Comprehensive energy system evaluation method considering park multi-energy complementation

Abstract

The invention belongs to the technical field of comprehensive energy park evaluation, and particularly relates to a comprehensive energy system evaluation method considering park multi-energy complementation. Aiming at the defect that the existing comprehensive energy system evaluation method is not comprehensive and accurate enough, the invention adopts the following technical scheme: the comprehensive energy system evaluation method considering park multi-energy complementation comprises the following steps: establishing a multi-level index system comprising multiple dimensions; related basic data of the target park are collected, and calculation of indexes of all levels is completed; completing the construction of a composite index evaluation system according to an analytic hierarchy process and an expert evaluation method; according to a scoring standard, performing score evaluation on each level of index of the target park, and determining a membership degree and a fuzzy comprehensive evaluation matrix; and according to the weight of the composite index evaluation system, calculating an evaluation score of the target park, and determining an evaluation grade. The method has the beneficial effects that a more comprehensive, accurate and reliable comprehensive evaluation result can be obtained, and powerful guidance is provided for subsequent improvement of the park.

Description

Technical Field

[0001] The present invention belongs to the technical field of comprehensive energy park evaluation, and specifically relates to a comprehensive energy system evaluation method considering multi-energy complementarity in a park. Background Art

[0002] The integrated energy system is an important part of the energy internet. It is not only a research hotspot in the energy field, but also the development direction of my country's current energy structure adjustment. The core of the integrated energy system is to achieve energy conversion, utilization and coordinated optimization, and promote the coupling and complementarity of multiple energy sources. A comprehensive and accurate evaluation of the integrated energy system can provide strong guidance for subsequent improvements and the planning and construction of my country's integrated energy parks.

[0003] The existing regional and park-level comprehensive energy system evaluation indicators often focus on the distribution side, ignoring the thermal and cold energy sides, as well as the coupling relationship between them, which is not comprehensive enough. In addition, the methods used in the evaluation process greatly affect the accuracy and efficiency of the evaluation. Summary of the invention

[0004] In view of the shortcomings of existing comprehensive energy system evaluation methods that are not comprehensive and accurate, the present invention provides a comprehensive energy system evaluation method that takes into account the multi-energy complementarity of the park, improves the comprehensiveness and accuracy of the evaluation, and provides powerful guidance for the subsequent improvement of the park and the planning and construction of my country's comprehensive energy park.

[0005] To achieve the above object, the present invention adopts the following technical solution: a comprehensive energy system evaluation method considering multi-energy complementarity in a park, the comprehensive energy system evaluation method considering multi-energy complementarity in a park comprising:

[0006] Step S1: Complete the weighting of the composite index evaluation system according to the hierarchical analysis method and the expert evaluation method, and establish a multi-level index system containing multiple dimensions;

[0007] Step S2: Collect relevant basic data of the target park and complete the calculation of indicators at all levels;

[0008] Step S3: According to the scoring criteria, the scores of various indicators of the target park are evaluated to determine the degree of membership and the fuzzy comprehensive evaluation matrix;

[0009] Step S4: Calculate the evaluation score of the target park and determine the evaluation level according to the weight of the composite indicator evaluation system;

[0010] Step S5: refer to the index evaluation scores of other parks and make targeted improvements to the indicators with lower scores in this park.

[0011] The comprehensive energy system evaluation method of the present invention taking into account the multi-energy complementarity of the park comprehensively considers various energy forms of the park and combines the hierarchical analysis method and the fuzzy comprehensive evaluation method to obtain a more comprehensive, accurate and reliable comprehensive evaluation result, which provides powerful guidance for the subsequent improvement of the park and the planning and construction of my country's comprehensive energy park, so as to increase the coupling of the system, ensure the reliable operation of the comprehensive energy system, and improve the utilization efficiency of energy.

[0012] As an improvement, in step S1, the multi-level indicator system is divided into technical dimension, economic dimension and environmental dimension.

[0013] As an improvement, in step S1, the technical dimension includes four first-level indicators, namely reliability, network loss rate, comprehensive energy utilization efficiency and demand-side response. Reliability includes system energy supply reliability, availability, mean trouble-free working time and system fault recovery time; network loss rate includes distribution network loss rate, heat pipe network loss rate and cooling pipe network loss rate; demand-side response includes peak shaving and valley filling amount and load forecast accuracy.

[0014] As an improvement, in step S1, the economic dimension includes three first-level indicators, namely unit electricity cost, system investment payback period and equipment economy, and equipment economy includes two second-level indicators: equipment utilization rate and equipment cost saving.

[0015] As an improvement, in step S1, the environmental protection dimension includes two first-level indicators, namely, gas pollutant emissions and the proportion of clean energy consumption. The gas pollutant emissions include two second-level indicators: carbon dioxide pollutant emission reduction and other gas pollutant emission reduction.

