Comprehensive evaluation method applied to building heating ventilation air conditioning system

Abstract

The invention discloses a comprehensive evaluation method applied to a building heating, ventilation and air conditioning system, and the method comprises the steps: obtaining the index data of the building heating, ventilation and air conditioning system, carrying out the sorting of the hierarchical relation between the building heating, ventilation and air conditioning systems through an interpretation structure model, and obtaining an index adjacency matrix; calculating an index reachable matrix based on the obtained index adjacent matrix, and performing hierarchical division on the index reachable matrix to establish an index structure model; calculating the weight of each level of index based on the obtained index structure model; and based on the calculated weight of each level of index, calculating the score of each level of index, and according to the score condition of each level of index, evaluating the building heating ventilation air-conditioning system. The comprehensive fuzzy evaluation method suitable for the building heating ventilation air-conditioning system is established, scientificity and universality of the evaluation result are enhanced, and scientific decision support is provided for selection and optimization of different building heating ventilation air-conditioning systems.

Description

Technical Field

[0001] This invention belongs to the field of air conditioning system evaluation technology, and in particular relates to a comprehensive evaluation method for building HVAC systems. Background Technology

[0002] Building air conditioning systems combine the air delivery performance of central air conditioning with the functionality of split-type air conditioners. They are a crucial component of office spaces, directly impacting the comfort of occupants. Researching comprehensive evaluation methods for building air conditioning systems is of great significance for further improving user experience and promoting energy-efficient development in the air conditioning industry.

[0003] To address the shortcomings of commonly used evaluation methods for residential air conditioning systems, such as incomplete evaluation indicators, complex evaluation processes, and strong subjectivity of evaluation results, a fuzzy comprehensive evaluation method for building air conditioning systems is proposed.

[0004] CN202411883582.2A discloses a method for evaluating the comprehensive performance of air conditioners. This method establishes a comprehensive performance evaluation system for air conditioners in different locations within a room; it uses the Analytic Hierarchy Process (AHP) to establish judgment matrices for the evaluation layer and the scheme layer and performs consistency checks, calculating the weights QY1 and QY2 of each evaluation index in the evaluation layer and the scheme layer; it calculates the total subjective weight QY of each scheme, QY = QY1 × QY2; it uses the entropy weight method to calculate the weight of each scheme in the scheme layer for each evaluation index in the evaluation layer and the weight of each evaluation index in the evaluation layer, finally calculating the total objective weight of each scheme; combining the AHP method and the entropy weight method, it evaluates the comprehensive performance of air conditioners in different locations within a standard room to obtain the optimal air conditioner location. However, this method does not use scientific methods to ensure the comprehensiveness of the indicators, nor does it consider indicator redundancy.

[0005] CN202510320829.8A discloses a comprehensive performance evaluation method for a medium-temperature chilled water centralized air conditioning system. Based on the characteristics of medium-temperature chilled water systems, a core indicator system is constructed. Weights are determined using a subjective and objective weighting method. Subjective weighting employs a 1-9 scale to construct a judgment matrix, and a consistency test is used to screen effective matrices and calculate initial weights. Objective weighting adjusts the initial weights based on the dispersion of expert scoring data. The system to be evaluated is then subjected to grey relational analysis to quantify comprehensive performance. However, this method only considers unit performance and fails to consider user experience.

[0006] Therefore, there is an urgent need for a comprehensive evaluation method for building HVAC systems that can take into account subjective factors and reflect the hierarchical relationship between various indicators, so that the evaluation can objectively reflect the actual situation. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a comprehensive evaluation method for building HVAC systems.

[0008] The present invention adopts the following technical solution.

