Energy consumption evaluation and diagnosis system for air conditioning system

Abstract

The present application discloses an air conditioning system energy consumption evaluation and diagnosis system, wherein the acquisition module is used to collect the historical energy consumption related data of all air conditioning systems in each time unit within a preset period; the energy consumption fitting module is used to obtain a three-dimensional energy consumption surface based on each air conditioning system according to all its historical energy consumption related data and working attribute values; the evaluation table determination module is used to determine the energy consumption related element set based on the three-dimensional energy consumption surface of each air conditioning system; all air conditioning systems in the building air conditioning system are divided to obtain a number of air conditioning system groups; based on each air conditioning system group, an evaluation table is obtained according to the energy consumption related element set of all its air conditioning systems; the determination module is used to locate the evaluation table of the air conditioning system group where the air conditioning system to be evaluated is located based on the air conditioning system to be evaluated, and perform energy consumption evaluation. Thus, the air conditioning systems in the building air conditioning system are managed in a targeted and diversified manner, and the accuracy and adaptability of energy consumption evaluation are improved.

Description

Technical Field

[0001] The invention relates to the technical field of energy consumption assessment, and in particular to an energy consumption assessment and diagnosis system for an air conditioning system. Background Art

[0002] At present, the indicator of the energy consumption evaluation method of air conditioning system is the annual energy consumption intensity per unit area kWh / (a·㎡). However, the existing energy consumption evaluation is not combined with energy-saving diagnosis. In addition, the existing energy consumption evaluation method collects the energy consumption value of the air conditioning system of the building for one year or one cooling season and divides it by the building area where the air conditioning system is set to obtain the annual energy consumption intensity per unit area of ​​the air conditioning system of the building. The energy consumption value includes: cold source energy consumption, distribution system energy consumption and terminal system energy consumption. However, this method has the following defects: 1. It can only evaluate the cumulative power consumption of the building air conditioning system in the entire cooling season, and cannot evaluate the actual operating performance of the air conditioning system; for building cases in different climate zones, the energy consumption intensity of the air conditioning system cannot be compared due to different operating times of the air conditioning system throughout the year and different meteorological parameters. The current annual air conditioning energy consumption evaluation index needs to be given according to the climate zone. However, the division of climate zones is artificially defined, which ultimately leads to a large deviation in the evaluation. 2. For the same building case, the annual energy consumption intensity per unit area in different years is affected by different meteorological parameters each year, and there will be a large deviation in the vertical comparison, which brings difficulties to the performance evaluation of the energy-saving operation transformation of the building air conditioning system.

[0003] The invention patent with patent application number 202110291191.1 discloses a method for evaluating and diagnosing energy consumption of air-conditioning systems. The energy consumption set of the air-conditioning system per unit area is calculated based on historical energy consumption data, and the energy consumption temperature curve is obtained by fitting with historical temperature data, so as to determine the maximum energy consumption value corresponding to each air-conditioning system, build a database, and then determine the first threshold, second threshold, third threshold and fourth threshold based on the sorted database to perform air-conditioning system operation status and energy-saving diagnosis location.

[0004] However, for each air-conditioning system, a large amount of data is obtained based on its historical energy consumption per unit area and its corresponding temperature to obtain an energy consumption temperature curve. According to the principle of fitting, there may be energy consumption values ​​corresponding to the same temperature that differ greatly but are fitted together to form a point on the curve (some historical data may have the same average outdoor temperature, but the working time or working type of this air-conditioning system in different historical environments or scenes may result in energy consumption values ​​corresponding to the outdoor temperature that differ greatly), resulting in certain errors, that is, ignoring other possible energy consumption values ​​corresponding to the same temperature. The relationship between the energy consumption of the air-conditioning system and the outdoor temperature cannot be accurately and comprehensively reflected on the energy consumption temperature curve, which may also cause errors and non-authenticity in the subsequent determination of energy consumption values ​​corresponding to specific temperatures. Although non-manual labeling is achieved, the accuracy is not satisfactory. In addition, in the actual building air-conditioning system scenario, different air-conditioning systems have complex differences due to factors such as their design, equipment performance, usage conditions, and working environment. If all air-conditioning systems are stored in a database for the selection of energy consumption value judgment intervals, judgment errors will inevitably occur. There is no regular division or targeted management for all air-conditioning systems in the building scene. Summary of the invention

[0005] The present application provides an air conditioning system energy consumption assessment and diagnosis system to carry out targeted and diversified management of air conditioning systems within a building air conditioning system, thereby improving the accuracy and adaptability of energy consumption assessment.

[0006] The present application provides an air conditioning system energy consumption evaluation and diagnosis system, including a collection module, an energy consumption fitting module, an evaluation table determination module, and a determination module;

[0007] The collection module is used to: S101, collect historical energy consumption related data of each time unit of all air-conditioning systems in the building air-conditioning system within a preset period of time, each historical energy consumption related data includes a unit area energy consumption value and an outdoor temperature value corresponding to each time unit;

[0008] The energy consumption fitting module is used to: S102, based on each air conditioning system, obtain a three-dimensional energy consumption surface according to all its historical energy consumption related data and the working attribute value determined by each historical energy consumption related data;

[0009] The evaluation table determination module is used for: S103, based on the three-dimensional energy consumption surface of each air-conditioning system, determining its energy consumption associated element set, the energy consumption associated element set includes the maximum unit area energy consumption value, the calibration temperature point, all working attribute values ​​corresponding to the calibration temperature point, and the unit area energy consumption value corresponding to each working attribute value in the three-dimensional energy consumption surface; S104, all air-conditioning systems in the building air-conditioning system are divided into regions to obtain a number of air-conditioning system groups; S105, based on each air-conditioning system group, according to the energy consumption associated element set of all its air-conditioning systems, a corresponding evaluation table is obtained; S106, based on the evaluation table corresponding to each air-conditioning system group, the maximum unit area energy consumption threshold and the temperature energy consumption threshold are determined;

[0010] The determination module is used for: S107, based on the air-conditioning system to be evaluated, according to all its historical energy consumption related data in a short period of time, determining the latest working attribute value of the air-conditioning system to be evaluated; S108, in the three-dimensional energy consumption surface of the air-conditioning system to be evaluated, determining the unit area energy consumption value E corresponding to the calibrated temperature point at the latest working attribute value, obtaining the maximum unit area energy consumption value Emax of the air-conditioning system to be evaluated, and locating to the evaluation table of the air-conditioning system group where the air-conditioning system to be evaluated is located, and using the corresponding maximum unit area energy consumption threshold and temperature energy consumption threshold to perform energy consumption evaluation.

