Building energy consumption evaluation and quota determination method based on improved analytic hierarchy process

Abstract

The invention discloses a building energy consumption evaluation and quota determination method based on an improved analytic hierarchy process, and relates to the technical field of building energy conservation, and the method comprises the steps: employing the improved analytic hierarchy process to calculate the weight value of each building energy consumption evaluation index under a building energy consumption evaluation index system; calculating a building energy consumption comprehensive score based on the weight value of each building energy consumption evaluation index, comparing the building energy consumption comprehensive score with a quota threshold value, and judging the grade of the building energy consumption according to a comparison result; calculating an independent quota of each building energy consumption evaluation index at the current time based on a predefined quota value of the building energy consumption evaluation index; and combining the independent quota of each building energy consumption evaluation index with the grade of the building energy consumption. The influence of subjective and objective factors is balanced by improving an analytic hierarchy process, dynamic updating is performed according to historical data through a sliding window mechanism, and the weight coefficient of the influence of each index on the building energy consumption level at the current time is determined.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy conservation, and in particular to a building energy consumption evaluation and quota determination method based on an improved hierarchical analysis method. Background Art

[0002] Building energy consumption refers to the total energy consumed by various types of buildings to maintain their normal functions throughout their lifecycle. This includes electricity, gas, and heat used for heating, cooling, ventilation, lighting, and electrical appliance operation. Energy consumption evaluations help understand a building's energy efficiency and identify weaknesses, thereby guiding energy-saving design and operations management. Energy consumption quotas, on the other hand, establish standard reference values ​​for building energy consumption, setting reasonable energy consumption control targets for buildings of different types, uses, and climate zones.

[0003] The Analytic Hierarchy Process (AHP) is commonly used in building energy consumption evaluation and quota determination. AHP is a systematic, hierarchical, multi-criteria decision-making method. Its core idea is to decompose the decision problem into a hierarchical structure of target layer, criterion layer, and solution layer. A judgment matrix is ​​constructed through pairwise comparison, subjective judgment is converted into quantitative indicators, the relative weight of each factor is calculated, and consistency test is performed to ensure logical rationality. However, the existing technology of building energy consumption evaluation and quota determination based on traditional AHP still has some defects, which are mainly reflected in the following aspects:

[0004] 1. The existing building energy consumption evaluation and quota formulation methods mainly rely on historical data statistics, ignoring subjective factors such as expert experience and equipment efficiency, resulting in one-sided results and a lack of balance between subjective and objective factors.

[0005] 2. Insufficient integration of multi-dimensional indicators. Traditional methods use a single indicator (such as energy consumption per unit area), which cannot reflect the coupled effects of multiple factors such as building characteristics, equipment efficiency, and usage behavior.

[0006] 3. Unable to adapt to newly built buildings or dynamic scenarios. The historical data method cannot cover newly built buildings or scenarios with no data, and lacks dynamic adjustment capabilities.

[0007] 4. The quota determination is not scientific enough, the traditional method ignores the priority of indicators, and it is difficult to guide energy-saving transformation.

[0008] 5. There is a lack of coordination between policies and industry standards, and energy consumption quotas are out of line with policy requirements, making them difficult to implement.

[0009] Currently, no effective solutions have been proposed for the problems in related technologies. Summary of the Invention

[0010] (1) Technical problems solved

[0011] In response to the shortcomings of the existing technology, the present invention provides a building energy consumption evaluation and quota determination method based on an improved hierarchical analysis method, which has the advantage of dynamically adjusting energy consumption indicators according to different building types to adapt to applications in different scenarios, thereby solving the problem of being unable to adapt to new buildings or dynamic scenarios.

[0012] (2) Technical solution

[0013] To achieve the above advantages of dynamically adjusting energy consumption indicators according to different building types to adapt to applications in different scenarios, the specific technical solutions adopted by the present invention are as follows:

[0014] A building energy consumption evaluation and quota determination method based on an improved hierarchical analysis method comprises:

[0015] Construct a building energy consumption evaluation index system and use the improved analytic hierarchy process to calculate the weight value of each building energy consumption evaluation index under the building energy consumption evaluation index system;

[0016] Calculate the comprehensive building energy consumption score based on the weighted values ​​of various building energy consumption evaluation indicators, compare the comprehensive building energy consumption score with the quota threshold, and determine the building energy consumption level based on the comparison results;

[0017] Based on the predefined quota values ​​of building energy consumption evaluation indicators, calculate the independent quotas of various building energy consumption evaluation indicators at the current time;

[0018] Based on the independent quotas of various building energy consumption evaluation indicators and the building energy consumption levels, various building energy consumption evaluation indicators are optimized and adjusted.

