Method and system for adjusting and analyzing annual benchmark energy consumption values ​​of buildings caused by climate

Abstract

The present invention relates to the technical field of building energy management, and specifically discloses a method and system for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate, comprising: S1, obtaining meteorological data and meteorological information of a target building through a weather forecast terminal; S2, providing a database, and establishing a communication connection with the weather forecast terminal; the database is used to store the meteorological data, meteorological information and historical annual benchmark energy consumption values ​​of the target building; S3, predicting or adjusting the annual benchmark energy consumption value of the target building in the next year according to the meteorological data, meteorological information and historical annual benchmark energy consumption values. The present invention can improve the efficiency of analyzing the annual benchmark energy consumption value of the target building.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy management, and in particular to a method and system for adjusting and analyzing annual benchmark energy consumption values ​​of buildings caused by climate. Background Art

[0002] The energy consumption benchmark value of a building refers to the standard value for measuring the energy consumption of a building under certain conditions, which is used to evaluate the energy efficiency and energy-saving effect of the building. In the contract energy management project, accurately determining the energy consumption benchmark value of the building is an important basis for evaluating the energy-saving effect and allocating energy-saving benefits. At present, the widely used method for determining the energy consumption benchmark value is mainly determined by the average energy consumption in the previous few years of the energy-saving transformation of the contract energy management project. If the transformation-related units have objections to the energy consumption benchmark value, the energy consumption benchmark is jointly approved by the owner unit of the project implementing the property management unit, the energy-saving service unit, and the energy-saving audit agency, taking into full account the peak-valley-flat electricity price standard and the natural increase (decrease) of the annual energy consumption of the project, and agreeing on the energy consumption benchmark adjustment rules in the contract (including but not limited to the increase and decrease of energy-consuming equipment, increase and decrease of personnel, changes in heating and cooling area, changes in equipment capacity, working hours, etc.). This not only helps to accurately reflect the true effect of energy-saving measures and avoid unfair evaluations caused by external variables, but also promotes the recognition and trust of all parties in energy-saving results, and ensures the transparency and rationality of energy-saving benefit distribution, thereby encouraging all parties to actively participate and promote the continuous optimization and improvement of energy-saving projects.

[0003] Commonly used methods for adjusting the annual benchmark energy consumption value of buildings include univariate time series method, support vector machine and other methods. Regardless of whether the univariate time series method or support vector machine is used, the data analysis is based on factors that directly affect the annual benchmark energy consumption value of buildings, such as building envelope structure, building orientation and layout, building use nature, heating and cooling systems in buildings, building lighting systems, common equipment and electrical appliances used in buildings, and the age and maintenance status of buildings to analyze the annual benchmark energy consumption value of buildings. Although the annual benchmark energy consumption value of buildings can be accurately obtained by analyzing the annual benchmark energy consumption value of buildings through direct factors such as structures and equipment that are closely related to buildings, there are many direct factors related to buildings, the amount of data is large, the calculation is relatively complex, and the calculation time is long.

[0004] The support vector machine is more sensitive to missing data, has a slow learning speed for large-scale samples, and takes a long time to model and predict, which is inefficient. The advantage of the multivariate nonlinear regression method is that it has a fast prediction speed, is insensitive to missing data, and has large errors. Summary of the invention

[0005] Aiming to improve the efficiency of the analysis of the annual benchmark energy consumption value of the target building, the first scheme provides an adjustment analysis method for the annual benchmark energy consumption value of the building caused by climate.

[0006] A method for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate, comprising: S1, obtaining meteorological data and meteorological information of a target building through a weather forecast terminal; S2, providing a database, and establishing a communication connection with the weather forecast terminal; the database is used to store the meteorological data, meteorological information and historical annual benchmark energy consumption values ​​of the target building; S3, predicting or adjusting the annual benchmark energy consumption value of the target building in the coming year according to the meteorological data, meteorological information and historical annual benchmark energy consumption values, dividing the meteorological data into extreme meteorological data and non-extreme meteorological data, obtaining the season corresponding to the extreme weather, calculating the average value of the non-extreme meteorological data of the season, and taking the average value of the non-extreme meteorological data of the season as the average meteorological data of the season.

