Comprehensive energy system carbon neutralization optimization adjustment method based on carbon emission constraint

Abstract

The invention provides an integrated energy system carbon neutralization optimization adjustment method based on carbon emission constraint, and belongs to the technical field of energy system management, and the method comprises the steps: setting a carbon emission target according to the carbon emission quota of an energy supply side; performing energy consumption characteristic analysis on the energy consumption data of the building users, and dividing the users into different load types; building a source-load joint simulation optimization platform; a multi-user collaborative response framework is established, an aggregator generates a preliminary temperature adjustment scheme according to load characteristics of different buildings, and different users are guided to perform collaborative adjustment; a differentiated temperature setting guidance scheme is generated in combination with a carbon emission target, user load characteristics and comfort requirements; the demand response effect is monitored in real time, and the adjustment scheme is dynamically adjusted. According to the method, collaborative optimization of the user and the energy supply side is achieved under the carbon emission constraint, it can be ensured that the overall carbon emission of the system does not exceed the quota, the operation efficiency of the comprehensive energy system can be effectively improved, and meanwhile the indoor comfort of the user is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy system management, and particularly relates to a carbon neutral optimization adjustment method for a comprehensive energy system based on carbon emission constraints. BACKGROUND

[0002] At present, the demand for reducing carbon emissions is increasing day by day in response to climate change. In order to achieve the goal of reducing carbon, countries usually set carbon emission quotas for power generation and heating enterprises. In order to meet these quota requirements, energy supply enterprises need to achieve the goal by improving their own energy utilization efficiency and reducing energy supply. However, it is difficult to completely meet the carbon emission constraints by adjusting the energy supply side alone, and demand side response has gradually become an important solution. In addition, the comprehensive energy system integrates natural gas, power grid and renewable energy and other forms of energy, and has higher flexibility, and has gradually become an important form of energy supply under carbon emission constraints. In the traditional demand response strategy, users adjust air conditioning and other load devices according to dynamic electricity prices or incentive signals. Due to the lack of coordination between different users, it is difficult to comprehensively consider the system operation efficiency and the comfort difference between users, and it is difficult to ensure the overall carbon emission reduction requirement.

[0003] Therefore, there is an urgent need for a comprehensive energy system optimization adjustment method that can consider user comfort and system energy efficiency under carbon emission constraints. SUMMARY

[0004] The present application provides a carbon neutral optimization adjustment method and device for a comprehensive energy system based on carbon emission constraints, to solve the defects in the prior art that it is difficult to comprehensively consider the system operation efficiency and the comfort difference between users, and it is difficult to ensure the overall carbon emission reduction requirement, and aims to achieve the carbon emission target constraint and improve the system operation efficiency and user comfort by considering the multi-user collaborative response.

[0005] In a first aspect, the present application provides a carbon neutral optimization adjustment method for a comprehensive energy system based on carbon emission constraints, comprising: S1, setting a carbon emission target according to the carbon emission quota of the energy supply side; S2, analyzing the energy consumption characteristics of the energy consumption data of the building users, and dividing the users into different load types; S3, establishing a source-load joint simulation model including the comprehensive energy system and the building air conditioning system; S4, establishing a multi-user collaborative response framework, generating a preliminary air conditioning temperature adjustment scheme for different users based on the load characteristics of different buildings, to guide the collaborative adjustment of different users; S5, taking the predicted mean vote PMV index as the optimization target, considering the carbon emission constraint, optimizing the preliminary air conditioning temperature adjustment scheme, and generating a differentiated air conditioning temperature setting guidance scheme; S6. Users set the air conditioning temperature according to the air conditioning temperature setting guide. Under carbon emission constraints, the air conditioning temperature setting guide is dynamically updated based on the actual needs of users and the response effect.

[0006] According to the carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints provided by the present invention, the energy consumption data source is historical data or real-time monitoring data, and the collection granularity is 15 minutes to 1 hour; user buildings are classified into three categories according to energy consumption characteristics: high load type, stable load type and low load type.