[0019] Preferably, the building energy consumption evaluation index system includes a target layer, a criterion layer and an index layer;

[0020] Among them, the target layer is the annual energy consumption limit per unit area of ​​office buildings;

[0021] The criteria layer is divided into building characteristic criteria, equipment efficiency criteria and usage behavior criteria based on the factors affecting energy consumption;

[0022] The indicator layer is the evaluation indicators under the building characteristics criteria, equipment efficiency criteria and usage behavior criteria;

[0023] Evaluation indicators under the building characteristics criteria include the heat transfer coefficient of the envelope and the window-to-wall ratio;

[0024] Evaluation indicators under the equipment efficiency criteria include air conditioning system energy efficiency ratio, lighting power density, elevator energy efficiency rating and renewable energy utilization rate;

[0025] Evaluation indicators under the usage behavior guidelines include equipment operating time, indoor temperature setting and traffic density.

[0026] Preferably, the weight values ​​of various building energy consumption evaluation indicators under the building energy consumption evaluation index system calculated using the improved hierarchical analysis method include:

[0027] Sort each building energy consumption evaluation index according to its importance, obtain the judgment matrix factors at each level based on the importance and construct a judgment matrix;

[0028] Each column of the judgment matrix is ​​normalized, and the weight coefficient of the building energy consumption evaluation index is calculated based on the matrix factors in the normalized judgment matrix. A sliding window mechanism is introduced to dynamically adjust the weight coefficient of the building energy consumption evaluation index.

[0029] The judgment matrix is ​​checked for consistency, and the matrix factors in the judgment matrix are adjusted based on the consistency test results.

[0030] Preferably, each column of the judgment matrix is ​​normalized, and the weight coefficient of the building energy consumption evaluation index is calculated according to the matrix factors in the normalized judgment matrix, including:

[0031] Normalize each column of the judgment matrix to obtain the matrix factor of each item in the normalized judgment matrix:

[0032] Based on the matrix factor of each item, the judgment matrix is ​​added according to each row to obtain a column vector, and the column vector is normalized to obtain a new column vector. Each item in the new column vector is used as the weight coefficient of the building energy consumption evaluation index.

[0033] Preferably, the sliding window mechanism is introduced to dynamically adjust the weight coefficient of the building energy consumption evaluation index, including:

[0034] Set the initial weights and extract historical data from the historical time point to the current time point to construct a historical data matrix;

[0035] The historical data of building energy consumption evaluation indicators in the historical data matrix are standardized to obtain standardized data, and the information entropy and objective weight of the standardized data are calculated using the entropy weight method;

[0036] Combine the subjective weights of historical time points with the objective weights of the current time point to form a fusion weight, and calculate and generate a new weight coefficient based on the fusion weight and standardized data;

[0037] A weight smoothing factor is introduced into the new weight coefficient to avoid sudden changes in the new weight coefficient, and a physical mechanism driving term is introduced to optimize the new weight coefficient.

[0038] Preferably, the expression for optimizing the new weight coefficient by introducing the physical mechanism driving term is:

[0039]

[0040] Where η represents the dynamic learning rate; W j t Indicates the weight of indicator j at the current time point; ΔT j represents the temperature deviation factor; represents the energy consumption score gradient; β represents the smoothing factor; W j t-1 Represents the weight value of indicator j at the previous time point.

[0041] Preferably, performing a consistency check on the judgment matrix and adjusting the matrix factors in the judgment matrix based on the consistency check result includes:

[0042] Calculate the maximum eigenvalue of the judgment matrix, and calculate the consistency index of the judgment matrix based on the maximum eigenvalue;

[0043] Based on the consistency index of the judgment matrix and the predefined average random consistency index, the random consistency ratio of the judgment matrix is ​​calculated;

[0044] The random consistency ratio is compared with the preset threshold. If the random consistency ratio is less than the preset threshold, it means that the judgment matrix has satisfactory consistency. Otherwise, it means that the judgment matrix does not have satisfactory consistency. The matrix factors in the judgment matrix are adjusted until the judgment matrix reaches satisfactory consistency.

[0045] Preferably, the calculation formula for the maximum eigenvalue of the judgment matrix is:

[0046]

[0047] The calculation formula of the consistency index of the judgment matrix is:

[0048]

[0049] Where λ max represents the maximum eigenvalue of the judgment matrix; n represents the number of matrix factors; ω i represents the weight coefficient of the i-th building energy consumption evaluation index; D represents the judgment matrix; CI represents the consistency index of the judgment matrix.

