Commercial building load simulation method and system considering multi-element influence

Abstract

According to the commercial building load simulation method and system considering the multi-element influence, the lighting load model, the elevator load model, the socket load model and the central air conditioner load model are constructed respectively, then simulation of the commercial building load is achieved, dynamic adjustability can be achieved according to dates, weather conditions and personnel conditions, and the simulation efficiency is improved. The method is high in generalization, can be suitable for simulation of building loads in different regions, and is also suitable for load simulation of commercial buildings pre-built in a certain region.

Description

Technical Field

[0001] The present invention belongs to the technical field related to the load simulation of commercial buildings, and particularly relates to a method and system for load simulation of commercial buildings considering the influence of multiple factors. Background Art

[0002] The statements in this part only provide background technical information related to the present invention, and do not necessarily constitute prior art.

[0003] Load simulation, as the test foundation of various dispatching and control algorithms of smart grids, is one of the essential capabilities of each energy management system. For algorithms such as virtual power plants and microgrid optimal dispatching, a commercial building load simulation system with multiple types of granularity and considering weather and date changes is an indispensable underlying environment for verifying various intelligent algorithms. However, most of the current load simulation algorithms cannot provide the load curve changes of multiple types and considering multiple conditions, resulting in low flexibility and fidelity. Currently, the so-called top-down simulation method that uses existing typical curves plus a certain amount of randomness is not only rigid but also cannot be flexibly changed according to weather and date, making the verification of various algorithms lose practical significance.

[0004] In addition, although the personnel system is considered in the existing commercial building load simulation, the design of its personnel system depends on analyzing the existing load conditions to establish a probability chain, resulting in the problem of poor generality of the simulation results due to over-refined modeling.

[0005] Therefore, how to comprehensively consider the influence of various situations such as the mobility of personnel, date, and weather conditions in commercial buildings on the load in commercial buildings, and flexibly simulate the fine-grained load of commercial buildings so that it can be applied to the load simulation of commercial buildings in different regions is a problem to be solved. Summary of the Invention

[0006] To overcome the deficiencies of the above-mentioned prior art, the present invention provides a method and system for load simulation of commercial buildings considering the influence of multiple factors, which can be dynamically adjusted according to date, weather conditions, and personnel conditions, has strong generalization ability, and can be applied to the load simulation of commercial buildings in different regions.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In the first aspect, the present invention provides a method for load simulation of commercial buildings considering the influence of multiple factors, including:

[0009] Dividing according to the load types in the building; wherein, the load types at least include: lighting load, elevator load, socket load, and central air-conditioning load.

[0010] Construct a lighting load model and an elevator load model respectively according to the impact of commuting time, weekdays and holidays, and the personnel flow in the building on the lighting load and elevator load;

[0011] Construct a socket load model based on the personnel flow in the building and the impact of different used devices on the socket load;

[0012] Construct a central air-conditioning load model based on the personnel flow in the building, weather conditions and the impact of time series on the central air-conditioning load;

[0013] Combine the lighting load model, the elevator load model, the socket load model and the central air-conditioning load model to obtain the commercial building load simulation result.

[0014] In a second aspect, the present invention provides a commercial building load simulation system considering the influence of multiple factors, including:

[0015] A division module, which is configured to: divide according to the load types in the building; wherein, the load types at least include: lighting load, elevator load, socket load and central air-conditioning load.

[0016] A first construction module, which is configured to: construct a lighting load model and an elevator load model respectively according to the impact of commuting time, weekdays and holidays, and the personnel flow in the building on the lighting load and elevator load;

[0017] A second construction module, which is configured to: construct a socket load model based on the personnel flow in the building and the impact of different used devices on the socket load;

[0018] A third construction module, which is configured to: construct a central air-conditioning load model based on the personnel flow in the building, weather conditions and the impact of time series on the central air-conditioning load;

[0019] A simulation module, which is configured to: combine the lighting load model, the elevator load model, the socket load model and the central air-conditioning load model to obtain the commercial building load simulation result.