[0007] According to the carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints provided by the present invention, the source-load joint simulation model is constructed using TRNSYS, DEST software or Python or MATLAB programs based on theoretical formulas.

[0008] According to the carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints provided by the present invention, the source-load joint simulation model is the TRNSYS-python joint simulation optimization platform; wherein, the integrated energy system includes a natural gas internal combustion engine, a photovoltaic power generation unit, a lithium bromide unit, an electric chiller unit, a heat pump and an energy storage device; the building air conditioning system includes a 3D building module, a lithium bromide unit, an electric chiller, a terminal air handling unit and a water flow PID controller.

[0009] According to the carbon neutrality optimization regulation method for integrated energy systems based on carbon emission constraints provided by the present invention, in step S4, high-load buildings are given priority in regulating their air conditioning temperature.

[0010] According to the carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints provided by the present invention, the predicted average evaluation PMV index includes the average PMV index and the per capita PMV index. ; ; in, n The total number of buildings, i Number the buildings. j Numbering by time Occ ij For the first j Hour i The occupancy rate of the building. Area i For the first i The area of ​​each building, Area total This refers to the total building area.

[0011] According to the method, the differentiated temperature regulation in step S5 needs to meet the requirements of system energy consumption reduction, carbon emission constraint and predicted mean vote (PMV) index.

[0012] In a second aspect, the application further provides a carbon neutral optimization regulation device for a comprehensive energy system based on carbon emission constraint, comprising: A target determination module is configured to set a carbon emission target according to a carbon emission quota of the energy supply side. A user classification module is configured to analyze energy consumption characteristics of energy consumption data of building users, and divide the users into different load types. A joint modeling module is configured to establish a source-load joint simulation model including the comprehensive energy system and the building air conditioning system. A cooperative response module is configured to establish a multi-user cooperative response framework, generate a preliminary air conditioning temperature regulation scheme for different users based on load characteristics of different buildings, and guide the cooperative regulation of different users. An optimization regulation module is configured to optimize the preliminary air conditioning temperature regulation scheme based on a predicted mean vote (PMV) index as an optimization target and considering the carbon emission constraint, and generate a differentiated air conditioning temperature setting guidance scheme. A dynamic control module is configured to set an air conditioning temperature according to the air conditioning temperature setting guidance scheme, and dynamically update the air conditioning temperature setting guidance scheme according to actual demand response effects of the users under the carbon emission constraint.

[0013] In a third aspect, the application provides an electronic device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the carbon neutral optimization regulation method for a comprehensive energy system based on carbon emission constraint according to the program.

[0014] In a fourth aspect, the application further provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the steps of the carbon neutral optimization regulation method for a comprehensive energy system based on carbon emission constraint.

[0015] The carbon neutral optimization regulation method and device for a comprehensive energy system based on carbon emission constraint have the following advantages compared with the prior art. (1) The application can ensure that the overall carbon emission of the system meets the policy requirements and improve the overall operation efficiency of the system by the demand response mode of multi-user cooperation and the integration of information of the energy supply side and the demand side by the aggregator. (2) The application adopts a differentiated temperature regulation guidance strategy to minimize the impact on user comfort and improve user participation willingness. (3) The method of the present application comprehensively considers carbon emission constraints during demand response, effectively ensuring that the overall carbon emissions of the system do not exceed the quota.

[0016] (4) The present application introduces an air conditioning temperature regulation framework based on a multi-objective optimization algorithm, which can intelligently adjust according to system load, carbon emission constraints and user demand, optimize system operation in real time, and enhance the autonomous adaptability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 is a flowchart of the carbon emission constraint-based integrated energy system carbon neutralization optimization regulation method provided by the present application; Figure 2 is a structural diagram of the carbon emission constraint-based integrated energy system carbon neutralization optimization regulation device provided by the present application; Figure 3 is a structural diagram of the electronic device provided by the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the present application will be described clearly and completely in the following combined with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0020] It should be noted that in the description of the embodiments of the present application, the terms "comprising", "containing" or any other variants thereof are intended to cover the non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitation, the element defined by the statement "comprising a" does not exclude the presence of other identical elements in the process, method, article or equipment comprising the element. The terms "upper", "lower" and the like indicate the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0021] The terms "first", "second", and the like used in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally a class, not limited to the number of objects, for example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / ", generally indicates that the front and rear associated objects are in a "or" relationship.

