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

Abstract

Disclosed is an economic evaluation method and system for a comprehensive energy service project. The method includes: constructing an economic evaluation index system for a comprehensive energy service project, wherein the economic evaluation index system includes operating costs, operating benefits, and financial indicators. each of the first-level indicators has one or more second-level indicators; establishing a scoring standard for the second-level indicators, and scoring the second-level indicators according to the scoring standard; according to the second-level indicators The subjective weight and objective weight of each index are obtained by network analysis method and anti-entropy weight method, respectively, and the combined weight value of each index is obtained according to the criterion of weight average; according to the score of the secondary index and the corresponding combination The weight value multiplies and sums the corresponding items to obtain the economic score value of the comprehensive energy service project. The method and system of the present disclosure can better reflect the economy of an integrated energy system.

Description

Economic Evaluation Method and System of Comprehensive Energy Service Project

technical field

The present disclosure relates to an economic evaluation method and system for a comprehensive energy service project.

Background technique

Energy is an important foundation for the development of human society. However, since the beginning of the 21st century, the rapid progress of science and technology and the rapid development of economy have caused a sharp increase in the consumption of earth's resources, and the energy problem has become increasingly prominent. With the decline of fossil energy reserves and the prominence of climate and environmental problems, the world has entered a critical period of energy transformation. Faced with challenges such as huge pressure on energy demand, many constraints on energy supply, serious damage to the ecological environment from energy production and consumption, and overall backward energy technology, the world is gradually promoting the construction of comprehensive energy projects. Comprehensive energy is developed by traditional energy suppliers relying on the infrastructure advantages of traditional energy supply to the direction of multi-supply of cooling, heat, electricity, gas, etc., to realize the mutual conversion, distribution, storage and consumption of various energy sources, and to achieve energy supply and use. A new energy system capable of diversification. Comprehensive energy service covers multiple links and is a technological revolution in the energy industry. The construction investment is large, the cycle is long, and the social impact is wide. It needs to be scientifically demonstrated to comprehensively demonstrate its economic, social and environmental benefits, and analyze its investment value and feasibility. necessity and necessity to achieve scientific decision-making. Therefore, methods and systems that can evaluate the economics of integrated energy systems will contribute to the scientific justification of integrated energy projects.

SUMMARY OF THE INVENTION

The present disclosure provides an economic evaluation method and system for a comprehensive energy service project. First, a set of core economic evaluation index system is constructed, which solves the shortcomings of the existing evaluation index system, such as being complicated and difficult to obtain. The entropy weight method is applied to the weight determination of the economic evaluation system, which ensures the reliability of the determined weight and realizes the effective economic evaluation of comprehensive energy services.

At least one embodiment of the present disclosure provides an economic evaluation method for an integrated energy service project, including:

Build an economic evaluation index system for comprehensive energy service projects, the economic evaluation index system includes comprehensive energy service projects including three first-level indicators of operating cost, operating income, and financial indicators, and each of the first-level indicators has one or more secondary indicators. level indicator;

establishing a scoring standard for the secondary indicator, and scoring the secondary indicator according to the scoring standard;

According to the scores of the secondary indicators, using network analysis method and anti-entropy weight method, the subjective weight and objective weight of each indicator are obtained respectively, and the combined weight value of each indicator is obtained according to the criterion of weight average;

According to the scores of the secondary indicators and the corresponding combined weight values, the corresponding items are multiplied and summed to obtain the economic score value of the comprehensive energy service project.

In some examples, the secondary indicators of operating costs include land rental costs, annual interest costs, equipment operating and maintenance costs, comprehensive network loss, annual failure service costs, charging loss rate, software operating and maintenance costs, communication operating and maintenance costs, One or more of the fixed costs of personnel, the secondary indicators of the operating income include one or more of the income from sales of energy, the income of information services, the income of financial services, and the income of auxiliary services, and the secondary indicators of the financial indicators include One or more of net present value rate, internal rate of return, payback period.

In some examples, the method for constructing the subjective weight and objective weight of each index is: constructing an influence matrix of the first-level index, obtaining the subjective weight of the first-level index by using a network analysis method; constructing the second-level index The influence matrix of , obtains the subjective weight of the secondary index by using network analysis method; normalizes the score of the secondary index to the interval (0, 1), and then uses the anti-entropy weight method to determine the objective weight of each indicator.