[0007] Beneficial effects: Compared with the existing technology, firstly, this solution analyzes the annual benchmark energy consumption value of the building by obtaining the factors that indirectly affect the annual benchmark energy consumption value of the building, and the weather data can be obtained from the weather forecast terminal, thereby reducing the amount of data analyzed and shortening the calculation time.

[0008] Secondly, affected by global warming, extreme weather occurs frequently, and in a certain year, the number of hot days or cold days is longer and lasts longer, which will directly affect the use time and frequency of the target building's cooling / heating equipment, thereby affecting the target building's energy consumption benchmark value. These devices are the main manifestation of the target building's annual energy consumption differences. Therefore, analyzing the target building's annual energy consumption benchmark value through weather data can ensure the accuracy of the target building's annual energy consumption benchmark value analysis.

[0009] Finally, this solution does not need to spend a lot of time on building various models to accurately obtain and analyze historical data. This solution obtains meteorological data from the weather forecast terminal for analysis, and the weather forecast terminal comes from official weather forecast data, which makes the results more real and effective, and the data is clean. Compared with other models or multivariate linear regression, it is used for calculation, the calculation speed is faster and more efficient. By making corrections to the results, the benchmark energy consumption value for a certain year in the future can be adjusted and analyzed in a short time and at a low cost.

[0010] Preferably, the method further includes: S301, correcting the annual benchmark energy consumption value of the building according to the historical annual benchmark energy consumption value; specifically, E=E b k; E is the revised benchmark energy consumption value of the building; E b is the historical benchmark energy consumption value of the building; k is the correction coefficient of the benchmark energy consumption value.

[0011] Preferably, the meteorological data includes temperature, humidity and wind speed; and further includes: S302, obtaining a correction coefficient k of the energy consumption reference value, specifically,

[0012]

[0013] Where k is the correction coefficient of the energy consumption benchmark value, T x-1 is the average outdoor air temperature of the previous year, T x is the average outdoor air temperature of the year; H x-1 is the average outdoor air humidity in the previous year, H x is the average outdoor air humidity of the year; W x-1 is the average outdoor wind speed in the previous year, W x is the average outdoor wind speed for the year; HDD x-1 Total degree days in the previous year; HDD x is the total number of degree days in the current year; x is the total number of years, and x≥2.

[0014] Preferably, the meteorological information includes the number of days with extreme weather and the number of days in each season.

[0015] Preferably, S2 also includes a first method for identifying extreme weather, which is used to receive prompt word information from a weather forecast terminal in real time. If the prompt word information from the weather forecast terminal is received, the weather on that day is judged to be extreme weather; if not, the weather on that day is non-extreme weather; wherein the prompt word information includes extreme, tropical cyclone, heat wave, tornado, thunderstorm, blizzard, sandstorm and tsunami.

[0016] Preferably, S2 also includes a second method for identifying extreme weather. If the meteorological data, wind speed, temperature, and humidity of the day are higher or lower than 90% of the median value of the historical wind speed, historical temperature, and historical humidity of at least 20 years stored in the database, the weather of the day is considered to be extreme weather.

[0017] The second scheme provides an adjustment and analysis system for the climate-induced annual benchmark energy consumption value of a building, which is used to execute the adjustment and analysis method for the climate-induced annual benchmark energy consumption value of a building described in the first scheme, including a data analysis module, the data analysis module includes an electronic device, the electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, when the processor executes the computer program, the electronic device executes the adjustment and analysis method for the climate-induced annual benchmark energy consumption value of a building.

[0018] Preferably, it also includes a data collection module, which includes a weather forecast terminal, and the weather forecast terminal is used to collect weather data.

[0019] Preferably, the data collection module further comprises a collection component and a mounting rod, the mounting rod is close to the target building, and the collection component is mounted on the mounting rod; the collection component is used to collect weather data outside the target building in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flowchart of a method for adjusting and analyzing the annual baseline energy consumption value of a building caused by climate according to at least one embodiment;

[0021] Figure 2 A schematic diagram of the structure of a system for adjusting and analyzing the annual baseline energy consumption value of a building caused by climate according to at least one embodiment;

[0022] Figure 3 The present invention is a schematic diagram of the electronic device structure of a system for adjusting and analyzing the annual baseline energy consumption value of a building caused by climate according to at least one embodiment. DETAILED DESCRIPTION

[0023] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0024] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the present invention belongs.