[0016] As an improvement, step S1 includes:

[0017] Step S11: compare the elements of each layer in the hierarchical analysis structure in pairs to construct the following judgment matrix:

[0018]

[0019] Step S12: Calculate the eigenvector W and eigenroot λ of the judgment matrix C according to the following formula:

[0020]

[0021]

[0022]

[0023]

[0024] Where: M i Represents the product of each row of the judgment matrix, a ijRepresents the elements in the judgment matrix, W=[W1,W2,…,W n ] T is the eigenvector of the judgment matrix, λ max is the maximum eigenvalue of the judgment matrix, (AW) i represents the i-th element of the vector AW;

[0025] Step S13, find the consistency index CI of the judgment matrix to complete the consistency test:

[0026]

[0027] Step S14: normalize the judgment matrix C that passes the consistency check to obtain a standardized judgment matrix.

[0028] 1. As an improvement, step S1 further includes:

[0029] Step S15: record the subordinate cloud as:

[0030]

[0031] In the formula, x0 represents the expected value of the fuzzy concept corresponding to the membership cloud, b represents the fuzziness degree of the fuzzy concept; δ max represents the variance of the random distribution of membership on the membership cloud expectation curve;

[0032] Step S16, assume that n experts give their own judgment matrices for a single ranking of a certain level;

[0033]

[0034] In the formula, A k is the judgment matrix given by the nth expert, It means that the nth expert in the i-th row and j-th column gives the judgment matrix;

[0035] Step S17, calculate the reverse membership cloud generator:

[0036] according to Calculate the sample mean of this set of data Sample first-order central moment Sample variance The cloud droplets generated by the cloud (Ex, En, He) are represented by random variables X, where:

[0037]

[0038]

[0039]

[0040] In the formula, Ex represents the expected value of X, En represents the first-order central moment of X, and He represents the variance of X;

[0041] Use random variable X to represent the cloud droplets generated by the cloud (Ex, En, He), and convert all elements in the judgment matrix into belonging cloud elements (Ex i,j ,En i,j ,He i,j ), and obtain the membership cloud judgment matrix of a certain level of single sorting.

[0042] As an improvement, step S3 includes:

[0043] Step S31: Determine the index set U = {u1, u2, ..., u m} and evaluation set V = {v1,v2,…,v n};

[0044] Step S32: According to the scoring criteria, the scores of various indicators of the target park are evaluated to determine the degree of membership and fuzzy

[0045] Comprehensive evaluation matrix

[0046] Step S33: perform fuzzy operation on the fuzzy comprehensive evaluation matrix and the weight of the index and normalize them to obtain the final

[0047] The fuzzy comprehensive evaluation vector B is expressed as:

[0048]

[0049] As an improvement, in step S4, according to the weight of the composite index evaluation system, the fuzzy comprehensive evaluation vector B is multiplied by the corresponding score of the evaluation set V to calculate the evaluation score S of the target park, which is expressed as:

[0050] S=V·B.

[0051] As an improvement, in step S4, a comprehensive evaluation grade is obtained according to the evaluation grade scoring table.

[0052] As an improvement, in step S5, the average value of each indicator is calculated, and improvements are made to the indicators of the park that are lower than the average value by a certain percentage.

[0053] The beneficial effects of the comprehensive energy system evaluation method considering the multi-energy complementarity of the park of the present invention are: establishing a multi-level indicator system containing multiple dimensions, comprehensively considering various energy forms of the park, and combining the hierarchical analysis method and the fuzzy comprehensive evaluation method, a more comprehensive, accurate and reliable comprehensive evaluation result can be obtained, which will provide powerful guidance for the subsequent improvement of the park and the planning and construction of my country's comprehensive energy park, so as to increase the coupling of the system, ensure the reliable operation of the comprehensive energy system, and improve the utilization efficiency of energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 Schematic diagram of the evaluation index system of the comprehensive energy system evaluation method according to the embodiment of the present invention.

[0055] Figure 2 It is a flow chart of the comprehensive energy system evaluation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The technical solutions of the embodiments of the present invention are explained and described below, but the following embodiments are only preferred embodiments of the present invention, not all. Based on the embodiments in the implementation mode, other embodiments obtained by those skilled in the art without creative work are all within the protection scope of the present invention.

[0057] The following is a specific explanation using a certain park as an example.

[0058] See also Figure 1 and Figure 2 The comprehensive energy system evaluation method of the embodiment of the present invention, first, completes the weight construction of the composite index evaluation system according to the hierarchical analysis method and the expert evaluation method, and establishes a multi-level index system containing multiple dimensions; then, collects the relevant basic data of the target park, and completes the calculation of indicators at all levels; secondly, according to the scoring standard, the scores of indicators at all levels of the target park are evaluated, and the membership degree and the fuzzy comprehensive evaluation matrix are determined; thirdly, according to the weight of the composite index evaluation system, the evaluation score of the target park is calculated, and the evaluation level is determined; finally, referring to the indicator evaluation scores of other parks, targeted improvements are made to the indicators with lower scores in this park.