[0050] Preferably, the building energy consumption comprehensive score is calculated based on the weighted values ​​of various building energy consumption evaluation indicators, and the building energy consumption comprehensive score is compared with the quota threshold. The building energy consumption level is determined according to the comparison result, including:

[0051] Determine the indicator type of the current building energy consumption evaluation indicator based on the weight value of each building energy consumption evaluation indicator, and the indicator type includes positive indicators and negative indicators;

[0052] Calculate the standardized scores of positive and negative indicators separately, and integrate the standardized scores to calculate the comprehensive building energy consumption score;

[0053] Determine the guidance score and constraint score based on the predefined building energy consumption quota corresponding to the building type, and compare the comprehensive building energy consumption score with the guidance score and constraint score respectively;

[0054] If the comprehensive score of building energy consumption is greater than the guidance score, it means that the building energy consumption is at an advanced level. If the comprehensive score of building energy consumption is between the guidance score and the constraint score, it means that the building energy consumption is at a baseline level. If the comprehensive score of building energy consumption is less than the constraint score, it means that the building energy consumption is at a constrained level.

[0055] Preferably, the calculation formula for the comprehensive building energy consumption score is:

[0056]

[0057] Where, S represents the comprehensive score of building energy consumption; S m Indicates the standardized score of positive indicators; S k represents the standardized score of negative indicators; M represents the total number of positive indicators; K represents the total number of negative indicators; m represents the number of positive indicators; k represents the number of negative indicators; Represents the weight value of indicator m at time point t; Represents the weight value of indicator k at time point t.

[0058] (3) Beneficial effects

[0059] Compared with the existing technology, the present invention provides a building energy consumption evaluation and quota determination method based on the improved hierarchical analysis method, which has the following beneficial effects:

[0060] (1) The present invention balances the influence of subjective and objective factors by improving the hierarchical analysis method, dynamically updates historical data through a sliding window mechanism, determines the weight coefficient of the impact of various indicators on the building energy consumption level at the current time, and coordinates with industry standards to determine the comprehensive score of building energy consumption, thereby achieving scientific quantification and multi-dimensional integration of building energy consumption levels, and providing an effective evaluation method for building energy consumption levels.

[0061] (2) In order to avoid extreme situations, the present invention introduces physical mechanism driving items to optimize the weights during the dynamic adjustment of indicators to ensure that the weights have good stability.

[0062] (3) The present invention uses the improved hierarchical analysis method and the building energy consumption quota values ​​of industry standards to determine the sub-item quotas of various indicators, which can clarify the priority of building energy consumption optimization, flexibly optimize the energy consumption of various indicators, and realize refined management of building energy consumption.

[0063] (4) The present invention can dynamically adjust energy consumption indicators according to different building types to adapt to applications in different scenarios, thereby providing an efficient, accurate and feasible technical tool for building energy conservation management. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 The present invention is a flowchart of a method for evaluating and determining building energy consumption based on an improved analytic hierarchy process. DETAILED DESCRIPTION

[0066] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. By referring to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0067] According to an embodiment of the present invention, a building energy consumption evaluation and quota determination method based on an improved analytic hierarchy process is provided.

[0068] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to the method for evaluating and determining building energy consumption and quota based on the improved analytic hierarchy process according to an embodiment of the present invention, the method includes:

[0069] S1. Construct a building energy consumption evaluation index system and use the improved hierarchical analysis method to calculate the weight value of each building energy consumption evaluation index under the building energy consumption evaluation index system.

[0070] Among them, the building energy consumption evaluation index system includes the target layer, the criterion layer and the index layer;

[0071] The target layer is determined as the annual energy consumption limit per unit area of ​​the office building;

[0072] The criteria layer is divided into three categories of criteria based on factors affecting energy consumption, including building characteristics, equipment efficiency, and usage behavior;

[0073] The indicator layer is a detailed indicator under each criterion layer; the evaluation indicators under the building characteristics criterion include the heat transfer coefficient of the envelope structure and the window-to-wall ratio; the evaluation indicators under the equipment efficiency criterion include the energy efficiency ratio of the air-conditioning system, the lighting power density, the elevator energy efficiency level, and the renewable energy utilization rate; the evaluation indicators under the usage behavior criterion include the equipment operating time, indoor temperature setting, and pedestrian flow density.

[0074] Among them, the weight values ​​of various building energy consumption evaluation indicators under the building energy consumption evaluation index system calculated using the improved hierarchical analysis method include:

[0075] Sort each building energy consumption evaluation index according to its importance, obtain the judgment matrix factors at each level based on the importance and construct a judgment matrix;

[0076] Each column of the judgment matrix is ​​normalized, and the weight coefficient of the building energy consumption evaluation index is calculated according to the matrix factors in the normalized judgment matrix. A sliding window mechanism is introduced to dynamically adjust the weight coefficient of the building energy consumption evaluation index.

