CN112633762A

CN112633762A - Building energy efficiency obtaining method and equipment

Info

Publication number: CN112633762A
Application number: CN202011637624.6A
Authority: CN
Inventors: 胡梦锦; 魏孟举; 刘雪飞; 刘钊; 王永利; 刘晨; 周泯含; 杨洋; 赵贤龙; 李嘉恒
Original assignee: State Grid Corp of China SGCC; Economic and Technological Research Institute of State Grid Hebei Electric Power Co Ltd
Current assignee: State Grid Corp of China SGCC; Economic and Technological Research Institute of State Grid Hebei Electric Power Co Ltd
Priority date: 2020-12-31
Filing date: 2020-12-31
Publication date: 2021-04-09

Abstract

The invention is suitable for the technical field of computers, and provides a building energy efficiency obtaining method and equipment, wherein the method comprises the following steps: collecting data of a plurality of preset energy efficiency indexes of a target building; determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes; determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm; and determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index. The invention can improve the accuracy of building energy efficiency acquisition.

Description

Building energy efficiency obtaining method and equipment

Technical Field

The invention belongs to the technical field of computers, and particularly relates to a building energy efficiency obtaining method and equipment.

Background

With the rapid development of social economy and science and technology, people's awareness of environmental protection and energy conservation is gradually improved, and more attention is paid to the effective utilization of energy. Accordingly, the concept of the integrated energy system is receiving attention, and buildings based on the integrated energy system are increasing. The building energy efficiency acquisition based on the comprehensive energy system has great effects on the design of a building planning stage, the operation management of energy equipment in a building operation stage and the like.

At present, the energy efficiency index and the weight are usually set by manual experience, and the acquisition of the energy efficiency of the building is realized by combining the data of the building. However, the subjectivity of the manual experience is strong, so that the accuracy of the acquired building energy efficiency is poor.

Disclosure of Invention

In view of this, the embodiment of the invention provides a building energy efficiency obtaining method and device, so as to solve the problem that building energy efficiency obtaining accuracy is poor in the prior art.

A first aspect of an embodiment of the present invention provides a method for acquiring building energy efficiency, including:

collecting data of a plurality of preset energy efficiency indexes of a target building;

determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes;

determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm;

and determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index.

A second aspect of an embodiment of the present invention provides a building energy efficiency obtaining apparatus, including:

the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring data of a plurality of preset energy efficiency indexes of a target building;

the processing module is used for determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes and determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes;

the processing module is further configured to determine a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm;

the processing module is further configured to determine an energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index.

A third aspect of embodiments of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to the first aspect when executing the computer program.

A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, which stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method according to the first aspect.

Compared with the prior art, the embodiment of the invention has the following beneficial effects: collecting data of a plurality of preset energy efficiency indexes of a target building; determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes; determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm; the energy efficiency value of the target building is determined according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index, the information entropy can be considered in the building energy efficiency obtaining process, the weighted value determined by the information entropy and the weighted value obtained by the hierarchical analysis algorithm are used for jointly determining the weighted value of each preset energy efficiency index, the objectivity of the information entropy and the subjectivity of the hierarchical analysis algorithm are combined, the weighted value of each preset energy efficiency index is more accurate, and the building energy efficiency obtaining accuracy is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a schematic structural diagram of a building energy efficiency acquisition system according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of a building energy efficiency obtaining method according to an embodiment of the present invention;

FIG. 3 is a flowchart illustrating a building energy efficiency obtaining method according to another embodiment of the present invention;

FIG. 4 is a flowchart illustrating a building energy efficiency obtaining method according to another embodiment of the present invention;

FIG. 5 is a flow chart of an implementation of an example embodiment of the present invention;

fig. 6 is a schematic structural diagram of a building energy efficiency obtaining apparatus according to an embodiment of the present invention;

fig. 7 is a schematic diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

In order to explain the technical means of the present invention, the following description will be given by way of specific examples.

With the rapid development of social economy and science and technology, people's awareness of environmental protection and energy conservation is gradually improved, more and more attention is paid to effective utilization of energy, and continuous energy waste gradually leads to energy crisis and serious environmental pollution. The energy development also faces the serious challenges of unreasonable energy consumption structure, mismatching energy supply and demand distribution, non-fusion of various energy systems, lack of reasonable investment return modes and the like, and the traditional micro-grid can not solve various problems at present. Therefore, how to distribute and efficiently utilize energy becomes a problem that needs to be regarded as important, which makes the concept of the integrated energy system increasingly focused. The comprehensive energy system has many research achievements in the aspects of modeling, planning, operation optimization and the like, and some practical buildings of the comprehensive energy system are developed, but a gap exists in the aspect of energy efficiency acquisition. In order to enable the building of the comprehensive energy system to play the greatest role in the development process of the comprehensive energy system, the energy efficiency of the building is essential. For example, in the building planning stage of building the integrated energy system project, in order to solve the problems of how to investment benefit ratio of each scheme, how much environmental influence is caused, which energy devices are adopted to make the integrated efficiency highest, and the like of the existing plurality of planning and building schemes, the energy efficiency is required to be obtained to obtain specific direct information or indirect information, and the most scientific and objective analysis decision is made in an auxiliary manner. For another example, in the operation stage after building construction is completed, how to manage the operation of the energy device to achieve maximum energy saving needs to acquire the building energy efficiency and perform control and adjustment according to the building energy efficiency.