[0022] The embodiments of the present application will be described below in conjunction with Figures 1-3 The embodiments of the present application provide a carbon emission constraint based integrated energy system carbon neutral optimization regulation method and device.

[0023] Figure 1 The flowchart of the carbon emission constraint based integrated energy system carbon neutral optimization regulation method provided by the present application is shown in Figure 1 The method comprises the following steps, but is not limited to the following steps: S1, setting a carbon emission target according to the carbon emission quota of the energy supply side.

[0024] Optionally, the aggregator sets a total carbon emission target according to the carbon emission quota of the energy supply enterprise, and decomposes it to each time period to determine the carbon emission target of each time period. Wherein, the carbon emission target setting can be based on relevant government policies and energy supply enterprise operation plans.

[0025] S2, analyzing the energy consumption data of the building users for energy consumption characteristics, and dividing the users into different load types.

[0026] The aggregator can collect the energy consumption data of various buildings in real time, including load curves and indoor environmental parameters, and divide the users into different load types.

[0027] The energy consumption data of the building user can be derived from historical data or real-time monitoring data, the time span can be several days to several months, and the data collection granularity can be 15 minutes to 1 hour. The user building can be divided into three types according to the energy consumption characteristics, i.e. high load type, stable load type and low load type.

[0028] S3, a source-load joint simulation model including the integrated energy system and the building air conditioning system is established.

[0029] Optionally, based on the thermodynamic theory, the key components of the supply side and the demand side are simulated and modeled to simulate the influence of different air conditioning temperature settings on the building thermal environment, system energy efficiency and carbon emission.

[0030] Optionally, the model in step 3 can use existing commercial software TRNSYS, DEST, etc., or can be modeled based on theoretical formulas using general software such as Python and MATLAB.

[0031] The integrated energy system includes a natural gas internal combustion engine, a photovoltaic power generation unit, a lithium bromide unit, an electric refrigeration unit, a heat pump and an energy storage device; the building air conditioning system includes a 3D building module, a lithium bromide unit, an electric refrigeration unit, an air handling unit and a water flow PID controller.

[0032] The air conditioning terminal equipment includes fan coil, air handling unit, etc., the fan speed is switched between high, medium and low according to the cooling load demand, and the water flow is adjusted in real time by the PID controller to ensure that the indoor temperature meets the set requirements.

[0033] S4, a multi-user collaborative response framework is established, and a preliminary air conditioning temperature adjustment scheme for different users is generated based on the load characteristics of different buildings to guide the collaborative adjustment of different users.

[0034] Optionally, the aggregator proposes a multi-user collaborative demand response framework according to the load types of different users, and generates a preliminary temperature adjustment scheme to guide the collaborative adjustment of different types of users.

[0035] For example, during the high load period, the high load type building with large adjustment potential is preferentially guided to adjust the air conditioning temperature to achieve the effect of peak load shifting.

[0036] S5, taking the predicted mean vote PMV index as the optimization target and considering the carbon emission constraint, the preliminary air conditioning temperature adjustment scheme is optimized to generate a differentiated air conditioning temperature setting guidance scheme.

[0037] Optionally, the aggregator acquires the operating status and energy efficiency information of energy supply equipment (such as gas turbines, heat pumps, and photovoltaic systems), and combines this with user-end information to design a differentiated air conditioning temperature setting guidance scheme. In each optimization process, carbon emissions are used as a constraint, and PMV (which can be set as average PMV and per capita PMV) is used as the optimization objective. Combined with a differential optimization algorithm, this ensures that user thermal comfort is maximized while meeting carbon emission constraints, generating precise air conditioning temperature adjustment schemes for different types of users.