[0025] The reference numerals in the drawings of the specification include:

[0026] A system 100 for adjusting and analyzing the annual baseline energy consumption value of a building caused by climate, a processor 101, an input device 102, an output device 103, a memory 104, a bus 105, and a computer program 1041.

[0027] Embodiment 1

[0028] like Figure 1 As shown, this embodiment provides a method for analyzing and adjusting the annual baseline energy consumption value of a building caused by climate.

[0029] S1, obtain the meteorological data and meteorological information of the target building through the weather forecast terminal.

[0030] Specifically, in this embodiment, the weather forecast terminal is a terminal of the weather forecast bureau, which collects data of the area where the target building is located as the meteorological data and meteorological information of the target building. In this way, it is only necessary to receive the official weather data of the area, store and count the weather data of the area, which is highly practical and low in cost. Meteorological data includes daily average temperature, daily average humidity, and daily average humidity. Meteorological information includes information on extreme weather and the number of days in each season. Extreme weather information includes the type of extreme weather, the time of occurrence, and the number of days it lasts.

[0031] S2, a database is provided, and a communication connection is established between the database and the weather forecast terminal; the database is used to store the meteorological data, meteorological information and historical annual benchmark energy consumption values ​​of the target building.

[0032] Specifically, a database is provided, and a one-way data connection is established between the database and the weather forecast terminal, that is, the weather forecast terminal sends the data to be stored to the database in a one-way manner. The database stores the historical annual benchmark energy consumption value, annual energy consumption value, outdoor daily average temperature, outdoor daily average humidity, outdoor daily average wind speed, heating degree days and cooling degree days of the target building for several years. In other embodiments, a collection device can be set in an open space or at the highest point outside the target building, and there is no obstruction within a range of 100 meters around the collection device. The collection device is used to collect the daily average temperature, daily average humidity and daily average wind speed. The daily average temperature, daily average humidity and daily average wind speed are transmitted to the weather forecast terminal, which is sorted and analyzed by the weather forecast terminal and then sent to the database for storage; the weather forecast terminal is a server that is self-set according to the collection device.

[0033] S301, specifically, the outdoor daily average temperature, daily average humidity, daily average wind speed, heating degree days and cooling degree days of the target building are counted on an annual basis to obtain the annual outdoor air temperature average value T, the annual outdoor air humidity average value H and the annual outdoor wind speed average value. In addition, the heating degree days and cooling degree days are counted to obtain the annual number of days (heating degree days + cooling degree days) HDD.

[0034] The calculation formula for baseline energy consumption is:

[0035] E=E b k (1)

[0036] In formula (1), E is the revised benchmark energy consumption value of the building, equivalent to equivalent electricity, unit: kWh; E b is the building benchmark energy consumption value, equivalent to equivalent electricity, unit: kWh; k is the correction coefficient of the energy consumption benchmark value. S302, specifically,

[0037]

[0038] In formula (2), T x-1 is the average outdoor air temperature of the previous year, T x is the average outdoor air temperature of the year; H x-1 is the average outdoor air humidity in the previous year, H x is the average outdoor air humidity of the year; W x-1 is the average outdoor wind speed in the previous year, W x is the average outdoor wind speed for the year; HDD x-1 Total degree days in the previous year (heating degree days + cooling degree days); HDD xis the total degree days of the year (heating degree days + cooling degree days); X is the total number of years, and X≥2.

[0039] Specifically, when X=2, the formula is expressed as the ratio of the temperature, humidity, wind speed, odd number of degree days in the first year to the temperature, humidity, wind speed, odd number of degree days in the second year. When X=3, the formula is expressed as the ratio of the temperature, humidity, wind speed, odd number of degree days in the first year to the temperature, humidity, wind speed, odd number of degree days in the second year, and the ratio of the temperature, humidity, wind speed, odd number of degree days in the second year to the temperature, humidity, wind speed, odd number of degree days in the third year, and the average of the above two ratios is taken. In this embodiment, preferably, X=3. When X=3, reference can be made to Test Example 1, which has a small amount of calculated data, but the error rate of the k value is less than 5%.