The embodiment of the invention collects data of a plurality of preset energy efficiency indexes of a target building; determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes; determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm; the energy efficiency value of the target building is determined according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index, the information entropy can be considered in the building energy efficiency obtaining process, the weighted value determined by the information entropy and the weighted value obtained by the hierarchical analysis algorithm are used for jointly determining the weighted value of each preset energy efficiency index, the objectivity of the information entropy and the subjectivity of the hierarchical analysis algorithm are combined, the weighted value of each preset energy efficiency index is more accurate, and the building energy efficiency obtaining accuracy is improved.

Fig. 1 is a schematic structural diagram of a building energy efficiency acquisition system according to an embodiment of the present invention. As shown in fig. 1, the system may include, but is not limited to, at least one of: energy consuming devices 11 of the building deployment, devices 12 for storing building data, third party data platforms 13, electronic devices 14 and user terminals 15.

Energy consuming devices 11 deployed in a building may include, but are not limited to, at least one of the following: photovoltaic equipment, electrical equipment, entrance guard's equipment, supervisory equipment, air conditioner, elevator, lighting apparatus, fire-fighting equipment etc.. The devices 12 that store building data may include, but are not limited to, at least one of the following: computers, cell phones, servers, etc., for example, building data may be stored on the device by building planning personnel or building management personnel. The third party data platform 13 may include, but is not limited to, a building data management platform, a third party data search platform, and the like. It should be noted that, for a building which is already built and is in an operating stage, data can be acquired by communicating with the energy consumption devices 11 deployed in the building, while when energy efficiency of the building in a planning stage is acquired, data cannot be acquired by communicating with the energy consumption devices 11 deployed in the building, and data such as energy consumption and an operating mode of each device can be acquired by the device 12 for storing building data and/or the third-party data platform 13 according to the model of the planned and deployed device.

The electronic device 14 may include, but is not limited to, at least one of the following: terminal devices, servers, etc. The method provided by the embodiment of the present invention can be implemented when the electronic device 14 executes a computer program, and specifically, the electronic device 14 acquires data of a plurality of preset energy efficiency indexes of a target building by communicating with the energy consumption device 11 deployed in the building, the device 12 for storing building data, and the third-party data platform 13, and processes the data of the plurality of preset energy efficiency indexes according to the method provided by the embodiment of the present invention to obtain an energy efficiency value of the target building.

The user terminal 15 may include, but is not limited to, at least one of the following: mobile phones, tablet computers, desktop computers, vehicle-mounted terminals, wearable devices, and the like. The user can view the energy efficiency value of the target building obtained by the electronic device 14 through the user terminal 15. For example, after obtaining the energy efficiency value of the target building, the electronic device 14 sends one or more of the energy efficiency value of the target building, data of each preset energy efficiency index, and the third weight value to the user terminal, so that the user terminal can display the data to the user for viewing. For another example, after receiving the query instruction input by the user, the user terminal 15 sends a query request to the electronic device 14, and the electronic device 14 sends one or more of the energy efficiency value, the data of each preset energy efficiency index, and the third weight value of the target building to the user terminal 15 according to the query request. It should be noted that, when the electronic device 14 is a terminal device with a display screen, after the electronic device 14 obtains the energy efficiency value of the target building, one or more of the energy efficiency value of the target building, data of each preset energy efficiency index, and the third weight value may be displayed so as to be convenient for the user to view.

Fig. 2 is a schematic flowchart of a building energy efficiency obtaining method according to an embodiment of the present invention. The execution subject of the method is the electronic device in fig. 1. As shown in fig. 2, the method includes:

s201, collecting data of a plurality of preset energy efficiency indexes of the target building.

In this embodiment, the target building is a building for which energy efficiency needs to be determined. The target building may be one or more, and is not limited herein. The preset energy efficiency index is an index influencing the energy efficiency of the building. The preset energy efficiency index may be preset by a user, or may be obtained by screening candidate indexes according to a certain rule, which is not limited herein. For example, the preset energy efficiency index may include, but is not limited to, at least one of: internal profitability, incremental investment static recycling period, building waste discharge, building unit energy consumption discharge, building waste discharge reduction, building renewable energy occupancy, building energy system utilization, building heat/cold efficiency, building exergy efficiency, building energy storage efficiency, equipment average utilization, building primary energy utilization, and building energy saving rate.

The electronic equipment can communicate with one or more of energy consumption equipment deployed in the target building, equipment for storing data of the target building, a third-party data platform and the like to acquire initial data of the target building, and then determine data of each preset energy efficiency index according to the initial data of the target building. For example, the initial data may include, but is not limited to, at least one of: the system comprises a power supply system, a power storage system, a power supply system, a.

S202, determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining the first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes.

In this embodiment, the number of the preset energy efficiency indexes is not limited herein. For example, if there are 17 preset energy efficiency indicators, the information entropy of each preset energy efficiency indicator is first calculated according to the data of the 17 preset energy efficiency indicators, and then the first weight value of each preset energy efficiency indicator is calculated according to the information entropy of the 17 preset energy efficiency indicators.

S203, determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm.

In this embodiment, the weight value determined by the information entropy is referred to as a first weight value, and the weight value determined by the hierarchical analysis algorithm is referred to as a second weight value. After the first weight value and the second weight value of each preset energy efficiency index are obtained, for each preset energy efficiency index, a third weight value of the preset energy efficiency index can be determined according to the first weight value and the second weight value of the preset energy efficiency index. The third weight value is a weight value used for obtaining the building energy efficiency subsequently.

