CN112150025A - Economic evaluation method and system for comprehensive energy service project - Google Patents

Economic evaluation method and system for comprehensive energy service project Download PDF

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CN112150025A
CN112150025A CN202011058057.9A CN202011058057A CN112150025A CN 112150025 A CN112150025 A CN 112150025A CN 202011058057 A CN202011058057 A CN 202011058057A CN 112150025 A CN112150025 A CN 112150025A
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董旭柱
彭长志
杨军
彭晓涛
刘首文
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State Grid Hubei Electric Power Co Ltd
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Abstract

The method comprises the following steps: constructing an economic evaluation index system of the comprehensive energy service project, wherein the economic evaluation index system comprises 3 primary indexes of operation cost, operation income and financial indexes, and each primary index has one or more secondary indexes; establishing a scoring standard of the secondary indexes, and scoring the secondary indexes according to the scoring standard; according to the scores of the secondary indexes, subjective weights and objective weights of the indexes are respectively obtained by a network analysis method and an anti-entropy weight method, and combined weight values of the indexes are obtained according to a weight average criterion; and multiplying and summing the corresponding items according to the scores of the secondary indexes and the corresponding combined weight values to obtain the economic score value of the comprehensive energy service item. The method and the system can better reflect the economy of the comprehensive energy system.

Description

Economic evaluation method and system for comprehensive energy service project
Technical Field
The disclosure relates to an economic evaluation method and system for an integrated energy service project.
Background
Energy is an important foundation for the development of human society, however, since the twenty-first century, the rapid progress of science and technology and the rapid development of economy lead to the rapid increase of the consumption of earth resources and the increasingly prominent energy problem. With the decline of fossil energy reserves, the climate and environment problems are prominent, and the world enters the key period of energy revolution. In the face of challenges of huge energy demand pressure, more energy supply restriction, serious damage to ecological environment caused by energy production and consumption, backward overall energy technology level and the like, the global popularization and construction of comprehensive energy engineering is gradually carried out. The comprehensive energy is developed in the direction of multi-supply of cold, heat, electricity, gas and the like by the traditional energy supplier depending on the advantages of infrastructure of traditional energy supply, realizes the mutual conversion, distribution, storage and consumption of various energy sources and realizes a new energy system with diversified energy supply and energy utilization. The comprehensive energy service covers a plurality of links, is a technical revolution of the energy industry, has large construction investment, long period and wide social influence range, needs scientific demonstration, comprehensively demonstrates the economic benefit, the social benefit and the environmental benefit, and analyzes the investment value, the feasibility and the necessity to realize scientific decision. Therefore, a method and system that can evaluate the economics of an integrated energy system would be helpful in scientific demonstrations of integrated energy projects.
Disclosure of Invention
The invention provides an economic evaluation method and system of an integrated energy service project, firstly, a set of core economic evaluation index system is constructed, the defects that the existing evaluation index system is complicated and difficult to obtain are overcome, a network analysis method-inverse entropy weight method is applied to weight determination of the economic evaluation system, the reliability of the determined weight is ensured, and effective economic evaluation of the integrated energy service is realized.
At least one embodiment of the present disclosure provides an economic evaluation method of an integrated energy service project, including:
constructing an economic evaluation index system of the comprehensive energy service project, wherein the economic evaluation index system comprises 3 primary indexes of the comprehensive energy service project, including operation cost, operation income and financial indexes, and each primary index has one or more secondary indexes;
establishing a scoring standard of the secondary indexes, and scoring the secondary indexes according to the scoring standard;
according to the scores of the secondary indexes, respectively obtaining subjective weights and objective weights of the indexes by using a network analysis method and an anti-entropy weight method, and obtaining combined weight values of the indexes according to a weight average criterion;
and multiplying and summing the corresponding items according to the scores of the secondary indexes and the corresponding combined weight values to obtain the economic score value of the comprehensive energy service item.