[0011] Preferably, the preset time period is set to the past two years, each time unit is set to every day, each air-conditioning system is composed of six components: a chiller, a cooling tower, a cooling water pump, a refrigeration water pump, an air-conditioning unit and an air-conditioning system terminal, and the energy consumption per unit area in each time unit of the air-conditioning system is: the ratio of the sum of the energy consumption generated by all time node components in the time unit to the area value covered by the air-conditioning system, and the outdoor temperature value is: the average outdoor temperature value in the time unit.

[0012] Preferably, the working attribute value determined by each historical energy consumption associated data is specifically:

[0013] A1. Based on the energy consumption generated by each time node component in each time unit, the working attribute value determined by each historical energy consumption associated data is calculated according to the following formula:

[0014]

[0015] Where W is the working attribute value corresponding to the historical energy consumption related data, is the fluctuation index of energy consumption generated by components at all time nodes in the corresponding time unit, is the fluctuation index of the outdoor temperature value at all time nodes in the corresponding time unit, is the energy consumption-temperature covariance index, N is the total number of all time nodes in the time unit, is the energy consumption value generated by the component at the i-th time node, is the average energy consumption of the component within a time unit, The outdoor temperature value at the i-th time node, The average outdoor temperature value within the time unit.

[0016] Preferably, the S102 specifically includes:

[0017] B1. Based on the working attribute values ​​corresponding to all historical energy consumption related data, all data points of the air conditioning system (outdoor temperature value, working attribute value, energy consumption per unit area) are obtained;

[0018] B2. Use the preset fitting algorithm to fit all data points to obtain a three-dimensional energy consumption surface. The X-axis coordinate is the outdoor temperature value after fitting, the Y-axis coordinate is the working attribute value after fitting, and the Z-axis coordinate is the three-dimensional area energy consumption value after fitting.

[0019] Preferably, the evaluation table of the air conditioning system group includes a first evaluation table and a second evaluation table, the first evaluation table represents the maximum energy consumption per unit area, and the second evaluation table represents the energy consumption per unit area corresponding to the calibration temperature point; S105 specifically includes:

[0020] C1. Sort the maximum energy consumption per unit area of ​​all air-conditioning systems in ascending order to obtain a first evaluation list;

[0021] C2. Sort all the working attribute values ​​of all the air-conditioning systems in ascending order to obtain a working attribute array, use a preset window to slide and search for a trip point from the beginning of the working attribute array, set the sliding step to 1, calculate the trip index in the current window each time it slides, and when the trip index is greater than the preset threshold, determine the trip point in the current window, and perform a sliding search from the next working attribute value of the trip point until the window slides and searches all the working attribute values ​​in the working attribute array to obtain all the trip points;

[0022] C3. Based on all the trip points, the work attribute array is divided into m work attribute intervals, where m is the number of the trip points plus 1;

[0023] C4. Based on each work attribute interval, the energy consumption per unit area corresponding to all the work attribute values ​​is formed into a sub-evaluation table, and the sub-evaluation tables corresponding to all the work attribute intervals are formed into a second evaluation table, and each sub-evaluation table is distinguished by a work attribute interval label;

[0024] The jump index in the current window is calculated according to the following formula:

[0025]

[0026] is the jump index of the current window, is the difference between the maximum and minimum values ​​of the working attribute value in the current window, that is, the difference value of the current window. is the average value of all window difference values ​​during the window sliding process, is the sum of the absolute values ​​of the differences between all adjacent working attribute values ​​in the current window, that is, the change amplitude of the current window. is the average value of the change amplitude of all windows during the window sliding process, is the preset weight coefficient.

[0027] Preferably, S106 specifically includes: based on the evaluation table corresponding to each air conditioning system group, determining the maximum energy consumption threshold per unit area according to the first evaluation table, including the first maximum energy consumption threshold per unit area and the second maximum energy consumption threshold per unit area, and determining the temperature energy consumption threshold corresponding to each working attribute interval label according to the second evaluation table, including the first temperature energy consumption threshold and the second temperature energy consumption threshold;

[0028] The maximum energy consumption per unit area corresponding to the first 25% in the first evaluation table is determined as the first maximum energy consumption per unit area E1, and the maximum energy consumption per unit area corresponding to the last 25% is determined as the second maximum energy consumption per unit area E2; the energy consumption values ​​corresponding to the first 25% in the corresponding sub-evaluation table are determined as the first temperature energy consumption threshold R1, and the energy consumption values ​​corresponding to the last 25% are determined as the second temperature energy consumption threshold R2;

[0029] In S108, energy consumption evaluation is performed using the corresponding maximum energy consumption threshold per unit area and temperature energy consumption threshold, specifically including:

[0030] When E≤R1 and E<Emax<∞, the energy consumption assessment risk level of the air-conditioning system to be assessed is low;

[0031] When R2<E<Emax and Emax>E1, the energy consumption evaluation risk level of the air-conditioning system to be evaluated is high, and an early warning maintenance message is sent to the administrator;

[0032] Otherwise, the energy consumption assessment risk level of the air-conditioning system to be assessed is medium.

[0033] Preferably, in S104, all air-conditioning systems in the building air-conditioning system are divided into regions to obtain a plurality of air-conditioning system groups, specifically including:

[0034] S201, based on the three-dimensional energy consumption surface of each air conditioning system, a section in the direction of the outdoor temperature value is obtained, and the temperature sensitivity is obtained according to the outdoor temperature value on the section and its corresponding unit area energy consumption value, which is specifically:

[0035]

[0036] in, is the temperature sensitivity of the air conditioning system, is the slope value of the surface formed by two adjacent data points on the section surface, is the minimum slope value on the section, is the maximum slope value on the section, is the preset outdoor temperature value step size, K is the total number of data points on the slice;

[0037] S202: Divide all the air-conditioning systems according to their temperature sensitivities based on a preset clustering algorithm to obtain a plurality of air-conditioning system groups.

[0038] Preferably, in A1, the method further comprises: adjusting the working attribute value of each historical energy consumption related data, specifically comprising:

[0039] S301, based on each time unit, calculating the ratio of the energy consumption per unit area of ​​each component to the energy consumption per unit area of ​​the air conditioning system: , is the energy consumption per unit area of ​​the nth component in the mth time unit of the air conditioning system, is the sum of the energy consumption per unit area of ​​all components of the air conditioning system. is the energy consumption per unit area of ​​the nth component in the mth time unit, and the component energy consumption ratio sequence in the mth time unit is obtained ( , ..., );

[0040] S302, based on the component energy consumption proportion sequence, using a preset quantization function, obtain the component energy consumption linkage value in each time unit:

[0041]

[0042] in, is the linkage value of component energy consumption in the corresponding time unit, is the weight coefficient of the energy consumption proportion of the nth component on the component energy consumption linkage value;

[0043] S303: Based on each time unit, the working attribute value is adjusted by using the component energy consumption linkage value, and a new working attribute value is obtained to replace the original working attribute value.