[0040] Degree days include cooling degree days and heating degree days. Degree days refer to the sum of outdoor temperatures below / above a base temperature during the heating / cooling season. In the heating season, if the building temperature is below 15°C, the building generally needs to be heated. In the cooling season, if the base temperature is above 28°C, the building generally needs to be cooled. Such temperature thresholds help to achieve efficient energy utilization while ensuring indoor environmental comfort. Through clear temperature trigger points, unnecessary energy consumption can be avoided, ensuring that the heating or cooling system is enabled only when the indoor temperature is really needed to be adjusted, thereby improving the comfort experience of the occupants and achieving the goal of energy conservation and emission reduction. It is also conducive to stabilizing the energy consumption cost of the building and improving the efficiency of energy management.

[0041] S2 specifically also includes, before calculating formula (2), optimizing the annual average temperature, annual average humidity and annual average wind speed according to the duration of extreme weather and the meteorological data of extreme weather.

[0042] Specifically, in order to facilitate the acquisition and analysis of data, this embodiment will calculate the meteorological data of extreme weather when accepting the official meteorological data as the meteorological data of this embodiment, thereby causing noise interference to the correction coefficient k value of the entire energy consumption benchmark value. When calculating the annual benchmark energy consumption value, extreme weather should be avoided as data noise to interfere with the calculation of the annual benchmark energy consumption value of the building.

[0043] In this embodiment, there are two methods for identifying whether the weather is extreme weather. The first method for identifying extreme weather is to obtain real-time prompt word information released by the official meteorological data center. The prompt word information includes the occurrence of extreme, tropical cyclones, heat waves, tornadoes, thunderstorms, blizzards, sandstorms and tsunamis. If the prompt word information appears, the weather on that day is considered to be extreme weather. The second method for identifying extreme weather is that if the meteorological data of the day, wind, temperature, and humidity are compared with the median value of at least 20 years of historical wind, historical temperature, and historical humidity stored in the database, it exceeds or is lower than 90%, then the weather on that day is considered to be extreme weather. In this way, when it is difficult to judge extreme weather, calculations can be performed in this way to obtain real data about extreme weather.

[0044] According to the Energy Saving Guidelines for Energy Conservation Renovation of Public Buildings compiled and issued by the General Office of the Ministry of Housing and Urban-Rural Development in July 2017, when the main energy consumption influencing factors of a building change by more than 5%, energy consumption correction can be made. For renovation projects that do generate additional energy saving rates due to energy consumption, the comprehensive energy saving rate generated by the correction cannot exceed 2%. In the prior art, E = E b k. Where E is the revised benchmark energy consumption value of the building, equivalent to equivalent electricity, unit: kWh; E b is the building benchmark energy consumption value, equivalent to equivalent electricity, unit: kWh; k is the correction coefficient of the energy consumption benchmark value. In this embodiment, when k≥0.05, the annual benchmark energy consumption value of the target building can be adjusted accordingly.

[0045] The beneficial effects of this embodiment

[0046] At present, the existing technology for adjusting and analyzing the annual energy consumption benchmark value of buildings focuses more on the structure or improvement of the target building itself, the number of equipment used inside the target building, and the energy consumption of the target building at different times. This is because these factors directly affect the annual energy consumption benchmark value of the building.