In some examples, the secondary indicators of the operational cost include one or more of land rental cost, annual interest cost, equipment operation and maintenance cost, network comprehensive loss, annual fault service cost, charge loss rate, software operation and maintenance cost, communication operation and maintenance cost, and personnel fixed cost, the secondary indicators of the operational revenue include one or more of selling energy revenue, information service revenue, financial service revenue, and auxiliary service revenue, and the secondary indicators of the financial indicators include one or more of net present rate, internal revenue rate, and investment recovery period.
In some examples, the subjective weight and the objective weight of each index are constructed by: constructing an influence matrix of the primary index, and obtaining the subjective weight of the primary index by using a network analysis method; constructing an influence matrix of the secondary indexes, and obtaining subjective weights of the secondary indexes by using a network analysis method; and normalizing the scores of the secondary indexes to an interval (0,1), and further determining the objective weight of each index by using an entropy-resisting weight method.
At least one embodiment of the present disclosure provides an economic evaluation system of an integrated energy service project, including:
the system comprises an economic evaluation index system module, a data processing module and a data processing module, wherein the economic evaluation index system module is used for constructing an economic evaluation index system of the comprehensive energy service project, the economic evaluation index system comprises 3 primary indexes of the comprehensive energy service project, the comprehensive energy service project comprises operation cost, operation income and financial indexes, and each primary index has one or more secondary indexes;
the scoring standard module is used for establishing a scoring standard of the secondary index;
the scoring module is used for scoring the secondary indexes according to the scoring standard;
the weight calculation module is used for respectively obtaining the subjective weight and the objective weight of each index by utilizing a network analysis method and an anti-entropy weight method according to the score of the secondary index and obtaining the combined weight value of each index according to a weight average criterion;
and the economic calculation module is used for multiplying and summing corresponding items according to the scores of the secondary indexes and the corresponding combined weight values to obtain the economic score value of the comprehensive energy service item.
At least one embodiment of the present disclosure provides an economic evaluation system of an integrated energy service project, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform all or part of the steps of the method.
At least one embodiment of the present disclosure provides a non-transitory computer readable storage medium having stored thereon a computer program that, when executed by a processor, performs all or part of the steps of the method.
The economic evaluation method and the economic evaluation system for the comprehensive energy service project have the following advantages and beneficial effects: (1) the subjective weight and the objective weight are respectively determined by a network analysis method and an anti-entropy weight method, and the method has reference value and universality compared with the weights obtained by an expert scoring method in the prior art, and can be better applied to engineering practice. (2) The core economic evaluation index obtained by considering the internal energy coupling of the comprehensive energy system is simple to calculate, can better reflect the economic efficiency of the comprehensive energy system, and is practical and feasible.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly described below.
Fig. 1 is a flowchart of an economic evaluation method for an integrated energy service project.
Detailed Description
Fig. 1 is a flowchart illustrating an implementation of an economic evaluation method for an integrated energy service project, which includes the following steps:
step 1, taking the considered comprehensive energy service project as a scene, and determining the main cost and the income source of the project according to the components and the operation characteristics of the comprehensive energy system. The considered comprehensive energy source scene generally comprises various energy sources such as cold, heat, electricity, gas and the like, and relates to a multi-energy complementary scene, a fishing light complementary photovoltaic power generation scene, a new energy big data scene, an electric automobile charging and discharging operation scene, a wind power heating scene and the like. The main cost generally comprises the investment acquisition cost, the operation maintenance cost and the annual outsourcing energy cost, and the income source generally comprises the energy selling income, the information data income and the investment delay income.
And 2, selecting an evaluation index.
From the perspective of energy flow, information flow and cash flow, the simplicity principle and the importance principle in the index selection principle are mainly considered, the multi-energy coupling relation in the comprehensive energy system is considered, a complete core economic evaluation index system is constructed, and then economic evaluation of the comprehensive energy service is developed.
On the basis of clear comprehensive energy economic connotation, a multi-dimensional and scientific standard for measuring the levels of all aspects of the energy is established, and a set of core economic evaluation index system is established, wherein the core economic evaluation index system comprises the following steps: the operation cost, the operation income and the financial index are specifically shown in the table 1.
