Electric heating cluster control method, device, equipment and medium

Abstract

The invention belongs to the technical field of electric heating control, and particularly relates to an electric heating cluster control method, device and equipment and a medium. The running state and the indoor temperature in the preset area are obtained; clustering is carried out according to the indoor temperature in the preset area, and electric heating in the preset area is grouped according to a clustering result; establishing a first objective function and a second objective function according to the running state; solving the first objective function to obtain the starting number of each group in the next time period; solving the second objective function to obtain the start-stop state of each heat pump in each group; and the starting number of each group and the starting and stopping states of the heat pumps in each group are controlled according to the starting and stopping states of the heat pumps in each group and the starting number of each group in the next time period. The electric heating clusters are clustered and grouped according to the temperature, the first target function is established to calculate the starting number of each group, then the on-off state of the heat pump in each group is calculated through the second target function, hierarchical control is achieved, the response speed is higher, and control is more accurate.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric heating control, and specifically relates to an electric heating cluster control method, device, equipment and medium. Background Art

[0002] In recent years, the heating direction has adopted the strategy of replacing coal with electricity, and a large number of new electric heating equipment have been built to meet the winter heating needs in rural areas. However, the access of a large number of distributed electric heating equipment to the distribution network has brought challenges to the safe and stable operation of the distribution network in rural areas. In particular, the load of electric heating equipment has a certain degree of randomness and is closely related to the external environment such as weather. Therefore, how to accurately predict the load curve of electric heating equipment is of great significance to the safe, stable and efficient operation of rural power grids.

[0003] The existing load forecasting methods are usually based on the operation mechanism model of physical characteristics. Based on the in-depth understanding of the internal structure and parameters of the load, the load operation mechanism model is established, and the load optimization scheduling is carried out on the basis of this model to achieve the load characteristics. However, it is very difficult to implement the demand response control method for the current mainstream decentralized electric heating load, and the internal motivation and degree of participation of different heat pumps in demand response vary greatly. Summary of the invention

[0004] The purpose of the present invention is to provide an electric heating cluster control method, device, equipment and medium to solve the technical problem that the existing electric heating cluster is too dispersed, resulting in slow control and untimely response.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides an electric heating cluster control method, comprising the following steps:

[0007] Obtain the operating status and indoor temperature in the preset area;

[0008] Clustering is performed according to the indoor temperature in the preset area, and the electric heating in the preset area is grouped according to the clustering result;

[0009] Establishing a first objective function and a second objective function according to the operating state;

[0010] Solve the first objective function to obtain the number of startups of each group in the next period;

[0011] Solving the second objective function to obtain the start and stop status of each heat pump in each group;

[0012] The start-up number of each group and the start-up and stop status of the heat pumps in each group are controlled according to the start-up and stop status of each heat pump in each group and the start-up number of each group in the next period.

[0013] A further improvement of the present invention is that the establishment of the first objective function comprises the following steps:

[0014] Calculate the number of machines started in the previous period in each group according to the operating status;

[0015] The power of a single machine when it is running is obtained, and according to the power of the single machine when it is running and the number of machines started in each group in the previous period, a first objective function is established with the goal of minimizing total power and minimizing power fluctuation.

[0016] A further improvement of the present invention is that the second objective function is established according to the operating state with the goal of minimizing the state change.

[0017] A further improvement of the present invention is that: the first objective function satisfies a first temperature constraint;

[0018] The establishment of the first temperature constraint comprises the following steps:

[0019] Get environmental data and outdoor temperature;

[0020] Calculate the average room temperature in the group in the previous period based on the indoor temperature;

[0021] The indoor temperature of the group in the next period is calculated based on the number of powered-on devices in each group in the next period, the average room temperature in the group in the previous period, the outdoor temperature and environmental data;

[0022] If the indoor temperature in the next time period group belongs to [minimum temperature, maximum temperature], the first temperature constraint is satisfied.

[0023] A further improvement of the present invention is that: the second objective function satisfies a second temperature constraint;

[0024] The establishment of the second temperature constraint comprises the following steps:

[0025] Obtain environmental data and outdoor temperature for each household;

[0026] Calculate the average room temperature of each household in the group in the previous period based on the indoor temperature;

[0027] The indoor temperature of each household in the group in the next period is calculated based on the start and stop status of each heat pump in each group, the average room temperature of each household in the group in the previous period, the outdoor temperature and the environmental data of each household;

[0028] If the indoor temperature of each household in the group in the next time period belongs to [minimum temperature, maximum temperature], the second temperature constraint is met.