[0020] In a third aspect, the present invention provides an electronic device, including a memory and a processor, and computer instructions stored on the memory and running on the processor. When the computer instructions are run by the processor, the method described in the first aspect is completed.

[0021] In a fourth aspect, the present invention provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the method described in the first aspect is completed.

[0022] Fifth aspect, the present invention provides a computer program product, including a computer program, which when executed by a processor, implements the method described in the first aspect.

[0023] The above one or more technical solutions have the following beneficial effects:

[0024] By respectively constructing an illumination load model, an elevator load model, a socket load model, and a central air-conditioning load model, the present invention realizes the simulation of the commercial building load. That is, it avoids the problem of poor generality of the simulation results caused by over-refined modeling, and can be dynamically adjusted according to the date, weather conditions, and personnel situation. It is applicable to the simulation of building loads in different regions, and also applicable to the load simulation of pre-constructed commercial buildings in a certain region.

[0025] The advantages of the additional aspects of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The specification drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention.

[0027] Figure 1 It is the simulation effect diagram of the total load of the commercial building corresponding to spring - weekday in the first embodiment of the present invention;

[0028] Figure 2 It is the simulation effect diagram of the sub-loads of each system in the commercial building corresponding to spring - weekday in the first embodiment of the present invention;

[0029] Figure 3 It is the simulation effect diagram of the total load of the commercial building corresponding to spring - weekend in the first embodiment of the present invention;

[0030] Figure 4 It is the simulation effect diagram of the sub-loads of each system in the commercial building corresponding to spring - weekend in the first embodiment of the present invention;

[0031] Figure 5 It is the simulation effect diagram of the total load of the commercial building corresponding to summer - weekday in the first embodiment of the present invention;

[0032] Figure 6 It is the simulation effect diagram of the sub-loads of each system in the commercial building corresponding to summer - weekday in the first embodiment of the present invention;

[0033] Figure 7 It is the simulation effect diagram of the total load of the commercial building corresponding to summer - weekend in the first embodiment of the present invention;

[0034] Figure 8This is the simulation effect diagram of the sub - loads of each system in the commercial building corresponding to summer - weekend in the first embodiment of the present invention;

[0035] Figure 9 This is the simulation effect diagram of the total load of the commercial building corresponding to autumn - weekday in the first embodiment of the present invention;

[0036] Figure 10 This is the simulation effect diagram of the sub - loads of each system in the commercial building corresponding to autumn - weekday in the first embodiment of the present invention;

[0037] Figure 11 This is the simulation effect diagram of the total load of the commercial building corresponding to autumn - weekend in the first embodiment of the present invention;

[0038] Figure 12 This is the simulation effect diagram of the sub - loads of each system in the commercial building corresponding to autumn - weekend in the first embodiment of the present invention;

[0039] Figure 13 This is the simulation effect diagram of the total load of the commercial building corresponding to winter - weekday in the first embodiment of the present invention;

[0040] Figure 14 This is the simulation effect diagram of the sub - loads of each system in the commercial building corresponding to winter - weekday in the first embodiment of the present invention;

[0041] Figure 15 This is the simulation effect diagram of the total load of the commercial building corresponding to winter - weekend in the first embodiment of the present invention;

[0042] Figure 16 This is the simulation effect diagram of the sub - loads of each system in the commercial building corresponding to winter - weekend in the first embodiment of the present invention;

[0043] Figure 17 This is the simulation effect diagram of the total load of the commercial building corresponding to winter - special holiday in the first embodiment of the present invention;

[0044] Figure 18 This is the simulation effect diagram of the sub - loads of each system in the commercial building corresponding to winter - special holiday in the first embodiment of the present invention. Detailed implementation manners

[0045] It should be noted that the following detailed description is exemplary and is intended to provide further illustration of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0046] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present invention.

