Train outdoor meteorological parameter generation method and system for air conditioning energy consumption analysis

Abstract

The present invention proposes a method and system for generating outdoor meteorological parameters of trains for air conditioning energy consumption analysis, and relates to the technical field of meteorological data processing. It includes obtaining typical annual meteorological data of cities where the train to be analyzed passes through stations; generating an annual time series of 8760 hours corresponding to the arrival of each train of the train to be analyzed throughout the year; combining the start and close rules of the train HVAC system, generating the annual time series required for the HVAC energy consumption analysis of each train of the train to be analyzed throughout the year; based on the annual time series required for the HVAC energy consumption analysis of each train of the train to be analyzed throughout the year, combined with the typical annual meteorological data of cities where the train passes through stations, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and the outdoor meteorological time series parameters of each train of the train to be analyzed throughout the year are obtained. The present invention generates a set of outdoor meteorological parameters required for the hourly energy consumption analysis of the accurate train HVAC system throughout the year that takes into account time and space transformations.

Description

Technical Field

[0001] The invention belongs to the technical field of meteorological data processing, and in particular relates to a method and a system for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis. Background Art

[0002] Due to its advantages of economy, convenience, energy conservation, safety and comfort, rail transit represented by high-speed rail transportation is an important way to achieve green land transportation and energy conservation in transportation. The energy consumption of the HVAC system in the passenger space of rail transit accounts for most of the energy consumption of auxiliary equipment, reaching nearly one-third of the energy consumption of the train traction system. Therefore, the energy-saving design and energy-saving operation of the train HVAC system have become important tasks for the low-carbon operation of rail transit.

[0003] For HVAC systems, accurate calculation of hourly cold / hot loads and precise analysis of annual operating energy consumption are necessary prerequisites for reasonable configuration of equipment capacity and efficient operation of the system. However, the outdoor meteorological parameters used in the current train air conditioning system design are mostly derived from linear specifications such as TB1951 "Passenger Car Air Conditioning Design Parameters" and GB / T 33193-1-2016 "Railway Vehicle Air Conditioning Part 1: Comfort Parameters". They are all steady-state calculations under fixed meteorological parameters, without considering the climate zone changes caused by seasonal / day-night alternation and train travel. It is difficult to accurately analyze the energy consumption of the HVAC system of the train in different seasons and driving positions, resulting in a lack of theoretical basis for intensive design and efficient operation. Summary of the invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a method and system for generating outdoor meteorological parameters of trains for air-conditioning energy consumption analysis, which utilizes the typical annual meteorological data parameters already available at each station along the train's route to generate a set of outdoor meteorological parameters required for accurate hourly energy consumption analysis of the train's HVAC system throughout the year that takes into account time and space transformations, thereby providing data support for accurate prediction of the load and energy consumption of the train's HVAC system.

[0005] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0006] A first aspect of the present invention provides a method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis.

[0007] The method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis comprises the following steps:

[0008] Obtain the train timetable for the train to be analyzed, determine the passing stations based on the train timetable, and obtain the typical annual meteorological data of the cities passing through the stations;

[0009] In the case of one train departure per day, generate an annual time series of 8760 hours corresponding to the arrival of each train in the whole year;

[0010] Based on the 8760-hour annual time series corresponding to the arrival of each train in the whole year, combined with the start and stop rules of the train HVAC system, the annual time series required for the measurement of HVAC energy consumption analysis of each train in the whole year is generated;

[0011] Based on the annual time series of measurements required for HVAC energy consumption analysis of each train in the whole year, combined with the typical annual meteorological data of the cities where the train passes through, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train in the whole year are obtained.

[0012] A second aspect of the present invention provides a train outdoor meteorological parameter generation system for air conditioning energy consumption analysis.

[0013] The train outdoor meteorological parameter generation system for air conditioning energy consumption analysis includes:

[0014] The module for acquiring meteorological data of passing stations is configured to: acquire the train schedule of the train to be analyzed, determine the passing stations according to the train schedule, and acquire the typical annual meteorological data of the cities of the passing stations;

[0015] The module for representing the time sequence of each train throughout the year is configured to: generate an annual time sequence of 8760 hours corresponding to the arrival of each train of the train to be analyzed throughout the year, assuming that one train departs every day;

[0016] The HVAC analysis time series representation module for each train throughout the year is configured to: generate the annual time series required for the HVAC energy consumption analysis of each train for the train to be analyzed throughout the year based on the 8760-hour annual time series corresponding to the arrival of each train for the train to be analyzed throughout the year, combined with the start and stop rules of the train HVAC system;

[0017] The weighted calculation module is configured as follows: based on the annual time series required for HVAC energy consumption analysis of each train to be analyzed throughout the year, combined with the typical annual meteorological data of the cities passing through the stations, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train to be analyzed throughout the year are obtained.