And S204, determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index.

In this embodiment, the energy efficiency value of the target building may be represented as an energy efficiency score or an energy efficiency class. The range of the energy efficiency level may be set by a user according to a requirement, and is not limited herein. For example, the energy efficiency value may be 85 points, or the energy efficiency value may be three levels of energy efficiency rating.

Fig. 3 is a flowchart illustrating a building energy efficiency obtaining method according to another embodiment of the present invention. On the basis of the embodiment shown in fig. 2, a specific implementation process for determining the information entropy of each preset energy efficiency index is described. As shown in fig. 3, the method includes:

s301, collecting data of a plurality of preset energy efficiency indexes of the target building.

S302, carrying out standardization processing on data of a plurality of preset energy efficiency indexes to generate an index matrix.

And S303, aiming at each preset energy efficiency index, determining the information entropy of the preset energy efficiency index according to the index matrix.

In this embodiment, there are a plurality of target buildings. The step of normalizing the data of the plurality of preset energy efficiency indexes may include: and aiming at each preset energy efficiency index, carrying out normalization processing on the data of the preset energy efficiency index of each target building. Firstly, generating an index matrix from the standardized data of each preset energy efficiency index of a plurality of target buildings, and then calculating the information entropy of each preset energy efficiency index according to the index matrix and a calculation formula of the information entropy.

For example, let Y be (Y) an index matrix formed by n preset energy efficiency indexes and m target buildings_ij)_n×m1,2, ·, n; j is 1, 2. Firstly, data of preset energy efficiency indexes are inputAnd (5) carrying out standardization processing.

Wherein, y_ijData representing the ith preset energy efficiency index of the jth target building, E_ijRepresents a pair y_ijThe resulting data were normalized.

According to a calculation formula of the information entropy, the information entropy of the ith preset energy efficiency index is as follows:

wherein, when E_ijWhen equal to 0, let E_ijlnE_ij＝0。

S304, determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes.

S305, determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm.

S306, determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index.

In this embodiment, an index matrix is generated by standardizing data of a plurality of preset energy efficiency indexes, and then, for each preset energy efficiency index, the information entropy of the preset energy efficiency index is determined according to the index matrix, so that the information entropy of each preset energy efficiency index can be accurately determined.

As an implementation manner of the present invention, on the basis of any one of the above embodiments, determining the first weight value of each preset energy efficiency index according to the information entropy of each preset energy efficiency index may include:

and for each preset energy efficiency index, dividing a first difference value by a second difference value to obtain a first weighted value of the preset energy efficiency index, wherein the first difference value is a difference value between 1 and the information entropy of the preset energy efficiency index, and the second difference value is a difference value between the total number of the preset energy efficiency indexes and the sum of the information entropies of the preset energy efficiency indexes.

In this embodiment, if the information entropy of the ith preset energy efficiency index is represented as h (i), and n preset energy efficiency indexes are provided, the first weighted value of the ith preset energy efficiency index may be represented as:

finally obtaining weight vectors W ═ (W) of n preset energy efficiency indexes₁”,w₂”,...,w_n”)。

As an implementation manner of the present invention, on the basis of any one of the above embodiments, determining the third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index may include:

and for each preset energy efficiency index, summing the product value of the first weight value and the first preset coefficient of the preset energy efficiency index and the product value of the second weight value and the second preset coefficient of the preset energy efficiency index to obtain a third weight value of the preset energy efficiency index.

In this embodiment, values of the first preset coefficient and the second preset coefficient may be set according to requirements, and are not limited herein. The first preset coefficient and the second preset coefficient are both smaller than 1. Optionally, the sum of the first preset coefficient and the second preset coefficient is equal to 1. For example, the first predetermined coefficient may be 0.7, and the second predetermined coefficient may be 0.3.

In this embodiment, by setting the first preset coefficient and the second preset coefficient, on one hand, the weight obtained by the information entropy and the weight obtained by the hierarchical analysis algorithm can be integrated, and the subjectivity of the weight obtained by the hierarchical analysis algorithm is adjusted by the objectivity of the weight obtained by the information entropy, so that the third weight value of each preset energy efficiency index is more appropriate, and on the other hand, the first preset coefficient and the second preset coefficient enable the user to adjust the specific gravity of the weight obtained by the information entropy and the specific gravity of the weight obtained by the hierarchical analysis algorithm in the third weight value, so that the application is wider.

Fig. 4 is a flowchart illustrating a building energy efficiency obtaining method according to another embodiment of the present invention. On the basis of any of the above embodiments, a specific implementation process of determining an energy efficiency value of a target building according to data of each preset energy efficiency index and a third weight value of each preset energy efficiency index is described. As shown in fig. 4, the method includes:

s401, collecting data of a plurality of preset energy efficiency indexes of the target building.

S402, determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining the first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes.

And S403, determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm.

S404, determining an energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index by adopting a matter element extension algorithm.

In this embodiment, modeling may be performed by using an object-wise extension algorithm to determine an energy efficiency value of the target building. The weight value of each preset energy efficiency index in the matter element extension algorithm is the third weight value of each preset energy efficiency index determined in the embodiment.