[0047] Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0048] Embodiment 1

[0049] This embodiment discloses a commercial building load simulation method considering the influence of multiple factors, including:

[0050] Dividing according to the load types in the building; wherein, the load types at least include: lighting load, elevator load, socket load, and central air-conditioning load.

[0051] Respectively constructing a lighting load model and an elevator load model according to the influence of commuting time, weekdays and holidays, and the personnel flow in the building on the lighting load and elevator load;

[0052] Based on the personnel flow in the building and the influence of different used devices on the socket load, constructing a socket load model;

[0053] Based on the personnel flow in the building, weather conditions, and the influence of time series on the central air-conditioning load, constructing a central air-conditioning load model;

[0054] Combining the lighting load model, the elevator load model, the socket load model, and the central air-conditioning load model to obtain the commercial building load simulation result.

[0055] The commercial building load simulation method considering the influence of multiple factors proposed in this embodiment can simulate as much as possible the commercial building load curves at various time granularities considering the influence of weather, holidays, load types, and time series, so as to provide a flexible experimental environment foundation for scenarios such as virtual power plants, new power systems, and new energy consumption in microgrids, and help verify the reliability of various prediction and control algorithms.

[0056] This embodiment divides the commercial building load into five types for separate modeling, namely: lighting system, elevator system, socket, central air-conditioning system, and other equipment.

[0057] For the maximum energy consumption proportion of each of the above parts, it can be determined by the user. This embodiment gives a feasible default ratio, that is, the lighting system is 15%, the elevator system is 15%, the socket is 15%, the central air-conditioning system is 50%, and other equipment is 5%.

[0058] The above ratio is the ratio relationship between the maximum load capacities of each part, and the actual energy consumption proportion during actual operation varies according to the actual situation.

[0059] In order to more realistically simulate the load of each system, in this embodiment, a personnel system is designed to simulate the personnel situation of those who go to work in the current office building. This system will have an interactive impact on other systems, and directly change the simulation situation of other systems through the changes in the personnel system. First, we set the maximum online ratio of personnel in the personnel system to 1. Before the start of work every day, a ratio of personnel supposed to arrive on the current day, i.e., the first ratio, will be randomly generated. α , then, let the ratio of actual working personnel on the current day be the second ratio β . It should be noted that the second ratio β changes over time. Then, it is also necessary to set the ratio of overtime personnel on the current day as the third ratio γ , and the overtime end time point δ .

[0060] The value ranges and generation methods of the above four parameters are shown in Table 1:

[0061]

[0062] The values of α, γ, and δ are obtained using the random function random within the given range. The distribution of β conforms to the random Poisson distribution (rising part) in the time period [round(0.327*T)~round(0.375*T)], conforms to the random Poisson distribution (falling part) in the time period [round(0.7535*T)~round(0.79167*T)], and conforms to the random chi-square distribution (falling part) in the time period [round(0.79167*T)~δ]; where T is the total time granularity of a day. For example, if there is one point per minute, there are 1440 points in a day, then T = 1440.

[0063] The prior art's design of the personnel system relies on analyzing the existing load situation to establish a probability chain. In this embodiment, in order to enhance the generalization possibility, instead of considering the details of personnel actions, the overall personnel presence situation and its change probability are considered, thus avoiding the problem of poor generalizability of the simulation results caused by over-refined modeling.

[0064] Lighting load model: The load size of the lighting system in commercial office buildings is mainly related to the working hours and work-holiday situations, and the lighting system will have a certain constant baseline value, that is, the basic load that is not affected by the above factors. This part of the basic load is set to 18 - 22% of the maximum load size of the lighting system. The specific ratio will be randomly generated within this range. Even if there are no personnel in the building, this part of the load will maintain the basic operation of the building itself.