TABLE 1 economic evaluation index System
Figure BDA0002711382790000031
Step 3, formulating a scoring standard of a secondary index under the primary index of economic evaluation according to the industry standard, the industry condition and the market rule, wherein the scoring standard specifically comprises the following steps:
cost indexes are as follows: the lower the cost data value obtained by the balance data is, the better the economic benefit is represented, the higher the corresponding economic index value is, the indexes are mainly compared with the industry reference cost according to the actual operation cost, the disclosure mainly refers to the national electric power photovoltaic power station economic evaluation standard specification and the brief analysis on the network service type project charge standard, and the scoring standard is as follows:
Figure BDA0002711382790000041
the scoring method adopted in the present disclosure is mainly based on a five-level scoring method, and the scoring result of the economic indicator is divided into an excellent value, a good value, an average value, a lower value, and a difference value, wherein for the reference cost, the economic level interval is between the excellent value and the good value, so the corresponding reference cost score is 80, and the subsequently used benchmark score is also 80. The operating reference cost for each cost class index is as follows:
TABLE 2 economic indicators scoring basis
Figure BDA0002711382790000042
The income type index is as follows: the higher the corresponding income and expense data value of the income type index is, the better the economic benefit of the representative service project is, the higher the corresponding economic index score is, the comparison of the income type index is mainly carried out according to the actual operation income and the theoretical maximum income, the scoring standard is mainly referred to the documents of China solar energy resource distribution and the like issued by the national meteorological bureau wind energy and solar energy resource assessment center, and the scoring standard is as follows:
Figure BDA0002711382790000043
theoretical maximum gain is average hours per year per day per system installed capacity per unit cost per unit price of electricity sold.
Financial indexes are as follows: the financial indexes such as net asset profitability, internal profitability and investment recovery period are subjected to scoring quantification according to the grade interval to which each index belongs and the corresponding score thereof by referring to the affiliated industry standard, specifically referring to 'performance standard evaluation value 2018 of medium-sized enterprises in the power industry'.
TABLE 3 industry financial data reference values
Figure BDA0002711382790000044
Figure BDA0002711382790000051
In a possible implementation, it is assumed that the integrated energy system of the a site is matched with projects including a natural gas energy source station, photovoltaic building integration, a ground photovoltaic and energy storage power station, a light storage integrated bus charging station, a sewage source heat pump and the like. The system adopts a mode of combining cold and heat sources, ice is stored and cooled when the electricity consumption is underestimated at night, and ice is melted and cooled when the electricity consumption is peak at daytime. The self-sufficient rate of the renewable energy power supply of the system is not lower than 50%, the annual rate of bank loan is 4.90%, the repayment age limit of the project is 10 years, the power price of the power grid is 0.67 yuan/(kW.h), and the loss rate of the power grid is 5%.
It is assumed that the scores of the secondary indexes of the integrated energy system in site a obtained according to the above scoring criteria are as follows, and are specifically shown in table 4.
TABLE 4 secondary index score for integrated energy service system
Figure BDA0002711382790000052
And 4, determining the weight.
The economic evaluation method involved in the disclosure calculates subjective weight and objective weight by using a network analysis method and an entropy weight resisting method, respectively, and the specific principle and mathematical description thereof are as follows.
1) Network analysis method
An Analytic Network Process (ANP) is a system decision method which is obtained by extending development on the basis of an Analytic Hierarchy Process (AHP), the method considers the characteristics of mutual influence and feedback of all elements in a hierarchical structure, can reflect the mutual influence relation of all components in an integrated energy system to a certain extent, is divided into a control factor layer and a network layer 2 part of elements, and can respectively correspond to a primary index and a secondary index in an integrated energy service economic index system. In addition, the network analysis method is used for determining subjective weight, and does not need original data, and only needs to determine the mutual influence relation between indexes.