[0077] Among them, each column of the judgment matrix is ​​normalized, and the weight coefficient of the building energy consumption evaluation index is calculated according to the matrix factors in the normalized judgment matrix, including:

[0078] Normalize each column of the judgment matrix to obtain the matrix factor of each item in the normalized judgment matrix:

[0079] Based on the matrix factor of each item, the judgment matrix is ​​added according to each row to obtain a column vector, and the column vector is normalized to obtain a new column vector. Each item in the new column vector is used as the weight coefficient of the building energy consumption evaluation index.

[0080] Among them, the sliding window mechanism is introduced to dynamically adjust the weight coefficients of building energy consumption evaluation indicators, including:

[0081] Set the initial weights and extract historical data from the historical time point to the current time point to construct a historical data matrix;

[0082] The historical data of building energy consumption evaluation indicators in the historical data matrix are standardized to obtain standardized data, and the information entropy and objective weight of the standardized data are calculated using the entropy weight method;

[0083] Combine the subjective weights of historical time points with the objective weights of the current time point to form a fusion weight, and calculate and generate a new weight coefficient based on the fusion weight and standardized data;

[0084] A weight smoothing factor is introduced into the new weight coefficient to avoid sudden changes in the new weight coefficient, and a physical mechanism driving term is introduced to optimize the new weight coefficient.

[0085] The judgment matrix is ​​checked for consistency, and the matrix factors in the judgment matrix are adjusted based on the consistency test results.

[0086] The consistency test of the judgment matrix and the adjustment of the matrix factors in the judgment matrix based on the consistency test result include:

[0087] Calculate the maximum eigenvalue of the judgment matrix, and calculate the consistency index of the judgment matrix based on the maximum eigenvalue;

[0088] Based on the consistency index of the judgment matrix and the predefined average random consistency index, the random consistency ratio of the judgment matrix is ​​calculated;

[0089] The random consistency ratio is compared with the preset threshold. If the random consistency ratio is less than the preset threshold, it means that the judgment matrix has satisfactory consistency. Otherwise, it means that the judgment matrix does not have satisfactory consistency. The matrix factors in the judgment matrix are adjusted until the judgment matrix reaches satisfactory consistency.

[0090] It should be noted that the hierarchical analysis method is a systematic and hierarchical multi-criteria decision-making method. Its core idea is to decompose the decision-making problem into a hierarchical structure including the target layer, the criterion layer and the solution layer, construct a judgment matrix through pairwise comparison, convert subjective judgment into quantitative indicators, calculate the relative weight of each factor, and ensure logical rationality through consistency test.

[0091] The present invention improves the analytic hierarchy process and introduces it into the building energy consumption evaluation process, combines subjective expert experience with objective industry standard data, and introduces a sliding window mechanism to dynamically adjust the weights, thereby effectively making up for the shortcomings of traditional methods that rely on single data.

[0092] In order to facilitate understanding of the above technical solution of the present invention, the following is a detailed description of the present invention's actual process of "using the improved hierarchical analysis method to calculate the weight values ​​of various building energy consumption evaluation indicators under the building energy consumption evaluation index system", which specifically includes:

[0093] Step 1: Construct a building energy consumption evaluation index judgment matrix;

[0094] Step 2: Calculate the weight coefficient of building energy consumption evaluation index;

[0095] Step 3: Conduct consistency test on the building energy consumption evaluation index judgment matrix;

[0096] Step 4: Based on historical data, introduce a sliding window mechanism to dynamically adjust the weight coefficient.

[0097] It should be noted that to evaluate the energy consumption level of a building, it is necessary to judge the importance of each indicator in the constructed building energy consumption index evaluation system, that is, to calculate and analyze the weight of each indicator. Because there are qualitative indicators in the evaluation indicators that cannot be quantitatively measured by data, the present invention adopts a hierarchical analysis method that combines qualitative and quantitative methods to analyze the listed evaluation indicators and determine the weight distribution of each indicator under the building energy consumption evaluation index evaluation system.

[0098] Step 1: Constructing a judgment matrix of building energy consumption evaluation indicators includes: comparing the evaluation indicators under each evaluation criterion in pairs, ranking the importance of achieving low energy consumption in buildings according to each evaluation indicator, and giving each level of judgment matrix factors according to the importance, to construct a judgment matrix D. The present invention relies on the group decision-making ability of experts in the carbon field and the professional experience and knowledge of each expert to judge the relative importance of the indicators. Based on the judgment matrix factors and their definitions, the factors of the same level are compared with each other in pairs to determine the order of importance between the factors, and a qualitative judgment is given on the relative importance of each factor at each level, wherein the expression of the judgment matrix D is:

[0099]

[0100] The judgment matrix D satisfies the constraints: d ij =1 / d ji , d ij >0, where d ij is the relative “importance” judgment value between building energy consumption evaluation index i and building energy consumption evaluation index j, and the order n is the total number of building energy consumption evaluation indicators, n = 9.