[0038] Specifically, the temperature setting adjustment for each user in step 5 can be comprehensively considered in conjunction with the user's PMV. It should be ensured that the user's indoor comfort is maintained while reducing system energy consumption and meeting carbon emission constraints. Energy supply side equipment includes natural gas generator sets, heat pumps and photovoltaic power generation systems, etc. The formulas for calculating average PMV and per capita PMV are shown in equations (1) and (2), respectively. In addition to the differential algorithm selected in this patent, the optimization method can also be based on dynamic programming, linear programming, etc. Furthermore, since different buildings have different load characteristics, the response of air conditioning systems to load adjustment varies greatly in different buildings. Therefore, it is necessary to prioritize the adjustment of buildings with high energy-saving potential in order to optimize the system's energy efficiency and reduce carbon emissions.

[0039] (1) (2) in, n The total number of buildings, i Number the buildings. j Numbering by time Occ ij For the first j Hour i The occupancy rate of the building. Area i For the first i The area of ​​each building, Area total This refers to the total building area.

[0040] S6. Users set the air conditioning temperature according to the air conditioning temperature setting guide. Under carbon emission constraints, the air conditioning temperature setting guide is dynamically updated based on the actual needs of users and the response effect.

[0041] Specifically, users adjust the air conditioning system according to the temperature settings provided by the aggregator. The aggregator monitors the demand response effect in real time and dynamically adjusts the adjustment scheme based on feedback to ensure that carbon emission constraints are met.

[0042] The present application introduces a real-time feedback mechanism, so that the system can dynamically adjust the optimization scheme according to the user's feedback and load changes. The aggregator adjusts the air conditioning temperature setting and the running state of the energy supply device in real time according to the user feedback information, environmental changes and load fluctuations, to ensure the efficient operation and stable performance of the system.

[0043] Figure 2 The present application provides a structure schematic diagram of a carbon emission constraint based integrated energy system carbon neutralization optimization adjustment device, as shown in Figure 2 The device comprises: A target determination module 210 is configured to set a carbon emission target according to the carbon emission quota of the energy supply side; A user classification module 220 is configured to analyze the energy consumption characteristics of the energy consumption data of the building users, and divide the users into different load types; A joint modeling module 230 is configured to establish a source-load joint simulation model including the integrated energy system and the building air conditioning system; A cooperative response module 240 is configured to establish a multi-user cooperative response framework, generate a preliminary air conditioning temperature adjustment scheme for different users based on the load characteristics of different buildings, and guide different users to adjust cooperatively; An optimization adjustment module 250 is configured to take the predicted mean evaluation PMV index as an optimization target, consider the carbon emission constraint, optimize the preliminary air conditioning temperature adjustment scheme, and generate a differentiated air conditioning temperature setting guidance scheme; A dynamic control module 260 is configured to set the air conditioning temperature according to the air conditioning temperature setting guidance scheme, and dynamically update the air conditioning temperature setting guidance scheme according to the actual demand response effect of the user under the carbon emission constraint.

[0044] It should be noted that the carbon emission constraint based integrated energy system carbon neutralization optimization adjustment device provided by the embodiments of the present application can perform the carbon emission constraint based integrated energy system carbon neutralization optimization adjustment method described in any of the above embodiments during specific operation, and the present embodiment will not be repeated.

[0045] The carbon emission constraint based integrated energy system carbon neutralization optimization adjustment method and device provided by the present application have the following advantages compared with the prior art: (1) The present application adopts a multi-user cooperative demand response mode, and integrates the information of the energy supply side and the demand side through the aggregator, which can ensure that the overall carbon emission of the system meets the policy requirements, and improve the overall operation efficiency of the system; (2) The present application adopts a differentiated temperature adjustment guidance strategy, which can minimize the impact on user comfort and improve user participation willingness; (3) The present application method comprehensively considers the carbon emission constraint in the demand response process, which can effectively ensure that the overall carbon emission of the system does not exceed the quota.