In the network layer with ANP there is an element A1,A2,......,AnEach element corresponds to one of the first level index and the second level index in the index system, element AiFor AjHas a direct influence of eij. Sequentially with AiComparing the direct influence degrees of other elements on the elements of the criterion to obtain corresponding judgment matrix, and obtaining A by using characteristic root methodiWeight vector under sub-criterion
Figure BDA0002711382790000061
See formula (1-1).
Figure BDA0002711382790000062
Combining the weight vectors under all the sub-criteria into a weight matrix, and filling 0 into the diagonal of the weight matrix to obtain the direct influence matrix WdAs shown in equation (1-2).
Figure BDA0002711382790000063
Then, an average comprehensive influence matrix W among all the indexes of each grade is obtained,
Figure BDA0002711382790000064
by using the method, the weighting matrix A can be obtained, and then the weighting super matrix of the system is calculated
Figure BDA0002711382790000065
Figure BDA0002711382790000066
And (3) carrying out 2k +1 times of evolution (k → + ∞) on the matrix to finally form a relatively stable matrix, wherein the nonzero values of all the rows are the same, so that subjective weight vectors of all the evaluation indexes are obtained:
Figure BDA0002711382790000067
2) entropy weight method
The anti-entropy weight method can objectively reflect the relation between indexes, and the basic idea is to determine objective weights according to the degree of index variability, the larger the information entropy obtained by calculation of a certain index is, the smaller the degree of index value variation is shown to be, so that the amount of information provided by the index value is relatively smaller, the smaller the function in comprehensive evaluation is, the smaller the assigned weight is, and vice versa.
The entropy weight method reflects the information content contained in each index through the entropy value, the smaller the entropy value is, the larger the index information content is, the larger the weight is, wherein the entropy is defined as:
Figure BDA0002711382790000071
wherein p isj(j ═ 1,2,3 … m) represents the probability of occurrence of each case, m being the total number of evaluation targets; the present disclosure adopts the method of inverse entropy weight to determine objective weight, and the inverse entropy definition is shown in the formula (1-7)
Figure BDA0002711382790000072
Setting that the element to be evaluated has m evaluation objects corresponding to the operation condition of the comprehensive energy service of the disclosure in each year; n evaluation indexes correspond to the number of secondary indexes in the economic evaluation index system; index values are x respectivelyij(i 1, 2.. multidot.n; j 1, 2.. multidot.m); the entropy weight method firstly needs to standardize the index
Figure BDA0002711382790000073
Wherein x isi,minMinimum value of index, xi,maxA maximum value of the index value; then the evaluation matrix is Y ═ Y (Y)ij)m×nThe inverse entropy of each index is determined from the evaluation matrix Y, see equations (1-9).
Figure BDA0002711382790000074
Wherein
Figure BDA0002711382790000075
Further determining an objective weight of each index according to the inverse entropy value:
Figure BDA0002711382790000076
3) integration of subjective and objective weights
Obtaining the subjective weight omega of the index system according to a network analysis methods＝{ωsiI is more than or equal to 1 and less than or equal to n; obtaining the objective weight omega of the index system according to the entropy weight methodo＝{ωoiI is more than or equal to 1 and less than or equal to n. The final combination weight omega can be determined by using the determined subjective weight and objective weight and adopting the criterion of averaging the subjective weight and the objective weightiSee formulas (1-11).
Figure BDA0002711382790000081
And 4.1, taking secondary indexes in the operation cost as an example, and solving the subjective weight of the operation cost by using a network analysis method. Firstly, the expert is hired to determine the influence relationship among the indexes, and the influence relationship among the secondary indexes is obtained by adopting 1-5 scales, as shown in a table 5.
TABLE 5 Secondary index impact matrix
Figure BDA0002711382790000082
And (3) combining the formulas (1-1) to (1-5), calculating to obtain normalized eigenvectors based on each macroscopic demand index, and combining the normalized eigenvectors into a weight matrix to obtain the direct influence matrix. The direct influence matrix is limited to obtain a final weight matrix, and therefore the subjective weight w of each index is obtaineds＝[0.1328 0.1173 0.1117 0.1097 0.1083 0.1066 0.1066 0.2039]。
The objective weight vector w of the index calculated by the entropy weight method can be obtained by calculation according to the formulas (1-6) - (1-10)o＝[0.1548 0.1248 0.0501 0.0501 0.1548 0.1345 0.1506 0.1803]。
The final weight values for each index can be obtained according to equations (1-11), and the final weight results are shown in table 6.