[0101] Step 2: Calculate the weight coefficient of building energy consumption evaluation index including:

[0102] Normalize each column of the judgment matrix D. After normalization, each factor μ in the matrix ij :

[0103]

[0104] The judgment matrix D is further added to each row to obtain an n×1 column vector (when n=9, it is an n×1 column vector). Each item in the column vector is defined as β i :

[0105]

[0106] Normalize the column vector to get a new n×1 column vector (when n=9, it is an n×1 column vector). Each item in the new column vector is defined as ω i :

[0107]

[0108] Among them, ω i The relative weight coefficients of each evaluation index under this evaluation criterion are:

[0109] W=(ω1,ω2,…,ω n ) T ;

[0110] Where, d ij It represents the relative “importance” judgment value between building energy consumption evaluation index i and building energy consumption evaluation index j, and n represents the total number of building energy consumption evaluation indicators; d lj Indicates the relative “importance” judgment value between building energy consumption evaluation index l and building energy consumption evaluation index j; μ ij Represents each factor in the normalized matrix; β i Represents each item in the column vector; ω i Represents each item in the new column vector, that is, the relative weight coefficient of each evaluation indicator under the evaluation criteria; W represents the indicator weight coefficient generated by the traditional hierarchical analysis method; T represents the historical data of the past T time points.

[0111] Step 3: Conduct consistency test on building energy consumption evaluation index judgment matrix, including:

[0112] Calculate the maximum eigenvalue λ of the judgment matrix D max :

[0113]

[0114] Calculate the consistency index CI of the judgment matrix D:

[0115]

[0116] Where λ max represents the maximum eigenvalue of the judgment matrix; n represents the total number of building energy consumption evaluation indicators; ω i represents the weight coefficient of the i-th building energy consumption evaluation index; D represents the judgment matrix; CI represents the consistency index of the judgment matrix.

[0117] The consistency test is used to measure the quality of the subjectively determined judgment matrix D and to judge the rationality of the weight coefficient.

[0118] The consistency test for the building energy consumption evaluation index judgment matrix also includes: introducing the average random consistency index RI for the multi-order judgment matrix D and defining the random consistency ratio CR = CI / RI. For multi-order judgment matrices, that is, when there are many similar elements, the average random consistency index of the judgment matrix is ​​also required.

[0119] When the random consistency ratio CR is less than 0.10, the determined judgment matrix D is considered to have satisfactory consistency, that is, the importance of each evaluation index is relatively reasonable; otherwise, it is considered that the obtained judgment matrix D has unreasonable evaluation indicators, and the corresponding factors of the obtained judgment matrix D need to be adjusted until satisfactory consistency is achieved.

[0120] Step 4: Based on historical data, introduce a sliding window mechanism to dynamically adjust the weight coefficients, including:

[0121] 1. Sliding window initialization:

[0122] The indicator weight coefficient W generated by the traditional hierarchical analysis method is set as the initial weight W (0) ;

[0123] Construct the data matrix W from time point t-T+1 to t t :

[0124] W=[D t-T+1 ,D t-T+2 ,…,D t ] T ;

[0125] In the formula, t represents the current time point, T represents the historical data of the past T time points, and D t Represents the indicator dataset recorded at time point y, with the dimension being the number of evaluation indicators n, D t-T+1 represents the indicator dataset recorded at time point t-T+1, D t-T+1 Represents the indicator dataset recorded at time point t-T+2.

[0126] Normalize the data of each evaluation index j in the window:

[0127]

[0128] Among them, the mean μ j and standard deviation σ j The calculation formula is as follows:

[0129]

[0130] Where μ j represents the mean; σ j represents the standard deviation; k represents a time point in a time window; d kj represents the data of indicator j at time point k; d tj Represents the data of indicator j at time point t; Represents the data normalized value of indicator j within a certain time window.

[0131] 2. Calculate objective weights using the entropy weight method based on historical data:

[0132] Entropy weight method to calculate information entropy E j and objective weight W j obj ,Information entropy can measure the volatility of indicators. The smaller its value is, the higher the weight of the indicator is;

[0133]

[0134] Where p kj E represents the probability of the occurrence of the data of indicator j at time point k; j represents information entropy; W j obj Represents objective weight.