[0018] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis as described in the first aspect of the present invention.

[0019] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis as described in the first aspect of the present invention are implemented.

[0020] One or more of the above technical solutions have the following beneficial effects:

[0021] The present invention provides a method and system for generating outdoor meteorological parameters of trains for air-conditioning energy consumption analysis. Firstly, an annual time series of 8760 hours corresponding to the arrival of each train of the train to be analyzed throughout the year is generated, and the on-off law of the train heating, ventilation and air-conditioning system is considered to obtain the annual time series required for the heating, ventilation and air-conditioning energy consumption analysis of each train of the train to be analyzed throughout the year; then, in combination with the typical annual meteorological data of the cities passing through the stations, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train of the train to be analyzed throughout the year are obtained, so as to provide data support for the accurate prediction of the load and energy consumption of the train heating, ventilation and air-conditioning system.

[0022] The present invention takes into account the climate zone changes caused by seasons / day and night alternations and train travel, and obtains the train's outdoor meteorological time series parameters that change with time and space based on the typical annual meteorological data (TMY) of the passing stations, which facilitates the subsequent accurate analysis of the train's HVAC system energy consumption in different seasons and driving positions.

[0023] The typical annual meteorological data of the cities where the train passes through includes temperature, relative humidity, wind speed, wind direction and solar radiation intensity. When the train is at the middle position between the ith and i+1th passing stations, the meteorological parameter data of the ith and i+1th passing stations are comprehensively considered, and the time series meteorological parameters of the middle position are weighted to form an accurate outdoor time series data set of the train.

[0024] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0026] Figure 1 This is a method step diagram of the first embodiment.

[0027] Figure 2 This is a flow chart of the method of the first embodiment.

[0028] Figure 3It is a system structure diagram of the second embodiment. DETAILED DESCRIPTION

[0029] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0030] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0031] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0032] Embodiment 1

[0033] As mentioned above, the outdoor meteorological parameters used in the current design of train air-conditioning systems are mostly derived from specifications such as TB1951 and GB / T33193-1-2016, and are steady-state calculations under fixed meteorological parameters. They do not take into account the changes in climate zones caused by seasonal / day-night alternations and train travel. It is difficult to accurately analyze the energy consumption of the HVAC system of the train in different seasons and driving positions, resulting in a lack of theoretical basis for intensive design and efficient operation.

[0034] In response to the above problems, this embodiment proposes a method for generating outdoor meteorological parameters of trains for air-conditioning energy consumption analysis. The method uses the typical annual meteorological data parameters already available at each station along which the train passes to generate the outdoor meteorological parameter set required for the hourly energy consumption analysis of the HVAC system throughout the year, thereby providing support for the accurate prediction of the load and energy consumption of the HVAC system on the train.

[0035] like Figure 1 As shown, the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis proposed in this embodiment may include the following steps:

[0036] Obtain the train timetable for the train to be analyzed, determine the passing stations based on the train timetable, and obtain the typical annual meteorological data of the cities passing through the stations;

[0037] In the case of one train departure per day, generate an annual time series of 8760 hours corresponding to the arrival of each train in the whole year;

[0038] Based on the 8760-hour annual time series corresponding to the arrival of each train in the whole year, combined with the start and stop rules of the train HVAC system, the annual time series required for the measurement of HVAC energy consumption analysis of each train in the whole year is generated;

[0039] Based on the annual time series of measurements required for HVAC energy consumption analysis of each train in the whole year, combined with the typical annual meteorological data of the cities where the train passes through, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train in the whole year are obtained.

[0040] Furthermore, Figure 2 As shown, the above process specifically includes:

[0041] Step 1: Retrieve and obtain typical annual meteorological data for cities along the route based on the train schedule for the train to be analyzed.

[0042] Assume that the train passes through n stations, the i-th station is counted as station i, and the "Standard Meteorological Data Manual for Buildings" (CTYW), "China Building Thermal Environment Analysis Special Meteorological Data Set" (CSWD) or according to the JGJ / T 346-2014 specification, the typical annual meteorological data (TMY) of each station is calculated based on the accumulated annual meteorological data of the stations, which is calculated as:

[0043]

[0044] Among them, the subscript i is the station number, i = 1, ... n, n is the number of stations passed; the subscript j is the time sequence of 8760 hours in a year; T is the temperature, RH is the relative humidity, V is the wind speed, is the wind direction, I is the solar radiation intensity; E i,j Represents the typical annual meteorological data of the city at the i-th transit station at the j-th time of the whole year.