[0044] Preferably, when the energy consumption assessment risk level of the air-conditioning system to be assessed is medium, the determination module is further used to:

[0045] S401, obtaining a component energy consumption proportion sequence and its corresponding component energy consumption linkage value of each time unit of the air-conditioning system to be evaluated in a short period of time;

[0046] S402, analyzing the energy consumption linkage values ​​of all components of the air-conditioning system to be evaluated within a short period of time, and determining a time unit corresponding to a component energy consumption linkage value having the largest difference with other component energy consumption linkage values ​​as a target time unit;

[0047] S403, comparing the component energy consumption ratio sequence of the target time unit with the component energy consumption ratio sequence of other time units, and determining the components whose difference values ​​are greater than a preset difference threshold as a key component set;

[0048] S404, using the method A1 to calculate the working attribute value within the target time unit, determine it as the calibration section value, and generate an update instruction to transmit to the evaluation table determination module;

[0049] The evaluation table determination module is also used for:

[0050] When receiving the update instruction, jump to step S201 to update the slices and temperature sensitivity of all air-conditioning systems, specifically including: using the received calibrated slice value as the fixed working attribute value on the Y axis, obtaining the calibrated slice in the direction of the outdoor temperature value, the calibrated slice is a slice whose working attribute value is the calibrated slice value in the three-dimensional energy consumption surface;

[0051] According to the new temperature sensitivity of all air-conditioning systems, step 202 is executed to obtain a new air-conditioning system group, steps S105 to S106 are executed to obtain a new evaluation table, and a secondary verification instruction is generated and transmitted to the determination module.

[0052] Preferably, when the determination module receives the secondary verification instruction, step S108 is executed to obtain the final evaluation risk level of the air-conditioning system to be evaluated, attach its key component set, generate an evaluation report and send it to the administrator.

[0053] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0054] By determining the working attribute value of the air-conditioning system based on the historical energy consumption related data of each air-conditioning system, and combining the historical energy consumption related data, considering the energy consumption behavior of the air-conditioning system under different working conditions in the fitting relationship between temperature and energy consumption, a three-dimensional energy consumption surface that more comprehensively displays the actual energy consumption operation of the air-conditioning system is obtained, thereby displaying the energy consumption performance of the air-conditioning system in a diversified and multi-dimensional manner to avoid large actual errors; according to the latest working attribute value of the air-conditioning system to be evaluated, the unit area energy consumption value corresponding to the calibration temperature point and the latest working attribute value is obtained in the corresponding three-dimensional energy consumption surface, and combined with its maximum unit area energy consumption value, the corresponding evaluation table is used to evaluate the energy consumption risk level, providing scientific guidance and basis for subsequent energy consumption optimization;

[0055] The zone division is carried out by using the temperature sensitivity obtained based on the three-dimensional energy consumption curve of all air-conditioning systems, rather than relying on the traditional prescribed air-conditioning system zone division, so that the zone division is more adaptable to the changing and complex environment, reduces human intervention and improves work efficiency;

[0056] By quantifying the component energy consumption proportion sequence of the air-conditioning system to obtain the component energy consumption linkage value, and adaptively adjusting the working attribute value in the corresponding time unit, the energy consumption behavior of the air-conditioning system can be more finely reflected, especially the energy consumption linkage between different components; based on the adjusted working attribute value and other relevant data, the refitted three-dimensional energy consumption surface can more accurately reflect the actual energy consumption of the air-conditioning system, thereby improving the accuracy of energy consumption assessment, taking into account the changes in the energy consumption correlation of different components in different time units, so that the three-dimensional energy consumption surface can adapt to more complex and changeable operating environments and different working conditions;

[0057] According to the initial assessment results of the air-conditioning system to be assessed, as well as the component energy consumption proportion sequence and its corresponding component energy consumption linkage value in the corresponding short-term time period, the conditions for the regional division of all air-conditioning systems are adaptively adjusted to make their adjustment rules adapt to the actual operating status characteristics of the air-conditioning system to be assessed, and further assessment and verification are carried out on the air-conditioning system to be assessed, so as to improve the assessment accuracy, avoid potential errors existing in the initial assessment ambiguity, and enhance the adaptability of the energy consumption assessment of the air-conditioning system to be assessed. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The present invention is a schematic diagram of the structure of an air conditioning system energy consumption evaluation and diagnosis system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0059] To facilitate the understanding of the present invention, the present application will be described more comprehensively below with reference to the relevant drawings; the drawings show preferred embodiments of the present invention, but the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, the purpose of providing these embodiments is to enable a more thorough and comprehensive understanding of the disclosed content of the present invention.

[0060] It should be noted that the terms “vertical”, “horizontal”, “up”, “down”, “left”, “right” and similar expressions used in this document are only for illustrative purposes and do not represent the only implementation method.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs; the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more related listed items.

[0062] Embodiment 1: Figure 1 The invention relates to an air conditioning system energy consumption evaluation and diagnosis system according to an embodiment of the present invention.

[0063] like Figure 1 As shown, an air conditioning system energy consumption evaluation and diagnosis system includes: a collection module, an energy consumption fitting module, an evaluation table determination module, and a determination module.

[0064] In some embodiments, the acquisition module is specifically used to:

[0065] S101, collecting historical energy consumption related data of all air-conditioning systems in the building air-conditioning system in each time unit within a preset period of time, the historical energy consumption related data includes the energy consumption value per unit area and the outdoor temperature value corresponding to each time unit, and each time unit corresponds to one historical energy consumption related data.

[0066] Specifically, the preset period can be set to the past two years, and each time unit can be set to every day, that is, the energy consumption per unit area and the outdoor temperature value of each air-conditioning system are collected every day in the past two years. Among them, each air-conditioning system is composed of six components: chiller, cooling tower, cooling water pump, freezing water pump, air-conditioning unit and air-conditioning system terminal. The energy consumption per unit area in each time unit of an air-conditioning system is: the ratio of the sum of the energy consumption generated by all time node components in the time unit to the area value covered by the air-conditioning system, and the outdoor temperature value is: the average outdoor temperature value in the time unit.

[0067] In some embodiments, the energy consumption fitting module is specifically used to:

[0068] S102, based on each air-conditioning system, energy consumption fitting is performed according to all its historical energy consumption related data and the working attribute value determined by each historical energy consumption related data (the historical energy consumption related data corresponding to each time unit) to obtain a three-dimensional energy consumption surface.

[0069] Specifically, the working attribute value determined by each historical energy consumption related data is determined as follows:

[0070] A1. Based on the energy consumption generated by each time node component in each time unit, the working attribute value determined by each historical energy consumption associated data is calculated according to the following formula:

[0071]

[0072] Where W is the working attribute value corresponding to the historical energy consumption related data, is the fluctuation index of energy consumption generated by components at all time nodes in the corresponding time unit, is the fluctuation index of the outdoor temperature value at all time nodes in the corresponding time unit, is the energy consumption-temperature covariance index, N is the total number of all time nodes in the time unit, is the energy consumption value generated by the component at the i-th time node, is the average energy consumption of the component within a time unit, The outdoor temperature value at the i-th time node, The average outdoor temperature value within the time unit.