[0046] (4) The application introduces an air conditioner temperature regulation framework based on a multi-objective optimization algorithm, which can intelligently adjust according to system load, carbon emission limit and user demand, optimize system operation in real time, and enhance the autonomous adaptability of the system.

[0047] Figure 3 is a structural schematic diagram of an electronic device provided by the application, as Figure 3 shown, the electronic device can include: a processor (processor) 310, a communications interface (communications interface) 320, a memory (memory) 330 and a communications bus 340, wherein the processor 310, the communications interface 320, the memory 330 complete mutual communication through the communications bus 340. The processor 310 can call the logic instructions in the memory 330 to execute the carbon emission constraint based comprehensive energy system carbon neutralization optimization regulation method, which includes: S1, setting a carbon emission target according to the carbon emission quota of the energy supply side; S2, analyzing the energy consumption characteristics of the energy consumption data of the building user, and dividing the user into different load types; S3, establishing a source-load joint simulation model including a comprehensive energy system and a building air conditioning system; S4, establishing a multi-user collaborative response framework, generating a preliminary air conditioning temperature regulation scheme for different users based on the load characteristics of different buildings to guide the collaborative adjustment of different users; S5, taking the predicted mean evaluation PMV index as the optimization target, considering the carbon emission constraint, optimizing the preliminary air conditioning temperature regulation scheme, and generating a differentiated air conditioning temperature setting guidance scheme; S6, the user sets the air conditioning temperature according to the air conditioning temperature setting guidance scheme, and dynamically updates the air conditioning temperature setting guidance scheme according to the actual demand response effect of the user under the carbon emission constraint.

[0048] In addition, the logic instructions in the memory 330 described above can be implemented in the form of a software function unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0049] In another aspect, the present application also provides a computer program product, which comprises a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method of optimizing adjustment of carbon neutralization of a comprehensive energy system based on carbon emission constraints provided by each of the above embodiments, the method comprising: S1, setting a carbon emission target according to a carbon emission quota of a power supply side; S2, analyzing energy consumption characteristics of energy consumption data of building users, and dividing the users into different load types; S3, establishing a source-load joint simulation model comprising a comprehensive energy system and a building air conditioning system; S4, establishing a multi-user collaborative response framework, generating a preliminary air conditioning temperature adjustment scheme for different users based on load characteristics of different buildings to guide collaborative adjustment of different users; S5, optimizing the preliminary air conditioning temperature adjustment scheme based on a predicted mean vote (PMV) index as an optimization target and considering carbon emission constraints, to generate a differentiated air conditioning temperature setting guidance scheme; and S6, setting air conditioning temperature according to the air conditioning temperature setting guidance scheme, and dynamically updating the air conditioning temperature setting guidance scheme according to actual demand response effects of the users under the carbon emission constraints.

[0050] In yet another aspect, the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the method of optimizing adjustment of carbon neutralization of a comprehensive energy system based on carbon emission constraints provided by each of the above embodiments, the method comprising: S1, setting a carbon emission target according to a carbon emission quota of a power supply side; S2, analyzing energy consumption characteristics of energy consumption data of building users, and dividing the users into different load types; S3, establishing a source-load joint simulation model comprising a comprehensive energy system and a building air conditioning system; S4, establishing a multi-user collaborative response framework, generating a preliminary air conditioning temperature adjustment scheme for different users based on load characteristics of different buildings to guide collaborative adjustment of different users; S5, optimizing the preliminary air conditioning temperature adjustment scheme based on a predicted mean vote (PMV) index as an optimization target and considering carbon emission constraints, to generate a differentiated air conditioning temperature setting guidance scheme; and S6, setting air conditioning temperature according to the air conditioning temperature setting guidance scheme, and dynamically updating the air conditioning temperature setting guidance scheme according to actual demand response effects of the users under the carbon emission constraints.