[0135] 3. Superposition of subjective and objective weights:

[0136] The weight W of the previous time point (t-1) and the objective weight W at the current time point obj Combined to form weight W f , while retaining historical weights, introducing objective weights driven by current data:

[0137] W j f =αW j t-1 +(1-α)W j obj ;

[0138] Where α represents the subjective weight attenuation coefficient, α∈[0,1]; W j t-1 Indicates the weight value of indicator j at the previous time point; W j obj Represents the objective weight value of indicator j at the current time point.

[0139] 4. Sliding window generates new weight coefficients:

[0140]

[0141] Where W j t Indicates the weight value of indicator j at the current time point; W j f W represents the fusion weight of data j at the current time point; t Indicates the weight value of each indicator; Indicates the weight value of indicator n.

[0142] 5. Based on historical data, the sliding window mechanism is introduced to dynamically adjust the weight coefficients. This also includes the introduction of a weight smoothing factor β to make weight changes smoother, avoid weight mutations, and maintain model stability:

[0143] W t =βW t-1 +(1-β)W t ;

[0144] Where W t Indicates the weight at the current time point; W t-1 represents the weight at the previous time point; β represents the weight smoothing factor.

[0145] 6. Physical drive weight correction based on temperature deviation factor:

[0146] As global warming becomes increasingly serious, extreme weather events occur more frequently, with extreme high temperatures being particularly severe. To prevent weight stability from deteriorating under extreme temperature conditions, a physical mechanism-driven term is introduced to optimize the weights:

[0147]

[0148] Where η represents the dynamic learning rate, which is calculated by the building thermal inertia coefficient: (U avg represents the average heat transfer coefficient of the enclosure structure); e represents the natural logarithm; ΔT j represents the temperature deviation factor, (T GB50189 The reference temperature is specified in the national standard GB50189); Indicates the indoor temperature at time t; represents the energy consumption score gradient, (S k is the standardized score of indicator k); W j t W represents the weight of indicator j at the current time point; j t-1 Represents the weight value of indicator j at the previous time point.

[0149] S2. Calculate the comprehensive building energy consumption score based on the weighted values ​​of various building energy consumption evaluation indicators, compare the comprehensive building energy consumption score with the quota threshold, and determine the building energy consumption level based on the comparison results.

[0150] Among them, the comprehensive building energy consumption score is calculated based on the weight value of each building energy consumption evaluation index, the comprehensive building energy consumption score is compared with the quota threshold, and the building energy consumption level is determined according to the comparison result.

[0151] Determine the indicator type of the current building energy consumption evaluation indicator based on the weight value of each building energy consumption evaluation indicator, and the indicator type includes positive indicators and negative indicators;

[0152] Calculate the standardized scores of positive and negative indicators separately, and integrate the standardized scores to calculate the comprehensive building energy consumption score.

[0153] It should be noted that if the indicator is a positive indicator, that is, the larger the quantitative value of the indicator, the better, then the standardized score of the indicator is:

[0154] S m = actual value / industry guidance value (m = 1, 2 ..., M < n, M is the number of positive indicators);

[0155] If the indicator is a reverse indicator, that is, the smaller the quantitative value of the indicator, the better, then the standardized score of the indicator is:

[0156] S k =Industry guidance value / actual value (k=1,2……,K<n, K is the number of reverse indicators);

[0157] It should be noted that in actual application, the positive and negative indicators should be judged according to the building type and location. For example, the positive indicators listed include the energy efficiency ratio of the air-conditioning system, the energy efficiency level of the elevator, and the utilization rate of renewable energy, that is, M = 3; the negative indicators listed include the heat transfer coefficient of the building envelope, the window-to-wall ratio, the lighting power density, the pedestrian flow density, the indoor temperature setting value, and the equipment operating time, that is, K = 6;

[0158] The calculation formula for the comprehensive building energy consumption score is:

[0159]

[0160] Where, S represents the comprehensive score of building energy consumption; S m Indicates the standardized score of positive indicators; S k represents the standardized score of negative indicators; M represents the total number of positive indicators; K represents the total number of negative indicators; m represents the number of positive indicators; k represents the number of negative indicators; Represents the weight value of indicator m at time point t; Represents the weight value of indicator k at time point t.

[0161] Determine the guidance score and constraint score based on the predefined building energy consumption quota corresponding to the building type, and compare the comprehensive building energy consumption score with the guidance score and constraint score respectively;

[0162] If the comprehensive score of building energy consumption is greater than the guidance score, it means that the building energy consumption is at an advanced level. If the comprehensive score of building energy consumption is between the guidance score and the constraint score, it means that the building energy consumption is at a baseline level. If the comprehensive score of building energy consumption is less than the constraint score, it means that the building energy consumption is at a constrained level.