[0045] If a year consists of 365 days, the total time series for the year is: 365 days * 24 hours / day = 8760 hours.

[0046] The passing stations in this embodiment refer to the stations that the train passes during its journey, including the departure station and the terminal station, where the departure station is numbered 1, the terminal station is numbered n, and the passing station is numbered i (1≤i≤n, and i is a positive integer). For example, all the stations of the train are represented as A, B, C, D, E, and F in sequence, then they are all passing stations, and are station 1, station 2, station 3, station 4, station 5, and station 6 in sequence.

[0047] Step 2: Generate an 8760-hour annual time series corresponding to the arrival of each train trip throughout the year.

[0048] This step 2 specifically corresponds to Figure 2 The time sequence corresponding to the arrival of the kth train at station i is 24(k-1)+M i generate.

[0049] First, the time when the same train passes through the station is expressed:

[0050] The departure time of the train to be analyzed is M1, and the time when it passes the i-th station is M i , the time it takes to reach the i-th stop after the departure is m i , then we can get M i =M1+m i .

[0051] After that, if one train departs every day, the annual time sequence of the kth train arriving at station i on the kth day of the year is 24(k-1)+M i ;

[0052] When 24(k-1)+M i >8760, the corresponding annual time series should be adjusted to 24(k-1)+M i -8760.

[0053] Step 3: Generate the annual time series of measurements required for heating, ventilation and air conditioning energy consumption analysis for each train trip.

[0054] This step three specifically corresponds to Figure 2 The annual time series required for energy consumption analysis of the HVAC system of the kth train generate.

[0055] This embodiment combines the on / off rules of the train HVAC system when generating the annual time series required for the HVAC energy consumption analysis of each train to be analyzed throughout the year. Considering that trains usually do not depart on the hour, and the HVAC system is usually turned on / off in advance before departure and after arrival to facilitate driving inspection and cleaning. Therefore, in the subsequent analysis of environmental control energy consumption, one more time should be measured before departure and after arrival to reflect the above situation.

[0056] Based on this, for the kth train:

[0057] The starting time of HVAC energy consumption analysis should be

[0058] The end time should be (Due to m n =M n -M1, which can also be expressed as and

[0059] A certain moment in the process is counted as in And is an integer. In the above formula is the floor symbol, M is the rounding symbol; n Indicates the arrival time of the terminal n.

[0060] Step 4: TMY meteorological parameters are called and outdoor meteorological parameters of the train are generated.

[0061] This step corresponds to Figure 2 In the process, the train's typical meteorological year time series meteorological parameters from departure station 1 to terminal station n are queried / generated.

[0062] The annual time series of HVAC energy consumption analysis required for each train to be analyzed throughout the year obtained in step 3 is used to generate the meteorological data set required for the kth train, which is expressed as: Among them, F represents the data for HVAC energy consumption analysis of a certain train at a certain time sequence throughout the year (indicated in the subscript), including elements; represents the initial time of the kth train during HVAC energy consumption analysis; represents the tth time after the initial time of HVAC energy consumption analysis for any kth train; represents the final moment of the HVAC energy consumption analysis for the kth train.

[0063] The meteorological data set required for the k-th train needs to be obtained first. The driving status at the moment is judged, such as Figure 2 As shown:

[0064] ① When That is, the vehicle has not yet started, so the meteorological data taken at this time (calculated as ) should be the departure station (station 1) of the year Weather data at the moment:

[0065]

[0066] ② When That is, the vehicle has arrived at the station, so the meteorological data taken at this time should be the terminal station (station n) of the year. Weather data at the moment:

[0067]

[0068] ③When At this time, the vehicle is moving and needs to judge With M i The relationship between:

[0069] If it appears At this time, the vehicle is between the i-th passing station and the i+1-th passing station, and the temporal outdoor meteorological parameters at this time are:

[0070]

[0071] Among them, E i,j is the typical annual meteorological data of the city at the jth time sequence of the ith transit station throughout the year; as mentioned above, Subscript i is the number of the station passed, i = 1, ... n, n is the number of stations passed; subscript j is the time sequence of 8760 hours in a year; T is the temperature, RH is the relative humidity, V is the wind speed, is the wind direction and I is the solar radiation intensity.