[0047] In this embodiment, first of all, the adjustment and analysis of the annual energy consumption benchmark value of the target building is more based on the factors that indirectly affect the building energy consumption benchmark value to analyze the target building energy consumption benchmark value, such as the outdoor temperature, humidity and wind speed of the target building. This is because in the current common buildings, such as residential buildings, office buildings, etc., when the energy consumption of electrical equipment such as computers, televisions, and light tubes in the buildings is not increased / decreased on a large scale, the annual energy consumption is not much different. For example, refrigeration equipment and heating equipment consume more energy than other ordinary equipment. In addition, affected by global warming, extreme weather occurs frequently, and in a certain year, the number of high temperature days or cold days is long and lasts for a long time, which will directly affect the use time and frequency of the target building's refrigeration / heating equipment, thereby interfering with the target building's annual benchmark energy consumption value and easily increasing it. Therefore, the annual energy consumption benchmark value of the target building is analyzed by analyzing the outdoor temperature, humidity and wind speed of the target building; at the same time, it is also analyzed according to the total degree days (cooling / heating degree days), and the number of days the heating / cooling equipment of the target building is directly obtained through the degree days. By correlating indirect factors with direct factors, the accuracy of the analysis of the annual energy consumption benchmark value of the target building is improved.

[0048] Secondly, the analysis method of this implementation has a small amount of calculation, is fast and simple. Generally, the annual average values ​​of temperature, wind speed and humidity in the area where the target building is located can be obtained from the existing weather forecast terminal, which reduces the calculation of the data volume. It only needs to count the total number of degree days to analyze the annual energy consumption benchmark value of the target building, which can be used to estimate the annual energy consumption benchmark value of the target building in the next year; when the k value is large, the annual energy consumption benchmark value of the target building can be adjusted.

[0049] Finally, the average outdoor temperature, humidity and wind speed of the target building obtained by the collection device can more accurately reflect the annual benchmark energy consumption of the target building, and further improve the accuracy of the statistical annual benchmark energy consumption value of the building.

[0050] Test Example 1

[0051] This test example is used to test the correction coefficient k of the energy consumption benchmark value provided in Example 1 to verify the accuracy of the k value. The database stores meteorological data and meteorological information of the target building area for 4 years from 2019 to 2022.

[0052] Table 1 Annual average meteorological data of the target building areas from 2019 to 2022

[0053] 2019 2020 2021 2022 Annual average temperature (℃) 20.1 20.5 19.7 19.2 Annual average humidity (%) 74.1 79.9 76.8 75.7 Annual average wind speed (m / s) 3.77 3.82 3.76 3.83 Heating degree days (days) 87 94 97 102 Cooling degree days (days) 113 102 93 104 Building benchmark energy consumption value Eb (kWh) 2701231 2741360 2776520 2420340

[0054] As shown in Table 1, Table 1 provides the annual average meteorological data of the target building area for 4 years from 2019 to 2022. According to formula (2) described in Example 1, k=1.01 is calculated through the data from 2019 to 2021, that is, x=3. The energy consumption value in 2022 is E=2546053.438. k*Eb / E=96.01%. 1.96.01%<5%, compared with the true value, the error value is less than 5% of the true value, within the error range, which fully shows that compared with the prior art, which directly calculates the direct heat of the building, the formula provided in this test example can have higher accuracy with a small amount of calculation.

[0055] In summary, the formula (2) described in the first embodiment is used to calculate the correction coefficient k of the energy consumption reference value with high accuracy and fast calculation speed.

[0056] Embodiment 2

[0057] Different from the first embodiment, in this embodiment, the correction coefficient of the energy baseline value is further corrected to obtain a more accurate corrected baseline energy consumption value of the target building.

[0058] At present, as the global climate gradually warms, extreme weather events occur frequently, such as heat waves, droughts, rainstorms, hurricanes, etc. The frequent occurrence of extreme events will further affect the annual benchmark energy consumption of the target building, and will also affect the predicted annual benchmark energy consumption of the target building in the next year. As an unstable and unavoidable factor, extreme events are always dynamically affecting the annual benchmark energy consumption of the target building. In addition, the longer the extreme weather lasts, the more complicated the adjustment and analysis of the annual benchmark energy consumption value of the target building will be.

[0059] When extreme weather occurs, the weather forecast terminal sends meteorological information to the database, including the duration of the extreme weather, temperature, humidity and wind speed. The database is also used to count the extreme weather that occurs in the target building every year. The database summarizes the extreme weather that occurs in the target building every year into an extreme weather module, and further divides it according to different seasons. The extreme weather that occurs in the cold season is divided into the first extreme weather submodule, and the extreme weather that occurs in the hot season is divided into the second extreme weather submodule, that is, the first extreme weather module includes the first extreme weather submodule and the second extreme weather submodule.