[0163] It should be noted that the guiding score T1 and the constraint score T2 are determined based on the building energy consumption quota in the industry standard corresponding to the building type, and the level of the actual building energy consumption comprehensive score is determined;

[0164] T1 = industry standard guide value / industry standard benchmark value;

[0165] T2 = industry standard guidance value / industry standard constraint value;

[0166] Advanced level: comprehensive score S>T1;

[0167] Baseline level: T2<comprehensive score S<T1;

[0168] Constraint level: comprehensive score S<T2;

[0169] For example, since this office building is located in Province XX and is a public building, according to the standards listed in the "Energy Consumption Quotas and Calculation Methods for Centralized Office Areas of Public Institutions" issued by Province XX, the guiding score T1 is determined to be 0.825 and the constraint score T2 is determined to be 0.673. The actual building energy consumption comprehensive score level is determined as follows:

[0170] Advanced level: comprehensive score S>0.825;

[0171] Baseline level: 0.673<comprehensive score S<0.825;

[0172] Constraint level: comprehensive score S < 0.673;

[0173] S3. Based on the predefined quota values ​​of the building energy consumption evaluation indicators, calculate the independent quotas of various building energy consumption evaluation indicators at the current time.

[0174] It should be noted that the weight values ​​of various indicators at the current time are obtained Calculate the independent quotas X for each indicator at the current time using the quota value C of the building energy consumption index in the "Energy Consumption Quota and Calculation Method for Centralized Office Areas of Public Institutions" i ;

[0175]

[0176] Where, X i Indicates the independent quotas of various indicators at the current time.

[0177] S4. Optimize and adjust the energy consumption evaluation indicators of various buildings based on their independent quotas and the building energy consumption levels.

[0178] It should be noted that, depending on the office building's energy consumption level, various building energy consumption indicators are adjusted based on the indicator weights and independent quotas for each indicator. If the building's comprehensive energy consumption score is less than the constraint score, an immediate renovation plan should be developed to reduce the building's energy consumption level. If the building's comprehensive energy consumption score is between the baseline score and the advanced score, no urgent intervention is required, but a medium- to long-term plan should be developed to guide the actual building's comprehensive energy consumption score closer to 1.

[0179] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A building energy consumption evaluation and quota determination method based on improved analytic hierarchy process, characterized in that: The method includes: Construct a building energy consumption evaluation index system and use the improved analytic hierarchy process to calculate the weight value of each building energy consumption evaluation index under the building energy consumption evaluation index system; Calculate the comprehensive building energy consumption score based on the weighted values ​​of various building energy consumption evaluation indicators, compare the comprehensive building energy consumption score with the quota threshold, and determine the building energy consumption level based on the comparison results; Based on the predefined quota values ​​of building energy consumption evaluation indicators, calculate the independent quotas of various building energy consumption evaluation indicators at the current time; Based on the independent quotas of various building energy consumption evaluation indicators and the building energy consumption levels, various building energy consumption evaluation indicators are optimized and adjusted.

2. The building energy consumption evaluation and quota determination method based on the improved analytic hierarchy process according to claim 1 is characterized in that: The building energy consumption evaluation index system includes a target layer, a criterion layer and an index layer; The target layer is the annual energy consumption limit per unit area of ​​office buildings; The criterion layer is divided into building characteristic criteria, equipment efficiency criteria and usage behavior criteria according to energy consumption influencing factors; The index layer is the evaluation index under the building characteristic criteria, equipment efficiency criteria and usage behavior criteria; Evaluation indicators under the building characteristics criteria include the heat transfer coefficient of the envelope and the window-to-wall ratio; Evaluation indicators under the equipment efficiency criteria include air conditioning system energy efficiency ratio, lighting power density, elevator energy efficiency rating and renewable energy utilization rate; Evaluation indicators under the usage behavior guidelines include equipment operating time, indoor temperature setting and traffic density.

3. The building energy consumption evaluation and quota determination method based on the improved analytic hierarchy process according to claim 1 is characterized in that: The weight values ​​of various building energy consumption evaluation indicators under the building energy consumption evaluation index system calculated by the improved hierarchical analysis method include: Sort each building energy consumption evaluation index by importance, obtain the judgment matrix factors at each level based on the importance, and construct a judgment matrix; Each column of the judgment matrix is ​​normalized, and the weight coefficient of the building energy consumption evaluation index is calculated based on the matrix factors in the normalized judgment matrix. A sliding window mechanism is introduced to dynamically adjust the weight coefficient of the building energy consumption evaluation index. The judgment matrix is ​​tested for consistency, and the matrix factors in the judgment matrix are adjusted based on the consistency test results.