[0009] A comprehensive evaluation method for building HVAC systems, comprising the following steps:

[0010] Step 1: Obtain the building HVAC system index data, and use the Interpretive Structure Model to sort out the hierarchical relationship between the building HVAC system indexes to obtain the index adjacency matrix;

[0011] Step 2: Calculate the reachability matrix of the indicators based on the adjacency matrix of the indicators obtained in Step 1, and perform hierarchical partitioning of the reachability matrix of the indicators to establish the indicator structure model;

[0012] Step 3: Based on the indicator structure model obtained in Step 2, calculate the weights of each level of indicator;

[0013] Step 4: Based on the weights of each level of indicators calculated in Step 3, calculate the scores of each level of indicators, and conduct a comprehensive evaluation of the building's HVAC system based on the scores of each level of indicators.

[0014] In step 1, the building HVAC system indicators include energy consumption indicators, environmental protection indicators, economic indicators, thermal comfort indicators, and air quality indicators.

[0015] In step 1, the hierarchical relationship between the indicators of the building HVAC system is sorted out using the Interpretive Structural Model, and the indicator adjacency matrix is ​​obtained. This includes judging the correlation and causality between the indicators Si and Sj of the building HVAC system, with a value of 0 or 1. Based on the judgment result, the indicator adjacency matrix A is constructed. Here, 0 represents that there is no direct influence between Si and Sj, i.e., no coupling effect, and 1 represents that there is a direct influence between Si and Sj, i.e., there is a coupling effect.

[0016] In step 2, the formula for calculating the index reachability matrix P is as follows:

[0017] P = (A + I) n+1

[0018] Where A represents the index adjacency matrix, I represents the identity matrix, and n represents the number of self-multiplications of the adjacency matrix plus the identity matrix.

[0019] In step 2, the hierarchical partitioning of the reachability matrix and the establishment of the indicator structure model include: dividing the reachability matrix P into a reachability set R(Si) and a priori set A(Si); calculating the intersection of R(Si) and A(Si) to obtain the top-level indicator; removing the corresponding row of the top-level indicator in the reachability matrix to obtain the second-level indicator; removing the corresponding column of the top-level indicator in the reachability matrix to obtain the third-level indicator; and using a directed graph to represent the hierarchical structure of the indicator structure model, with the top level corresponding to the top-level indicator, followed by the second-level indicator and the third-level indicator in sequence.

[0020] The reachability set R(Si) is the set of column indices corresponding to the matrix elements in the row corresponding to index Si of the reachability matrix that contain 1.

[0021] The preceding set A(Si) is the set of row indices corresponding to the matrix elements in the column corresponding to index Si in the reachability matrix that contain 1.

[0022] Step 3 involves calculating the weights of each level of indicator, including:

[0023] Step 301: Construct a judgment matrix. The elements in the judgment matrix represent the relative importance of each pair of indicators at the same level. A scale is used to represent the relative importance of the indicators.

[0024] Step 302: Find the largest eigenvalue of the judgment matrix;

[0025] Step 303: Perform a consistency check on the judgment matrix. If the consistency check passes, proceed to step 304. If the consistency check fails, return to step 301 to reconstruct the judgment matrix.

[0026] Step 304: Normalize the eigenvector corresponding to the largest eigenvalue of the judgment matrix to obtain the weight sequence of the same level index to the previous level index.

[0027] In step 303, the consistency check of the judgment matrix includes calculating the check coefficient according to the following formula:

[0028]

[0029] in, λ represents the consistency index; RI represents the average random consistency index of the judgment matrix; max CR is the largest eigenvalue of the judgment matrix, and n is the order of the judgment matrix; if CR < 0.1, the judgment matrix is ​​considered to have passed the one-time test; if CR ≥ 0.1, the judgment matrix is ​​considered to have failed the consistency test, and it is necessary to return to step A1 to reconstruct the judgment matrix.

[0030] Step 4 involves calculating the scores for each level of indicators, including:

[0031] Step 401: For the third-level indicator A k,j Calculate the score F of the third-level indicator. k,j The evaluation effect of each third-level indicator is determined based on the score;

[0032] Step 402: Determine the weight ω of each third-level indicator. k，j For each second-level indicator A k (k = 1, 2...m), determine the weight ω of each third-level indicator it contains. k,j , satisfying ω k,j >0:

[0033] Step 403: Calculate the score F of the second-level indicator. k ,in, p k The number of second-level indicators is used to determine the evaluation effect of each second-level indicator based on the score.