TABLE 6 comprehensive energy scene indicator weight values
Figure BDA0002711382790000083
Figure BDA0002711382790000091
And 5, determining the economic evaluation value.
According to the scoring results of each index of the project and the corresponding weight thereof, the corresponding terms are multiplied and summed, and the economic score of the project is 74.4, which is shown as 7.
TABLE 7 index weights and scores
Figure BDA0002711382790000092
In an exemplary embodiment, there is also provided an economic evaluation system of an integrated energy service project, including: the economic evaluation index system module is used for constructing an economic evaluation index system of the comprehensive energy service project according to the method, the economic evaluation index system comprises 3 primary indexes of the operation cost, the operation income and the financial index of the comprehensive energy service project, and each primary index has one or more secondary indexes; the scoring standard module is used for establishing a scoring standard of the secondary index according to the method; the scoring module is used for scoring the secondary indexes according to the scoring standard; the weight calculation module is used for respectively obtaining subjective weight and objective weight of each index by utilizing a network analysis method and an anti-entropy weight method according to the score of the secondary index, and obtaining the relative importance degree of the subjective weight and the objective weight according to the basic theory of matrix theory so as to obtain a final weight value; and the economic calculation module is used for multiplying and summing corresponding items according to the scores of the secondary indexes and the corresponding weights to obtain the economic score value of the comprehensive energy service item. The specific implementation methods of the weight calculation module and the economy calculation module refer to the weight determination part in the step 4 above.
In an exemplary embodiment, there is also provided an economic evaluation system of an integrated energy service project, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform all or part of the steps of the method.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, on which a computer program is stored, which when executed by a processor implements all or part of the steps of the method. For example, the non-transitory computer readable storage medium may be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Claims (7)

1. A method for evaluating the economy of an integrated energy service project is characterized by comprising the following steps:
constructing an economic evaluation index system of the comprehensive energy service project, wherein the economic evaluation index system comprises 3 primary indexes of the comprehensive energy service project, including operation cost, operation income and financial indexes, and each primary index has one or more secondary indexes;
establishing a scoring standard of the secondary indexes, and scoring the secondary indexes according to the scoring standard;
according to the scores of the secondary indexes, respectively obtaining subjective weights and objective weights of the indexes by using a network analysis method and an anti-entropy weight method, and obtaining combined weight values of the indexes according to a weight average criterion;
and multiplying and summing the corresponding items according to the scores of the secondary indexes and the corresponding combined weight values to obtain the economic score value of the comprehensive energy service item.
2. The economic evaluation method of the integrated energy service project according to claim 1, wherein the subjective weight and the objective weight of each index are constructed by: constructing an influence matrix of the primary index, and obtaining the subjective weight of the primary index by using a network analysis method; constructing an influence matrix of the secondary indexes, and obtaining subjective weights of the secondary indexes by using a network analysis method; and normalizing the scores of the secondary indexes to an interval (0,1), and further determining the objective weight of each index by using an entropy-resisting weight method.
