Regional heat supply system flexible adjustment method and device based on multi-user thermal comfort priority game, electronic equipment and storage medium

Abstract

The invention provides a regional heat supply system flexible adjustment method and device based on a multi-user thermal comfort priority game, electronic equipment and a storage medium, and relates to the technical field of energy scheduling. Determining a dynamic mapping rule between the plurality of heat users and the heat source temperature, and analyzing the influence of the heat source change on the temperature dynamic characteristic of each heat user at the future moment to obtain first data; comparing the adjusting capabilities of different flexible adjusting methods when the thermal comfort of different heat users is taken as an optimization target and the thermal comfort weighted values of all the heat users are taken as the optimization target to obtain second data; and determining a target flexible adjustment scheme according to the first data and the second data. According to the method, a plurality of heat user thermal comfort priority games are considered, only one heat user thermal comfort ratio is considered, and the thermal comfort of all heat users is considered at the same time, so that the calculation speed of an optimization adjustment strategy can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy scheduling, and in particular, to a flexible regulation method, device, electronic device and storage medium for a district heating system based on a multi-user thermal comfort priority game. Background Art

[0002] The district heating system mainly includes parts such as a power generation unit, a power grid, a heating system, a heating pipeline network, a heat exchanger, an electricity user, a heat user, etc. The power generation unit includes a gas turbine combined heat and power unit, a thermal power unit and a wind power unit. The total sum of the electricity output is always equal to the user's electricity load at all times to ensure the power balance of the power system. The residential heat load is provided by the combined heat and power unit. In order to give priority to ensuring the thermal comfort of users, the electricity output of the thermal power unit is determined by the heat output. Among them, the heating system includes multiple heat users, which are connected to the heat source through a complex pipeline network structure. The heat source is still a single heat source, but the heat users change from single nodes to multiple nodes.

[0003] Since the planning of the heat supply amount of the heat source in the district heating system needs to take into account the comfort of multiple heat users, and the heat transfer process is more complex, the complexity of the electro-thermal coordination optimization calculation for the district heating system with multiple heat users is relatively large. Summary of the Invention

[0004] The present invention provides a flexible regulation method, device, electronic device and storage medium for a district heating system based on a multi-user thermal comfort priority game, so as to solve the defect that the complexity of the electro-thermal coordination optimization calculation for the district heating system with multiple heat users in the prior art is relatively large. By considering the multi-user thermal comfort priority game and only considering the thermal comfort of one heat user rather than considering the thermal comfort of all heat users at the same time as the optimization goal, the calculation speed of the optimization regulation strategy can be greatly improved. When the scale of the district heating system is large and the number of heat user groups reaches hundreds, it is beneficial to simplify the algorithm.

[0005] The present invention provides a flexible regulation method for a district heating system based on a multi-user thermal comfort priority game, which is applied to a district heating system. The district heating system includes multiple heat users, and the method includes the following steps: Based on the heat transfer dynamic model of the district heating system including a complex pipe network and multiple heat users, determine the dynamic mapping rule between multiple heat users and the heat source temperature, and analyze the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping rule, so as to obtain the first data; Set the regulation capacity provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization goal, and take the thermal comfort of each heat user as the secondary optimization goal respectively. Through the multi-user thermal comfort priority game, compare the regulation capacities corresponding to different flexible regulation methods when taking the thermal comfort of different heat users as the optimization goal and when taking the weighted value of the thermal comfort of all heat users as the optimization goal, and obtain the second data; Determine the target flexible regulation scheme according to the first data and the second data. The target flexible regulation scheme is to select a flexible regulation scheme with the thermal comfort of one heat user as the optimization goal to replace the flexible regulation scheme considering the weighted value of the thermal comfort of all heat users as the optimization goal.

[0006] According to a flexible regulation method for a district heating system based on multi-user thermal comfort priority game provided by the present invention, based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, determine the dynamic mapping law between multiple heat users and the heat source temperature, and analyze the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law, and obtain the first data, including: Collect the heat transfer parameters of each heat user node. The heat transfer parameters include the heat transfer coefficient from the primary network to the secondary network, the heat transfer area, the secondary network flow rate, the heat transfer coefficient from the secondary network to the user, the heat transfer area, and the steady-state heat transfer coefficient from the user to the outside and the heat transfer area of the enclosure structure; Use the pipe network hydraulic calculation model to calculate the hydraulic parameters of each branch of the pipe network and form a heat transfer contribution matrix; According to the calculation formula of the total pump power of the pipe network, combined with the total volume flow rate of the main road, the total pressure drop, the resistance coefficient and the pump efficiency, calculate the total pump power of the pipe network; Input the heat transfer parameters of each heat user node, the heat transfer contribution matrix and the total pump power of the pipe network into the heat transfer dynamic model for optimization calculation to obtain the dynamic mapping law; According to the heat transfer characteristics of the pipeline and the heat exchange constraints of the heat exchange station, and the dynamic mapping law, analyze the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments to obtain the first data.

[0007] According to a flexible regulation method for a district heating system based on multi-user thermal comfort priority game provided by the present invention, the heat transfer characteristics of the pipeline and the heat exchange constraints of the heat exchange station include user steady-state heat exchange constraints, pipe network heat transfer constraints and minimum indoor temperature constraints. The user steady-state heat exchange constraints are used to constrain the heat transfer parameters of each heat user node, the pipe network heat transfer constraints are used to constrain the parameters of heat transfer in the pipeline in the heat supply pipe network, and the minimum indoor temperature constraints are used to constrain the minimum indoor temperature of the heat user node.

[0008] A flexible regulation method for a district heating system based on a multi - user thermal comfort priority game provided by the present invention, determining the target flexible regulation scheme according to the first data and the second data, includes: Determine the target flexible regulation scheme according to the first data and the second data, where the target flexible regulation scheme is a flexible regulation scheme with the thermal comfort of the heat user farthest from the heat source selected as the optimization target.

[0009] A flexible regulation method for a district heating system based on a multi - user thermal comfort priority game provided by the present invention, obtaining the second data by comparing, through the multi - user thermal comfort priority game, the regulation capabilities of different flexible regulation methods when different heat user thermal comforts are used as optimization targets and when the weighted value of all heat user thermal comforts is used as the optimization target, includes: Through the multi - user thermal comfort priority game, compare the situations where the thermal comforts of other heat users corresponding to different flexible regulation methods are within the allowable range when different heat user thermal comforts are used as optimization targets and when the weighted value of all heat user thermal comforts is used as the optimization target; According to the situations where the thermal comforts of other heat users are within the allowable range, determine the regulation capabilities of different flexible regulation methods to obtain the second data.

[0010] A flexible regulation method for a district heating system based on a multi - user thermal comfort priority game provided by the present invention, the situations where the thermal comforts of other heat users corresponding to different flexible regulation methods are within the allowable range when different heat user thermal comforts are used as optimization targets and when the weighted value of all heat user thermal comforts is used as the optimization target, include: Determine a heat transfer dynamic model, where the heat transfer dynamic model includes operation constraints, optimization targets, and decision variables. The operation constraints include district heating system constraints, gas turbine combined heat and power unit and thermal power unit constraints, and power grid and wind turbine unit constraints. The optimization targets include the regulation capabilities provided by the district heating system for suppressing new - energy fluctuations throughout the day and the thermal comforts of each heat user. The decision variables include the hourly heat supply temperature of the heat source, the heat output of the combined heat and power unit, the output of the thermal power unit, and the output of the wind power. Through the heat transfer dynamic model, compare the situations where the thermal comforts of other heat users corresponding to different flexible regulation methods are within the allowable range when different heat user thermal comforts are used as optimization targets and when the weighted value of all heat user thermal comforts is used as the optimization target.

[0011] A flexible regulation method for a district heating system based on a multi - user thermal comfort priority game provided by the present invention, the gas turbine combined heat and power unit and thermal power unit constraints include: heat - to - power ratio, ramp - up / down constraints, and unit limit output.

[0012] A flexible regulation method for a district heating system based on multi - user thermal comfort priority game provided by the present invention, the constraint conditions of the district heating system include: thermal load flexibility constraint, heating temperature ramp constraint, upper and lower limits of the heat source supply water temperature, power consumption of the heating system pump, and temperature feedback regulation constraint.

[0013] A flexible regulation method for a district heating system based on multi - user thermal comfort priority game provided by the present invention, the constraints of the power grid and wind turbine units include: power grid power balance constraint, wind power limit output constraint, and line capacity constraint.