[0034] Step 404: Determine the weight ω of each second-level indicator. k The evaluation objective is the weight ω of each indicator in the indicator adjacency matrix. k >0, and

[0035] Step 405: Calculate the comprehensive evaluation score F, where,

[0036] In step 401, the third-level index score F is calculated. k,j include:

[0037] The third-level indicators are scored using the following formula:

[0038]

[0039] Where μ1(x), μ2(x), and μ3(x) are the membership functions of the third-level indicators, used to calculate the membership degree of the third-level indicators for good, medium, and poor; a1, a2, and a3 are the numerical values ​​for judging the third-level indicators as good, medium, and poor.

[0040] Meanwhile, the present invention provides a building HVAC system index analysis system, including an index adjacency matrix construction module, an index structure model construction module, an index weight calculation module, and an index score calculation module;

[0041] The indicator adjacency matrix construction module is used to obtain indicator data of building HVAC systems, and to sort out the hierarchical relationship between building HVAC systems using the Interpretive Structure Model to obtain the indicator adjacency matrix.

[0042] The indicator structure model construction module calculates the indicator reachability matrix based on the obtained indicator adjacency matrix and performs hierarchical division of the indicator reachability matrix to establish the indicator structure model.

[0043] The indicator weight calculation module calculates the weights of indicators at each level based on the obtained indicator structure model.

[0044] The indicator score calculation module calculates the scores for each level of indicator based on the weights of the calculated indicators, and conducts a comprehensive evaluation of the building's HVAC system based on the scores of each level of indicator.

[0045] A terminal includes a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to perform steps according to any one of the methods.

[0046] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of any of the methods described.

[0047] The beneficial effects of this invention are as follows: Compared with the prior art, this invention has the following significant advantages: This invention takes the building HVAC system as the overall evaluation target and establishes a multi-level evaluation index system for building HVAC systems, comprising two primary indicators, five secondary indicators, and twenty-two tertiary indicators. The classification is clear, progressive, and comprehensive, making the evaluation results more accurate. In the evaluation process, this invention uses the tertiary quantitative indicators as the underlying basis for the qualitative indicators. The thirty-nine quantitative indicators can be accurately measured, calculated, and statistically analyzed, thereby improving the objectivity of the evaluation method. Simultaneously, the relative importance scale of the judgment matrix is ​​provided during the evaluation process, leaving room for subjective adjustment. This combination of subjective and objective approaches allows the evaluation to objectively reflect the actual situation while also enabling adjustments based on different scenarios. Attached Figure Description

[0048] Figure 1 This is a flowchart of a comprehensive evaluation method for building HVAC systems according to the present invention;

[0049] Figure 2 This is a schematic diagram of the evaluation index system of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0051] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0052] This invention provides a comprehensive evaluation method for building HVAC systems, such as... Figure 1 The diagram shows a flowchart of a comprehensive evaluation method for building HVAC systems according to the present invention. The method includes:

[0053] Step 1: Obtain the building HVAC system index data, and use the Interpretive Structure Model to sort out the hierarchical relationship between the building HVAC system indexes to obtain the index adjacency matrix;

[0054] In one embodiment of the present invention, in step 1, the building HVAC system indicators include energy consumption indicators, environmental protection indicators, economic indicators, thermal comfort indicators, and air quality indicators.

[0055] In one embodiment of the present invention, an interpretive structural model is used to sort out the hierarchical relationship between indicators of building heating, ventilation and air conditioning system. Based on the correlation between indicators, an adjacency matrix is ​​obtained, and the correlation and causality between two indicators are judged, with a value of 0 or 1; 0 represents that there is no direct influence between indicators, i.e., no coupling effect, and 1 represents that there is a direct influence between them, i.e., there is a coupling effect; and a direct relationship matrix (adjacency matrix) A between each indicator is established.