At least one embodiment of the present disclosure provides an economic evaluation system for an integrated energy service project, including:

The economic evaluation index system module is used to construct the economic evaluation index system of the comprehensive energy service project. A level indicator has one or more secondary indicators;

The scoring standard module is used to establish the scoring standard of the secondary indicator;

A scoring module, configured to score the secondary indicators according to the scoring standard;

The weight calculation module is used to obtain the subjective weight and the objective weight of each index by using the network analysis method and the anti-entropy weight method according to the score of the secondary index, and obtain the combined weight value of each index according to the criterion of weight average. ;

The economic calculation module is used for multiplying and summing the corresponding items according to the scores of the secondary indicators and the corresponding combined weight values to obtain the economic score value of the comprehensive energy service project.

At least one embodiment of the present disclosure provides an economic evaluation system for an integrated energy service item, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the method of all or part of the steps.

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, implements all or part of the steps of the method.

The economic evaluation method and system of the comprehensive energy service project disclosed in the present disclosure have the following advantages and beneficial effects: (1) Selecting the network analysis method and the anti-entropy weight method to determine the subjective weight and the objective weight respectively, which is better than the weight obtained by relying on the expert scoring method in the past. It has more reference value and universality, and can be better applied to engineering practice. (2) Considering the core economic evaluation index obtained by the internal energy coupling of the integrated energy system, the calculation is simple, and it can better reflect the economy of the integrated energy system, which is practical and feasible.

Description of drawings

In order to describe the technical solutions of the embodiments of the present invention more clearly, the accompanying drawings of the embodiments will be briefly introduced below.

Figure 1 is a flow chart of the realization of an economic evaluation method for a comprehensive energy service project.

Detailed ways

Figure 1 shows a flow chart of the realization of an economic evaluation method for an integrated energy service project. The specific steps are as follows:

Step 1: Taking the comprehensive energy service project under consideration as a scenario, according to the components and operating characteristics of the comprehensive energy system, determine the main cost and revenue sources of the project. The comprehensive energy scenarios considered generally include cold, heat, electricity, gas and other energy sources, involving multi-energy complementary scenarios, fishing-light complementary photovoltaic power generation scenarios, new energy big data scenarios, electric vehicle charging and discharging operation scenarios, wind power heating scenarios, etc. . The main costs generally include investment and acquisition costs, operation and maintenance costs, and annual outsourced energy costs. The sources of revenue generally include energy sales revenue, as well as information and data benefits and investment delay benefits.

Step 2, selection of evaluation indicators.

From the perspective of energy flow, information flow, and cash flow, focus on the principle of simplicity and importance in the selection principles of indicators, and consider the multi-energy coupling relationship within the integrated energy system to build a complete core economic evaluation index system. Then carry out the economic evaluation of comprehensive energy services.

On the basis of clarifying the connotation of comprehensive energy economy, establish a multi-dimensional and scientific standard for measuring its various aspects, and build a set of core economic evaluation index system, the first level of which includes: operating costs, operating income, financial indicators , and the specific index system is shown in Table 1.

Table 1 Economic evaluation index system

Step 3: According to industry standards, industry conditions, and market rules, the scoring standards for the second-level indicators under the first-level indicators of economic evaluation are formulated, as follows:

本公开所采用的打分方法主要基于五档打分法，将经济性指标的得分结果分为优秀值、良好值、平均值、较低值、较差值，其中对于参考成本，其所处的经济性水平区间为良好值与优秀值之间，故对应的参考成本分数为80分，且后续所使用的基准分数也为80分。每一项成本类指标的运营参考成本如下所示：Cost indicators: The lower the value of the cost data obtained from the revenue and expenditure data, the better the economic benefit, and the higher the corresponding economic index score. Such indicators are mainly based on the comparison between the actual operating cost and the industry reference cost. The disclosure mainly refers to the "Guodian Electric Power Photovoltaic Power Station Economic Evaluation Standard Description" and "Brief Analysis on the Charging Standards for Network Service Projects". The scoring standards are:

The scoring method adopted in the present disclosure is mainly based on the five-level scoring method, and the scoring results of economic indicators are divided into excellent value, good value, average value, low value, and poor value. The performance level interval is between the good value and the excellent value, so the corresponding reference cost score is 80 points, and the subsequent benchmark score is also 80 points. The operational reference cost of each cost category indicator is as follows:

Table 2 Scoring basis for economic indicators

Revenue indicators: The higher the corresponding revenue and expenditure data value of the revenue indicators, the better the economic benefits of the service project, and the higher the corresponding economic indicators. Such indicators are mainly based on actual operating revenue and theoretical maximum revenue. The comparison mainly refers to documents such as "Distribution of Solar Energy Resources in China" issued by the Wind Energy and Solar Energy Resources Evaluation Center of the National Meteorological Administration. The scoring criteria are:

Theoretical maximum income = annual average sunshine time * system installation capacity * comprehensive efficiency * unit price of electricity.