[0073] The volatility index may be set as a standard deviation, and the specific calculation method may refer to the relevant existing algorithms, which will not be elaborated in the present invention.

[0074] Specifically, according to all its historical energy consumption related data and the working attribute value determined by each historical energy consumption related data, energy consumption fitting is performed to obtain a three-dimensional energy consumption surface, which specifically includes:

[0075] B1. Based on the working attribute values ​​corresponding to all historical energy consumption related data, all data points of the air-conditioning system (outdoor temperature value, working attribute value, energy consumption per unit area) are obtained.

[0076] B2. Use a preset fitting algorithm (for example, multiple regression, interpolation, approximation, etc.) to fit all data points to obtain a three-dimensional energy consumption surface. The X-axis coordinate is the outdoor temperature value after fitting, the Y-axis coordinate is the working attribute value after fitting, and the Z-axis coordinate is the three-dimensional area energy consumption value after fitting.

[0077] Among them, the three-dimensional energy consumption surface is generated based on all the data points of the air-conditioning system, which shows the relationship between energy consumption and the change of outdoor temperature and working attribute value. The principle of generating this surface is to use the existing fitting software to fit the data so that the fitted surface can accurately reflect the relationship in the original data. In the fitting process, the outdoor temperature value, working attribute value and energy consumption value of each data point are considered, and a smooth surface is generated based on the distribution and trend of these data points.

[0078] In the three-dimensional energy consumption surface process, the working attribute value is introduced as the third parameter, and its function can be regarded as the weight that affects the energy consumption-temperature fitting. Specifically, for data points with similar or identical working attribute values, their weights in the fitting process will be greater, which means that the fitting surface will be closer to the actual energy consumption values ​​of these points, thereby avoiding the situation in which large actual errors are generated in the energy consumption-temperature fitting process due to the large differences in energy consumption values ​​corresponding to the same outdoor temperature values ​​under different working conditions of the air-conditioning system.

[0079] Suppose an air-conditioning system in a building has a large difference in energy consumption under different working conditions (such as cooling, heating, dehumidification, etc.). If only the relationship between outdoor temperature and energy consumption is considered, the fitted curve may not accurately reflect the actual energy consumption behavior of the air-conditioning system. However, if the working attribute value is introduced as the third parameter, the fitted three-dimensional surface can more accurately reflect the energy consumption behavior of the air-conditioning system under different working conditions. Specifically, when performing subsequent energy consumption evaluation, a corresponding energy consumption value can be found on the three-dimensional surface based on the current working attribute value and outdoor temperature. This energy consumption value will be more accurate and true because it takes into account the impact of working attributes on energy consumption-temperature, and can more accurately evaluate the energy consumption performance of the air-conditioning system and provide more powerful support for subsequent energy-saving optimization.

[0080] In some embodiments, the evaluation table determination module is specifically used to:

[0081] S103, based on the three-dimensional energy consumption surface of each air-conditioning system, determine its energy consumption associated element set, the energy consumption associated element set includes the maximum energy consumption value per unit area in the three-dimensional energy consumption surface, the calibrated temperature point, all working attribute values ​​corresponding to the calibrated temperature point in the three-dimensional energy consumption surface, and the energy consumption value per unit area corresponding to each working attribute value.

[0082] The calibration temperature point is set according to the actual scene, which is used to represent the energy consumption per unit area of ​​different air-conditioning systems at the same calibration temperature point, and is used to determine the operating status of the air-conditioning system in the future. The calibration temperature point is selected to represent the point that best represents the energy consumption operating status of the air-conditioning system in the actual scene. For example, the calibration temperature point is set to 30℃.

[0083] S104, all air-conditioning systems in the building air-conditioning system are divided into regions to obtain a plurality of air-conditioning system groups, each of which includes at least one air-conditioning system.

[0084] S105: Based on each air-conditioning system group, an evaluation table corresponding to the air-conditioning system group is obtained according to the energy consumption associated element sets of all the air-conditioning systems therein.

[0085] The evaluation table includes a first evaluation table and a second evaluation table. The first evaluation table represents the maximum energy consumption per unit area, and the second evaluation table represents the energy consumption per unit area corresponding to the calibration temperature point.

[0086] Specifically, step S105 includes:

[0087] C1. Sort the maximum energy consumption per unit area of ​​all air-conditioning systems in ascending order to obtain a first evaluation list.

[0088] C2. Sort all the working attribute values ​​of all the air-conditioning systems in ascending order to obtain a working attribute array, and use the preset window to slide and search for the jump point from the beginning of the working attribute array. The sliding step is set to 1 (if the jump point is retrieved in the current window, the step changes according to the position of the jump point). Each time the window slides, the jump index in the current window is calculated. When the jump index is greater than the preset threshold, the jump point is determined in the current window, and a sliding search is performed from the next working attribute value of the jump point until the window slides and searches all the working attribute values ​​in the working attribute array to obtain all the jump points.

[0089] Specifically, the trip index in the current window is calculated according to the following formula:

[0090]

[0091] in, is the jump index of the current window, is the difference between the maximum and minimum values ​​of the working attribute value in the current window, that is, the difference value of the current window. It is the average value of all window difference values ​​during the window sliding process, which is used for standardization , differentiate different windows, is the sum of the absolute values ​​of the differences between all adjacent working attribute values ​​in the current window, that is, the change amplitude of the current window. It is the average value of the change amplitude of all windows during the window sliding process, which is used for standardization , differentiate different windows, It is a preset weight coefficient used to balance the importance of difference value and change amplitude in the jump index.

[0092] in, , M is the number of all windows processed so far, is the change amplitude of the jth window; , is the difference value of the j-th window.

[0093] Specifically, when the trip index is greater than a preset threshold, a trip point is determined within the current window, including:

[0094] D1. Calculate the difference between each pair of adjacent working attribute values ​​in the current window: For the current window [w1,w2, ...,wn], calculate the difference between each pair of adjacent working attribute values ​​|wi+1-wi|, where i ranges from 1 to n-1, and n is the number of working attribute values ​​in the current window.

[0095] D2. Find the maximum difference point: Find the two adjacent working attribute values ​​corresponding to the maximum difference value in the calculated difference values, and determine the larger working attribute value as the potential jump point. This position is the point where the data in the window changes most dramatically, that is, the potential jump point.

[0096] D3, update window and slide: after determining the jump point of the current window, update the starting position of the window to the next position of the jump point, and continue to slide the window to find the next jump point.

[0097] C3. Based on all the jump points, the work attribute array is divided into m work attribute intervals, where m is the number of jump points plus 1.