[0056] Step 2: Calculate the reachability matrix of the indicators based on the adjacency matrix of the indicators obtained in Step 1, and divide the reachability matrix of the indicators into levels to establish the indicator structure model.

[0057] In one embodiment of the present invention, the calculation of the index reachability matrix based on the index adjacency matrix obtained in step 1 includes: for Si, Sj∈S, Si and Sj represent indices in the adjacency matrix. If there is any path from Si to Sj, then Si is said to reach Sj.

[0058] In this embodiment, after obtaining the index adjacency matrix, the reachability matrix P = (A + I) is obtained by adding the identity matrix to the index adjacency matrix and performing at most n-fold exponentiation. n+1 =(A+I) n ≠(A+I) n-1 ≠…≠(A+I) 2 ≠(A+I), where A represents the index adjacency matrix, and n represents the number of times the index adjacency matrix plus the identity matrix is ​​multiplied. After the nth power operation, the matrix no longer changes. The reachable matrix P reflects the direct and indirect relationships between the indicators in the system.

[0059] The hierarchical partitioning and structural modeling of the reachability matrix is ​​as follows: The reachability matrix P is divided into two sets: the reachability set R(Si) and the preceding set A(Si). The set of column indicators corresponding to the matrix elements with a value of 1 in the row corresponding to the indicator Si in the reachability matrix represents the indicator that indicator Si can reach, and is represented as follows:

[0060] R(S i )={S j ∈N|m ij =1}

[0061] In the formula, N is the set of all nodes; m ij Let m be the reachability value from node i to node j, where m is the reachability value when node i is associated with node j. ij =1.

[0062] In the reachability matrix, the column corresponding to index Si contains the set of row indices corresponding to matrix elements with a value of 1. This represents the index of the target index, expressed as:

[0063] A(S i )={S j ∈N|m ij =1}

[0064] In the formula, N is the set of all nodes; m ij Let m be the reachability value of the association from node i to node j, where m is the reachability value when node i is associated with node j. ij =1.

[0065] Calculate the intersection of R(Si) and A(Si). The index in R(Si)∩A(Si)=R(Si) is the system's top-level index, i.e., the index of the highest-level target layer. After obtaining the top-level index, temporarily remove the corresponding row of the top-level index in the reachability matrix to obtain the second-level index; remove the corresponding column of the top-level index in the reachability matrix to obtain the third-level index. After the hierarchical level is assigned, a directed graph is used to represent the hierarchical structure of the index structure model, with the top level corresponding to the top-level index, followed by the second-level and third-level indices. This invention divides all index sets into three layers to construct an evaluation index system model, such as... Figure 2 As shown, A is the highest-level, top-level indicator; A1, A2...Am are the second-level indicators contained in the first-level indicator A; Am1,...Ampm are the third-level indicators contained in the second-level indicator Am.

[0066] Step 3: Based on the indicator structure model obtained in Step 2, calculate the weights of each level of indicator.

[0067] In one embodiment of the present invention, step 3, calculating the weights of each level of indicators using the analytic hierarchy process (AHP) includes:

[0068] Step 301: Construct a judgment matrix. The elements in the judgment matrix represent the relative importance of each pair of indicators at the same level. A scale is used to represent the relative importance of the indicators.

[0069] Step 302: Find the largest eigenvalue of the judgment matrix;

[0070] Step 303: Perform a consistency check on the judgment matrix. If the consistency check passes, proceed to step 304. If the consistency check fails, return to step 301 to reconstruct the judgment matrix.

[0071] Step 304: Normalize the eigenvector corresponding to the largest eigenvalue of the judgment matrix to obtain the weight sequence of the same level index to the previous level index.