The implementation steps of the matter element extension algorithm may include:

step one, determining an object element

The energy efficiency value of the target building to be evaluated is recorded as N, the characteristic thereof is recorded as C, the characteristic quantity value is recorded as v, and N is assumed to have a plurality of characteristics C₁,C₂,...C_nThe n features correspond to a magnitude v₁,v₂,...v_nThen, it can be expressed as:

wherein, R is N-dimensional matter element, abbreviated as R ═ N, c, v)

c represents n characteristics of the object to be evaluated, c ═ c₁,c₂,...c_n)

v denotes the magnitude of n features, v ═ v₁,v₂,...v_n)

Step two, determining the classical domain

The classical domain is determined according to the characteristics of the object element to be evaluated and the interval of the magnitude of the object element, and the evaluation grade is assumed to be divided into m grades, and N is used_j(j 1.. m) and the jth rank is denoted by c_iN, and the i-th evaluation index is represented by v_jiThe value range of the ith evaluation index under the grade j is represented by (i ═ 1.. n), and the value range is represented by an interval (a)_ji,b_ji) The expression shows that N, c, v are combined in an ordered triad form to form a classical domain object element R_j:

Step three, determining section areas

R for nodal region_pIs represented by v_piFor node-domain matter element with respect to feature c_iV is the range of_pi＝(a_pi,b_pi)(i＝1...n)

Wherein (a)_pi,b_pi) Is (a)_ji,b_ji) j 1.. m, the union of all ranges of the i-th index.

Node domain matter element R_pCan be expressed as:

(4) determining the object to be evaluated

Setting y target buildings, and evaluating the energy efficiency value of the target buildingN_xIs represented by R_x:

Wherein v is₁,v₂,...v_nAnd expressing the score of each preset energy efficiency index of the target building, wherein the score is obtained from the data of each preset energy efficiency index after standardization. For example, the corresponding score may be obtained according to an interval in which the normalized data of each preset energy efficiency index falls. And carrying out weighted summation on the scores of the preset energy efficiency indexes through the third weight values of the preset energy efficiency indexes to obtain the energy efficiency value of the target building. The third weighted values of the preset energy efficiency indexes can be obtained according to the steps of the above embodiments, and are not described herein again.

According to the embodiment of the invention, the entropy weight algorithm and the analytic hierarchy process are combined to determine the weight value in the matter element extension algorithm, so that the accuracy of the matter element extension algorithm is improved, and the accuracy of target building energy efficiency assessment is improved.

Optionally, on the basis of any of the foregoing embodiments, the process of determining the second weighted value of each preset energy efficiency index by using an analytic hierarchy process includes: establishing a hierarchical structure model; constructing a judgment matrix; sorting the hierarchical lists and checking consistency; the method specifically comprises the following steps of (1) carrying out overall hierarchical ordering and consistency inspection:

step one, establishing a hierarchical structure model

When the analytic hierarchy process is applied to analyzing and evaluating problems, firstly, the problems are systematized, factors are layered, and a factor hierarchical structure model is constructed. Under this model, complex problems are decomposed into components that form several levels of elements by attributes and relationships. The factors of the upper layer are used as criteria to dominate the factors of the lower layer, and the factors of the lower layer are the refinement of the factors of the upper layer. These levels are generally classified into three categories: a target layer: there is and only one element in this layer, the predetermined target of the analytical evaluation problem; a criterion layer; the layer comprises intermediate links related to the realization of the target, and can be composed of a plurality of layers, including a criterion and a sub-criterion which need to be considered; ③ scheme layer: the level should belong to the lowest level in the hierarchical model, and various measures, decision schemes and the like which can be selected for achieving the factors of the target level are included. In this embodiment, the target layer includes energy efficiency values of the target buildings, the criterion layer includes preset energy efficiency indexes, and the plan layer includes the target buildings.

Step two, constructing a judgment matrix

After the hierarchical structure model is established, the membership of the upper and lower layer factors is determined. To determine the importance of each layer of elements relative to the previous layer of objects, a decision matrix needs to be constructed. The factors of each layer are compared pairwise according to the evaluation standard of artificial quantification, in this embodiment, the Saaty1-9 scaling method is adopted, and the factor x is represented by using a specific numerical scale (1-9)_iRatio factor x_jOf relative importance, establish the decision matrix a ═ a_ij)_n×n. The decision matrix scale and meaning are shown in the following table:

TABLE 1 judge matrix Scale and implications

Step three, hierarchical single ordering and consistency inspection

The hierarchical single ordering refers to the importance ordering of the factors of the same hierarchy in the hierarchical analysis method to the index factors of the previous hierarchy, and generally, the judgment matrix A is calculated as (a)_ij)_n×nCorresponding to the maximum eigenvalue λ_maxIs determined.

1) The judgment matrix A is equal to (a)_ij)_n×nNormalizing by columns to obtain a matrix

Namely, it is

2) Computing matrices

Average of the sums of the rows, i.e.

Calculating to obtain w ═ w₁,w₂,…,w_n]^TI.e. the calculated feature vector.

3) Calculating and judging the maximum characteristic root lambda of matrix_max。

4) And (3) checking consistency: in order to ensure the reasonability of the weight distribution obtained by applying the analytic hierarchy process, the consistency among the importance degrees of all elements needs to be checked, namely consistency check is carried out, and the condition that the relative importance degrees of all factors are contradictory is avoided. First, the consistency index CI of the judgment matrix A is calculated, namely

A larger value of CI indicates a worse consistency of the decision matrix, and the random consistency ratio is defined as CR, i.e.