[0059] Table 1 is the calculation results of the three-level indicators obtained by sorting and calculating the basic data of the selected target parks.

[0060] Table 1 Calculation results of indicators of a certain park

[0061]

[0062]

[0063] Table 2 shows the weights and total weights of indicators at all levels determined according to the actual situation of the target park, using the analytic hierarchy process and expert evaluation method.

[0064] Table 2 Index weights determined by analytic hierarchy process

[0065]

[0066]

[0067] The judgment matrix is ​​obtained based on the fuzzy cloud analysis method. The specific process is as follows.

[0068] 1) Record the subordinate cloud as:

[0069]

[0070] In the formula, x0 represents the expected value of the fuzzy concept corresponding to the membership cloud, b represents the fuzziness degree of the fuzzy concept; δ max Represents the variance of the random distribution of membership on the membership cloud expectation curve.

[0071] 2) Method for generating subordinate cloud

[0072] Assume that n experts give their own judgment matrices for a certain level of single ranking:

[0073]

[0074] In the formula, A k is the judgment matrix given by the nth expert, It means that the nth expert in the i-th row and j-th column gives the judgment matrix.

[0075] 3) Calculate the reverse membership cloud generator:

[0076] according to Calculate the sample mean of this set of data Sample first-order central moment Sample variance

[0077] The cloud droplets generated by the cloud (Ex, En, He) are represented by random variables X, where:

[0078]

[0079]

[0080]

[0081] In the formula, Ex represents the expected value of X, En represents the first-order central moment of X, He represents the variance of X, and the random variable X represents the cloud droplets generated by the cloud (Ex, En, He). All elements in the judgment matrix are converted into cloud elements (Ex i,j ,En i,j ,He i,j ), and obtain the membership cloud judgment matrix of a certain level of single sorting.

[0082] 4) Calculate the eigenvector W and eigenroot λ of the judgment matrix C according to the following formula:

[0083]

[0084]

[0085]

[0086]

[0087] Where: M i Represents the product of each row of the judgment matrix, a ij Represents the elements in the judgment matrix, W=[W1,W2,…,W n ] T is the eigenvector of the judgment matrix, λ max is the maximum eigenvalue of the judgment matrix, (AW) i Represents the i-th element of the vector AW.

[0088] Table 3 is the membership of each secondary indicator obtained by fuzzy comprehensive evaluation of each indicator in Table 1 using the trapezoidal membership function based on the evaluation set V = [10090807060].

[0089] Table 3 Calculation results of index membership

[0090]

[0091]

[0092] The M(∧,∨) operator is used to calculate the fuzzy comprehensive evaluation vector of each primary indicator, and the fuzzy comprehensive evaluation matrix is:

[0093]

[0094] According to the combined weights in Table 2:

[0095] W=[0.3081 0.0509 0.2235 0.0352 0.1084 0.0179 0.0247 0.0743 0.1570] T

[0096] Obtain the total fuzzy comprehensive evaluation vector and perform normalization:

[0097] B=[0.2925 0.2925 0.1905 0.1495 0.0750] (2)

[0098] Based on the evaluation set V and the total fuzzy comprehensive evaluation vector B, according to the weighted average principle, the final evaluation score S is obtained:

[0099] S=V·B T =85.78 (3)

[0100] The comprehensive energy system project was evaluated by multi-level fuzzy comprehensive evaluation method, and the final evaluation score was 85.78 points. According to the evaluation grade score table shown in Table 4, the comprehensive evaluation grade of this system was "good".

[0101] Table 4 Evaluation grade score table

[0102]

[0103] Afterwards, based on the calculation results of the indicators in Table 2 of other parks, targeted improvements can be made to the indicators that are below a certain proportion of the average value (such as 60%, 80%, etc.).

[0104] The comprehensive energy system evaluation method considering the multi-energy complementarity of the park provided by the embodiment of the present invention takes into account multiple aspects such as the economy, low carbon and technological advancement of the system, avoids the problem of biased evaluation results caused by sticking to unilateral factors, and is more comprehensive and systematic; through the fuzzy cloud-based comprehensive evaluation method, the score can be quantified, combined with the weight, the performance of each factor can be analyzed more clearly, and subsequent improvements can be carried out in a targeted manner.

[0105] The above is only a specific implementation of the invention, but the protection scope of the invention is not limited thereto. Those skilled in the art should understand that the invention includes but is not limited to the contents described in the above specific implementation. Any modification that does not deviate from the functional and structural principles of the invention will be included in the scope of the claims.