[0029] A further improvement of the present invention is that the environmental data includes: average thermal resistance of houses in the group, average thermal capacity of houses in the group and control interval.

[0030] A further improvement of the present invention is that the start and stop status of each heat pump in each group and the number of units started in each group in the next period meet the on / off number constraint, that is, the number of units started in each group in the next period is greater than or equal to the sum of the start and stop status of each heat pump in the group.

[0031] In a second aspect, the present invention provides an electric heating cluster control device, comprising:

[0032] Data acquisition module: used to obtain the operating status and indoor temperature in the preset area;

[0033] Grouping module: used to cluster according to the indoor temperature in the preset area, and group the electric heating in the preset area according to the clustering results;

[0034] Establishment module: used for establishing the first objective function and the second objective function according to the operation status;

[0035] The first solution module is used to solve the first objective function to obtain the number of startups of each group in the next period;

[0036] The second solution module is used to solve the second objective function to obtain the start and stop status of each heat pump in each group;

[0037] Control module: used to control the startup quantity of each group and the startup and stop status of the heat pumps in each group according to the startup and stop status of each heat pump in each group and the startup quantity of each group in the next period.

[0038] In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned electric heating cluster control method when executing the computer program.

[0039] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, which implements the above-mentioned electric heating cluster control method when executed by a processor.

[0040] Compared with the prior art, the present invention has at least the following beneficial effects:

[0041] The present invention clusters the electric heating clusters according to the temperature, establishes a first objective function to calculate the number of startups in each group, and then calculates the switch state of the heat pump in each group through a second objective function, thereby realizing hierarchical control, faster response speed, and more accurate control.

[0042] The present invention limits the solutions of the first objective function and the second objective function through temperature constraints, ensures the stability of heating, and achieves the standard of approximately meeting the control of a single user, so as to reduce the load power of the electric heating cluster. This ensures user comfort and reduces load power;

[0043] The present invention ensures the accuracy of control by setting the number of on / off machines. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 This is a flow chart of an electric heating cluster control method of the present invention;

[0046] Figure 2 This is a structural block diagram of an electric heating cluster control device of the present invention. DETAILED DESCRIPTION

[0047] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0048] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0049] Example 1

[0050] An electric heating cluster control method, such as Figure 1 As shown, the following steps are included:

[0051] S1. Obtaining the operating status and indoor temperature in a preset area;

[0052] S2. Clustering is performed according to the indoor temperature in the preset area, and the electric heating in the preset area is grouped according to the clustering result;

[0053] S3, establishing a first objective function and a second objective function according to the operating state;

[0054] S4, solving the first objective function to obtain the number of startups of each group in the next period;

[0055] S5, solving the second objective function to obtain the start and stop status of each heat pump in each group;

[0056] S6. Control the startup quantity of each group and the startup and shutdown state of the heat pumps in each group according to the startup and shutdown state of each heat pump in each group and the startup quantity of each group in the next period.

[0057] Specifically, in the step of obtaining the operating status and indoor temperature in the preset area, the indoor temperature and operating status obtained are data of the previous period, and the indoor temperature is represented by T r0,i Indicates that the running state is k i 'express;

[0058] Specifically, the steps of establishing the first objective function and the second objective function according to the operating state include:

[0059] Calculate the number of machines started in the previous period in each group according to the operating status;

[0060] Obtain the power of a single machine when it is running, and establish a first objective function based on the power of the single machine when it is running and the number of machines powered on in each group in the previous period with the goal of minimizing total power and minimizing power fluctuation;

[0061] According to the running state, a second objective function is established with the goal of minimizing the state change;

[0062] Running status k i 'A variable of 0 / 1, indicating the start / stop status;

[0063] Specifically, in the step of calculating the number of startups in each group in the previous period according to the operating status, the operating status of each heat pump in the group is added to obtain the startup number K of the group in the previous period. m ', m = 1, 2, 3...N, N is the number of groups, and m is the number of heat pumps in this group.