[0014] A flexible regulation method for a district heating system based on multi - user thermal comfort priority game provided by the present invention, the heating system constraint of the district heating system further includes, according to the transmission delay characteristics of the heating pipe network, constraining the heat source to provide the heat load of users at high - heat - load moments in advance for a period of time.

[0015] A flexible regulation method for a district heating system based on multi - user thermal comfort priority game provided by the present invention, comparing through the heat transfer dynamic model the different flexible regulation methods when the optimization objectives are the thermal comfort of different heat users and the weighted value of the thermal comfort of all heat users, and whether the thermal comfort of other heat users is within the allowable range, including: A method of optimizing only for the operation of the thermal system, with the optimization objective being the best thermal comfort of different heat users; or, A method of optimizing only from the power system level, with the optimization objective being the minimum wind curtailment at all times; or, A method of overall optimizing the district heating system, with the minimum wind curtailment at all times of the day as the primary optimization objective and the best thermal comfort of different heat users as the secondary optimization objective The present invention also provides a flexible regulation device for a district heating system based on multi - user thermal comfort priority game, which is applied to a district heating system. The district heating system includes multiple heat users, and includes the following modules: The first analysis module is used to determine the dynamic mapping rule between multiple heat users and the heat source temperature based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, and analyze the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping rule, so as to obtain the first data; The second analysis module is used to set the regulation capacity provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization goal, and the thermal comfort of each heat user as the secondary optimization goal respectively. Through the multi-user thermal comfort priority game, compare the regulation capacity sizes of different flexible regulation methods corresponding to taking the thermal comfort of different heat users as the optimization goal and taking the weighted value of the thermal comfort of all heat users as the optimization goal, and obtain the second data; The scheme acquisition module is used to determine the target flexible regulation scheme according to the first data and the second data. The target flexible regulation scheme is a flexible regulation scheme that selects the thermal comfort of one heat user as the optimization goal to replace the flexible regulation scheme that considers the weighted value of the thermal comfort of all heat users as the optimization goal.

[0016] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, it implements the flexible regulation method of the district heating system based on multi-user thermal comfort priority game as described in any one of the above.

[0017] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the flexible regulation method of the district heating system based on multi-user thermal comfort priority game as described in any one of the above.

[0018] The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the flexible regulation method of the district heating system based on multi-user thermal comfort priority game as described in any one of the above.

[0019] The flexible regulation method, device, electronic device and storage medium of the district heating system based on multi-user thermal comfort priority game provided by the present invention, by considering the multi-user thermal comfort priority game and only considering the thermal comfort of one heat user rather than considering the thermal comfort of all heat users as the optimization goal, can greatly improve the calculation speed of the optimization regulation strategy. When the scale of the district heating system is large and the number of heat user groups reaches hundreds, it is beneficial to simplify the algorithm. Description of the Drawings

[0020] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a schematic diagram of the architecture of the district heating system provided by the present invention.

[0022] Figure 2 It is a schematic flow chart of the flexible regulation method for the district heating system based on the multi - user thermal comfort priority game provided by the present invention.

[0023] Figure 3 It is a schematic flow chart of obtaining the first data provided by the present invention.

[0024] Figure 4 It is the electricity load and wind power limit processing curve provided by the present invention.

[0025] Figure 5 It is a schematic flow chart of implementing the flexible regulation method for the district heating system provided by the present invention.

[0026] Figure 6 It is a schematic diagram of the overall framework of the heat transfer dynamic model provided by the present invention.

[0027] Figure 7 It is a schematic diagram of the comparison of the indoor temperature of users under the scheme of only ensuring the thermal comfort of a single node provided by the present invention.

[0028] Figure 8 It is a schematic diagram of the heat supply temperature of the heat source when separately ensuring the thermal comfort of different user nodes provided by the present invention.

[0029] Figure 9 It is a schematic diagram of the comparison between the total air rejection volume of the system and the total thermal comfort provided by the present invention.

[0030] Figure 10 It is a schematic structural diagram of the flexible regulation device for the district heating system based on the multi - user thermal comfort priority game provided by the present invention.

[0031] Figure 11 It is a schematic physical structure diagram of the electronic device provided by the present invention. Detailed implementation manners

[0032] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0033] The district heating system mainly includes a power generation unit, a power grid, a heating system, a heating pipeline network, a heat exchanger, electricity users, heat users, etc. The power generation unit includes a gas turbine combined heat and power unit, a thermal power unit, and a wind power unit. The total sum of the electricity output is always equal to the electricity load of the users to ensure the power balance of the power system. The residential heat load is provided by the combined heat and power unit. To give priority to ensuring the thermal comfort of users, the electricity output of the thermal power unit is determined by the heat output. Among them, the heating system includes multiple heat users, which are connected to the heat source through a complex pipeline network structure. The heat source is still a single heat source, but the heat users change from single nodes to multiple nodes.

[0034] Since the planning of the heat supply of the heat source in the district heating system needs to take into account the comfort of multiple heat users, and the heat transfer process is more complex, the complexity of the electro-thermal coordinated optimization calculation for the district heating system with multiple heat users is relatively large.

[0035] In view of this, the embodiment of the present invention provides a flexible adjustment method for a district heating system based on the priority game of multi-user thermal comfort, including: based on the dynamic heat transfer model of the district heating system including a complex pipe network and multiple heat users, determining the dynamic mapping law between multiple heat users and the heat source temperature, and analyzing the influence of the heat source change on the dynamic characteristics of the temperature of each heat user at future moments to obtain the first data; comparing the adjustment capabilities of different flexible adjustment methods when different heat user thermal comforts are used as optimization objectives and the weighted value of the thermal comforts of all heat users is used as the optimization objective to obtain the second data; determining the target flexible adjustment plan according to the first data and the second data. The target flexible adjustment plan is to select a flexible adjustment plan with the thermal comfort of a single heat user as the optimization objective to replace the flexible adjustment plan with the weighted value of the thermal comforts of all heat users as the optimization objective. This method takes into account the priority game of the thermal comforts of multiple heat users, and only considering the thermal comfort of a single heat user can greatly improve the calculation speed of the optimization adjustment strategy compared with considering the thermal comforts of all heat users at the same time. When the scale of the district heating system is large and the number of heat user groups reaches hundreds, it is beneficial to simplify the algorithm.

[0036] Next, the technical solutions in the embodiments of the present invention will be described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0037] Figure 1 It is a schematic diagram of the architecture of the district heating system provided by the present invention. As Figure 1 shown, the present invention takes the problem of abandoned wind in the winter wind power consumption in the northeast region of China as the background, and determines that the regional district heating system includes a gas turbine combined heat and power unit and a thermal power unit, a heating system, and a power grid and a wind power unit. The district heating system includes multiple heat users.

[0038] Figure 2It is a schematic flowchart of a flexible regulation method for a district heating system based on a multi-user thermal comfort priority game provided by the present invention. The flexible regulation method for a district heating system based on a multi-user thermal comfort priority game can be applied to an electronic device in the district heating system, and the electronic device can be various types of devices with information processing capabilities during implementation. For example, the electronic device may include a personal computer, a laptop, a handheld computer, or a server, etc.; the electronic device can also be a mobile terminal, for example, the mobile terminal may include a mobile phone, a vehicle-mounted computer, a tablet computer, or a projector, etc. As Figure 2 shown, the method may include the following steps 101 to step 102: Step 101: Based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, determine the dynamic mapping law between multiple heat users and the heat source temperature, and analyze the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law, so as to obtain the first data.

[0039] It should be noted that there are many ways to determine the dynamic mapping law between multiple heat users and the heat source temperature based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users. For example, it can be determined based on the adjustment parameters involved in multi-heat user thermal comfort adjustment, or determined according to the adjustment logic, etc. The present invention does not limit the method of determining the dynamic mapping law between multiple heat users and the heat source temperature based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, and analyzing the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain the first data.

[0040] Step 102: Set the regulation capacity provided by the district heating system for new energy fluctuation suppression throughout the day as the primary optimization goal, and take the thermal comfort of each heat user as the secondary optimization goal. Through multi-user thermal comfort priority game, compare the regulation capacities corresponding to different flexible regulation methods when taking the thermal comfort of different heat users as the optimization goal and when taking the weighted value of the thermal comfort of all heat users as the optimization goal, so as to obtain the second data.

[0041] Step 103: Determine the target flexible regulation scheme according to the first data and the second data. The target flexible regulation scheme is to select a flexible regulation scheme with the thermal comfort of one heat user as the optimization goal to replace the flexible regulation scheme considering the weighted value of the thermal comfort of all heat users as the optimization goal.