[0072] The above step 4 finally generates the kth train at Outdoor weather parameters at all times

[0073] Step 5: Summarize the outdoor meteorological time series parameters corresponding to each train of the train to be analyzed throughout the year to form an outdoor meteorological parameter set for the HVAC energy consumption analysis of the train to be analyzed throughout the year.

[0074] The outdoor meteorological time series parameters corresponding to each train The data are sorted to form an array array, and the outdoor meteorological parameter set for the HVAC energy consumption analysis of the train throughout the year is obtained.

[0075] When applying the outdoor meteorological parameter set for the annual HVAC energy consumption analysis of the above-mentioned train, the data set is substituted into the annual load calculation model of the air-conditioning system such as the RC model, or the artificial environment control energy consumption software such as EnergyPlus, DeST and TYNSYS, as the outdoor hourly meteorological parameters for the thermal process analysis such as the heat gain of the enclosure structure, the introduction of fresh air and the natural lighting of the transparent enclosure structure. The operating energy consumption of the kth train in the driving stage under the typical annual meteorological data can be calculated, and the operating energy consumption of the 365 trains in the driving stage throughout the year is added together to obtain the total operating energy consumption of the HVAC system of the train to be analyzed throughout the year.

[0076] Embodiment 2

[0077] This embodiment discloses a train outdoor meteorological parameter generation system for air conditioning energy consumption analysis.

[0078] like Figure 3 As shown, the train outdoor meteorological parameter generation system for air conditioning energy consumption analysis includes:

[0079] The module for acquiring meteorological data of passing stations is configured to: acquire the train schedule of the train to be analyzed, determine the passing stations according to the train schedule, and acquire the typical annual meteorological data of the cities of the passing stations;

[0080] The module for representing the time sequence of each train throughout the year is configured to: generate an annual time sequence of 8760 hours corresponding to the arrival of each train of the train to be analyzed throughout the year, assuming that one train departs every day;

[0081] The HVAC analysis time series representation module for each train throughout the year is configured to: generate the annual time series required for the HVAC energy consumption analysis of each train for the train to be analyzed throughout the year based on the 8760-hour annual time series corresponding to the arrival of each train for the train to be analyzed throughout the year, combined with the start and stop rules of the train HVAC system;

[0082] The weighted calculation module is configured as follows: based on the annual time series required for HVAC energy consumption analysis of each train to be analyzed throughout the year, combined with the typical annual meteorological data of the cities passing through the stations, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train to be analyzed throughout the year are obtained.

[0083] Embodiment 3

[0084] The purpose of this embodiment is to provide a computer-readable storage medium.

[0085] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis as described in Example 1 of the present disclosure.

[0086] Embodiment 4

[0087] The purpose of this embodiment is to provide an electronic device.

[0088] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis as described in Example 1 of the present disclosure are implemented.

[0089] The steps involved in the apparatuses of the above embodiments 2, 3 and 4 correspond to the method embodiment 1, and the specific implementation methods can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0090] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0091] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis, characterized in that: The following steps are involved: Obtain the train timetable for the train to be analyzed, determine the passing stations based on the train timetable, and obtain the typical annual meteorological data of the cities passing through the stations; In the case of one train departure per day, an annual time series of 8760 hours corresponding to the arrival of each train in the whole year is generated, including: First, the time when the same train passes through the station is expressed: Assume that the departure time of the same train is M1, and the time when it passes the i-th station is M i , the time it takes to reach the i-th stop after the departure is m i , then M i =M1+m i ; Then, the annual time series of the k-th train arriving at the i-th station on the k-th day of the year is expressed as 24(k-1)+M i ; When 24(k-1)+M i >8760, the corresponding annual time series is adjusted to 24(k-1)+M i -8760; Based on the 8760-hour annual time series corresponding to the arrival of each train in the whole year, combined with the start and stop rules of the train HVAC system, the annual time series required for the HVAC energy consumption analysis of each train in the whole year is generated, specifically: For the kth train, the start time of HVAC energy consumption analysis is expressed as 24(k-1)+ ; The end time of HVAC energy consumption analysis is expressed as 24(k-1) + +1; During the HVAC energy consumption analysis, a certain moment is expressed as 24(k-1)+ +t, where 0≤t≤ +1 and an integer; in, is the floor symbol, M is the rounding symbol; n represents the arrival time of terminal n; Based on the annual time series of measurements required for HVAC energy consumption analysis of each train in the whole year, combined with the typical annual meteorological data of the cities where the train passes through, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train in the whole year are obtained.