Claims

1. A comprehensive energy system evaluation method considering multi-energy complementarity in a park, characterized by: The comprehensive energy system evaluation method considering multi-energy complementarity in the park includes: Step S1: Complete the weighting of the composite index evaluation system according to the hierarchical analysis method and the expert evaluation method, and establish a multi-level index system containing multiple dimensions; Step S2: Collect relevant basic data of the target park and complete the calculation of indicators at all levels; Step S3: According to the scoring criteria, the scores of various indicators of the target park are evaluated to determine the degree of membership and the fuzzy comprehensive evaluation matrix; Step S4: Calculate the evaluation score of the target park and determine the evaluation level according to the weight of the composite indicator evaluation system; Step S5: refer to the index evaluation scores of other parks and make targeted improvements to the indicators with lower scores in this park.

2. According to claim 1, a comprehensive energy system evaluation method considering multi-energy complementarity in a park is characterized by: In step S1, the multi-level indicator system is divided into technical dimension, economic dimension and environmental dimension.

3. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 2 is characterized by: In step S1, the technical dimension includes four first-level indicators, namely reliability, network loss rate, comprehensive energy utilization efficiency and demand-side response. Reliability includes system energy supply reliability, availability, mean trouble-free working time and system fault recovery time; network loss rate includes distribution network loss rate, heat pipe network loss rate and cooling pipe network loss rate; demand-side response includes peak shaving and valley filling amount and load forecast accuracy.

4. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 2 is characterized by: In step S1, the economic dimension includes three primary indicators, namely unit electricity cost, system investment payback period and equipment economy. Equipment economy includes two secondary indicators: equipment utilization rate and equipment cost saving.

5. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 2 is characterized by: In step S1, the environmental protection dimension includes two first-level indicators, namely, gas pollutant emissions and the proportion of clean energy consumption. The gas pollutant emissions include two second-level indicators: carbon dioxide pollutant emission reduction and other gas pollutant emission reduction.

6. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 1 is characterized by: Step S1 includes: Step S11: compare the elements of each layer in the hierarchical analysis structure in pairs to construct the following judgment matrix: Step S12: Calculate the eigenvector W and eigenroot λ of the judgment matrix C according to the following formula: Where: M i Represents the product of each row of the judgment matrix, a ij Represents the elements in the judgment matrix, W=[W1,W2,…,W n ] T is the eigenvector of the judgment matrix, λ max is the maximum eigenvalue of the judgment matrix, (AW) i represents the i-th element of the vector AW; Step S13, find the consistency index CI of the judgment matrix to complete the consistency test: Step S14: normalize the judgment matrix C that passes the consistency check to obtain a standardized judgment matrix.

7. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 1 is characterized by: Step S1 also includes: Step S15: record the subordinate cloud as: In the formula, x0 represents the expected value of the fuzzy concept corresponding to the membership cloud, b represents the fuzziness degree of the fuzzy concept; δ max represents the variance of the random distribution of membership on the membership cloud expectation curve; Step S16, assume that n experts give their own judgment matrices for a single ranking of a certain level; In the formula, A k is the judgment matrix given by the nth expert, It means that the nth expert in the i-th row and j-th column gives the judgment matrix; Step S17, calculate the reverse membership cloud generator: according to Calculate the sample mean of this set of data Sample first-order central moment Sample variance The cloud droplets generated by the cloud (Ex, En, He) are represented by random variables X, where: In the formula, Ex represents the expected value of X, En represents the first-order central moment of X, and He represents the variance of X; Use random variable X to represent the cloud droplets generated by the cloud (Ex, En, He), and convert all elements in the judgment matrix into belonging cloud elements (Ex i,j ,En i,j ,He i,j ), and obtain the membership cloud judgment matrix of a certain level of single sorting.

8. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 1 is characterized by: Step S3 include: Step S31: Determine the index set U = {u1, u2, ..., u m } and evaluation set V = {v1,v2,…,v n }; Step S32: According to the scoring criteria, the scores of various indicators of the target park are evaluated to determine the degree of membership and the fuzzy comprehensive evaluation matrix. Step S33: perform fuzzy operation on the fuzzy comprehensive evaluation matrix and the weight of the index and normalize them to obtain the final fuzzy comprehensive evaluation vector B, which is expressed as:

9. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 7 is characterized by: In step S4, according to the weight of the composite index evaluation system, the fuzzy comprehensive evaluation vector B is multiplied by the corresponding score of the evaluation set V to calculate the evaluation score S of the target park, which is expressed as: S = V·B; In step S4, a comprehensive evaluation grade is obtained according to the evaluation grade scoring table.

10. The comprehensive energy system evaluation method considering multi-energy complementarity in a park according to claim 1 is characterized by: In step S5, the average value of each indicator is calculated, and improvements are made to the indicators of the park that are lower than the average value by a certain percentage.

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