[0042] It can be understood that the flexible regulation method of the district heating system based on the game of thermal comfort priorities of multiple heat users takes into account the game of thermal comfort priorities of multiple heat users. Moreover, taking the thermal comfort of only one heat user as the optimization goal instead of considering the thermal comfort of all heat users simultaneously can greatly improve the calculation speed of the optimization regulation strategy. When the scale of the district heating system is large and the number of heat user groups reaches hundreds, it is beneficial to simplify the algorithm.

[0043] In some embodiments, based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, determining the dynamic mapping law between multiple heat users and the heat source temperature, and analyzing the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain the first data may include: collecting the heat exchange parameters of each heat user node, where the heat exchange parameters include the heat transfer coefficient, heat exchange area, and secondary network flow rate from the primary network to the secondary network, the heat transfer coefficient and heat exchange area from the secondary network to the user, as well as the steady-state heat transfer coefficient from the user to the outdoors and the heat exchange area of the building envelope; using the pipe network hydraulic calculation model to calculate the hydraulic parameters of each branch of the pipe network and form a heat transfer contribution matrix; calculating the total pump work of the pipe network according to the calculation formula of the total pump work of the pipe network, combining the total volume flow rate, total pressure drop, resistance coefficient, and pump efficiency of the main road; inputting the heat exchange parameters of each heat user node, the heat transfer contribution matrix, and the total pump work of the pipe network into the heat transfer dynamic model for optimization calculation to obtain the dynamic mapping law; analyzing the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the heat transfer characteristics of the pipeline, the heat exchange constraints of the heat exchange station, and the dynamic mapping law to obtain the first data.

[0044] Figure 3 It is a schematic flow chart of obtaining the first data provided by the present invention. As Figure 3 shown, based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, determining the dynamic mapping law between multiple heat users and the heat source temperature, and analyzing the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain the first data may include: Step 201: Collect the heat exchange parameters of each heat user node, where the heat exchange parameters include the heat transfer coefficient, heat exchange area, and secondary network flow rate from the primary network to the secondary network, the heat transfer coefficient and heat exchange area from the secondary network to the user, as well as the steady-state heat transfer coefficient from the user to the outdoors and the heat exchange area of the building envelope.

[0045] It should be noted that the heat exchange parameters of each heat user node specifically include the following three items: a) The heat transfer coefficient, heat exchange area, and secondary network flow rate from the primary network to the secondary network; b) The heat transfer coefficient and heat exchange area from the secondary network to the user; c) The steady-state heat transfer coefficient from the user to the outdoors and the heat exchange area of the building envelope.

[0046] In the case study, to simplify the calculation process, based on the research data, the heat transfer coefficient of the enclosure structure for all users can be uniformly set to 2 W / (m 2 ·K), and the radiator coefficient is set to 5.69 W / (m 2 ·K). The heat exchanger area of the heat exchange station, the enclosure structure area, the radiator area on the user side, etc. are shown in Table 1. The flow rates of the primary network and the secondary network and the heat exchanger parameters of the heat exchange station are shown in Table 2.

[0047] Table 1 User heat transfer parameters corresponding to each heat exchange station Table 2 Heat exchange station heat transfer parameters corresponding to each heat user Step 202: Use the hydraulic calculation model of the pipe network to calculate the hydraulic parameters of each branch of the pipe network and form a heat transfer contribution matrix.

[0048] It should be noted that the flow velocities of each branch of the pipe network are different. The flow velocity of the pipe section farthest from the heat source is used as the reference data for the flow state of the pipe network to analyze the effect of the electro-thermal coordination optimization scheme for the multi-heat user node system. The corresponding hydraulic parameters of other pipe sections in this case are calculated using the hydraulic calculation model of the pipe network. The calculation results of the pipe network composite heat transfer contribution matrix are shown in Table 3.

[0049] Table 3 Heat transfer contribution matrix table of each pipeline at different pipe section flow velocities Step 203: According to the calculation formula of the total pump power of the pipe network, combined with the total volume flow rate, total pressure drop, resistance coefficient and pump efficiency of the main pipeline, calculate the total pump power of the pipe network.

[0050] It should be noted that the pipe network contains multiple pipes. The total pump power of the pipe network is equal to the product of the total volume flow rate of the main pipeline and the total pressure drop. The total pressure drop is equal to the main pipeline pressure drop plus the branch pipeline pressure drop. Based on this, the calculation formula for the total pump power of the circulation pumps of the supply pipe and the return pipe of the pipe network is derived as shown in Equation (5.2).

[0051] The total pressure drop of the pipe network is shown in Equation (5.3).

[0052] (5.3); Substitute Equation (5.3) into Equation (5.2) to obtain the total pump power P pmp,sum expression for a system with multiple user nodes and multiple pipe network branches, as shown in Equation (5.4).

[0053] (5.4); Among them, P pump,sum represents the pump power, in kW; Ga and Gg represent the flow rate, in kg / s; S represents the resistance coefficient, in Pa / (m 3 / h) 2 ; η represents the pump efficiency; 0.02592 is the unit conversion coefficient.

[0054] (5.2); Among them, P pump,p represents the pump power, in kW; G v represents the flow rate, in m 3 / s.

[0055] Step 204: Input the heat transfer parameters of each heat user node, the heat transfer contribution matrix, and the total pump work of the pipe network into the heat transfer dynamic model for optimization calculation to obtain the dynamic mapping rule.

[0056] It should be noted that the method of inputting the heat transfer parameters of each heat user node, the heat transfer contribution matrix, and the total pump work of the pipe network into the heat transfer dynamic model for optimization calculation to obtain the dynamic mapping rule can be to determine the user thermal comfort adjustment constraint according to the parameters in the heat transfer parameters of each heat user node, the heat transfer contribution matrix, and the total pump work of the pipe network, or to determine the user thermal comfort adjustment constraint according to the calculation logic therein. The present invention does not limit the method of inputting the heat transfer parameters of each heat user node, the heat transfer contribution matrix, and the total pump work of the pipe network into the heat transfer dynamic model for optimization calculation to obtain the dynamic mapping rule.

[0057] Step 205: Analyze the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the heat transfer characteristics of the pipeline, the heat exchange station heat exchange constraint, and the dynamic mapping rule to obtain the first data.

[0058] Exemplarily, the central heating system in the multi-heat user system example includes one heat source and six user nodes (including heat exchange stations and user groups). Based on the investigated data, the multi-node case is analyzed and solved. The parameters that need to be measured also include other parameters. For example, when the user electric load of the 6-node user increases, the supporting power generation units include wind turbine units, combined heat and power units, and thermal power units, and their scales are also larger than those in the single-user node example. There are 2 combined heat and power units, 1 standby and 1 in use, with the maximum and minimum power generation powers being 50 MW and 24 MW respectively, and the unit ramp-up constraint being 30 MW / h. There is 1 thermal power unit, with the maximum and minimum limit outputs being 70 MW and 24 MW respectively, and the ramp-up constraint being 35 MW / h.

[0059] It can be understood that by determining the influence of the heat source change on the dynamic characteristics of the temperature of each heat user at future moments according to the above parameters and obtaining the first data, more accurate analysis data results can be obtained.

[0060] Figure 4 is the curve for handling the electricity load and wind power limit provided by the present invention. As Figure 4 shown, the hourly limit output curve of the wind turbine records the hourly limit output curves and hourly electricity load curves of a series of wind farms of different scales throughout the day. It can be seen that the demand of the electricity load does not fully match the ability of the wind power limit output.

[0061] Based on the flexible regulation method of the district heating system based on the multi-user thermal comfort priority game provided by the present invention, based on the heat transfer dynamic model considering the overall operation of the pipe network and the system, the relevant parameters of the heat exchange process of the above 6 user nodes, the heat transfer contribution matrix, and the return water mixing temperature expression can be input into the optimization model for optimization calculation.

[0062] In some embodiments, the heat transfer characteristics of the pipeline and the heat exchange station heat exchange constraints include user steady-state heat exchange constraints, pipe network heat transfer constraints, and minimum indoor temperature constraints. The user steady-state heat exchange constraints are used to constrain the heat exchange parameters of each heat user node, the pipe network heat transfer constraints are used to constrain the parameters of heat transfer in the pipeline in the heat supply pipe network, and the minimum indoor temperature constraints are used to constrain the minimum indoor temperature of the heat user node.