4. A building energy consumption evaluation and quota determination method based on improved analytic hierarchy process according to claim 3, characterized in that: Normalizing each column of the judgment matrix and calculating the weight coefficient of the building energy consumption evaluation index according to the matrix factors in the normalized judgment matrix includes: Normalize each column of the judgment matrix to obtain the matrix factor of each item in the normalized judgment matrix: Based on the matrix factor of each item, the judgment matrix is ​​added according to each row to obtain a column vector, and the column vector is normalized to obtain a new column vector. Each item in the new column vector is used as the weight coefficient of the building energy consumption evaluation index.

5. The building energy consumption evaluation and quota determination method based on the improved analytic hierarchy process according to claim 3 is characterized in that: The sliding window mechanism is introduced to dynamically adjust the weight coefficients of building energy consumption evaluation indicators, including: Set the initial weights and extract historical data from the historical time point to the current time point to construct a historical data matrix; The historical data of building energy consumption evaluation indicators in the historical data matrix are standardized to obtain standardized data, and the information entropy and objective weight of the standardized data are calculated using the entropy weight method; Combine the subjective weights of historical time points with the objective weights of the current time point to form a fusion weight, and calculate and generate a new weight coefficient based on the fusion weight and standardized data; A weight smoothing factor is introduced into the new weight coefficient to avoid sudden changes in the new weight coefficient, and a physical mechanism driving term is introduced to optimize the new weight coefficient.

6. A building energy consumption evaluation and quota determination method based on improved analytic hierarchy process according to claim 5, characterized in that: The expression for optimizing the new weight coefficient by introducing the physical mechanism driving term is: Where η represents the dynamic learning rate; W j t Indicates the weight of indicator j at the current time point; ΔT j represents the temperature deviation factor; represents the energy consumption score gradient; β represents the smoothing factor; W j t-1 Represents the weight value of indicator j at the previous time point.

7. The building energy consumption evaluation and quota determination method based on the improved analytic hierarchy process according to claim 3 is characterized in that: The performing consistency test on the judgment matrix and adjusting the matrix factors in the judgment matrix based on the consistency test result includes: Calculate the maximum eigenvalue of the judgment matrix, and calculate the consistency index of the judgment matrix based on the maximum eigenvalue; Based on the consistency index of the judgment matrix and the predefined average random consistency index, the random consistency ratio of the judgment matrix is ​​calculated; The random consistency ratio is compared with the preset threshold. If the random consistency ratio is less than the preset threshold, it means that the judgment matrix has satisfactory consistency. Otherwise, it means that the judgment matrix does not have satisfactory consistency. The matrix factors in the judgment matrix are adjusted until the judgment matrix reaches satisfactory consistency.

8. The building energy consumption evaluation and quota determination method based on the improved analytic hierarchy process according to claim 7 is characterized in that: The calculation formula of the maximum eigenvalue of the judgment matrix is: The calculation formula of the consistency index of the judgment matrix is: Where λ max represents the maximum eigenvalue of the judgment matrix; n represents the number of matrix factors; ω i represents the weight coefficient of the i-th building energy consumption evaluation index; D represents the judgment matrix; CI represents the consistency index of the judgment matrix.

9. The building energy consumption evaluation and quota determination method based on the improved analytic hierarchy process according to claim 1 is characterized in that: The building energy consumption comprehensive score is calculated based on the weighted values ​​of various building energy consumption evaluation indicators, and the building energy consumption comprehensive score is compared with the quota threshold. The building energy consumption level is determined according to the comparison result, including: Determining the indicator type of the current building energy consumption evaluation indicator based on the weight value of each building energy consumption evaluation indicator, wherein the indicator type includes positive indicators and negative indicators; Calculate the standardized scores of positive and negative indicators separately, and integrate the standardized scores to calculate the comprehensive building energy consumption score; Determine the guidance score and constraint score based on the predefined building energy consumption quota corresponding to the building type, and compare the comprehensive building energy consumption score with the guidance score and constraint score respectively; If the comprehensive score of building energy consumption is greater than the guidance score, it means that the building energy consumption is at an advanced level. If the comprehensive score of building energy consumption is between the guidance score and the constraint score, it means that the building energy consumption is at a baseline level. If the comprehensive score of building energy consumption is less than the constraint score, it means that the building energy consumption is at a constrained level.

10. A building energy consumption evaluation and quota determination method based on improved analytic hierarchy process according to claim 9, characterized in that: The calculation formula for the comprehensive building energy consumption score is: Where, S represents the comprehensive score of building energy consumption; S m Indicates the standardized score of positive indicators; S k represents the standardized score of negative indicators; M represents the total number of positive indicators; K represents the total number of negative indicators; m represents the number of positive indicators; k represents the number of negative indicators; Represents the weight value of indicator m at time point t; Represents the weight value of indicator k at time point t.

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