[0072] In one embodiment of the present invention, the overall evaluation objective of the building HVAC system includes two primary indicators: building HVAC equipment indicators and building HVAC user experience indicators. The building HVAC equipment indicators include two secondary indicators: energy consumption indicators, environmental protection indicators, and economic indicators. The energy consumption indicators include six tertiary indicators: power system, building envelope, daily load rate, daily peak-valley difference rate, cooling water transport coefficient, and system energy efficiency ratio. The environmental protection indicators include five tertiary indicators: refrigerant, carbon emissions, exhaust method, noise control, and vibration reduction method. The economic indicators include four tertiary indicators: initial investment, annual operating cost, service life, and subsequent costs. The building HVAC user experience indicators include two secondary indicators: thermal comfort indicators and air quality indicators. The thermal comfort indicators include three tertiary indicators: temperature, relative humidity, and air velocity. The air quality indicators include four tertiary indicators: fresh air volume, particulate matter concentration, bacterial content, and carbon dioxide concentration.

[0073] Table 1. Indicator System for Building Heating, Ventilation and Air Conditioning Systems

[0074]

[0075] In this embodiment, the weights of each level of indicators are calculated using the analytic hierarchy process as follows:

[0076] A1: Construct a judgment matrix. The elements in the judgment matrix represent the relative importance of each pair of indicators at the same level. By comparing indicators pairwise, the inaccuracy caused by comparing factors with different properties can be reduced. A scale of 1-9 is used to represent the relative importance of indicators.

[0077] A2: Find the largest eigenvalue of the judgment matrix;

[0078] A3: Define the consistency index CI. The consistency test of the judgment matrix includes calculating the test coefficient according to the following formula:

[0079]

[0080] Where, λ max CI is the largest eigenvalue of the judgment matrix, n is the order of the judgment matrix, and RI is the average random consistency index of the judgment matrix, the standard value of which is determined by the order of the judgment matrix; the final test coefficients are obtained from CI and RI. If CR < 0.1, the judgment matrix is ​​considered to have passed the one-time test; if CR ≥ 0.1, the consistency test has not been passed, and the process needs to return to step A1 to reconstruct the judgment matrix.

[0081] A4: After normalizing the eigenvector corresponding to the largest eigenvalue of the judgment matrix, the weight sequence of the same level index to the previous level index can be obtained.

[0082] Table 2: Meaning of each matrix

[0083] Serial Number matrix order Meaning 1 H1 6×6 Energy consumption index AHP judgment matrix 2 H2 5×5 Environmental Indicator AHP Judgment Matrix 3 H3 4×4 Economic Indicator AHP Judgment Matrix 4 H4 3×3 Thermal comfort index AHP judgment matrix 5 H5 4×4 Air Quality Indicator (AHP) Judgment Matrix 6 H6 2×2 AHP Decision Matrix for HVAC Systems

[0084] Table 3 Weight vectors of each indicator

[0085] weight vector Weight vector calculation results ω1 [0.462 0.255 0.140 0.073 0.034.034] ω2 [0.159 0.12 0.06 0.262 0.41] ω3 [0.585 0.184 0.164 0.066] ω4 [0.636 0.260 0.104] ω5 [0.389 0.389 0.154 0.069] ω6 [0.75 0.25]

[0086] Step 4: Based on the weights of each level of indicators calculated in Step 3, calculate the scores of each level of indicators, and conduct a comprehensive evaluation of the building's HVAC system based on the scores of each level of indicators.

[0087] In one embodiment of the present invention, the calculation of scores for each indicator using the fuzzy evaluation method includes:

[0088] Step 401: For the third-level indicator A k，J Calculate the score F of the third-level indicator. k，j The evaluation effect of each third-level indicator is determined based on the score;

[0089] Step 402: Determine the weight ω of each third-level indicator. k,J For each second-level indicator A k (k = 1, 2...m), determine the weight ω of each third-level indicator it contains. k，j , satisfying ω k，j >0;

[0090] Step 403: Calculate the score F of the second-level indicator. k ,in, p k The number of second-level indicators is used to determine the evaluation effect of each second-level indicator based on the score.