[0051] Those skilled in the art can clearly understand the technical solutions of the various embodiments from the above description of the embodiments, and the various embodiments can be implemented by means of software with the necessary general hardware platforms, and of course, can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, and the like, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0052] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features therein; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing carbon neutrality in a comprehensive energy system based on carbon emission constraints, characterized in that, include: S1. Set carbon emission targets based on carbon emission quotas on the energy supply side; S2. Analyze the energy consumption characteristics of building users' energy consumption data and classify users into different load types; S3. Establish a source-load joint simulation model that includes the integrated energy system and the building air conditioning system; S4. Establish a multi-user collaborative response framework to generate preliminary air conditioning temperature adjustment schemes for different users based on the load characteristics of different buildings, so as to guide different users to coordinate adjustment. S5. Using the predicted average evaluation PMV index as the optimization target and considering carbon emission constraints, optimize the preliminary air conditioning temperature regulation scheme and generate a differentiated air conditioning temperature setting guidance scheme. S6. Users set the air conditioning temperature according to the air conditioning temperature setting guide. Under carbon emission constraints, the air conditioning temperature setting guide is dynamically updated based on the actual needs of users and the response effect.

2. The carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints according to claim 1, characterized in that, The energy consumption data is sourced from historical data or real-time monitoring data, with a collection granularity of 15 minutes to 1 hour. User buildings are classified into three categories based on their energy consumption characteristics: high-load type, stable-load type, and low-load type.

3. The carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints according to claim 1, characterized in that, The source-load co-simulation model was constructed using TRNSYS and DEST software.

4. The carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints according to claim 3, characterized in that, The source-load co-simulation model is based on the TRNSYS-python co-simulation optimization platform; The integrated energy system includes a natural gas internal combustion engine, a photovoltaic power generation unit, a lithium bromide unit, an electric refrigeration unit, a heat pump, and an energy storage device; the building air conditioning system includes a 3D building module, a lithium bromide unit, an electric refrigeration unit, a terminal air handling unit, and a water flow PID controller.

5. The carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints according to claim 2, characterized in that, In step S4, high-load buildings are given priority in adjusting their air conditioning temperature.

6. The carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints according to claim 3, characterized in that, in, The predicted average evaluation PMV index includes the average PMV index and the per capita PMV index; ； ； in, n The total number of buildings, i Number the buildings. j Numbering by time Occ ij For the first j Hour i The occupancy rate of the building. Area i For the first i The area of ​​each building, Area total This refers to the total building area.

7. The carbon neutrality optimization and regulation method for integrated energy systems based on carbon emission constraints according to claim 3, characterized in that, In step S5, the differentiated temperature adjustment must simultaneously meet the requirements of reducing system energy consumption, constraining carbon emissions, and predicting average evaluation PMV index.

8. A carbon neutrality optimization and regulation device for an integrated energy system based on carbon emission constraints, characterized in that, include: The target setting module is used to set carbon emission targets based on the carbon emission quotas on the energy supply side; The user classification module is used to analyze the energy consumption characteristics of building users' energy consumption data and classify users into different load types. The joint modeling module is used to establish a source-load joint simulation model that includes the integrated energy system and the building air conditioning system; The collaborative response module is used to establish a multi-user collaborative response framework, generate preliminary air conditioning temperature adjustment schemes for different users based on the load characteristics of different buildings, and guide different users to coordinate adjustments. The optimization and adjustment module is used to optimize the initial air conditioning temperature adjustment scheme with the predicted average evaluation PMV index as the optimization target and considering carbon emission constraints, and generate a differentiated air conditioning temperature setting guidance scheme. The dynamic control module is used by users to set the air conditioning temperature according to the air conditioning temperature setting guide. Under carbon emission constraints, the air conditioning temperature setting guide is dynamically updated according to the actual needs of users.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the carbon neutrality optimization regulation method for an integrated energy system based on carbon emission constraints as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the carbon neutrality optimization regulation method for an integrated energy system based on carbon emission constraints as described in any one of claims 1 to 7.

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