[0060] Specifically, the first extreme weather module includes the temperature, humidity, wind speed and duration of extreme weather. The temperature, humidity, wind speed and duration of the weather of the first sub-extreme weather module and the second sub-extreme weather module of each year in the past years are analyzed, and a neural network model, such as a convolutional neural network model, is used to predict the temperature, humidity, wind speed and duration of extreme weather in the next year. After obtaining the prediction result of extreme weather, the prediction result is that the similarity rate of extreme weather occurring in the next year relative to historical extreme weather is Ω, 0≤Ω≤1. In this embodiment, the neural network model has been trained, and its training and establishment can be set according to conventional means of the prior art.

[0061] This will result in a more accurate K value to accurately analyze or adjust the annual benchmark energy consumption value of the target building.

[0062] This embodiment is a brief description, and for matters not covered, please refer to the first embodiment.

[0063] Embodiment 3

[0064] Different from the above-mentioned embodiment, this embodiment provides a system for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate. A system for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate includes:

[0065] The data acquisition module includes a collection component and a mounting rod. The mounting rod is fixedly installed on the outside of the target building, and the collection component is installed on the mounting rod.

[0066] Specifically, the collection component includes a temperature and humidity sensor and an anemometer. The collection component is installed on a mounting rod, which is a prior art, and a person skilled in the art can install it according to actual needs. The mounting rod is fixedly installed in an unobstructed and ventilated position outside the target building. The collection module is used to collect weather data outside the target building in real time, and the environmental parameters include temperature, humidity and wind speed.

[0067] like Figure 2 As shown, the data analysis module includes an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the electronic device implements a method for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate in any of the above embodiments.

[0068] Specifically, Figure 3As shown, the electronic device may include: one or more processors 101, one or more input devices 102, one or more output devices 103, one or more memories 104, and a computer program stored in the memory 104 and executable on the processor. The processor 101, input device 102, output device 103, and memory 104 are interconnected via a bus 105. The memory 104 is used to store a computer program, the computer program includes program instructions, and the processor 101 is configured to call the program instructions to execute the method steps described in the above method embodiment.

[0069] It should be understood that in this embodiment, the processor 101 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0070] The input device 102 may include a keyboard, etc., and the output device 103 may include a display (LCD, etc.), a speaker, etc.

[0071] The memory 104 may include a read-only memory and a random access memory, and provides instructions and data to the processor 101. A portion of the memory 104 may also include a non-volatile random access memory. For example, the memory 104 may also store information on the device type.

[0072] In a specific implementation, the processor 101, input device 102, and output device 103 described in the embodiment of the present invention can execute the implementation method described in the embodiment of a method and system for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate provided in the embodiment of the present invention, which will not be repeated here.

[0073] It should be noted that for a more specific description of the workflow of the electronic device and the adjustment analysis method for the climate-induced annual benchmark energy consumption value of the building, please refer to the aforementioned method embodiment section, which will not be repeated here.

[0074] Embodiment 4

[0075] Different from the previous embodiment, in this embodiment, the memory described in this embodiment should be understood in a broad sense, and can be not only a hardware component for temporarily storing data in a computer system, but also a physical medium that can store digital information and be read by a computer. These media can be permanent or temporary, including but not limited to hard disks and solid-state drives.

[0076] Specifically, the memory may be an internal storage unit of the electronic device described in any embodiment, such as a hard disk or memory of the system. The memory may also be an external storage device of the system, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the system. Further, the memory may also include both an internal storage unit of the system and an external storage device. The memory is used to store the computer program and other programs and data required by the system. The memory may also be used to temporarily store data that has been output or is to be output.

[0077] The memory includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0078] This embodiment is a brief description, and the contents not involved can refer to the previous embodiments.

[0079] In this specification, a lot of specific details are described. However, it is understood that embodiments of the present invention can be put into practice without these specific details. In some examples, known methods, systems and techniques are not shown in detail, so as not to obscure the understanding of this specification. In the description of this specification, the description of reference terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, methods, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this specification.