[0065] The movable lighting load of commercial office buildings is directly related to the attendance of employees. Therefore, the generation of the movable lighting load in this part can be calculated by directly multiplying the maximum movable lighting load by the current actual attendance ratio β of the second type. However, it should be noted that within the time period of [round(0.37847*T)~round(0.75*T)], due to various unknown interference considerations, the movable lighting load calculated previously needs to be added with a random interference multiplier to simulate the fluctuation situation. The random interference multiplier selected in this embodiment is a Gaussian perturbation multiplier, and the value range of the multiplier is between [0.8~1].

[0066] In addition, since it is the lunch break time during the noon period, considering that many employees may leave the company or turn off the equipment to rest, therefore, during the noon period, the movable lighting calculated previously also needs to be multiplied by an amplitude factor that first decreases and then increases and conforms to the Poisson distribution. The maximum value of this factor is 1, and the minimum value is 0.5.

[0067] Elevator load model: The load size of the elevator system in commercial office buildings is mainly related to the commuting situation, lunch break situation, and work-holiday situation. And the elevator system will also have a certain constant baseline value, that is, the basic load amount that is not affected by the above factors. This part of the basic load amount is set to 15~20% of the maximum load size of the elevator system. The specific ratio will be randomly generated within this range. Even if there are no people in the building, this part of the load will maintain the basic operation of the building itself.

[0068] The movable elevator load of commercial office buildings is directly related to the personnel flow situation, and the power consumption of elevator operation will also change according to whether it is fully loaded or half loaded. Therefore, it is set that the fully loaded operation consumes 100% of the maximum movable elevator load, and the half loaded operation consumes 70% of the maximum movable elevator load.

[0069] Specifically, according to the setting of the personnel system, it is considered that the elevator system is in a fully loaded state during the commuting time period and the lunch break and meal time period:

[0070] (t=[94 / 288*T-108 / 288*T],[217 / 288*T-228 / 288*T],[138 / 288*T,150 / 288*T])

[0071] Within the time period corresponding to the fully loaded state, the movable elevator load takes the product of the maximum value of the movable elevator load and the random interference multiplier. The value range of the random multiplier is between [0.8~1]. And within the time period of [1 / 288*T-93 / 288*T], since there are no staff members, it is defaulted that the elevator stops running.

[0072] At other time points except the above three special time periods in [94 / 288*T - 228 / 288*T], the elevator is default to be in the half-load operation state. The movable load of the elevator is the product of 70% of the maximum value of the elevator's movable load and the random disturbance multiplier, and the value range of the random disturbance multiplier is between [0 - 0.8].

[0073] During the time period of [229 / 288*T - δ], the change of the elevator's movable load fluctuates with the leaving of overtime workers. The movable load of the elevator is 70% of the maximum value of the elevator's movable load multiplied by (the leaving proportion of overtime workers at the current moment divided by the total proportion of overtime workers on the same day) and then multiplied by the random disturbance multiplier, and the value range of the random disturbance multiplier is between [0.9 - 1].

[0074] Socket load model: The design of the socket system is similar to but different from that of the lighting system. This system also highly depends on the fluctuations of the personnel system and has a certain reference value, which is considered to be randomly generated between 10% and 15% of the maximum socket load. Even when there are no people in the building, this part of the load will maintain the basic operation of the building itself.

[0075] Due to the differences in the used equipment and the randomness of time nodes, although the consumption of the movable load of the socket system will show several large peaks with the coming and going of people, when t = [109 / 288*T - 216 / 288*T] and the existing working people remain unchanged, the randomness of the socket's fluctuation is significantly stronger than that of the lighting system. Therefore, the generation of the movable load of the socket system still maintains the mode of directly multiplying the maximum load of the socket system by the current proportion β of working people and then multiplying by a disturbance factor; when t = [109 / 288*T - 216 / 288*T], the size fluctuation of the disturbance factor will increase, generally taking values between [0.3 - 1] to simulate the high randomness of the socket system load fluctuation during the simulation working stage, and at other times, the disturbance factor takes values between [0.8 - 1].