[0098] C4. Based on each work attribute interval, the energy consumption values ​​per unit area corresponding to all the work attribute values ​​are formed into a sub-evaluation table, and the sub-evaluation tables corresponding to all the work attribute intervals are formed into a second evaluation table, and each sub-evaluation table is distinguished by a work attribute interval label.

[0099] S106, based on the evaluation table corresponding to each air-conditioning system group, determine the maximum energy consumption threshold per unit area according to the first evaluation table, including the first maximum energy consumption threshold per unit area and the second maximum energy consumption threshold per unit area; determine the temperature energy consumption threshold corresponding to each working attribute interval label according to the second evaluation table, including the first temperature energy consumption threshold and the second temperature energy consumption threshold.

[0100] Among them, the maximum energy consumption threshold per unit area is determined according to the first evaluation table, specifically including: the maximum energy consumption value per unit area corresponding to the first 25% in the first evaluation table is determined as the first maximum energy consumption value per unit area E1, and the maximum energy consumption value per unit area corresponding to the last 25% is determined as the second maximum energy consumption value per unit area E2; the temperature energy consumption threshold corresponding to each working attribute interval label is determined according to the second evaluation table, specifically including: the energy consumption value corresponding to the first 25% in the corresponding sub-evaluation table is determined as the first temperature energy consumption threshold R1, and the energy consumption value corresponding to the last 25% is determined as the second temperature energy consumption threshold R2.

[0101] In some embodiments, the determination module is specifically used to:

[0102] S107 , based on the air-conditioning system to be evaluated, according to all historical energy consumption related data of the air-conditioning system in a short period of time, determining the latest working attribute value of the air-conditioning system to be evaluated.

[0103] Among them, the short-term time period can be set to nearly one week, and can be dynamically adjusted according to actual conditions. The historical energy consumption related data of each time unit in the short-term time period is obtained, and the calculation method of step A1 is used to obtain the working attribute value of each historical energy consumption related data of the air-conditioning system to be evaluated, and all working attribute values ​​in the short-term time period are averaged to obtain the latest working attribute value of the air-conditioning system to be evaluated.

[0104] S108, in the three-dimensional energy consumption surface of the air-conditioning system to be evaluated, determine the energy consumption value E per unit area corresponding to the calibrated temperature point at the latest working attribute value, obtain the maximum energy consumption value Emax per unit area of ​​the air-conditioning system to be evaluated, and locate the evaluation table of the air-conditioning system group where the air-conditioning system to be evaluated is located according to the working attribute interval of the air-conditioning system to be evaluated and the latest working attribute value, and use the corresponding maximum energy consumption threshold per unit area and temperature energy consumption threshold to perform energy consumption evaluation.

[0105] Specifically, the energy consumption evaluation is performed using the corresponding maximum energy consumption per unit area threshold and the maximum energy consumption per unit area value of the temperature energy consumption threshold, including:

[0106] When E≤R1 and E<Emax<∞, it means that the energy consumption per unit area of ​​the air-conditioning system to be evaluated is very low, and even at the calibration temperature it is far below the limit of the high-energy-consuming air-conditioning system, and its maximum energy consumption per unit area is also far lower than the highest energy consumption of other air-conditioning systems. The energy consumption evaluation risk level of the air-conditioning system to be evaluated is low;

[0107] When R2<E<Emax and Emax>E1, it means that the maximum energy consumption per unit area of ​​the air-conditioning system to be evaluated is very high, and the energy consumption per unit area at the calibration temperature is not low. The energy consumption evaluation risk level of the air-conditioning system to be evaluated is high, and an early warning maintenance message is sent to the administrator;

[0108] Otherwise, the energy consumption assessment risk level of the air-conditioning system to be assessed is medium; for example, when R1<E≤R2 and E1<Emax≤E2 and E<Emax, it means that the maximum energy consumption per unit area of ​​the air-conditioning system to be assessed is at a medium level, and the energy consumption value at the rated temperature is also at a medium level, and the energy consumption assessment risk level of the air-conditioning system to be assessed is medium.

[0109] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0110] By determining the working attribute value of the air-conditioning system based on the historical energy consumption related data of each air-conditioning system (outdoor temperature and corresponding energy consumption per unit area), the working attribute value is introduced and combined with the historical energy consumption related data, and the energy consumption behavior of the air-conditioning system under different working conditions is considered in the fitting relationship between temperature and energy consumption, so as to obtain a three-dimensional energy consumption surface that more comprehensively displays the actual energy consumption operation of the air-conditioning system, thereby displaying the energy consumption performance of the air-conditioning system in a diversified and multi-dimensional manner to avoid large actual errors;

[0111] The energy consumption related element set (maximum unit area energy consumption value, all working attribute values ​​corresponding to the calibration temperature point and the corresponding unit area energy consumption value) is determined through the three-dimensional energy consumption surface of the air-conditioning system. According to the pre-set regional division of the building air-conditioning system and all energy consumption related element sets of each air-conditioning system group, a corresponding personalized evaluation table is generated to achieve targeted management and evaluation of air-conditioning systems in different areas, thereby improving the accuracy and personalized targeting of energy consumption evaluation.

[0112] According to the latest working property value of the air-conditioning system to be evaluated, the corresponding three-dimensional energy consumption surface is located to obtain the energy consumption value per unit area corresponding to the calibrated temperature point and the latest working property value. Combined with its maximum energy consumption value per unit area, the corresponding evaluation table is used to evaluate the energy consumption hazard level, providing scientific guidance and basis for subsequent energy consumption optimization. Accurate energy consumption evaluation and targeted system optimization data support are helpful to improve the overall energy efficiency of the building air-conditioning system.

[0113] Embodiment 2: In embodiment 1, the building area is divided according to the traditional air-conditioning system, and a targeted energy consumption assessment is performed on each area. Although this can help to effectively differentiate the management and assessment of the entire building area, the management and assessment results are not satisfactory. This is because the traditional air-conditioning system areas are artificially defined, but due to the overly complex differences in the internal operating principles of different air-conditioning systems, fixed divisions cannot adapt to the changing and complex environment, which may lead to disorder in the subsequent assessment management and inaccurate assessment results.

[0114] Therefore, the embodiments of the present application are optimized to a certain extent based on the above embodiments.

[0115] In some embodiments, in step S104, all air conditioning systems in the building air conditioning system are divided into regions to obtain a number of air conditioning system groups, specifically including:

[0116] S201, based on the three-dimensional energy consumption surface of each air conditioning system, a section in the direction of the outdoor temperature value is obtained, and the temperature sensitivity is obtained according to the outdoor temperature value on the section and its corresponding unit area energy consumption value, which is specifically:

[0117]

[0118] in, is the temperature sensitivity of the air conditioning system, is the slope value of the surface formed by two adjacent data points on the section surface, is the minimum slope value on the section, is the maximum slope value on the section, is the preset outdoor temperature value step size, and K is the total number of data points on the slice.

