permit allocation method of the subjective and objective method of weighting of combination according to claim 3, its feature exist In, in step 3, calculating the process that each regional power industry carbon emission weighs quota is,Step 401：Calculate i-th of regional carbon emission quota comprehensive weight：<mrow> <msub> <mi>&omega;</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>+</mo> <msub> <mi>&beta;</mi> <mi>i</mi> </msub> </mrow> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>+</mo> <msub> <mi>&beta;</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>;</mo> </mrow>Step 402：Calculate i-th of regional carbon emission quota：Qi=ωi*Q。
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108647976A (en) * | 2018-04-17 | 2018-10-12 | 湖北碳排放权交易中心有限公司 | A kind of carbon Asset Registration registration management method and system based on carbon emissions trading |
| CN110689269A (en) * | 2019-09-30 | 2020-01-14 | 天津大学 | Carbon emission evaluation method based on autoregressive distribution hysteresis model and Kaya formula |
| CN113112176A (en) * | 2021-04-26 | 2021-07-13 | 国网(衢州)综合能源服务有限公司 | Enterprise carbon emission visual early warning system based on big data |
| CN113657816A (en) * | 2021-03-05 | 2021-11-16 | 重庆首讯科技股份有限公司 | Method for analyzing saturation of expressway service area |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108647976A (en) * | 2018-04-17 | 2018-10-12 | 湖北碳排放权交易中心有限公司 | A kind of carbon Asset Registration registration management method and system based on carbon emissions trading |
| CN110689269A (en) * | 2019-09-30 | 2020-01-14 | 天津大学 | Carbon emission evaluation method based on autoregressive distribution hysteresis model and Kaya formula |
| CN113657816A (en) * | 2021-03-05 | 2021-11-16 | 重庆首讯科技股份有限公司 | Method for analyzing saturation of expressway service area |
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