[0076] In addition, since it is the lunch break during the noon period and considering that many employees may leave the company or turn off their devices to rest, during the noon period, the calculated value of the movable load of the socket system should also be multiplied by an amplitude factor that first decreases and then increases and conforms to the Poisson distribution. The maximum value of this factor is 1 and the minimum value is 0.5.

[0077] Central air-conditioning load model: The air-conditioning load is the most complex part in the design of building systems. This system is not only highly correlated with the fluctuations of the personnel system, but also greatly related to weather conditions and time series relationships. Due to the pursuit of comfort in commercial office buildings, generally, the use of air conditioners is mainly affected by temperature. The air-conditioning load is divided into two parts: ventilation system (fixed consumption): accounting for 35% of the maximum central air-conditioning system load; heating and cooling system: accounting for 65% of the maximum central air-conditioning system load.

[0078] Among them, the ventilation system is basically in the all-day-on mode. However, although the ventilation system is on all day, when there are no working personnel in the early morning, the power of the ventilation system should still be smaller compared to other times. Therefore, when t = [1 / 288*T - 93 / 288*T], the load consumption of the ventilation system is 70 - 80% of that in other times, and the specific value is randomly generated. At other times, the load of the ventilation system is multiplied by a small random operator on the basis of 15% of the maximum central air-conditioning system load to simulate a certain random fluctuation, where the value range of the small random operator is (0.9 - 1).

[0079] In order to simulate the real-world scenario more realistically, considering the temperature and humidity differences between indoors and outdoors, and the fact that the air conditioner actually regulates the indoor temperature and humidity, an indoor temperature and humidity system is established in this embodiment. When there are no people, it is considered that the indoor temperature is completely determined by the outdoor temperature.

[0080] For the heating and cooling system, when there are no people at work, this system is also in a silent state and does not consume energy. When there are people at work, the load consumption of the heating and cooling system is also related to the weather data at that time. Only when the temperature data exceeds the second temperature threshold such as 27° or is lower than the first temperature threshold such as 18°, the heating and cooling system is turned on. After it is turned on, within one hour, there will also be multiple output-maintenance state switches, which are manifested as multiple high and low fluctuations similar to sine waves in the load consumption within one hour.

[0081] Whether the system is turned on or not is related to the input weather data temperature every hour. The initial peak amplitude after it is turned on is obtained by multiplying the maximum movable heating and cooling system load by the amplitude factor, that is, ((0.75 * |current hour temperature / temperature threshold|) * 0.8), where the temperature threshold here refers to the second temperature threshold or the first temperature threshold; when the temperature is lower than 18°, the initial peak amplitude is obtained by multiplying the maximum movable heating and cooling system load by the amplitude factor, that is, ((-1 / 13 * current hour temperature / first temperature threshold + 8 / 13) * 0.8).

[0082] When the amplitude factor is greater than 1, the amplitude factor is set to 1 for calculation, and when the amplitude factor is less than 0, the amplitude factor is set to 0 for calculation.

[0083] When the indoor temperature enters the specified temperature, the specified temperature when the heating system is turned on is the first temperature threshold, and the specified temperature when the cooling system is turned on is the second temperature threshold; then considering the interaction effect between indoor and outdoor temperatures and the heating and cooling capabilities of the heating and cooling systems, after the heating and cooling systems are turned on, it is calculated that for each startup, the indoor temperature rises or falls by a preset degree such as 1.5 degrees every 5 minutes. When the temperature first drops to (the second temperature threshold - the preset degree) such as 24.5 degrees or rises to (the second temperature threshold + the preset degree) such as 26 degrees, the system enters the standby state, and the load consumption at this time is 1 / 2 of that in the startup state. Then, the indoor temperature begins to be affected by the outdoor temperature for cooling or heating, and the indoor temperature changes by the indoor-outdoor temperature difference multiplied by a set ratio such as 1 / 20 per minute. When the indoor temperature reaches the warning line at the next moment, the heating and cooling systems are turned on again, and the average load output restores the amplitude peak value. This cycle continues until the end of the day when all overtime workers have left and the temperature system of the commercial building is turned off.