[0119] S202: Divide all the air-conditioning systems according to their temperature sensitivities based on a preset clustering algorithm to obtain a plurality of air-conditioning system groups.

[0120] Among them, the preset clustering algorithm can be set to a K-means clustering algorithm, which works by dividing all temperature sensitivity data into Q clusters. The center of each cluster is the mean of all data in the cluster. The temperature sensitivity of each air-conditioning system is used as input data, and the K-means clustering algorithm is executed to output Q clusters, each cluster corresponding to an air-conditioning system group.

[0121] It should be noted that the elbow rule can be used to determine the optimal number of clusters. The elbow rule selects the optimal Q value by evaluating the clustering effect under different Q values. The relevant specific process of determining the number of clusters can refer to the prior art, and the present invention will not go into details. Finally, the air-conditioning systems in each air-conditioning system group have similar temperature sensitivity characteristics, and an independent evaluation table is created for each group for subsequent energy consumption evaluation.

[0122] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0123] By dividing the area based on the temperature sensitivity obtained from the three-dimensional energy consumption curve of all air-conditioning systems, rather than relying on the traditional air-conditioning system division area, the area division is more adaptable to the changing and complex environment, which helps to reduce the disorder of subsequent evaluation management and improve the accuracy of the evaluation; using clustering algorithm for area division, the area can be dynamically adjusted according to actual data, which improves the flexibility of management, reduces human intervention and improves work efficiency;

[0124] An independent evaluation table is created for each air conditioning system group, which takes into account the similarities of the air conditioning systems within the group, making the energy consumption evaluation more accurate and helping to formulate more effective energy consumption management strategies, thereby achieving better energy conservation and emission reduction.

[0125] Embodiment 3: Since the air-conditioning system operates in a complex and changeable environment or in different working states, the nature of the linkage work between different components must be different, that is, the energy consumption correlation between the components is also different. Therefore, under the same external conditions, due to the difference in their working nature, their energy consumption must also be different.

[0126] Therefore, the embodiments of the present application are optimized to a certain extent based on the above embodiments.

[0127] In some embodiments, in step A1, the method further includes: adjusting the working attribute value of each historical energy consumption related data, specifically including:

[0128] S301, based on each time unit, calculating the ratio of the energy consumption per unit area of ​​each component to the energy consumption per unit area of ​​the air conditioning system: , is the energy consumption per unit area of ​​the nth component in the mth time unit of the air conditioning system, is the sum of the energy consumption per unit area of ​​all components of the air conditioning system. is the energy consumption per unit area of ​​the nth component in the mth time unit, and the component energy consumption ratio sequence in the mth time unit is obtained ( , ..., ).

[0129] S302, based on the component energy consumption proportion sequence, using a preset quantization function, obtain the component energy consumption linkage value in each time unit:

[0130]

[0131] in, is the linkage value of component energy consumption in the corresponding time unit, is the influence weight coefficient of the energy consumption proportion of the nth component on the component energy consumption linkage value. The influence weight value of each component is set according to the actual scenario to distinguish different component energy consumption values.

[0132] S303, based on each time unit, the working attribute value is adjusted using the component energy consumption linkage value to obtain a new working attribute value to replace the original working attribute value, specifically: W'=W×(1+α× ), W' is the new working attribute value, W is the original working attribute value, is the component energy consumption linkage value in the corresponding time unit, and α is the preset adjustment coefficient.

[0133] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0134] By quantifying the component energy consumption proportion sequence of the air-conditioning system to obtain the component energy consumption linkage value, and adaptively adjusting the working attribute value in the corresponding time unit, the energy consumption behavior of the air-conditioning system can be more finely reflected, especially the energy consumption linkage between different components; based on the adjusted working attribute value and other relevant data, the re-fitted three-dimensional energy consumption surface can more accurately reflect the actual energy consumption of the air-conditioning system, thereby improving the accuracy of energy consumption assessment, and taking into account the changes in the energy consumption correlation of different components in different time units, the three-dimensional energy consumption surface can adapt to more complex and changeable operating environments and different working conditions.

[0135] Embodiment 4: In embodiments 1 to 3, although the energy consumption of the air-conditioning system to be evaluated is evaluated by constructing a three-dimensional energy consumption curve and other methods, due to the complexity of the building air-conditioning system itself, the risk of evaluation error can be further reduced by dividing the area according to the temperature sensitivity of the air-conditioning system. However, in fact, errors are inevitable. Therefore, when the evaluation result is high or low, the general trend of air-conditioning energy consumption can be clarified. However, when the evaluation result is medium, it often has a certain ambiguity, and the energy consumption characteristics of different components and their contribution to the overall energy consumption are different. Therefore, how to provide auxiliary support for the evaluation results is extremely critical at this time.

[0136] Therefore, the embodiments of the present application are optimized to a certain extent based on the above embodiments.

[0137] In some embodiments, when the energy consumption assessment risk level of the air-conditioning system to be assessed is medium, the determination module is further configured to:

[0138] S401, obtaining a component energy consumption proportion sequence of each time unit of the air-conditioning system to be evaluated in a short period of time and its corresponding component energy consumption linkage value.

[0139] The specific method for obtaining the component energy consumption ratio sequence of each time unit and its corresponding component energy consumption linkage value may refer to the specific implementation content of Example 3, and the present invention will not elaborate on this.

[0140] S402, analyzing the energy consumption linkage values ​​of all components of the air-conditioning system to be evaluated within a short period of time, and determining a time unit corresponding to a component energy consumption linkage value having the largest difference from the energy consumption linkage values ​​of other components as a target time unit.

[0141] Specifically, by comparing the component energy consumption linkage values ​​of each time unit, find the one with the largest difference (each component energy consumption linkage value can be subtracted from the remaining component energy consumption linkage values, and the sum of all differences is used as the basis for judgment, and the time unit corresponding to the component energy consumption linkage value with the largest sum of differences is selected) as the target time unit.

[0142] S403, comparing the component energy consumption ratio sequence of the target time unit with the component energy consumption ratio sequence of other time units, and determining the components with difference values ​​greater than a preset difference threshold as a key component set.

[0143] For example, assume that the air-conditioning system to be evaluated has 5 time units in a short period of time, and each time unit has a component energy consumption ratio sequence, which contains the energy consumption ratio of each component in the air-conditioning system to be evaluated, and the target time unit has been determined to be the 3rd time unit. Furthermore, the component energy consumption ratio sequence of the 3rd time unit is compared one by one with the component energy consumption ratio sequences of the other 4 time units, and the comparison method is to calculate the difference in energy consumption ratio of the same component in different time units.