3. The method for evaluating the economic efficiency of an integrated energy service project according to claim 1 or 2, wherein the subjective weight is determined by:
network layer with ANPElement A1,A2,......,AnEach element corresponds to one of the first-level index and the second-level index in the economic evaluation index system, and the element AiFor AjHas a direct influence of eijSequentially with AiComparing the direct influence degrees of other elements on the elements of the criterion to obtain corresponding judgment matrix, and obtaining A by using characteristic root methodiWeight vector under sub-criterion
Figure FDA0002711382780000011
See formula (1-1);
Figure FDA0002711382780000012
combining the weight vectors under all the sub-criteria into a weight matrix, and filling 0 into the diagonal line of the weight matrix to obtain a direct influence matrix W shown in the formula (1-2)d：
Figure FDA0002711382780000021
Obtaining an average comprehensive influence matrix W among all the grade indexes shown in the formula (1-3):
Figure FDA0002711382780000022
obtaining a weighting matrix A, and calculating a weighting super matrix according to the formula (1-4)
Figure FDA0002711382780000023
Figure FDA0002711382780000024
To the weighted super matrix
Figure FDA0002711382780000025
And (3) carrying out 2k +1 evolutions (k → + ∞) to finally form a relatively stable matrix, wherein the nonzero values of all the rows of the matrix are the same, thereby obtaining the subjective weight vector of each evaluation index shown in the formula (1-5):
Figure FDA0002711382780000026
4. the method for economic evaluation of an integrated energy service project according to claim 1 or 2, wherein the objective weight is determined by:
let the index values of n evaluation indexes be xij(i＝1,2,...,n；j＝1,2,...,m)；
The indices were normalized as follows (1-6):
Figure FDA0002711382780000027
wherein x isi,minMinimum value of index, xi,maxA maximum value of the index value;
establishing an evaluation matrix of Y ═ Yij)m×nAnd determining the inverse entropy of each index according to the following formula (1-7) according to the evaluation matrix Y:
Figure FDA0002711382780000028
wherein
Figure FDA0002711382780000029
Further determining an objective weight of each index according to the inverse entropy value:
Figure FDA00027113827800000210
5. an economic evaluation system for an integrated energy service project, comprising:
the system comprises an economic evaluation index system module, a data processing module and a data processing module, wherein the economic evaluation index system module is used for constructing an economic evaluation index system of the comprehensive energy service project, the economic evaluation index system comprises 3 primary indexes of the comprehensive energy service project, the comprehensive energy service project comprises operation cost, operation income and financial indexes, and each primary index has one or more secondary indexes;
the scoring standard module is used for establishing a scoring standard of the secondary index;
the scoring module is used for scoring the secondary indexes according to the scoring standard;
the weight calculation module is used for respectively obtaining the subjective weight and the objective weight of each index by utilizing a network analysis method and an anti-entropy weight method according to the score of the secondary index and obtaining the combined weight value of each index according to a weight average criterion;
and the economic calculation module is used for multiplying and summing corresponding items according to the scores of the secondary indexes and the corresponding combined weight values to obtain the economic score value of the comprehensive energy service item.
6. An economic evaluation system for an integrated energy service project, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the steps of the method of any one of claims 1-4.
7. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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CN112766785B (en) * 2021-01-28 2024-03-15 中国人寿保险股份有限公司上海数据中心 Quality evaluation method, system, equipment and storage medium for insurance data
CN113435686A (en) * 2021-04-28 2021-09-24 国网冀北电力有限公司计量中心 Evaluation method and device for heat accumulating type electric heating system
CN113393094A (en) * 2021-05-31 2021-09-14 欣旺达电子股份有限公司 Energy system evaluation method, device, equipment and storage medium
CN113487215A (en) * 2021-07-21 2021-10-08 武昌理工学院 Intelligent evaluation and regulation method for indexes of green building group
CN113705984A (en) * 2021-08-11 2021-11-26 中冶南方城市建设工程技术有限公司 Green construction evaluation method and system for foundation pit engineering
CN113705984B (en) * 2021-08-11 2024-05-03 中冶南方城市建设工程技术有限公司 Environment-friendly construction evaluation method and system for foundation pit engineering
CN113946966A (en) * 2021-10-21 2022-01-18 广东电网有限责任公司广州供电局 Performance evaluation method of heterogeneous energy system exergy and related device thereof
CN113946966B (en) * 2021-10-21 2022-11-29 广东电网有限责任公司广州供电局 Performance evaluation method for heterogeneous energy system exergy and related device thereof
CN116362609A (en) * 2023-03-28 2023-06-30 国网江苏省电力有限公司经济技术研究院 Economic and technical evaluation method for big data of power grid engineering

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Application publication date: 20201229