Financial indicators: financial indicators return on net assets, internal rate of return, and investment payback period refer to the industry standards, specifically refer to the "Evaluation Value of Performance Standards for Medium-sized Enterprises in the Electric Power Industry 2018", according to the level range of each indicator and its corresponding score. Quantify.

Table 3 Reference value of industry financial data

In a possible implementation, it is assumed that the integrated energy system in place A includes projects such as natural gas energy stations, building-integrated photovoltaics, ground photovoltaic and energy storage power stations, bus charging stations with integrated photovoltaics and storage, and sewage source heat pumps. The system uses a combination of cold and heat sources to store ice for cooling when electricity consumption is underestimated at night, and melt ice to release cooling when electricity consumption peaks during the day. The self-sufficiency rate of the system’s renewable energy power supply is not less than 50%, the annual bank loan interest rate is 4.90%, the repayment period of the project is 10 years, the grid electricity price is 0.67 yuan/(kW·h), and the network loss rate is 5%.

It is assumed that the scores of the secondary indicators of the integrated energy system of A-site obtained according to the above scoring criteria are as follows, as shown in Table 4.

Table 4 Scores of secondary indicators of integrated energy service system

Step 4, the weight is determined.

The economic evaluation method involved in the present disclosure adopts the network analysis method and the anti-entropy weight method to calculate the subjective weight and the objective weight, and the specific principles and mathematical descriptions thereof are described below.

1) Network analysis method

Analytic network process (ANP) is a systematic decision-making method extended and developed on the basis of analytic hierarchy process (AHP). It can reflect the mutual influence of each component in the integrated energy system to a certain extent. It is divided into two elements: the control factor layer and the network layer, which can correspond to the first-level and second-level indicators in the comprehensive energy service economic index system respectively. In addition, the network analysis method is used to determine the subjective weight, it does not need the original data, but only needs to determine the mutual influence relationship between the indicators.

见式(1-1)。Suppose that there are elements A ₁ , A ₂ ,...,A _n in the network layer of ANP, each element corresponds to an index in the first-level index or second-level index in the index system, and element A _i is for A _j The degree of direct influence is e _ij . Taking A _i as the sub-criteria in turn, compare the direct influence degree of the remaining elements on the criterion element pairwise to obtain the corresponding judgment matrix, and then use the characteristic root method to obtain the weight vector under the A _i sub-criteria

See formula (1-1).

Combine the weight vectors under all subcriteria into the weight matrix, and fill in 0 on the diagonal of the weight matrix to obtain the direct influence matrix W _d , as shown in formula (1-2).

Then, the average comprehensive influence matrix W between each level index is obtained,

Using the above method, the weighted matrix A can also be obtained, and then the system weighted supermatrix can be calculated.

Perform 2k+1 evolutions on the above matrix (k→+∞), and finally form a relatively stable matrix, and the non-zero values of each row are the same, thus obtaining the subjective weight vector of each evaluation index:

2) Anti-entropy weight method

The anti-entropy weight method can objectively reflect the relationship between indicators. The basic idea is to determine the objective weight according to the variability of the indicators. The greater the information entropy obtained from the calculation of a certain indicator, the smaller the degree of variation of the indicator value should be. Therefore, the amount of information it provides is relatively less, and the smaller the role it plays in the comprehensive evaluation, the smaller the weight assigned to it, and vice versa.

The entropy weight method reflects the amount of information contained in each index through the entropy value. The smaller the entropy value, the greater the amount of information of the index, and the greater its weight. The definition of entropy is:

where p _j (j=1, 2, 3...m) represents the probability of occurrence of each situation, and m is the total number of evaluation objects; the present disclosure selects the anti-entropy weight method to determine the objective weight, and its anti-entropy definition is shown in the formula ( 1-7)

It is assumed that there are m evaluation objects for the elements to be evaluated, corresponding to the operation of the comprehensive energy service disclosed in the present disclosure; n evaluation indicators, corresponding to the number of secondary indicators in the economic evaluation index system of the present disclosure; the index values are respectively x _ij (i=1,2,...,n; j=1,2,...,m); the entropy weight method first needs to standardize the indicators

Among them, the minimum value of x _i,min index value, the maximum value of x _i,max index value; then there is an evaluation matrix Y=(y _ij ) _m×n , according to the evaluation matrix Y, determine the inverse entropy of each index, see Formula (1-9).