[0064] Specifically, the first objective function:

[0065]

[0066] Where minS represents the first objective function, P 0 Indicates the power when a single machine is running; K m Indicates the number of devices in the mth group that are powered on in the next period; K m ' represents the number of machines started in the mth group in the previous period; in the objective function, K m 2 Used to indicate total power, (K m -K m ') 2 Used to indicate fluctuations in power.

[0067] The first objective function is used to obtain the number of machines started in each group in the next period, completing the first level of optimization.

[0068] Specifically, the first objective function satisfies a first temperature constraint;

[0069] The establishment of the first temperature constraint includes the following steps:

[0070] Get environmental data and outdoor temperature;

[0071] Calculate the average room temperature in the group in the previous period based on the indoor temperature;

[0072] The indoor temperature of the group in the next period is calculated based on the number of powered-on devices in each group in the next period, the average room temperature in the group in the previous period, the outdoor temperature and environmental data;

[0073] If the indoor temperature in the next time period group belongs to [minimum temperature, maximum temperature], the first temperature constraint is satisfied;

[0074] If the indoor temperature in the next time period group does not belong to [minimum temperature, maximum temperature], the first temperature constraint is not met.

[0075] Specifically, the minimum temperature and the maximum temperature are set according to the actual situation;

[0076] As a preferred implementation mode of this embodiment, the maximum temperature is 26°C and the minimum temperature is 16°C.

[0077] Specifically, the environmental data include: average thermal resistance R of the houses in the group m 、Average heat capacity of houses in the group C m and control interval △t;

[0078] The control interval △t is generally 15 minutes and can be adjusted according to actual conditions.

[0079] Specifically, when the indoor temperature in the next period of time is calculated based on the number of power-on units in each group in the next period of time, the average room temperature in the group in the previous period of time, the outdoor temperature and environmental data, the calculation is performed according to the following formula:

[0080]

[0081] T r,m ∈[T min ,T max ]

[0082] Where, T r,m Indicates the indoor temperature in the next time period group, P 0 Indicates the power when a single machine is running, R m Indicates the average thermal resistance of the houses in the group, C m represents the average heat capacity of the houses in the group, △t represents the control interval, T out Indicates the outdoor temperature, T r0,m Indicates the average room temperature within the group during the previous period.

[0083] Specifically, the second objective function, for the mth group, there are n m For each household, the optimization is performed as follows to obtain the start and stop instructions of each heat pump in the group:

[0084]

[0085] where i = 1, 2, 3, ..., n m

[0086] In the formula, k i ' indicates the running state, k i Indicates the running status at the next moment;

[0087] Specifically, the second objective function satisfies the second temperature constraint;

[0088] The establishment of the second temperature constraint includes the following steps:

[0089] Obtain environmental data and outdoor temperature for each household;

[0090] Calculate the average room temperature of each household in the group in the previous period based on the indoor temperature;

[0091] The indoor temperature of each household in the group in the next period is calculated based on the start and stop status of each heat pump in each group, the average room temperature of each household in the group in the previous period, the outdoor temperature and the environmental data of each household;

[0092] If the indoor temperature of each household in the group in the next period belongs to [minimum temperature, maximum temperature], the second temperature constraint is satisfied;

[0093] If the indoor temperature of each household in the group in the next time period does not belong to [minimum temperature, maximum temperature], the second temperature constraint is not met.

[0094] Specifically, when the indoor temperature of each household in the group in the next period is calculated based on the operating status at the next moment, the average room temperature of each household in the group in the previous period, the outdoor temperature and the environmental data of each household, the calculation is performed according to the following formula:

[0095]

[0096] Where, T r,i represents the indoor temperature of the i-th household in the group in the next period, P 0 Indicates the power when a single machine is running, R i represents the average thermal resistance of the i-th household in the group, C i represents the average heat capacity of the i-th household in the group, △t represents the control interval, T out Indicates the outdoor temperature, T r0,i Represents the average room temperature of the i-th household in the group during the previous period.