[0063] Among them, for a heat supply pipe network containing multiple user nodes, the indoor temperatures of each node are different. The traditional pipe network regulation does not fully consider the heat transfer characteristics of the pipeline and the heat exchange station heat exchange constraints. The electro-thermal coordinated optimization method proposed by the present invention comprehensively considers the user steady-state heat exchange constraints, the pipe network heat transfer constraints, and the minimum indoor temperature constraints. In order to rationally allocate resources in the coordinated dispatching and ensure the thermal comfort of each node, the maximum wind power consumption and the lowest total system energy consumption are achieved.

[0064] Exemplarily, (1) User steady-state heat exchange constraints. The heat exchange process can be the heat exchange process between the primary network and the secondary network, between the secondary network and the user, and between the user and the outdoor atmospheric environment.

[0065] (2) Pipe network heat transfer constraints. The power dispatching system adjusts the output of each power plant unit every 15 minutes, while the adjustment period of the heat supply pipe network is relatively long compared with the power dispatching period. Usually, the temperature is adjusted only once every dozens of minutes or even several hours. The focus of the present invention is to incorporate the heat supply pipe network regulation into the power dispatching framework. Therefore, in order to unify the time scale of the operation regulation of each part of the district heating system, the present invention establishes a heat transfer equation with a 15-minute adjustment period for the heat supply pipe network.

[0066] (3) Minimum indoor temperature constraint: Since the optimal indoor temperature in winter is 20°C and the allowable range is 20 ± 2°C, the minimum indoor temperature constraint can be set to 18 degrees.

[0067] In some embodiments, determining the target flexible adjustment scheme according to the first data and the second data may include: determining the target flexible adjustment scheme according to the first data and the second data, where the target flexible adjustment scheme is a flexible adjustment scheme with the thermal comfort of the heat user farthest from the heat source as the optimization target.

[0068] In some embodiments, by multi-user thermal comfort priority game, comparing the adjustment capabilities of different flexible adjustment methods when different heat user thermal comfort is used as the optimization target and when the weighted value of all heat user thermal comfort is used as the optimization target to obtain the second data may include: by multi-user thermal comfort priority game, comparing different flexible adjustment methods when different heat user thermal comfort is used as the optimization target and when the weighted value of all heat user thermal comfort is used as the optimization target, and determining whether the thermal comfort of other heat users is within the allowable range; according to whether the thermal comfort of other heat users is within the allowable range, determining the adjustment capabilities of different flexible adjustment methods to obtain the second data.

[0069] It can be understood that a multi-heat user system refers to a heating system that includes multiple heat users and is connected to the heat source through a complex pipeline network structure. The heat source is still a single heat source, but the heat users change from single nodes to multiple nodes, and there is a relatively complex heat transfer process. The planning of the heat supply of the heat source needs to consider the comfort factors of multiple heat users, and the user thermal comfort also needs to be replaced by the superposition of the indoor temperature thermal deviation amounts of multiple nodes.

[0070] For the case of multi-heat user nodes (composed of multi-heat user nodes, complex pipe network topologies, large thermal power plants, thermal power plants and wind farms), the present invention can obtain the total thermal deviation amount and compare it with the heat load fluctuation range. If the total thermal deviation amount is not within the heat load fluctuation range, it means that the thermal comfort is not good. If the total deviation amount is within the heat load fluctuation range, it means that the thermal comfort is good. Based on the judgment result, the heat supply of the heat source can be adjusted.

[0071] It can be understood that in the case of multi-user nodes, by obtaining the total thermal deviation amount, analyzing the feasibility of the influence of electric-heat coordination optimization on wind power consumption, analyzing the influence of preferentially ensuring the comfort of different nodes on the overall performance of the system, and determining the heat distribution and optimization principles when a single heat source faces multi-user group nodes, it can provide a theoretical basis for the optimal operation of actual complex pipe networks.

[0072] Figure 5 It is a flow chart showing the implementation of the flexible adjustment method for the district heating system provided by the present invention. AsFigure 5 As shown, the flexible regulation scheme for user thermal comfort regulation of the district heating system, the constraints of gas turbine combined heat and power units and thermal power units, the constraints of the power grid and wind turbine units, and the optimization objectives and decision variables of the district heating system to achieve the coordinated operation of electricity and heat in the district heating system may include: Step 301: Determine the heat transfer dynamic model. The heat transfer dynamic model includes operation constraints, optimization objectives, and decision variables. The operation constraints include district heating system constraints, gas turbine combined heat and power unit and thermal power unit constraints, and power grid and wind turbine unit constraints. The optimization objectives include the regulation capacity provided by the district heating system for suppressing new energy fluctuations throughout the day and the thermal comfort of each heat user. The decision variables include the hourly heat supply temperature of the heat source, the heat output of the combined heat and power unit, the output of the thermal power unit, and the output of the wind power. Step 302: Compare different flexible regulation methods with different thermal comfort levels of heat users as the optimization objective and the weighted value of the thermal comfort levels of all heat users as the optimization objective through the heat transfer dynamic model, and check whether the thermal comfort levels of other corresponding heat users are within the allowable range.

[0073] Figure 6 is a schematic diagram of the overall framework of the heat transfer dynamic model provided by the present invention. As Figure 6 shown, it is the overall framework of the heat transfer dynamic model considering the overall operation of the pipe network and the system proposed by the present invention. The heat transfer dynamic model is mainly composed of three elements: operation constraints, optimization objectives, and decision variables. Since the power system and the district heating system are coupled through combined heat and power units, the operation constraints and decision variable elements are further divided into three types: power system, district heating system, and electro-thermal coupling. The operation constraints consist of the operation constraints of the power grid, thermal power units, wind turbine units, etc. in the power system, the pipe network heat transfer constraints, heat exchange constraints, and combined heat and power unit constraints in the district heating system. The decision variables include the hourly heat supply temperature of the heat source, the heat output of the combined heat and power unit, the output of the combined heat and power unit, the output of the thermal power unit, and the output of the wind power. The combined heat and power unit constraints and decision variables belong to both the power system and the district heating system, which is the electro-thermal coupling part. The optimization objective is a two-level optimization objective considering the minimum all-day wind power curtailment and the best user thermal comfort.

[0074] The district heating system includes parts such as gas turbine combined heat and power units, wind farms, centralized heating systems, and power grids. The operation constraints of each part are specifically described as follows.

[0075] The constraints of the gas turbine combined heat and power units and thermal power units include: the heat-electricity ratio, ramp constraints, and unit limit output.

[0076] (1) Heat-electricity ratio constraint The power system and the thermal system are coupled through a cogeneration unit. The heat - to - power ratio of a gas - turbine cogeneration unit is equal to the ratio of the heat supply to the power supply, as shown in Equation (4.47), and mainly depends on the overall thermal efficiency. The electric - heat dispatch studied in this invention mainly focuses on the operating characteristics of the heat - power network. Therefore, the operating characteristics of the cogeneration unit are not analyzed in depth, and it is assumed that the unit operates in a fixed heat - to - power ratio mode.

[0077] (4.47); In the formula, ε represents the heat - to - power ratio of the cogeneration unit, Q CHP,t represents the heat output of the cogeneration unit at time t, W; P CHP,t represents the electric output at time t, W.

[0078] (2) Ramp - rate constraint The ramp - rate constraints of the cogeneration unit and the thermal power unit satisfy Equation (4.48).

[0079] (4.48); In the formula, P CHP,up represents the upward ramp - rate constraint of the cogeneration unit, W / h; P CHP,t-1 represents the electric output of the cogeneration unit at the previous moment, W; P CHP,down represents the downward ramp - rate constraint of the cogeneration unit, W / h; P thp,t represents the electric output at time t, W; P thp,up represents the upward ramp - rate constraint of the thermal power unit, W / h; P thp,t-1 represents the electric output of the thermal power unit at the previous moment, W; P thp,down represents the downward ramp - rate constraint of the thermal power unit, W / h.

[0080] (3) Unit's maximum output The maximum output constraints of the cogeneration unit and the thermal power unit satisfy Equation (4.49).

[0081] (4.49); In the formula, P CHP,max represents the maximum electric output of the cogeneration unit, P CHP,min represents the minimum electric output of the cogeneration unit; in the formula, P thp,max represents the maximum electric output of the thermal power unit, P thp,min represents the minimum electric output of the thermal power unit.