根据反熵值进一步确定每一个指标的客观权重：in

The objective weight of each indicator is further determined according to the anti-entropy value:

3) Combination of subjective weight and objective weight

According to the network analysis method, the subjective weight of the index system is obtained as ω _s ={ω _si |1≤i≤n}; according to the anti-entropy weight method, the objective weight of the index system is obtained as ω _o ={ω _oi |1≤i ≤n}. Using the determined subjective weight and objective weight, and adopting the criterion of averaging the subjective weight and the objective weight, the final combined weight ω _i can be determined, as shown in formula (1-11).

Step 4.1, this example takes the secondary index in the operating cost as an example, and uses the network analysis method to solve its subjective weight. First, hire experts to determine the influence relationship between the indicators, and use the scale of 1 to 5 to obtain the influence relationship between the secondary indicators, as shown in Table 5.

Table 5 Impact Matrix of Secondary Indicators

Combined with equations (1-1) to (1-5), the normalized eigenvectors based on each macro demand index can be calculated and combined into a weight matrix to obtain a direct impact matrix. The limit of the direct influence matrix is obtained to obtain the final weight matrix, so as to obtain the subjective weight of each index ws = [0.1328 _0.1173 0.1117 0.1097 0.1083 0.10660.1066 0.2039].

According to formulas (1-6)-(1-10), the objective weight vector w _o =[0.1548 0.1248 0.0501 0.0501 0.1548 0.1345 0.1506 0.1803] can be obtained by calculating by the anti-entropy weight method.

According to formula (1-11), the final weight value of each index can be obtained, and the final weight result is shown in Table 6.

Table 6 Index weights of comprehensive energy scenarios

Step 5, determine the economic evaluation value.

According to the scoring results of various indicators of the project and their corresponding weights, the corresponding items are multiplied and summed, and the economic score of the project can be obtained as 74.4 points, as shown in 7.

Table 7 Indicator weights and scores

In an exemplary embodiment, an economic evaluation system for an integrated energy service project is also provided, including: an economic evaluation index system module for constructing an economic evaluation index system for an integrated energy service project according to the method described above, the The economic evaluation index system includes three first-level indicators, including operating cost, operating income, and financial indicators of comprehensive energy service projects, and each of the first-level indicators has one or more second-level indicators; the scoring standard module is used for the above-mentioned The method establishes the scoring standard of the secondary index; the scoring module is used to score the secondary index according to the scoring standard; the weight calculation module is used to use the network analysis method according to the score of the secondary index. and anti-entropy weight method, respectively obtain the subjective weight and objective weight of each index, according to the basic theory of matrix theory to find out the relative importance of the subjective and objective weight, and then get the final weight value; According to the scores and corresponding weights of the level indicators, the corresponding items are multiplied and summed to obtain the economic score value of the comprehensive energy service project. For the specific implementation method of the weight calculation module and the economic calculation module, please refer to the weight determination section in step 4 above.

In an exemplary embodiment, there is also provided 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 method all or part of the steps.

In an exemplary embodiment, there is also provided a non-transitory computer-readable storage medium having stored thereon a computer program that, 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 ROM, RAM, CD-ROM, magnetic tape, floppy disk, 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,......,A_nEach element corresponds to one of the first-level index and the second-level index in the economic evaluation index system, and the element A_iFor A_jHas a direct influence of e_ijSequentially with A_iComparing 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 method_iWeight vector under sub-criterion

See formula (1-1);

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：

Obtaining an average comprehensive influence matrix W among all the grade indexes shown in the formula (1-3):

obtaining a weighting matrix A, and calculating a weighting super matrix according to the formula (1-4)

To the weighted super matrix

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):

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 x_ij(i＝1,2,...,n；j＝1,2,...,m)；

The indices were normalized as follows (1-6):

wherein x is_i,minMinimum value of index, x_i,maxA maximum value of the index value;

establishing an evaluation matrix of Y ═ Y_ij)_m×nAnd determining the inverse entropy of each index according to the following formula (1-7) according to the evaluation matrix Y:

wherein

Further determining an objective weight of each index according to the inverse entropy value:

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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