[0097] T r,i ∈[T min ,T max ]

[0098] Specifically, the start and stop status of each heat pump in each group and the number of units started in each group in the next period meet the on / off number constraint;

[0099] The number of on / off machines is constrained as follows: the number of on / off machines in each group in the next period is greater than or equal to the sum of the on / off states of each heat pump in the group;

[0100]

[0101] The start / stop status is 0 / 1, indicating whether the heat pump of each household is turned on or off.

[0102] Stability determination of the control strategy of the method in this embodiment: This control strategy comprehensively considers the characteristics of the heterogeneity of distributed electric heating users, analyzes the dynamic control relationship between load aggregators and users, establishes a scheduling mechanism based on distributed electric heating on the load side with load aggregators as the intermediary, and constructs a two-layer control model. The upper model aims to minimize the total load power of the large electric heating group based on the load aggregator, and the independent variable is the power fluctuation of the large electric heating group. The lower model aims to minimize the load power fluctuation of a single user in the electric heating user group, and the independent variable is the load power change.

[0103] The control error can be reduced: The double-layer control strategy proposed based on the present invention can effectively reduce the uncertainty error caused by single-layer control. Among them, the first layer collects indoor and outdoor temperatures and house-related thermodynamic parameters to perform the first clustering control on users with similar load characteristics to reduce the load power of the electric heating cluster. Secondly, the second-layer user control strategy proposed based on the first-layer clustering performs detailed control according to the specified constraints to achieve the standard of approximately meeting the control of a single user, so as to reduce the load power of the electric heating cluster. It is achieved by both ensuring user comfort and reducing load power.

[0104] The data volume required is small and the control speed is fast. Unlike deep learning algorithms that require a large amount of data for model pre-training, the control strategy proposed in this patent only requires the indoor and outdoor temperatures at several moments in the past and the historical values ​​of the house's thermodynamic parameters to complete the control. The data volume required is small and the control speed is fast.

[0105] Example 2

[0106] An electric heating cluster control device, such as Figure 2 As shown, including:

[0107] Data acquisition module: used to obtain the operating status and indoor temperature in the preset area;

[0108] Grouping module: used to cluster according to the indoor temperature in the preset area, and group the electric heating in the preset area according to the clustering results;

[0109] Establishment module: used for establishing the first objective function and the second objective function according to the operation status;

[0110] The first solution module is used to solve the first objective function to obtain the number of startups of each group in the next period;

[0111] The second solution module is used to solve the second objective function to obtain the start and stop status of each heat pump in each group;

[0112] Control module: used to control the startup quantity of each group and the startup and stop status of the heat pumps in each group according to the startup and stop status of each heat pump in each group and the startup quantity of each group in the next period.

[0113] Specifically, in the step of obtaining the operating status and indoor temperature in the preset area, the indoor temperature and operating status obtained are data of the previous period, and the indoor temperature is represented by T r0,i Indicates that the running state is k i 'express;

[0114] Specifically, the steps of establishing the first objective function and the second objective function according to the operating state include:

[0115] Calculate the number of machines started in the previous period in each group according to the operating status;

[0116] Obtain the power of a single machine when it is running, and establish a first objective function based on the power of the single machine when it is running and the number of machines powered on in each group in the previous period with the goal of minimizing total power and minimizing power fluctuation;

[0117] According to the running state, a second objective function is established with the goal of minimizing the state change;

[0118] Running status k i 'A variable of 0 / 1, indicating the start / stop status;

[0119] Specifically, in the step of calculating the number of startups in each group in the previous period according to the operating status, the operating status of each heat pump in the group is added to obtain the startup number K of the group in the previous period. m ', m = 1, 2, 3...N, N is the number of groups, and m is the number of heat pumps in this group.

[0120] Specifically, the first objective function:

[0121]

[0122] Where minS represents the first objective function, P 0 Indicates the power when a single machine is running; K m Indicates the number of devices in the mth group that are powered on in the next period; K m ' represents the number of machines started in the mth group in the previous period; in the objective function, K m 2Used to indicate total power, (K m -K m ') 2 Used to indicate fluctuations in power.

[0123] The first objective function is used to obtain the number of machines started in each group in the next period, completing the first level of optimization.