[0144] For example, for component A, the difference between its energy consumption ratio in the third time unit and the energy consumption ratio in the other four time units is calculated to obtain four difference values. The preset difference threshold is set to 10%. If the difference between the energy consumption ratio of component A in the third time unit and the other time units exceeds 10%, component A is determined to be a key component.

[0145] Similarly, all components in the air-conditioning system to be evaluated are compared and judged as above, and all components whose energy consumption ratio in the third time unit differs from other time units by more than the preset difference threshold are combined to obtain the key component set in the target time unit. This key component set reflects which components have significantly changed their energy consumption ratio in the target time unit, which may have a potential impact on the overall energy consumption of the air-conditioning system. Therefore, in subsequent energy consumption optimization or research, these key components can be focused on to propose more targeted optimization suggestions or research directions.

[0146] S404: Calculate the working attribute value within the target time unit using the method of A1, determine it as the calibration section value, and generate an update instruction to transmit to the evaluation table determination module.

[0147] In some embodiments, the evaluation table determination module is further configured to:

[0148] When an update instruction is received, jump to step S201 to update the sections and temperature sensitivity of all air-conditioning systems, specifically including: using the received calibrated section value as the fixed working attribute value on the Y-axis to obtain a calibrated section in the direction of the outdoor temperature value, and the calibrated section is a section in the three-dimensional energy consumption surface whose working attribute value is the calibrated section value.

[0149] According to the new temperature sensitivity of all air-conditioning systems, step 202 is executed to obtain a new air-conditioning system group, steps S105 to S106 are executed to obtain a new evaluation table, and a secondary verification instruction is generated and transmitted to the determination module.

[0150] In some embodiments, when the determination module receives the secondary verification instruction, step S108 is executed to obtain the final evaluation risk level of the air-conditioning system to be evaluated, attach its key component set, generate an evaluation report and send it to the administrator for further energy-saving research and optimization.

[0151] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0152] According to the initial evaluation results of the air-conditioning system to be evaluated, as well as the component energy consumption proportion sequence and its corresponding component energy consumption linkage value in the corresponding short-term period, the conditions for the regional division of all air-conditioning systems are adaptively adjusted to make the adjustment rules adapt to the actual operating status characteristics of the air-conditioning system to be evaluated, and further evaluate and verify the air-conditioning system to be evaluated, so as to improve the accuracy of the evaluation, avoid the potential errors existing in the ambiguity of the initial evaluation, and enhance the adaptability of the energy consumption evaluation of the air-conditioning system to be evaluated;

[0153] By analyzing all energy consumption proportion sequences and component energy consumption linkage values ​​in a short period of time, the key component set that is most likely to be further optimized for the energy consumption operation of the air-conditioning system to be evaluated is identified, further avoiding the ambiguity of the energy consumption assessment hazard level and providing targeted data recommendations for subsequent post-energy optimization or research.

[0154] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An air conditioning system energy consumption evaluation and diagnosis system, characterized in that: It includes a collection module, an energy consumption fitting module, an evaluation table determination module, and a determination module; The collection module is used to: S101, collect historical energy consumption related data of each time unit of all air-conditioning systems in the building air-conditioning system within a preset period of time, each historical energy consumption related data includes a unit area energy consumption value and an outdoor temperature value corresponding to each time unit; The energy consumption fitting module is used to: S102, based on each air conditioning system, obtain a three-dimensional energy consumption surface according to all its historical energy consumption related data and the working attribute value determined by each historical energy consumption related data; The working attribute value determined by each historical energy consumption associated data is specifically: A1. Based on the energy consumption generated by each time node component in each time unit, the working attribute value determined by each historical energy consumption associated data is calculated according to the following formula: ； Where W is the working attribute value corresponding to the historical energy consumption related data, is the fluctuation index of energy consumption generated by components at all time nodes in the corresponding time unit, is the fluctuation index of the outdoor temperature value at all time nodes in the corresponding time unit, is the energy consumption-temperature covariance index, N is the total number of all time nodes in the time unit, is the energy consumption value generated by the component at the i-th time node, is the average energy consumption of the component within a time unit, The outdoor temperature value at the i-th time node, The average outdoor temperature value within the time unit; The S102 specifically includes: B1. Based on the working attribute values ​​corresponding to all historical energy consumption related data, all data points of the air conditioning system (outdoor temperature value, working attribute value, energy consumption per unit area) are obtained; B2. Use the preset fitting algorithm to fit all data points to obtain a three-dimensional energy consumption surface, where the X-axis coordinate is the outdoor temperature value after fitting, the Y-axis coordinate is the working attribute value after fitting, and the Z-axis coordinate is the three-dimensional area energy consumption value after fitting; The evaluation table determination module is used for: S103, based on the three-dimensional energy consumption surface of each air-conditioning system, determining its energy consumption associated element set, the energy consumption associated element set includes the maximum unit area energy consumption value, the calibration temperature point, all working attribute values ​​corresponding to the calibration temperature point, and the unit area energy consumption value corresponding to each working attribute value in the three-dimensional energy consumption surface; S104, all air-conditioning systems in the building air-conditioning system are divided into regions to obtain a number of air-conditioning system groups; S105, based on each air-conditioning system group, according to the energy consumption associated element set of all its air-conditioning systems, a corresponding evaluation table is obtained; S106, based on the evaluation table corresponding to each air-conditioning system group, the maximum unit area energy consumption threshold and the temperature energy consumption threshold are determined; The determination module is used for: S107, based on the air-conditioning system to be evaluated, according to all its historical energy consumption related data in a short period of time, determining the latest working attribute value of the air-conditioning system to be evaluated; S108, in the three-dimensional energy consumption surface of the air-conditioning system to be evaluated, determining the unit area energy consumption value E corresponding to the calibrated temperature point at the latest working attribute value, obtaining the maximum unit area energy consumption value Emax of the air-conditioning system to be evaluated, and locating to the evaluation table of the air-conditioning system group where the air-conditioning system to be evaluated is located, and using the corresponding maximum unit area energy consumption threshold and temperature energy consumption threshold to perform energy consumption evaluation.

2. The air conditioning system energy consumption evaluation and diagnosis system according to claim 1, characterized in that: The preset time period is set to the past two years, each time unit is set to every day, each air-conditioning system is composed of six components: a chiller, a cooling tower, a cooling water pump, a refrigeration water pump, an air-conditioning unit and an air-conditioning system terminal. The energy consumption per unit area in each time unit of the air-conditioning system is: the ratio of the sum of the energy consumption generated by all time node components in the time unit to the area value covered by the air-conditioning system, and the outdoor temperature value is: the average outdoor temperature value in the time unit.