[0091] Step 404: Determine the weight ω of each second-level indicator. k The evaluation objective is the weight ω of each indicator in the indicator adjacency matrix.k >0, and

[0092] Step 405: Calculate the comprehensive evaluation score F, where,

[0093] In one embodiment of the present invention, the third-layer score F is calculated in step 401. k,j include:

[0094] The third-level indicators are scored using the following formula:

[0095]

[0096] Where μ1(x), μ2(x), and μ3(x) are the membership functions of the third-level indicators, used to calculate the membership degrees of the third-level indicators for good, average, and poor; a1, a2, and a3 are the numerical values ​​for judging the third-level indicators as good, average, and poor. The membership degrees of each level of indicators and the calculation results are shown in Tables 4 and 5.

[0097] Table 4. Function membership degrees and scores of each indicator

[0098]

[0099]

[0100] Table 5 Scores of Secondary and Primary Indicators

[0101]

[0102] From the overall evaluation score, the building's air conditioning system performs well in various aspects. The energy consumption index score is 81.84, with good performance in daily load rate and daily peak-valley difference rate, but lower scores in power system and annual operating costs. The environmental protection index score is 83.82, with excellent performance in refrigerant and carbon emission indicators, indicating some effectiveness in environmental protection. The economic index score is 86.94, with good initial investment performance, but annual operating costs affect the overall economic efficiency.

[0103] The thermal comfort index was 81.02, indicating that some indicators such as temperature and relative humidity were acceptable, but indicators such as airflow velocity still need improvement, suggesting the need to increase the ventilation rate. The air quality index was 85.06, placing it at a slightly above-average level. Looking at the primary indicators, the HVAC equipment index was 83.81, and the HVAC user experience index was 82.37, indicating that the overall system performance was good, but there is still room for optimization, especially in areas where improvement is needed.

[0104] Meanwhile, this invention provides a comprehensive evaluation method for building HVAC systems, including an indicator adjacency matrix construction module, an indicator structure model construction module, an indicator weight calculation module, and an indicator score calculation module, characterized in that:

[0105] The indicator adjacency matrix construction module is used to obtain indicator data of building HVAC system, and uses the Interpreted Structure Model to sort out the hierarchical relationship between the indicators of building HVAC system to obtain the indicator adjacency matrix.

[0106] The indicator structure model construction module calculates the indicator reachability matrix based on the obtained indicator adjacency matrix and performs hierarchical division of the indicator reachability matrix to establish the indicator structure model.

[0107] The indicator weight calculation module calculates the weights of indicators at each level based on the obtained indicator structure model.

[0108] The indicator score calculation module calculates the scores for each level of indicator based on the weights of the calculated indicators, and conducts a comprehensive evaluation of the building's HVAC system based on the scores of each level of indicator.

[0109] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0110] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0111] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0112] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A comprehensive evaluation method for building HVAC systems, characterized in that, The method includes the following steps: Step 1: Obtain the building HVAC system index data, and use the Interpretive Structure Model to sort out the hierarchical relationship between the building HVAC system indexes to obtain the index adjacency matrix; Step 2: Calculate the reachability matrix of the indicators based on the adjacency matrix of the indicators obtained in Step 1, and perform hierarchical partitioning of the reachability matrix of the indicators to establish the indicator structure model; Step 3: Based on the indicator structure model obtained in Step 2, calculate the weights of each level of indicator; Step 4: Based on the weights of each level of indicators calculated in Step 3, calculate the scores of each level of indicators, and conduct a comprehensive evaluation of the building's HVAC system based on the scores of each level of indicators.

2. The comprehensive evaluation method for building HVAC systems according to claim 1, characterized in that: In step 1, the building HVAC system index data includes energy consumption index, environmental protection index, economic index, thermal comfort index, and air quality index.