Wherein, RI is the average random consistency index of the judgment matrix A, and the value of RI is only related to the order of the matrix and can be obtained by table look-up.

TABLE 2 random consistency index RI values

In general, the smaller CR, the better the judgment matrix consistency. CR < 0.10 indicates that the matrix is judged to have acceptable satisfactory consistency, otherwise, the matrix should be adjusted and corrected.

The feature vector w passing the consistency check is ═ w₁,w₂,…,w_n]^TEach item in the set is determined as a second weighted value of each preset energy efficiency index.

In this embodiment, the analytic hierarchy process takes into account the knowledge and experience of experts and the preference of decision makers, but has a large subjective randomness. The entropy weight method is based on the information entropy theory, and the principle is that the smaller the information entropy of the index is, the larger the variation degree is, the larger the effective information amount provided by the index is, the larger the corresponding weight is, and otherwise, the smaller the weight is. When the values of the evaluated object on a certain index are the same, the entropy value reaches the maximum, which indicates that the index does not provide any useful information and can be removed from an evaluation index system, so that the result of the entropy weight method is objective but cannot reflect the knowledge and experience of experts and the opinions of decision makers. The embodiment integrates the advantages of the building energy efficiency evaluation system and the building energy efficiency evaluation system, and index weights combined subjectively and objectively are obtained to evaluate the building energy efficiency, so that the accuracy of energy efficiency evaluation is improved.

As an implementation manner of the present invention, on the basis of any of the above embodiments, determining an energy efficiency value of the target building according to data of each preset energy efficiency index and a third weighted value of each preset energy efficiency index may include determining a score of each preset energy efficiency index according to the data of each preset energy efficiency index, and obtaining the energy efficiency value of the target building by weighting and summing the scores of each preset energy efficiency index by a formula R ═ GW. Wherein, R is the energy efficiency value of the target building, G is the score determined after the data of each preset energy efficiency index is standardized, and W is the third weighted value of each preset energy efficiency index.

Alternatively, the preset energy efficiency index may be divided into a very large index and a very small index. Before determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index, preprocessing the indexes of different types to convert the indexes into very large indexes. Specifically, the formula for converting the data of the extremely small index into the data of the extremely large index is as follows: x ═ X_max-X. Wherein X' is data of the index after pretreatment; x_maxIs the maximum value of the data of the index; x is the data actual value of the index.

As an implementation manner of the present invention, on the basis of any of the above embodiments, the acquiring data of a plurality of preset energy efficiency indexes of a target building includes:

the method comprises the steps of communicating with a target device to collect initial data of a target building, wherein the target device comprises at least one of the following items: energy consumption equipment deployed by the target building, equipment for storing target building data and a third-party data platform;

determining data of a plurality of preset energy efficiency indexes of the target building according to the initial data, wherein the preset energy efficiency indexes comprise at least one of the following items: internal profitability, incremental investment static recovery period, building waste discharge, building unit energy consumption discharge, building waste discharge reduction, building renewable energy ratio, building energy system utilization, building heat/cold efficiency, building exergy efficiency, building energy storage efficiency, equipment average utilization, building primary energy utilization, building energy saving rate;

storing the initial data and pushing the initial data to the user terminal.

In this embodiment, the preset energy efficiency index may include, but is not limited to, at least one of the following types: the method comprises the following steps of obtaining an economic energy efficiency index, an environmental energy efficiency index and a physical energy efficiency index, wherein the economic energy efficiency index can include but is not limited to at least one of the following items: internal rate of return, incremental investment static recovery period. The environmental class energy efficiency indicator may include, but is not limited to, at least one of: building waste discharge amount, building unit energy consumption discharge amount, building waste discharge reduction rate and building renewable energy ratio. The physical energy efficiency evaluation index aims to reflect that after an internal comprehensive energy system is established in a building, the energy utilization efficiency can be improved, the energy is saved, the primary energy consumption is reduced, energy efficiency indexes are established mainly from three angles of energy transmission, energy conversion and energy utilization, and specifically, the physical energy efficiency evaluation index can include but is not limited to at least one of the following: the intelligent building energy system utilization rate, the building heat/cold efficiency, the building exergy efficiency, the building energy storage efficiency, the equipment average utilization rate, the building primary energy utilization rate and the building energy saving rate. The following respectively describes a calculation formula for determining data of each preset energy efficiency index of the target building according to the initial data:

(1) building economic energy efficiency index

1.1 internal yield calculation formula:

wherein IRR is the internal yield, B_pFor cash flow per epoch, t represents the number of epochs.

1.2 incremental investment static recovery period calculation formula:

wherein, I_reThe incremental investment required by the cold, heat and electric quantity which are the same as those of the traditional separate production system is output for the comprehensive energy system; c_trAnd C_intThe annual operating costs of the traditional separate production system and the comprehensive energy system respectively comprise fuel cost, labor cost, equipment maintenance cost, equipment depreciation and the like.

(2) Building environment type energy efficiency index

2.1 building waste discharge amount calculation formula:

wherein B is the equivalent number of total pollution; m is_xThe discharge amount of nitrogen, carbon and sulfide; a is_xThe equivalent values of nitrogen, carbon and sulfide.