[0084] Load models of other equipment: The loads in this part are mainly to be compatible with some loads that may be difficult to classify in many different office buildings. Therefore, we believe that the occurrence of the loads in this part is uniformly random throughout the entire time period, and the magnitude ratio of each occurrence is also uniformly random between (0, 1). The generation method of uniform randomness depends on the Sobol sequence.

[0085] Based on the load models constructed in the above various parts, this embodiment simulates the load of the commercial building. This embodiment focuses on adding the consideration of adaptability to the local climate, so that the simulation situation can vary realistically according to weather conditions.

[0086] The simulation schematic diagram of the commercial building is as Figures 1 - 18 shown.

[0087] Embodiment 2

[0088] The purpose of this embodiment is to provide a commercial building load simulation system considering the influence of multiple factors, including:

[0089] A division module, which is configured to: divide according to the load types in the building; wherein, the load types at least include: lighting load, elevator load, socket load, and central air-conditioning load.

[0090] A first construction module, which is configured to: respectively construct a lighting load model and an elevator load model according to the commuting time, weekdays and holidays, and the influence of the personnel flow in the building on the lighting load and elevator load;

[0091] A second construction module, which is configured to: construct a socket load model based on the personnel flow in the building and the influence of different used devices on the socket load;

[0092] A third building block configured to build a central air-conditioning load model based on the impact of the personnel flow in the building, weather conditions, and time series on the central air-conditioning load;

[0093] A simulation module configured to obtain a commercial building load simulation result by combining the lighting load model, the elevator load model, the socket load model, and the central air-conditioning load model.

[0094] In more embodiments, there is also provided:

[0095] An electronic device includes a memory, a processor, and computer instructions stored on the memory and running on the processor. When the computer instructions are run by the processor, the method described in Embodiment 1 is completed. For the sake of brevity, it will not be elaborated here.

[0096] It should be understood that in this embodiment, the processor 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, off-the-shelf programmable gate arrays FPGA, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0097] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0098] A computer-readable storage medium for storing computer instructions, which when executed by a processor, completes the method described in Embodiment 1.

[0099] The method in Embodiment 1 can be directly embodied as being executed and completed by a hardware processor, or by a combination of hardware and software modules in the processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method. To avoid repetition, it will not be described in detail here.

[0100] A computer program product includes a computer program, which when executed by a processor, implements the method described in Embodiment 1.

[0101] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which are executed in a device on a target real or virtual processor to perform the processes / methods described above. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or divided as needed among program modules. The machine-executable instructions for program modules can be executed within local or distributed devices. In a distributed device, program modules can be located in local and remote storage media.

[0102] The computer program code for implementing the method of the present invention can be written in one or more programming languages. This computer program code can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program code is executed by the computer or other programmable data processing device, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code can be executed entirely on the computer, partially on the computer, as a stand-alone software package, partially on the computer and partially on a remote computer, or entirely on a remote computer or server.

[0103] In the context of the present invention, the computer program code or related data can be carried by any suitable carrier so that a device, apparatus, or processor can perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals can include electrical, optical, radio, acoustic, or other forms of propagated signals, such as carrier waves, infrared signals, etc.

[0104] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with this embodiment can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0105] Although the specific implementation manners of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation to the protection scope of the present invention. Those skilled in the art should understand that, based on the technical solution of the present invention, various modifications or deformations that can be made by those skilled in the art without creative efforts are still within the protection scope of the present invention.

Claims

1. A commercial building load simulation method considering the influence of multiple factors, characterized in that, Including: Dividing according to the load types in the building; wherein, the load types at least include: lighting load, elevator load, socket load, and central air-conditioning load. Respectively constructing a lighting load model and an elevator load model according to the commuting time, weekdays and holidays, and the influence of the personnel flow in the building on the lighting load and elevator load; Constructing a socket load model based on the personnel flow in the building and the influence of different used devices on the socket load; Constructing a central air-conditioning load model based on the personnel flow in the building, weather conditions, and the influence of time series on the central air-conditioning load; Combining the lighting load model, the elevator load model, the socket load model, and the central air-conditioning load model to obtain the load simulation result of the commercial building.