3. The comprehensive evaluation method for building HVAC systems according to claim 1, characterized in that: In step 2, the hierarchical partitioning of the reachability matrix and the establishment of the index structure model include: Divide the reachability matrix P into a reachability set R(Si) and a priori set A(Si), calculate the intersection of R(Si) and A(Si), and obtain the highest-order index. The second-level indicators are obtained by removing the corresponding row of the top-level indicator in the reachability matrix, and the third-level indicators are obtained by removing the corresponding column of the top-level indicator in the reachability matrix. A directed graph is used to represent the hierarchical structure of the indicator structure model. The top layer corresponds to the top-level indicator, and the next layers are the second-level indicators and the third-level indicators, respectively.

4. The comprehensive evaluation method for building HVAC systems according to claim 3, characterized in that: The preceding set A(Si) is the set of row indices corresponding to the matrix elements in the column corresponding to index Si in the reachability matrix that contain 1.

5. The comprehensive evaluation method for building HVAC systems according to claim 1, characterized in that: Step 3 involves calculating the weights of each level of indicator, including: Step 301: Construct a judgment matrix. The elements in the judgment matrix represent the relative importance of each pair of indicators at the same level. A scale is used to represent the relative importance of the indicators. Step 302: Find the largest eigenvalue of the judgment matrix; Step 303: Perform a consistency check on the judgment matrix. If the consistency check passes, proceed to step 304. If the consistency check fails, return to step 301 to reconstruct the judgment matrix. Step 304: Normalize the eigenvector corresponding to the largest eigenvalue of the judgment matrix to obtain the weight sequence of the same level index to the previous level index.

6. The comprehensive evaluation method for building HVAC systems according to claim 5, characterized in that: In step 303, the consistency check of the judgment matrix includes calculating the check coefficient according to the following formula: in, RI represents the consistency index; λmax represents the average random consistency index of the judgment matrix; n is the order of the judgment matrix; if CR < 0.1, the judgment matrix is ​​considered to have passed the one-time test; if CR ≥ 0.1, the judgment matrix is ​​considered to have failed the consistency test and needs to be returned to step A1 to reconstruct the judgment matrix.

7. A comprehensive evaluation method for building HVAC systems according to claim 1, 5, or 8, characterized in that: Step 4 involves calculating the scores for each level of indicators, including: Step 401: For the third-level indicator A k,j Calculate the score F of the third-level indicator. k，j The evaluation effect of each third-level indicator is determined based on the score; Step 402: Determine the weight ω of each third-level indicator. k，j For each second-level indicator A k (k = 1, 2...m), determine the weight ω of each third-level indicator it contains. k，j , satisfying ω k,j >0; Step 403: Calculate the score F of the second-level indicator. k ,in, p k The number of second-level indicators is used to determine the evaluation effect of each second-level indicator based on the score. Step 404: Determine the weight ω of each second-level indicator. k The evaluation objective is the weight ω of each indicator in the indicator adjacency matrix. k >0, and Step 405: Calculate the comprehensive evaluation score F, where, 8. A building HVAC index analysis system utilizing the method of any one of claims 1-7, comprising an index adjacency matrix construction module, an index structure model construction module, an index weight calculation module, and an index score calculation module, characterized in that: The indicator adjacency matrix construction module is used to obtain indicator data of building HVAC system, and uses the Interpreted Structure Model to sort out the hierarchical relationship between the indicators of building HVAC system to obtain the indicator adjacency matrix. The indicator structure model construction module calculates the indicator reachability matrix based on the obtained indicator adjacency matrix and performs hierarchical division of the indicator reachability matrix to establish the indicator structure model. The indicator weight calculation module calculates the weights of indicators at each level based on the obtained indicator structure model. The indicator score calculation module calculates the scores for each level of indicator based on the weights of the calculated indicators, and conducts a comprehensive evaluation of the building's HVAC system based on the scores of each level of indicator.

9. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-8.

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