2.2 a calculation formula of unit energy consumption and emission of the building:

the unit energy consumption emission of the building refers to the ratio of the emission of certain pollutants to the energy consumption of the system in a certain period. Wherein C is the pollution equivalent number generated by unit energy consumption; and E is the energy consumption of the system.

2.3 a calculation formula of the building waste emission reduction rate:

wherein, F₀Representing the amount of waste F generated by the energy consumed by the original output of the required cooling and heating capacity₁The waste amount of energy consumed by the originally output required cold and hot electric quantity after the intelligent optimization of the building is expressed.

2.4 building renewable energy ratio calculation formula:

wherein E is_renewThe method represents the annual power generation amount of renewable energy sources in urban comprehensive energy sources, and comprises solar energy, geothermal energy, biomass energy, wind energy and the like. Q_elcRepresenting the total power generation in the city.

(3) Physical energy efficiency index of building

3.1 wisdom building energy system utilization ratio computational formula:

wherein, P_eNet output power for the system; s_hOutputting heat for the system; s_cOutputting cold energy for the system; v is the natural gas consumption; q_LIs natural gas with low heat value; p_iNet input power to the system.

3.2 building heat/cold efficiency calculation formula:

wherein Q is_r(l)Heat/cold output for the system, V_r(l)Amount of natural gas consumed for production of heat/cold, p_r(l)The amount of electricity consumed to produce heat/cold.

3.3 building exergy efficiency calculation formula:

wherein E is_ORepresents, originally B_h、B_CB is the energy mass coefficient of heat energy, cold energy and natural gas, and is defined as the capacity of converting energy into electric energy to the maximum extent theoretically, E_OFor net output of electricity to the system, E_iNet input power to the system.

3.4 electric building energy storage efficiency calculation formula:

wherein, P_COIndicating the input electric quantity, P, of the electric energy-storing and accumulating element_CIAnd the output electric quantity of the electric energy storage and power storage element is represented.

3.5 equipment average utilization calculation formula:

wherein, T₀Planning the working time length for a unit; t is the actual working time of the equipment in unit time; n is a radical of_eThe number of devices in the energy link in the comprehensive energy system. The planned working time is calculated by optimization.

3.6 building primary energy utilization rate calculation formula:

wherein the content of the first and second substances,Q_e、Q_c、Q_hrespectively supplying power, refrigerating capacity and heating capacity to the system; q₁Is the primary energy consumption of the system.

3.7 building energy-saving rate calculation formula:

wherein E₀For the fuel consumption (converted to standard coal) of a conventional production-by-production system, E₁The fuel consumption (converted into standard coal quantity) of the intelligent building post-system is improved.

The electronic device may seamlessly integrate data from various sources, receive files from a data gateway through a wired network or a wireless network, and receive files from a third-party data platform through interfaces such as OPC (OLE for Process Control) to collect initial data.

The electronic device may store the initial data locally or to a cloud storage space. In addition, the electronic equipment can also perform preliminary analysis on mass initial data to realize strong calculation performance, detect and identify the problems of equipment operation, low efficiency and the like based on the automatic analysis of the equipment and energy consumption data by the artificial intelligence engine, and automatically acquire independent preliminary corresponding improvement suggestions of each equipment. The electronic equipment can present the initial data, so that a user can access the data through the user terminal at any time and any place, present the data to users with different levels of authority in a plurality of data exhibition modes, and control access.

On the basis of any of the above embodiments, after determining the energy efficiency value of the target building, the method may further include at least one of the following steps:

in the first embodiment, the energy efficiency value of the target building and the data of each preset energy efficiency index are displayed.

In this embodiment, the electronic device has a display, and the energy efficiency value of the target building and the data of each preset energy efficiency index can be displayed through the display for the user to view.

In a second implementation manner, the energy efficiency value of the target building and data of each preset energy efficiency index are sent to the user terminal.

In this embodiment, the electronic device may send the energy efficiency value of the target building and the data of each preset energy efficiency index to the user terminal, so that the user can view the data through the user terminal.

In the third embodiment, the operation mode of the energy device of the target building is controlled according to the energy value of the target building.

In this embodiment, the target building is constructed and in the operation stage, the electronic device may control the operation mode of the energy device of the target building according to the energy value of the target building. For example, when the energy efficiency value of the target building exceeds the preset energy efficiency upper limit, the electronic device may control some or all energy devices of the target building to switch from the normal operation mode to the energy saving operation mode, so as to reduce energy consumption.

The building energy efficiency evaluation method is described below by using an embodiment. Take 3 intelligent building type integrated energy system buildings as an example for explanation. The building 1 is a commercial building in the Yangtze river delta area, and the total land area is about 2.41 ten thousand meters²The system is a medium-high-end complex covering offices, business hotels and block businesses. The building 2 is an international airport in the plain area of the middle part, and the total building area of the building 2 reaches 21.2 ten thousand meters²Equipped with an integrated energy system station. The building 3 is a newly-built school in the coastal region, and the total occupied area is 17 ten thousand meters²There are 42 teaching classes, and the energy station is mainly used in teaching building and dormitory building, and is a demonstration building advocating the use of clean energy.

The main operating parameters of some systems of 3 buildings are shown in the following table:

TABLE 3 Main operating parameters of part of the System of a building

Fig. 5 shows an implementation flow of the embodiment, and the specific implementation process refers to the above embodiments, which is only briefly described herein and is not repeated. The implementation process comprises the following steps:

s501, an index system is established, namely data of each preset energy efficiency index of the target building are determined and collected.