2. The commercial building load simulation method considering the influence of multiple factors as described in claim 1, wherein, The determination of the personnel flow situation is specifically as follows: Setting the maximum upper limit ratio of personnel to 1; Before the daily work start time, randomly generating the first ratio of the personnel due to arrive on the day; Setting the ratio of the actually arrived employees on the day as the second ratio, and the overtime employees on the day as the third ratio; According to the different times of each day, weekdays and holidays, using a random function to determine the value ranges of the first ratio, the second ratio, and the third ratio.

3. The commercial building load simulation method considering the influence of multiple factors according to claim 2, wherein In the lighting load model, determining the movable lighting load of the commercial building by multiplying the maximum movable lighting load by the second ratio of the currently actually arrived employees.

4. The commercial building load simulation method considering the influence of multiple factors as described in claim 1, wherein In the elevator load model, setting the elevator system operation to be in a fully loaded state during the commuting time period and the lunch break time period, and at this time taking the product of the maximum movable elevator load and the random disturbance multiplier as the movable elevator load; When the elevator system operation is in a half-loaded state, taking the product of a set ratio of the maximum movable elevator load and the random disturbance multiplier as the movable elevator load.

5. The commercial building load simulation method considering the influence of multiple factors as described in claim 2, characterized in that, In the socket load model, when the number of employees at work remains unchanged, the movable load of the socket system is the product of maintaining the maximum socket load, the second ratio of the currently actually arrived employees, and the disturbance factor; During the lunch break time period of the personnel in the commercial building, the movable load of the socket system is the product of maintaining the maximum socket load and the amplitude factor that first decreases and then increases and conforms to the Poisson distribution.

6. The commercial building load simulation method considering the influence of multiple factors as described in claim 1, characterized in that, In the central air-conditioning load model, after the air-conditioning system is turned on, the amplitude initial peak is the product of the maximum movable heating and cooling system load and the amplitude factor; when the indoor temperature reaches the specified temperature, calculating the load for cooling or heating according to the difference between the current temperature and the specified temperature; when the indoor temperature begins to be affected by the outdoor temperature for cooling or heating, the indoor temperature changes by the product of the indoor-outdoor temperature difference and the set ratio per minute, and when the indoor temperature reaches the warning line at the next moment, the heating and cooling system is turned on again, and the average load output resumes the amplitude initial peak, and so on in a cycle until the air-conditioning system is turned off.

7. A commercial building load simulation system considering the influence of multiple factors, characterized in that, Including: A dividing module, which is configured to: divide according to the load types in the building; wherein, the load types at least include: lighting load, elevator load, socket load, and central air-conditioning load. A first constructing module, which is configured to: respectively construct a lighting load model and an elevator load model according to the commuting time, weekdays and holidays, and the influence of the personnel flow in the building on the lighting load and elevator load; A second construction module, configured to: construct a socket load model based on the personnel flow situation in the building and the influence of different used devices on the socket load; A third construction module, configured to: construct a central air-conditioning load model based on the personnel flow situation in the building, the weather condition, and the influence of time series on the central air-conditioning load; A simulation module, configured to: combine the lighting load model, the elevator load model, the socket load model, and the central air-conditioning load model to obtain a commercial building load simulation result.

8. An electronic device, characterized in that, Comprising a memory, a processor, and computer instructions stored on the memory and running on the processor, when the computer instructions are run by the processor, the method according to any one of claims 1-6 is completed.

9. A computer-readable storage medium, characterized in that, For storing computer instructions, when the computer instructions are executed by the processor, the method according to any one of claims 1-6 is completed.

10. A computer program product, characterized in that, Comprising a computer program, when the computer program is executed by the processor, the method according to any one of claims 1-6 is implemented.

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