3. The air conditioning system energy consumption evaluation and diagnosis system according to claim 1, characterized in that: The evaluation table of the air conditioning system group includes a first evaluation table and a second evaluation table, the first evaluation table represents the maximum energy consumption per unit area, and the second evaluation table represents the energy consumption per unit area corresponding to the calibration temperature point; The S105 specifically includes: C1. Sort the maximum energy consumption per unit area of ​​all air-conditioning systems in ascending order to obtain a first evaluation list; C2. Sort all the working attribute values ​​of all the air-conditioning systems in ascending order to obtain a working attribute array, use a preset window to slide and search for a trip point from the beginning of the working attribute array, set the sliding step to 1, calculate the trip index in the current window each time it slides, and when the trip index is greater than the preset threshold, determine the trip point in the current window, and perform a sliding search from the next working attribute value of the trip point until the window slides and searches all the working attribute values ​​in the working attribute array to obtain all the trip points; C3. Based on all the trip points, the work attribute array is divided into m work attribute intervals, where m is the number of the trip points plus 1; C4. Based on each work attribute interval, the energy consumption per unit area corresponding to all the work attribute values ​​is formed into a sub-evaluation table, and the sub-evaluation tables corresponding to all the work attribute intervals are formed into a second evaluation table, and each sub-evaluation table is distinguished by a work attribute interval label; The jump index in the current window is calculated according to the following formula: ； is the jump index of the current window, is the difference between the maximum and minimum values ​​of the working attribute value in the current window, that is, the difference value of the current window. is the average value of all window difference values ​​during the window sliding process, is the sum of the absolute values ​​of the differences between all adjacent working attribute values ​​in the current window, that is, the change amplitude of the current window. is the average value of the change amplitude of all windows during the window sliding process, is the preset weight coefficient.

4. The air conditioning system energy consumption evaluation and diagnosis system according to claim 3, characterized in that: The S106 specifically includes: based on the evaluation table corresponding to each air conditioning system group, determining the maximum energy consumption threshold per unit area according to the first evaluation table, including the first maximum energy consumption threshold per unit area and the second maximum energy consumption threshold per unit area, and determining the temperature energy consumption threshold corresponding to each working attribute interval label according to the second evaluation table, including the first temperature energy consumption threshold and the second temperature energy consumption threshold; The maximum energy consumption per unit area corresponding to the first 25% in the first evaluation table is determined as the first maximum energy consumption per unit area E1, and the maximum energy consumption per unit area corresponding to the last 25% is determined as the second maximum energy consumption per unit area E2; the energy consumption values ​​corresponding to the first 25% in the corresponding sub-evaluation table are determined as the first temperature energy consumption threshold R1, and the energy consumption values ​​corresponding to the last 25% are determined as the second temperature energy consumption threshold R2; In S108, energy consumption evaluation is performed using the corresponding maximum energy consumption threshold per unit area and temperature energy consumption threshold, specifically including: When E≤R1 and E<Emax<∞, the energy consumption assessment risk level of the air-conditioning system to be assessed is low; When R2<E<Emax and Emax>E1, the energy consumption evaluation risk level of the air-conditioning system to be evaluated is high, and an early warning maintenance message is sent to the administrator; Otherwise, the energy consumption assessment risk level of the air-conditioning system to be assessed is medium.

5. The air conditioning system energy consumption evaluation and diagnosis system according to claim 4, characterized in that: In S104, all air conditioning systems in the building air conditioning system are divided into regions to obtain a number of air conditioning system groups, specifically including: S201, based on the three-dimensional energy consumption surface of each air conditioning system, a section in the direction of the outdoor temperature value is obtained, and the temperature sensitivity is obtained according to the outdoor temperature value on the section and its corresponding unit area energy consumption value, which is specifically: ； in, is the temperature sensitivity of the air conditioning system, is the slope value of the surface formed by two adjacent data points on the section surface, is the minimum slope value on the section, is the maximum slope value on the section, is the preset outdoor temperature value step size, K is the total number of data points on the slice; S202: Divide all the air-conditioning systems into several air-conditioning system groups according to the temperature sensitivity of all the air-conditioning systems based on a preset clustering algorithm.

6. The air conditioning system energy consumption evaluation and diagnosis system according to claim 5, characterized in that: In the above A1, it also includes: adjusting the working attribute value of each historical energy consumption related data, specifically including: S301, based on each time unit, calculate the ratio of the unit area energy consumption value of each component to the unit area energy consumption value of the air conditioning system: , is the energy consumption per unit area of ​​the nth component in the mth time unit of the air conditioning system, is the sum of the energy consumption per unit area of ​​all components of the air conditioning system. is the energy consumption per unit area of ​​the nth component in the mth time unit, and the component energy consumption ratio sequence in the mth time unit is obtained ; S302, based on the component energy consumption proportion sequence, using a preset quantization function, obtain the component energy consumption linkage value in each time unit: ； in, is the linkage value of component energy consumption in the corresponding time unit, is the weight coefficient of the energy consumption proportion of the nth component on the component energy consumption linkage value; S303: Based on each time unit, the working attribute value is adjusted by using the component energy consumption linkage value, and a new working attribute value is obtained to replace the original working attribute value.

7. The air conditioning system energy consumption evaluation and diagnosis system according to claim 6, characterized in that: When the energy consumption evaluation risk level of the air-conditioning system to be evaluated is medium, the determination module is further used to: S401, obtaining a component energy consumption proportion sequence and its corresponding component energy consumption linkage value of each time unit of the air-conditioning system to be evaluated in a short period of time; S402, analyzing the energy consumption linkage values ​​of all components of the air-conditioning system to be evaluated within a short period of time, and determining a time unit corresponding to a component energy consumption linkage value having the largest difference with other component energy consumption linkage values ​​as a target time unit; S403, comparing the component energy consumption ratio sequence of the target time unit with the component energy consumption ratio sequence of other time units, and determining the components whose difference values ​​are greater than a preset difference threshold as a key component set; S404, using the work attribute value in the target time unit calculated in A1, determining it as the calibration section value, and generating an update instruction to transmit to the evaluation table determination module; The evaluation table determination module is also used for: When receiving the update instruction, jump to step S201 to update the slices and temperature sensitivity of all air-conditioning systems, specifically including: using the received calibrated slice value as the fixed working attribute value on the Y axis, obtaining the calibrated slice in the direction of the outdoor temperature value, the calibrated slice is a slice whose working attribute value is the calibrated slice value in the three-dimensional energy consumption surface; According to the new temperature sensitivity of all air-conditioning systems, step 202 is executed to obtain a new air-conditioning system group, steps S105 to S106 are executed to obtain a new evaluation table, and a secondary verification instruction is generated and transmitted to the determination module.

8. The air conditioning system energy consumption evaluation and diagnosis system according to claim 7, characterized in that: When the determination module receives the secondary verification instruction, step S108 is executed to obtain the final evaluation risk level of the air-conditioning system to be evaluated, attach its key component set, generate an evaluation report and send it to the administrator.

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