[0082] Furthermore, the constraint conditions of the district heating system also include: heat - load flexibility constraint, heating - temperature ramp - rate constraint, upper and lower limits of the heat - source water - supply temperature, power consumption of the heating - system pump, and temperature feedback - regulation constraint.

[0083] (1) Heat - load flexibility constraint The flexible constraint of the heat load is determined by thermal comfort. According to the winter heating standard of buildings, the optimal indoor temperature is 20 °C. According to the building heating standard, thermal comfort fluctuates within a range, which belongs to flexible constraint. The present invention proposes to characterize the user's thermal comfort by the heat deviation amount, which refers to the difference between the actual indoor temperature and the optimal indoor temperature. The fluctuation range of the heat load is determined by the maximum and minimum allowable heat deviation amounts. The flexible constraint of the heat load is shown in Equation (4.50).

[0084] (4.50); In the formula, T dev,t represents the heat deviation amount at time t, °C; T dev,min , T dev,max respectively represent the minimum and maximum allowable heat deviation amounts, and this limit is related to factors such as the building type and use of the heat user. Since overheating and underheating of the heat supply will respectively cause the indoor temperature of the user to be too high or too low, both belong to the performance of poor thermal comfort. Therefore, the present invention proposes the concept of the absolute value of the heat deviation amount. In the optimization calculation, the best thermal comfort is when the absolute value of the heat deviation amount is the smallest.

[0085] (2) Ramp constraint of the heating temperature Since the present invention adjusts the heating pipe network once every 15 minutes, and the adjustment frequency is much higher than that of the traditional heating pipe network, it is necessary to constrain the ramp characteristics of the heat source water supply temperature. The present invention does not explore the variation law of the temperature with the intake air volume of the gas turbine cogeneration unit, etc. Only based on the investigated empirical data, the upward and downward ramp constraints within 15 minutes are set to 3 °C, as shown in Equation (4.51).

[0086] (4.51); In the formula, T source,t represents the heat source heating temperature at time t, °C; T source,t represents the heat source heating temperature at time (t - 1), °C.

[0087] (3) Upper and lower limits of the heat source water supply temperature According to the adjustment law of the heating system, the heat source water supply temperature is between the minimum limit temperature and the maximum limit temperature, and the unit is °C. The constraint equation is shown in Equation (4.52).

[0088] (4.52); (4) Power consumption of the pump in the heating system The pump work is a key component of the energy consumption of the central heating system. The calculation formula of the circulating pump work is shown in Equation (4.53).

[0089] (4.53); Among them, P pump,t represents the pump power, in kW; G represents the flow rate, in kg / s; S represents the resistance coefficient, in Pa / (m 3 / h) 2 ; η represents the pump efficiency.

[0090] (5) Temperature feedback regulation constraint Due to the temperature feedback regulation mechanism, there may be a deviation between the actual heating temperature and the planned heating temperature, and their relationship is determined by the temperature feedback regulation constraint.

[0091] Furthermore, the constraints of the power grid and wind turbine units include: power grid power balance constraint, wind power limit output constraint, and line capacity constraint.

[0092] (1) Power grid power balance constraint (4.54); In the formula, P wind,t represents the actual wind power output at time t, in W; P user,t represents the residential electricity load at time t, in W; P pump,t represents the power consumption of the circulating pump, in W. Among them, the electric output of the combined heat and power unit is equal to the ratio of the heat supply Q CHP,t to the heat-electricity ratio ε, as shown in formula (4.55).

[0093] (4.55); (2) Wind power limit output (4.56); In the formula, P wind,max,t represents the wind power limit output at time t.

[0094] (3) Line capacity constraint (4.57); In the formula, P tr,t represents the power grid transmission capacity at time t, and P tr,min , P tr,max represent the minimum and maximum power grid transmission capacities at time t respectively. It is assumed in the present invention that the line transmission capacities involved are all within the limit values, and the influence of the power grid transmission capacity on the regulation of the thermal system and the coordinated operation of the district heating system is not considered.

[0095] In some embodiments, the optimization objective of the district heating system may include simultaneously ensuring the lowest indoor temperature of all multi-user nodes, or only ensuring the thermal comfort of a single heat user node.

[0096] Further, the ensuring of the thermal comfort of only a single heat user node may include: ensuring the thermal comfort of only the heat user node farthest from the heat source, so as to ensure the heat load of all heat users while maximizing the consumption of wind power.

[0097] It can be understood that considering only the comfort of a single node has the advantage of low computational complexity.

[0098] Exemplarily, different schemes can be adopted for the optimal scheduling of multiple heat user nodes. It is possible to ensure the lowest indoor temperature of all nodes simultaneously, or only ensure the thermal comfort of a single node (i.e., only restrict the lowest indoor temperature of this node to be greater than or equal to 18°C). The following compares the total thermal comfort and the variation law of wind power consumption of the electro-thermal coordination optimization schemes that ensure the thermal comfort of different users. The distances of 6 user nodes from the heat source from near to far are: No. 1 (166m), No. 5 (394m), No. 4 (450m), No. 2 (483m), No. 3 (602m), No. 6 (1307m).

[0099] Figure 7 It is a schematic diagram of the comparison of the indoor temperatures of users under the scheme of only ensuring the thermal comfort of a single node provided by the present invention. As shown in Figure 7 (a) to (f) are the hourly indoor temperature curves of each user under the electro-thermal coordination optimization scheme of only ensuring the thermal comfort of a single user. For the same scheme, the indoor temperatures of users from high to low are: No. 4, No. 1, No. 3, No. 5, No. 2, No. 6. The distances of 6 heat exchange stations from the heat source from near to far are: No. 1, No. 5, No. 4, No. 2, No. 3, No. 6. According to the analysis, due to the time delay and heat loss in the heat transfer of the pipeline, the closer the node is to the heat source, the higher the temperature of the primary network heat medium water flowing into the node heat exchange station. The "far cold and near hot" phenomenon is a common thermal imbalance phenomenon, and this phenomenon still exists when the heating system and the power system are jointly operated. However, in this example, the order of the indoor temperatures of users is inconsistent with the sorting of the primary network water supply temperatures of the heat exchange stations. The magnitude relationship of the indoor temperatures of users at No. 1, No. 5, No. 2, and No. 6 is consistent with the sorting of the primary network heat medium water temperatures on the heat exchange station side. Only the sorting of the indoor temperatures of the users belonging to the No. 4 and No. 3 heat exchange stations has changed. It can be seen from Table 1 that calculated based on the proportion of the user's enclosure area, the proportion of the primary network water flow rate to the enclosure structure area of the No. 4 and No. 3 heat exchange stations is larger than that of other stations. This is the reason why the indoor temperatures of No. 4 and No. 3 are higher than those of users closer to the heat source. That is to say, the amount of heat distributed by the heat medium water to each user is not only determined by the distance of the heat user from the heat source, but also related to factors such as the mass flow rate of the primary network heat medium water of each heat exchange station, the area and heat transfer coefficient of the heat exchanger, the area and heat transfer coefficient of the radiator, and the user's enclosure area.

[0100] Figure 7(a) to (f) show the optimal solutions of each scheme when considering the thermal comfort of different nodes separately. Comparing the indoor temperature curves of the same user under different schemes, it can be seen that the user reaches the highest temperature at about 11 am and 22 pm. The reason is that the wind power is low and the electricity load is high at these two times, and the heat storage of the heat network can be achieved by increasing the thermal power output. From 7 am to 1 am, the temperature of the same user under different schemes is basically the same. From 1 am to 7 am the next day, the room temperature of the same user tends to be stable, but the room temperature of users under different schemes is no longer the same. The room temperature of user No. 6 during this period was 16.3°C, which was higher than the indoor temperature of other nodes. The results show that the thermal load of all users can be guaranteed by considering only the thermal comfort of the user node farthest from the heat source, that is, node No. 6.

[0101] It can be seen that only ensuring the thermal comfort of the heat user node farthest from the heat source to achieve the guarantee of the heat load of all heat users and maximize the wind power consumption can greatly reduce the amount of calculation.

[0102] In some embodiments, the heating system constraints of the regional heating system further include constraining the heat source to provide the user heat load at a time when the heat load is higher a period of time in advance according to the transmission delay characteristics of the heating pipe network.

[0103] It should be noted that the current "heat-based electricity" operation mode results in higher thermal power output during periods of higher thermal load. The nighttime period of higher thermal load coincides with the period of high wind power generation, which is also the period of low electricity load. Excessive thermal power output leads to insufficient space for wind power grid connection and consumption, which may cause serious wind curtailment.