S502, determining the object element, the classical domain and the section domain.

And S503, determining the matter element to be evaluated.

S504, constructing a judgment matrix.

And S505, calculating the hierarchical weight.

And S506, judging whether the consistency of each level is checked, if not, jumping to S505, and if so, executing S507.

And S507, calculating a combined weight, namely a second weight value of each preset energy efficiency index determined by an analytic hierarchy process in the above embodiment.

S508, data normalization processing, namely normalization processing performed before information entropy is determined in the above-described embodiment.

S509, the weights obtained by the analytic hierarchy process are corrected by the weights obtained by the information entropy, so as to obtain the weights of the preset energy efficiency indicators, that is, in the above embodiment, the third weight value is determined by the first weight value and the second weight value.

And S510, determining a building energy efficiency value according to the data and the weighted value of each preset energy efficiency index.

And S511, ending.

The data and the score of the determined preset energy efficiency indexes of the buildings are as follows:

TABLE 4 data and scores of each preset energy efficiency index of a building

And finally, determining the energy efficiency value of each building according to the score and the corresponding weight value of the preset energy efficiency index of each building, wherein the results are as follows:

TABLE 5 energy efficiency values for each building

It can be seen that the energy efficiency value of building 1 is the highest, and the energy efficiency value of building 2 is the lowest.

In addition, the advantages and disadvantages of the building can be analyzed through the specific scores of the preset energy efficiency indexes. If the indexes of the intelligent building 1 such as comprehensive energy utilization rate, renewable energy ratio and primary energy utilization rate of the building are high, the comprehensive energy utilization rate, the clean energy ratio and the primary energy utilization of the system are superior indexes, and the building incremental investment recovery period, the building energy saving rate and the like are low, the building energy saving rate and the incremental recovery period are required to be improved and optimized. Although the effective values of the buildings 2 and 3 are similar, the superior and inferior indexes of the 2 buildings are different: the advantage indexes of the building 2 are mainly the annual building investment cost value and the building heat/cold efficiency, which shows that the building pays more attention to economic indexes, and the competitiveness of energy consumption indexes is relatively weak, such as the comprehensive energy utilization rate, the building exergy efficiency and the cold efficiency index score are low, which shows that the energy waste is serious in order to obtain considerable economic benefit; the most main advantage indexes of the building 3 are building renewable energy ratio, namely clean energy ratio is large, and other energy consumption indexes such as building waste emission reduction rate are low. From the above analysis, it can be seen that the intelligent building energy efficiency evaluation method evaluation system provided by the embodiment can evaluate one system more comprehensively, and can also clarify the advantages and disadvantages of the system through specific index scores.

The embodiment of the invention has the following beneficial effects: (1) the intelligent building energy efficiency assessment method considering big data and cloud architecture has more constituent units and more energy types, and indexes and utilization efficiency of various aspects such as water, electricity, gas, heat, energy storage and the like are considered for energy forms of various aspects in a comprehensive energy system. (2) The big data and cloud architecture technology are fully utilized to complete data acquisition, data processing, data presentation and data storage. Data acquisition can seamlessly integrate data from various sources, and receive data from data gateway files through a wired or wireless network. And receiving the file of the third-party system through an interface such as OPC (OLE for process control) and the like. Data processing can store data in the cloud end, and carry out preliminary analysis to massive data, realize powerful computational performance, based on artificial intelligence engine, automatic analysis equipment and energy consumption data, detect and discern equipment operation and inefficiency scheduling problem, the preliminary improvement suggestion that each equipment corresponds is obtained automatically. The data presentation can be accessed through Web and Mobile at any time and any place, and the data is presented to users with different levels of authority in a plurality of data presentation modes and is controlled to be accessed. Big data and cloud architecture technology focus on solving the comprehensive energy consumption (including water, electricity, gas, heat, etc.) problem of building, and the user can select or stack according to actual demand. (3) By the aid of the designed comprehensive benefit evaluation tool, a decision support tool can be provided for investment builders of the comprehensive energy building, comprehensive benefits of the comprehensive energy building are evaluated according to specific conditions, the decision sinking cost of an energy supplier is reduced, and the service level of the comprehensive energy building is improved. Therefore, the embodiment of the invention can scientifically evaluate the utilization rate of various comprehensive energy sources so as to achieve the purposes of optimizing the comprehensive energy source system of the building in time and reducing the planning and construction cost of the new building.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Fig. 6 is a schematic structural diagram of a building energy efficiency obtaining apparatus according to an embodiment of the present invention. As shown in fig. 6, the building energy efficiency acquisition device 60 includes: an acquisition module 601 and a processing module 602.

The system comprises an acquisition module 601, a data acquisition module and a data processing module, wherein the acquisition module is used for acquiring data of a plurality of preset energy efficiency indexes of a target building;

the processing module 602 is configured to determine an information entropy of each preset energy efficiency index according to data of a plurality of preset energy efficiency indexes, and determine a first weight value of each preset energy efficiency index according to the information entropy of the plurality of preset energy efficiency indexes;

the processing module 602 is further configured to determine a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, where the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm;

the processing module 602 is further configured to determine an energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index.