2. The method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis according to claim 1, characterized in that: The typical annual meteorological data of the cities passing through the station are specifically expressed as follows: AND i,j ={T i,j , HR i,j , V i,j , φ i,j , I i,j }; Among them, the subscript i is the number of the site passed, i=1,…n, n is the number of sites passed; the subscript j is the time sequence of 8760 hours in a year; T is the temperature, RH is the relative humidity, V is the wind speed, φ is the wind direction, and I is the solar radiation intensity; E i,j Represents the typical annual meteorological data of the city at the i-th transit station at the j-th time of the whole year.

3. The method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis according to claim 1, characterized in that: The outdoor meteorological time series parameters of each train to be analyzed throughout the year include: The outdoor weather time series parameters of the kth train are set as ;in, represents the initial time of the kth train during HVAC energy consumption analysis; represents the tth time after the initial time of HVAC energy consumption analysis for any kth train; represents the final moment of HVAC energy consumption analysis for the kth train; then: When 24(k-1)+ +t<24(k-1)+M1, that is, the train has not yet departed, so the meteorological data taken at this time should be the 24(k-1)+ + Weather data at time t; When 24(k-1)+ +t>24(k-1)+M n , that is, the train has arrived at the station at this time, so the meteorological data taken at this time should be the 24th (k-1)+ + Weather data at time t.

4. The method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis according to claim 3, characterized in that: A weighted method is used to generate the time-series outdoor meteorological parameters when each train is between two stations. For the kth train, the specific parameters are: When 24(k-1)+M1<24(k-1)+ +t<24(k-1)+M n , then the vehicle needs to judge during the moving process +t and M i The relationship between: If M i < +t <M i+1 , then the train is between the i-th passing station and the i+1-th passing station, and the temporal outdoor meteorological parameters at this time are: 。 5. The method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis according to claim 1, characterized in that: Also includes: The outdoor meteorological time series parameters corresponding to each train of the train to be analyzed throughout the year are summarized to form an outdoor meteorological parameter set for the HVAC energy consumption analysis of the train to be analyzed throughout the year.

6. A train outdoor meteorological parameter generation system for air conditioning energy consumption analysis, characterized in that: include: The module for acquiring meteorological data of passing stations is configured to: acquire the train schedule of the train to be analyzed, determine the passing stations according to the train schedule, and acquire the typical annual meteorological data of the cities of the passing stations; The module for representing the time sequence of each train throughout the year is configured to generate the 8760-hour annual time sequence corresponding to the arrival of each train of the train to be analyzed throughout the year, assuming that one train departs every day, including: First, the time when the same train passes through the station is expressed: Assume that the departure time of the same train is M1, and the time when it passes the i-th station is M i , the time it takes to reach the i-th stop after the departure is m i , then M i =M1+m i ; Then, the annual time series of the k-th train arriving at the i-th station on the k-th day of the year is expressed as 24(k-1)+M i ; When 24(k-1)+M i >8760, the corresponding annual time series is adjusted to 24(k-1)+M i -8760; The HVAC analysis time series representation module for each train throughout the year is configured as follows: based on the 8760-hour annual time series corresponding to the arrival of each train throughout the year for the train to be analyzed, combined with the start and stop rules of the train HVAC system, the annual time series required for the measurement of HVAC energy consumption analysis for each train throughout the year for the train to be analyzed is generated, specifically: For the kth train, the start time of HVAC energy consumption analysis is expressed as 24(k-1)+ ; The end time of HVAC energy consumption analysis is expressed as 24(k-1) + +1; During the HVAC energy consumption analysis, a certain moment is expressed as 24(k-1)+ +t, where 0≤t≤ +1 and an integer; in, is the floor symbol, M is the rounding symbol; n represents the arrival time of terminal n; The weighted calculation module is configured as follows: based on the annual time series required for HVAC energy consumption analysis of each train to be analyzed throughout the year, combined with the typical annual meteorological data of the cities passing through the stations, a weighted method is used to generate the time series outdoor meteorological parameters when each train is between two stations, and finally the outdoor meteorological time series parameters of each train to be analyzed throughout the year are obtained.

7. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps in the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis as described in any one of claims 1 to 5 are implemented.

8. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the method for generating outdoor meteorological parameters of a train for air conditioning energy consumption analysis as described in any one of claims 1 to 5 are implemented.

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