[0104] It can be seen that the consumption of wind power requires the power system to have sufficient regulation capacity. The heating network can be used to improve the regulation capacity of the power system due to its transmission delay characteristics and passive heat storage capacity. The specific working principle is to incorporate the transmission delay of the network into the electric-heat coordination optimization, so that the heat source can provide the user's heat load at that time in advance. Then the user's heat load at night when wind power is large and the heat load is high also needs to be supplied in advance. Compared with the case where the transmission delay is not considered, this method has lower heating and thermal power unit output during the night period when wind power is large and the heat load is high, providing more space for wind power grid connection and consumption. For example, at 3 a.m., the heat load is the highest and the wind power output is the largest. If the transmission delay of the network is not considered, the heating (i.e., the heat output of the cogeneration unit) at 3 a.m. is the highest, the thermal power unit has the largest electrical output, and the wind power grid connection space may be insufficient, resulting in the maximum wind abandonment. If the transmission delay is considered, the heat source needs to arrange the highest heating in advance (for example, at 2 a.m.), so that the peak time of the largest wind power at 3 a.m. can be staggered, and the wind abandonment at 3 a.m. can be reduced.

[0105] In some embodiments, calculating the decision variable through the heat transfer dynamic model may include: optimizing only for the operation of the thermal system, with the optimization objective being the best thermal comfort for different heat users; or, optimizing only from the level of the power system, with the optimization objective being the minimum wind curtailment at all times; or, optimizing the district heating system as a whole, with the minimum wind curtailment at all times of the day as the primary optimization objective and the best thermal comfort for different heat users as the secondary optimization objective.

[0106] It can be understood that to achieve the optimal operation of the thermal and power systems, it is necessary to consider the system operation indicators of both. From the perspective of the thermal system, the total thermal comfort of users at each moment is selected as the evaluation index, and the thermal deviation is used to characterize the degree of thermal comfort here. From the perspective of the power system, the maximum total wind power consumption at each moment is selected as the optimization objective, that is, the minimum total wind curtailment is the optimization objective. There are the following optimization methods.

[0107] First, optimize only for the operation of the thermal system. Since the thermal comfort requires that the temperature cannot be too high or too low, the absolute value of the thermal deviation is used to characterize the thermal comfort, and the optimization objective is the best thermal comfort for different heat users. The optimization objective is shown in Equation (4.58).

[0108] (4.58); Second, optimize only from the level of the power system, without considering the operation constraints of the thermal deviation at each moment. The optimization objective is the minimum wind curtailment at all times, as shown in Equation (4.59).

[0109] (4.59); In the formula, P curw,t represents the wind curtailment at time t.

[0110] Third, optimize the district heating system as a whole, with the minimum wind curtailment at all times of the day as the primary optimization objective and the minimum absolute value of the total thermal deviation throughout the day as the secondary optimization objective, as shown in Equation (4.60). In addition, the minimum indoor temperature is not lower than 18 °C (set according to the recommended minimum indoor temperature value in the winter heating standard).

[0111] (4.60); Among them, i represents the node number, and P icurw, t represents the wind curtailment of the i-th node at time t, in W; T idev, t represents the thermal deviation of the i-th node at time t, in °C; α is a weight coefficient, with a value of a minimum value, such as 0.001, aiming to transform it into an optimization problem considering only the best thermal comfort when the wind curtailment is 0.

[0112] The decision variables are the hourly heat supply temperature of the heat source, the heat supply quantity and electricity output of the heat and power unit, the output of the thermal power unit, and the hourly wind power output.

[0113] The above is the dynamic heat transfer model considering the overall operation of the pipeline network and the system, comprehensively considering the dynamic characteristics of heat transfer in the pipeline network, the pipeline network temperature feedback regulation mechanism, the operation characteristics of the heat exchanger, and the operation constraints of the power system. This model can provide accurate operation boundaries for the district heating system and realize the coordinated and optimized operation of the system that takes into account the performance indicators of both the power and heat systems.

[0114] Next, the effects of the embodiments of the present invention in an actual application scenario will be described.

[0115] Figure 8 It is a schematic diagram of the heat supply temperature of the heat source when the present invention separately guarantees the thermal comfort of different user nodes. As Figure 8 shown, it is the optimal heat supply temperature curve under different electro-thermal coordinated optimization schemes. The results show that the overall trends of the curves are similar. The heat supply temperature reaches the maximum around 10:00 - 12:00 in the morning and 22:00 at night. Since the wind power output is small and the electricity load is large, it is necessary to increase the thermal power output to ensure the power balance of the power system and start heat storage in the heat network at the same time. During the periods when the wind power limit output is large, that is, around 1:00 - 7:00 in the early morning and 17:00, the differences in the heat supply temperatures of each scheme are relatively large. The reason is that in order to ensure the consumption of wind power, it is necessary to reduce the thermal power output, which will inevitably lead to a decrease in the indoor temperature of users. The heat supply temperatures of the heat source under each scheme from low to high are: the schemes that only consider the thermal comfort of user nodes No. 4, 1, 3, 5, 2, and 6. This conclusion echoes the Figure 7 conclusion.

[0116] Figure 9 It is a schematic diagram of the comparison between the total wind power rejection of the system and the total thermal comfort provided by the present invention. As Figure 9 shown, it shows the total wind power rejection and the total thermal comfort under different electro-thermal coordinated optimization schemes. Figure 9 The abscissa is the serial number of the user node for which the thermal comfort is separately guaranteed. It can be seen from the figure that the total wind power rejection throughout the day is the largest and the thermal comfort is the best when only considering the thermal comfort of the farthest node, that is, user node No. 6. The smaller the absolute sum of the thermal deviation is, the more comfortable it is. The total wind power rejection throughout the day from large to small is: the cases of only considering the thermal comfort of user nodes No. 6, 2, 5, 3, 1, and 4. The order of thermal comfort from good to bad is the same as the order of wind power rejection. Thus, it can be seen that it is difficult to simultaneously ensure the optimal thermal comfort and the total wind power rejection throughout the day. The total wind power rejection when only considering the thermal comfort of the user node farthest from the heat source, that is, node No. 6, is about 2.5% higher than that when only considering No. 4, and the thermal comfort is improved by about 8%. In short, the dynamic heat transfer model proposed by the present invention can quantitatively design the heat supply temperature of the heat source, the thermal power output, etc. according to the multi-user thermal comfort requirements and the wind power consumption requirements. It can ensure the heat load of all heat users, maximize the consumption of wind power, and greatly reduce the calculation amount.

[0117] The flexible regulation method for district heating systems provided by the present invention, on the one hand, considers the game of thermal comfort priorities among multiple heat users. By only considering the thermal comfort of one heat user, it ensures that the thermal comfort of multiple heat users is within the allowable range. On the other hand, considering only the thermal comfort of one heat user as the optimization goal instead of considering the thermal comfort of all heat users simultaneously can greatly improve the calculation speed of the optimization regulation strategy. When the scale of the district heating system is large and the number of heat user groups reaches several hundred, the method proposed by the present invention is beneficial to simplify the algorithm.

[0118] Based on the foregoing embodiments, an embodiment of the present invention provides a flexible regulation device for a district heating system based on the game of multi-user thermal comfort priorities. Each module included in the device, as well as each unit included in each module, can be implemented by a processor; of course, it can also be implemented by specific logic circuits. During the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0119] The flexible regulation device for a district heating system based on the game of multi-user thermal comfort priorities provided by the present invention will be described below. The flexible regulation device for a district heating system based on the game of multi-user thermal comfort priorities described below can be mutually corresponding and referred to the flexible regulation method for a district heating system based on the game of multi-user thermal comfort priorities described above.

[0120] Figure 10 It is a schematic structural diagram of the flexible regulation device for a district heating system based on the game of multi-user thermal comfort priorities provided by the present invention. As Figure 10 shown, the device 400 includes a first analysis module 401, a second analysis module 402, and a solution acquisition module 403, wherein: The first analysis module 401 is used to determine the dynamic mapping law between multiple heat users and the heat source temperature based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, and analyze the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain first data; The second analysis module 402 is used to set the regulation ability provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization goal, and respectively use the thermal comfort of each heat user as the secondary optimization goal. Through the game of multi-user thermal comfort priorities, compare the regulation ability sizes corresponding to different flexible regulation methods when using the thermal comfort of different heat users as the optimization goal and when using the weighted value of the thermal comfort of all heat users as the optimization goal to obtain second data.