[0080] In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, systems, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples without contradiction.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for adjusting and analyzing the annual benchmark energy consumption value of a building caused by climate, characterized in that: include: S1, obtaining the meteorological data and meteorological information of the target building through the weather forecast terminal; S2, a database is provided, and a communication connection is established between the database and the weather forecast terminal; the database is used to store the meteorological data, meteorological information and historical annual benchmark energy consumption values ​​of the target building; S3, predicting or adjusting the annual benchmark energy consumption value of the target building in the next year based on meteorological data, meteorological information and historical annual benchmark energy consumption values; The meteorological data are divided into extreme meteorological data and non-extreme meteorological data, the season corresponding to the extreme weather is obtained, the average value of the non-extreme meteorological data of the season is calculated, and the average value of the non-extreme meteorological data of the season is used as the average meteorological data of the season.

2. The adjustment and analysis method for annual benchmark energy consumption value of buildings caused by climate according to claim 1 is characterized in that: Also includes: S301, predicting the annual benchmark energy consumption value of the target building based on the historical annual benchmark energy consumption value; specifically, E = E b k; E is the revised benchmark energy consumption value of the building; E b is the historical benchmark energy consumption value of the building; k is the correction coefficient of the benchmark energy consumption value.

3. The adjustment and analysis method for annual benchmark energy consumption value of buildings caused by climate according to claim 2 is characterized in that: The meteorological data includes temperature, humidity and wind speed; and further includes: S302, obtaining a correction coefficient k of the energy consumption reference value, Where k is the correction coefficient of the energy consumption benchmark value, T x-1 is the average outdoor air temperature of the previous year, T x is the average outdoor air temperature of the year; H x-1 is the average outdoor air humidity in the previous year, H x is the average outdoor air humidity of the year; W x-1 is the average outdoor wind speed in the previous year, W x is the average outdoor wind speed for the year; HDD x-1 Total degree days in the previous year; HDD x is the total number of degree days in the current year; x is the total number of years, and x≥2.

4. The adjustment and analysis method for annual benchmark energy consumption value of buildings caused by climate according to claim 1 is characterized in that: Weather information includes the number of days with extreme weather and the number of days in each season.

5. The adjustment and analysis method for annual benchmark energy consumption value of buildings caused by climate according to claim 1, characterized in that: S2 also includes a first method for identifying extreme weather, the first method for identifying extreme weather is used to receive prompt word information from a weather forecast terminal in real time, if the prompt word information from the weather forecast terminal is received, it is determined that the weather on that day is extreme weather, if not received, the weather on that day is non-extreme weather; Among them, the prompt word information includes extreme, tropical cyclone, heat wave, tornado, thunderstorm, blizzard, sandstorm and tsunami.

6. The adjustment and analysis method for climate-induced annual benchmark energy consumption of buildings according to claim 1, characterized in that: S2 also includes a second method for identifying extreme weather. If the meteorological data of the day, wind speed, temperature, and humidity are higher or lower than 90% of the median value of the historical wind speed, historical temperature, and historical humidity stored in the database for at least 20 years, the weather on that day is considered to be extreme weather.

7. A system for adjusting and analyzing the annual benchmark energy consumption value of buildings caused by climate, characterized in that: A method for executing the adjustment and analysis method for the climate-induced annual benchmark energy consumption value of a building as described in any one of claims 1 to 6, comprising a data analysis module, the data analysis module comprising an electronic device, the electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the electronic device executes the adjustment and analysis method for the climate-induced annual benchmark energy consumption value of a building.

8. The adjustment and analysis system for annual benchmark energy consumption value of buildings caused by climate according to claim 7 is characterized in that: It also includes a data collection module, which includes a weather forecast terminal, and the weather forecast terminal is used to collect weather data.

9. The adjustment and analysis system for annual benchmark energy consumption value of buildings caused by climate according to claim 8, characterized in that: The data collection module also includes a collection component and a mounting rod. The mounting rod is close to the target building, and the collection component is installed on the mounting rod. The collection component is used to collect weather data outside the target building in real time.

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