In the embodiment of the invention, data of a plurality of preset energy efficiency indexes of a target building are acquired; determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes, and determining a first weighted value of each preset energy efficiency index according to the information entropy of the preset energy efficiency indexes; determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index, wherein the second weighted value of each preset energy efficiency index is determined according to a hierarchical analysis algorithm; the energy efficiency value of the target building is determined according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index, the information entropy can be considered in the building energy efficiency obtaining process, the weighted value determined by the information entropy and the weighted value obtained by the hierarchical analysis algorithm are used for jointly determining the weighted value of each preset energy efficiency index, the objectivity of the information entropy and the subjectivity of the hierarchical analysis algorithm are combined, the weighted value of each preset energy efficiency index is more accurate, and the building energy efficiency obtaining accuracy is improved.

Optionally, the processing module 602 is configured to:

carrying out standardization processing on data of a plurality of preset energy efficiency indexes to generate an index matrix;

and aiming at each preset energy efficiency index, determining the information entropy of the preset energy efficiency index according to the index matrix.

Optionally, the processing module 602 is configured to:

and determining the energy efficiency value of the target building by adopting a matter element extension algorithm according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index.

Optionally, the acquisition module 601 is configured to:

the device also comprises a sending module, wherein the sending module is used for:

storing the initial data and pushing the initial data to the user terminal.

Optionally, the apparatus further comprises a display module, the display module is configured to:

and displaying the energy efficiency value of the target building and data of each preset energy efficiency index.

Optionally, the sending module is further configured to:

and sending the energy efficiency value of the target building and the data of each preset energy efficiency index to the user terminal.

Optionally, the processing module 602 is further configured to:

and controlling the operation mode of the energy equipment of the target building according to the energy value of the target building.

The building energy efficiency obtaining apparatus provided in this embodiment may be configured to execute the method embodiments described above, and the implementation principle and the technical effect are similar, which are not described herein again.

Fig. 7 is a schematic diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 7, the electronic apparatus 7 of this embodiment includes: a processor 70, a memory 71 and a computer program 72, such as a building energy efficiency acquisition program, stored in said memory 71 and operable on said processor 70. The processor 70, when executing the computer program 72, implements the steps in the above-described embodiments of the building energy efficiency obtaining method, such as the steps 201 to 204 shown in fig. 2. Alternatively, the processor 70, when executing the computer program 72, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 61 to 62 shown in fig. 6.

Illustratively, the computer program 72 may be partitioned into one or more modules/units that are stored in the memory 71 and executed by the processor 70 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 72 in the electronic device 7.

The electronic device 7 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The electronic device 7 may include, but is not limited to, a processor 70 and a memory 71. It will be appreciated by those skilled in the art that fig. 7 is only an example of the electronic device 7, and does not constitute a limitation of the electronic device 7, and may comprise more or less components than those shown, or some components may be combined, or different components, for example, the electronic device 7 may further comprise an input-output device, a network access device, a bus, etc.

The Processor 70 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 71 may be an internal storage unit of the electronic device 7, such as a hard disk or a memory of the electronic device 7. The memory 71 may also be an external storage device of the electronic device 7, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the electronic device 7. The memory 71 is used for storing the computer program and other programs and data required by the apparatus/terminal device. The memory 71 may also be used to temporarily store data that has been output or is to be output.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims

1. A building energy efficiency obtaining method is characterized by comprising the following steps:

2. The building energy efficiency obtaining method according to claim 1, wherein determining the information entropy of each preset energy efficiency index according to the data of the preset energy efficiency indexes comprises:

carrying out standardization processing on the data of the plurality of preset energy efficiency indexes to generate an index matrix;

3. The building energy efficiency obtaining method according to claim 1, wherein determining the first weighted value of each preset energy efficiency index according to the information entropy of each preset energy efficiency index comprises:

and for each preset energy efficiency index, dividing a first difference value by a second difference value to obtain a first weighted value of the preset energy efficiency index, wherein the first difference value is a difference value between 1 and the information entropy of the preset energy efficiency index, and the second difference value is a difference value between the total number of the preset energy efficiency indexes and the sum of the information entropy of each preset energy efficiency index.

4. The building energy efficiency obtaining method according to claim 1, wherein determining a third weighted value of each preset energy efficiency index according to the first weighted value and the second weighted value of each preset energy efficiency index comprises:

5. The building energy efficiency obtaining method according to claim 1, wherein determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weighted value of each preset energy efficiency index comprises:

and determining the energy efficiency value of the target building according to the data of each preset energy efficiency index and the third weight value of each preset energy efficiency index by adopting a matter element extension algorithm.

6. The building energy efficiency obtaining method according to any one of claims 1 to 5, wherein the collecting data of a plurality of preset energy efficiency indexes of the target building comprises:

collecting initial data of the target building by communicating with a target device, wherein the target device comprises at least one of: the energy consumption equipment deployed by the target building, the equipment for storing the target building data and a third-party data platform;

and storing the initial data and pushing the initial data to a user terminal.

7. The building energy efficiency acquisition method according to any one of the claims 1-5, characterized in that the method further comprises at least one of the following steps:

displaying the energy efficiency value of the target building and data of each preset energy efficiency index;

sending the energy efficiency value of the target building and data of each preset energy efficiency index to a user terminal;

and controlling the operation mode of the energy equipment of the target building according to the effective value of the target building.

8. A building energy efficiency acquisition device, comprising:

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1-7 are implemented when the computer program is executed by the processor.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.