[0121] A solution determination module 403 is configured to determine a target flexible adjustment solution according to the first data and the second data. The target flexible adjustment solution is a flexible adjustment solution with the thermal comfort of one heat user as the optimization target, so as to replace the flexible adjustment solution with the weighted value of the thermal comfort of all heat users as the optimization target.

[0122] In some embodiments, the first analysis module 401 is specifically configured to: collect the heat exchange parameters of each heat user node, where the heat exchange parameters include the heat exchange coefficient from the primary network to the secondary network, the heat exchange area, the secondary network flow rate, the heat exchange coefficient from the secondary network to the user, the heat exchange area, and the steady-state heat exchange coefficient of the user to the outdoors and the heat exchange area of the building envelope; Use the pipe network hydraulic calculation model to calculate the hydraulic parameters of each branch of the pipe network and form a heat transfer contribution matrix; According to the calculation formula of the total pump power of the pipe network, combined with the total volume flow rate of the main road, the total pressure drop, the resistance coefficient and the pump efficiency, calculate the total pump power of the pipe network; Input the heat exchange parameters of each heat user node, the heat transfer contribution matrix and the total pump power of the pipe network into the heat transfer dynamic model for optimization calculation to obtain the dynamic mapping law; According to the heat transfer characteristics of the pipeline and the heat exchange constraints of the heat exchange station, and the dynamic mapping law, analyze the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments to obtain the first data.

[0123] In some embodiments, the heat transfer characteristics of the pipeline and the heat exchange constraints of the heat exchange station include user steady-state heat exchange constraints, pipe network heat transfer constraints and minimum indoor temperature constraints. The user steady-state heat exchange constraints are used to constrain the heat exchange parameters of each heat user node, the pipe network heat transfer constraints are used to constrain the parameters of heat transfer in the pipeline in the heat supply pipe network, and the minimum indoor temperature constraints are used to constrain the minimum indoor temperature of the heat user node.

[0124] In some embodiments, the solution determination module 403 is specifically configured to: determine the target flexible adjustment solution according to the first data and the second data. The target flexible adjustment solution is a flexible adjustment solution with the thermal comfort of the heat user farthest from the heat source as the optimization target.

[0125] In some embodiments, the second analysis module 402 includes a comfort comparison unit and a data acquisition unit, where The comfort comparison unit is configured to compare, through a multi-user thermal comfort priority game, whether the thermal comfort of other heat users corresponding to different flexible adjustment methods when different heat user thermal comforts are used as optimization targets and when the weighted value of the thermal comforts of all heat users is used as the optimization target is within the allowable range; The data acquisition unit is configured to determine the magnitude of the adjustment capabilities corresponding to different flexible adjustment methods based on whether the thermal comfort of other heat users is within the allowable range, and obtain the second data.

[0126] In some embodiments, the comfort comparison unit is specifically configured to: determine a heat transfer dynamic model, where the heat transfer dynamic model includes operating constraints, optimization objectives, and decision variables. The operating constraints include heating system constraints, gas turbine combined heat and power unit and thermal power unit constraints, and power grid and wind turbine unit constraints. The optimization objectives include the adjustment capabilities provided by the district heating system throughout the day for suppressing new energy fluctuations and the thermal comfort of each heat user. The decision variables include the hourly heat supply temperature of the heat source, the heat output of the combined heat and power unit, the output of the thermal power unit, and the output of the wind power; compare, through the heat transfer dynamic model, the situations where the thermal comfort of other heat users corresponding to different flexible adjustment methods when different heat user thermal comforts are used as optimization objectives and when the weighted value of the thermal comforts of all heat users is used as the optimization objective are within the allowable range.

[0127] In some embodiments, the gas turbine combined heat and power unit and thermal power unit constraints include: the heat-electricity ratio, the ramp constraint, and the unit's maximum output.

[0128] In some embodiments, the constraint conditions of the district heating system further include: heat load flexibility constraint, heating temperature ramp constraint, upper and lower limits of the heat source water supply temperature, power consumption of the heating system pump, and temperature feedback adjustment constraint.

[0129] In some embodiments, the power grid and wind turbine unit constraints include: power grid power balance constraint, wind power maximum output constraint, and line capacity constraint.

[0130] In some embodiments, the heating system constraint of the district heating system further includes, according to the transmission delay characteristics of the heating pipeline network, constraining the heat source to provide the heat load of users at high heat load moments in advance for a period of time.

[0131] In some embodiments, the comfort comparison unit is specifically configured to: in the mode of optimizing only the operation of the thermal system, the optimization objective is the best thermal comfort of different heat users; or, in the mode of optimizing only from the power system level, the optimization objective is the minimum wind power curtailment at all times; For the mode of overall optimization of the district heating system, the minimum wind power curtailment at all times throughout the day is used as the primary optimization objective, and the best thermal comfort of different heat users is used as the secondary optimization objective.

[0132] In the embodiments of the present invention, by considering the thermal comfort priority game of multiple heat users and only considering the thermal comfort of one heat user instead of all heat users, the optimization objective can greatly improve the calculation speed of the optimization regulation strategy. When the scale of the district heating system is large and the number of heat user groups reaches several hundred, it is beneficial to simplify the algorithm.

[0133] Figure 11 It is a schematic physical structure diagram of the electronic device provided by the present invention. As Figure 11 shown, the electronic device 500 may include: a processor 510, a communication interface 520, a memory 530, and a communication bus 540. Among them, the processor 510, the communication interface 520, and the memory 530 complete mutual communication through the communication bus 540. The processor 510 can call the logical instructions in the memory 530 to execute the flexible regulation method for the district heating system based on the multi-user thermal comfort priority game. The method includes: Based on the heat transfer dynamic model of the district heating system including complex pipe networks and multiple heat users, determine the dynamic mapping law between multiple heat users and the heat source temperature, and analyze the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain the first data; Set the regulation ability provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization objective, and the thermal comfort of each heat user as the secondary optimization objective respectively. Through the multi-user thermal comfort priority game, compare the regulation ability sizes of different flexible regulation methods corresponding to taking the thermal comfort of different heat users as the optimization objective and taking the weighted value of the thermal comfort of all heat users as the optimization objective to obtain the second data; Determine the target flexible regulation scheme according to the first data and the second data. The target flexible regulation scheme is to select a flexible regulation scheme with the thermal comfort of one heat user as the optimization objective to replace the flexible regulation scheme with the weighted value of the thermal comfort of all heat users as the optimization objective.

[0134] In addition, when the logical instructions in the above-mentioned memory 530 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0135] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the flexible regulation method of the district heating system based on multi-user thermal comfort priority game provided by the above-mentioned various methods. The method includes: Based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, determine the dynamic mapping law between multiple heat users and the heat source temperature, and analyze the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain first data; Set the regulation ability provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization goal, and the thermal comfort of each heat user as the secondary optimization goal respectively. Through multi-user thermal comfort priority game, compare the regulation ability sizes of different flexible regulation methods corresponding to taking the thermal comfort of different heat users as the optimization goal and taking the weighted value of the thermal comfort of all heat users as the optimization goal to obtain second data; Determine the target flexible regulation scheme according to the first data and the second data. The target flexible regulation scheme is to select a flexible regulation scheme with the thermal comfort of a heat user as the optimization goal to replace the flexible regulation scheme considering the weighted value of the thermal comfort of all heat users as the optimization goal.

[0136] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired means (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless means (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that can be stored by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0137] In another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a flexible adjustment method for a district heating system based on a multi-user thermal comfort priority game provided by the above methods. The method includes: Based on the heat transfer dynamic model of a district heating system including a complex pipe network and multiple heat users, determine the dynamic mapping law between multiple heat users and the heat source temperature, and analyze the influence of heat source changes on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law to obtain first data; Set the adjustment ability provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization goal, and the thermal comfort of each heat user as the secondary optimization goal respectively. Through the multi-user thermal comfort priority game, compare the adjustment ability of different flexible adjustment methods corresponding to different thermal comfort of heat users as the optimization goal and the weighted value of the thermal comfort of all heat users as the optimization goal to obtain second data; Determine the target flexible adjustment scheme according to the first data and the second data. The target flexible adjustment scheme is to select a flexible adjustment scheme with the thermal comfort of one heat user as the optimization goal to replace the flexible adjustment scheme with the weighted value of the thermal comfort of all heat users as the optimization goal.

[0138] The above computer-readable storage medium may adopt any combination of one or more computer-readable media. The computer-readable media may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the context of the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0139] The computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including - but not limited to - an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0140] The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including - but not limited to - wireless, wire, optical fiber, radio frequency (RF), etc., or any suitable combination of the above.

[0141] Computer program code for performing the operations of this specification can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., by connecting through the Internet using an Internet service provider).

[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative effort.

[0143] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several 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 each embodiment or some parts of the embodiments.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A flexible regulation method for district heating systems based on multi-user thermal comfort priority games, characterized in that Applied to a district heating system, the district heating system includes a plurality of heat users, and the method includes: Based on the heat transfer dynamic model of a district heating system including a complex pipe network and a plurality of heat users, determining the dynamic mapping law between the plurality of heat users and the heat source temperature, and analyzing the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law, to obtain first data; Setting the regulation capacity provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization goal, and respectively taking the thermal comfort of each heat user as the secondary optimization goal. Through multi-user thermal comfort priority game, comparing the regulation capacity of different flexible regulation methods corresponding to taking the thermal comfort of different heat users as the optimization goal and taking the weighted value of the thermal comfort of all heat users as the optimization goal, to obtain second data; Determining a target flexible regulation scheme according to the first data and the second data, the target flexible regulation scheme is a flexible regulation scheme that selects the thermal comfort of one heat user as the optimization goal, to replace the flexible regulation scheme that considers the weighted value of the thermal comfort of all heat users as the optimization goal.

2. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 1, characterized in that The step of based on the heat transfer dynamic model of a district heating system including a complex pipe network and a plurality of heat users, determining the dynamic mapping law between the plurality of heat users and the heat source temperature, and analyzing the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the dynamic mapping law, to obtain first data, includes: Collecting the heat exchange parameters of each heat user node, the heat exchange parameters include the heat exchange coefficient from the primary network to the secondary network, the heat exchange area, the secondary network flow rate, the heat exchange coefficient from the secondary network to the user, the heat exchange area, and the steady-state heat exchange coefficient from the user to the outdoors and the heat transfer area of the building envelope; Calculating the hydraulic parameters of each branch of the pipe network by using the pipe network hydraulic calculation model, and forming a heat transfer contribution matrix; Calculating the total pump power of the pipe network according to the calculation formula of the total pump power of the pipe network, in combination with the total volume flow rate of the main road, the total pressure drop, the resistance coefficient and the pump efficiency; Inputting the heat exchange parameters of each heat user node, the heat transfer contribution matrix and the total pump power of the pipe network into the heat transfer dynamic model for optimization calculation, to obtain the dynamic mapping law; Analyzing the influence of the heat source change on the temperature dynamic characteristics of each heat user at future moments according to the heat transfer characteristics of the pipeline and the heat exchange constraints of the heat exchange station, and the dynamic mapping law, to obtain first data.

3. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 2, characterized in that The heat transfer characteristics of the pipeline and the heat exchange constraints of the heat exchange station include user steady-state heat exchange constraints, pipe network heat transfer constraints and minimum indoor temperature constraints. The user steady-state heat exchange constraints are used to constrain the heat exchange parameters of each heat user node, the pipe network heat transfer constraints are used to constrain the parameters of heat transfer in the pipeline in the heat supply pipe network, and the minimum indoor temperature constraints are used to constrain the minimum indoor temperature of the heat user node.

4. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 1, characterized in that The step of determining the target flexible regulation scheme according to the first data and the second data includes: Determining the target flexible regulation scheme according to the first data and the second data, the target flexible regulation scheme is a flexible regulation scheme that selects the thermal comfort of the heat user farthest from the heat source as the optimization goal.

5. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 1, wherein By means of multi - user thermal comfort priority game, comparing the regulation capabilities corresponding to different flexible regulation methods when taking the thermal comfort of different heat users as the optimization target and when taking the weighted value of the thermal comfort of all heat users as the optimization target, to obtain second data, including: By means of multi - user thermal comfort priority game, comparing different flexible regulation methods when taking the thermal comfort of different heat users as the optimization target and when taking the weighted value of the thermal comfort of all heat users as the optimization target, to check whether the thermal comfort of other heat users is within the allowable range; According to whether the thermal comfort of other heat users is within the allowable range, determine the regulation capabilities corresponding to different flexible regulation methods, so as to obtain the second data.

6. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 5, wherein The step of, by means of multi - user thermal comfort priority game, comparing different flexible regulation methods when taking the thermal comfort of different heat users as the optimization target and when taking the weighted value of the thermal comfort of all heat users as the optimization target, to check whether the thermal comfort of other heat users is within the allowable range, includes: Determine a heat transfer dynamic model, where the heat transfer dynamic model includes operation constraints, optimization objectives and decision variables. The operation constraints include heating system constraints, gas turbine combined heat and power unit and thermal power unit constraints, and power grid and wind turbine unit constraints. The optimization objectives include the regulation capabilities provided by the district heating system for suppressing new - energy fluctuations throughout the day and the thermal comfort of each heat user. The decision variables include the hourly heat supply temperature of the heat source, the heat output of the combined heat and power unit, the output of the thermal power unit and the output of the wind power; Through the heat transfer dynamic model, compare different flexible regulation methods when taking the thermal comfort of different heat users as the optimization target and when taking the weighted value of the thermal comfort of all heat users as the optimization target, to check whether the thermal comfort of other heat users is within the allowable range.

7. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 6, characterized in that The gas turbine combined heat and power unit and thermal power unit constraints include: the heat - to - power ratio, ramp - up / down constraints and unit limit output.

8. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 6, characterized in that The constraint conditions of the district heating system include: heat load flexibility constraint, heating temperature ramp - up / down constraint, upper and lower limits of the heat source supply temperature, power consumption of the heating system pump, and temperature feedback regulation constraint.

9. The flexible regulation method for a district heating system based on multi-user thermal comfort priority game according to claim 6, characterized in that The power grid and wind turbine unit constraints include: power grid power balance constraint, wind power limit output constraint and line capacity constraint.

10. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 6, characterized in that, The heating system constraints of the district heating system also include, according to the transmission delay characteristics of the heating pipe network, constraining the heat source to provide the heat load of users at high - heat - load moments in advance for a period of time.

11. The flexible regulation method of the district heating system based on the multi-user thermal comfort priority game according to claim 6, characterized in that, The step of, through the heat transfer dynamic model, comparing different flexible regulation methods when taking the thermal comfort of different heat users as the optimization target and when taking the weighted value of the thermal comfort of all heat users as the optimization target, to check whether the thermal comfort of other heat users is within the allowable range, includes: An optimization method that only optimizes the operation of the thermal system, with the optimization objective being the best thermal comfort of different heat users; or, An optimization method that only optimizes from the power system level, with the optimization objective being the minimum wind curtailment at all times; or, An optimization method that globally optimizes the district heating system, with the minimum wind curtailment at all times throughout the day as the primary optimization objective and the best thermal comfort of different heat users as the secondary optimization objective.

12. A flexible adjustment device for a district heating system based on a multi-user thermal comfort priority game, characterized in that, Applied to a district heating system, the district heating system includes a plurality of heat users, and the device includes: A first analysis module, configured to determine the dynamic mapping rule between a plurality of heat users and the heat source temperature based on the heat transfer dynamic model of a district heating system including a complex pipe network and a plurality of heat users, and analyze the influence of the heat source change on the temperature dynamic characteristics of each heat user at a future moment according to the dynamic mapping rule, so as to obtain first data; A second analysis module, configured to set the regulation ability provided by the district heating system throughout the day for new energy fluctuation suppression as the primary optimization target, and respectively take the thermal comfort of each heat user as the secondary optimization target. Through the multi-user thermal comfort priority game, compare the regulation ability sizes corresponding to different flexible regulation methods when taking the thermal comfort of different heat users as the optimization target and when taking the weighted value of the thermal comfort of all heat users as the optimization target, so as to obtain second data; A scheme acquisition module, configured to determine a target flexible regulation scheme according to the first data and the second data, where the target flexible regulation scheme is a flexible regulation scheme that selects the thermal comfort of one heat user as the optimization target to replace the flexible regulation scheme that considers the weighted value of the thermal comfort of all heat users as the optimization target.

13. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the flexible regulation method for a district heating system based on multi-user thermal comfort priority game as described in any one of claims 1 to 11.

14. 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 flexible regulation method for a district heating system based on multi-user thermal comfort priority game as described in any one of claims 1 to 11.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the flexible regulation method for a district heating system based on multi-user thermal comfort priority game as described in any one of claims 1 to 11.

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