[0124] Specifically, the first objective function satisfies a first temperature constraint;

[0125] The establishment of the first temperature constraint includes the following steps:

[0126] Get environmental data and outdoor temperature;

[0127] Calculate the average room temperature in the group in the previous period based on the indoor temperature;

[0128] The indoor temperature of the group in the next period is calculated based on the number of powered-on devices in each group in the next period, the average room temperature in the group in the previous period, the outdoor temperature and environmental data;

[0129] If the indoor temperature in the next time period group belongs to [minimum temperature, maximum temperature], the first temperature constraint is satisfied;

[0130] If the indoor temperature in the next time period group does not belong to [minimum temperature, maximum temperature], the first temperature constraint is not met.

[0131] Specifically, the minimum temperature and the maximum temperature are set according to the actual situation;

[0132] As a preferred implementation mode of this embodiment, the maximum temperature is 26°C and the minimum temperature is 16°C.

[0133] Specifically, the environmental data include: average thermal resistance R of the houses in the group m 、Average heat capacity of houses in the group C m and control interval △t;

[0134] The control interval △t is generally 15 minutes and can be adjusted according to actual conditions.

[0135] Specifically, when the indoor temperature in the next period of time is calculated based on the number of power-on units in each group in the next period of time, the average room temperature in the group in the previous period of time, the outdoor temperature and environmental data, the calculation is performed according to the following formula:

[0136]

[0137] T r,m ∈[T min ,T max ]

[0138] Where, T r,mIndicates the indoor temperature in the next time period group, P 0 Indicates the power when a single machine is running, R m Represents the average thermal resistance of the houses in the group, C m represents the average heat capacity of the houses in the group, △t represents the control interval, T out Indicates the outdoor temperature, T r0,m Indicates the average room temperature within the group during the previous period.

[0139] Specifically, the second objective function, for the mth group, there are n m For each household, the optimization is performed as follows to obtain the start and stop instructions of each heat pump in the group:

[0140]

[0141] where i = 1, 2, 3, ..., n m

[0142] In the formula, k i ' indicates the running state, k i Indicates the running status at the next moment;

[0143] Specifically, the second objective function satisfies the second temperature constraint;

[0144] The establishment of the second temperature constraint includes the following steps:

[0145] Obtain environmental data and outdoor temperature for each household;

[0146] Calculate the average room temperature of each household in the group in the previous period based on the indoor temperature;

[0147] The indoor temperature of each household in the group in the next period is calculated based on the start and stop status of each heat pump in each group, the average room temperature of each household in the group in the previous period, the outdoor temperature and the environmental data of each household;

[0148] If the indoor temperature of each household in the group in the next period belongs to [minimum temperature, maximum temperature], the second temperature constraint is satisfied;

[0149] If the indoor temperature of each household in the group in the next time period does not belong to [minimum temperature, maximum temperature], the second temperature constraint is not met.

[0150] Specifically, when the indoor temperature of each household in the group in the next period is calculated based on the operating status at the next moment, the average room temperature of each household in the group in the previous period, the outdoor temperature and the environmental data of each household, the calculation is performed according to the following formula:

[0151]

[0152] Where, T r,i represents the indoor temperature of the i-th household in the group in the next period, P 0Indicates the power when a single machine is running, R i represents the average thermal resistance of the i-th household in the group, C i represents the average heat capacity of the i-th household in the group, △t represents the control interval, T out Indicates the outdoor temperature, T r0,i Represents the average room temperature of the i-th household in the group during the previous period.

[0153] T r,i ∈[T min ,T max ]

[0154] Specifically, the start and stop status of each heat pump in each group and the number of units started in each group in the next period meet the on / off number constraint;

[0155] The number of on / off machines is constrained as follows: the number of on / off machines in each group in the next period is greater than or equal to the sum of the on / off states of each heat pump in the group;

[0156]

[0157] The start / stop status is 0 / 1, indicating whether the heat pump of each household is turned on or off.

[0158] Example 3

[0159] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, an electric heating cluster control method according to embodiment 1 is implemented.

[0160] Example 4

[0161] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, an electric heating cluster control method of embodiment 1 is implemented.

[0162] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

[0163] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0165] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0167] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for controlling electric heating clusters, It is characterized in that The following steps are involved: Obtain the operating status and indoor temperature in the preset area; Clustering is performed according to the indoor temperature in the preset area, and the electric heating in the preset area is grouped according to the clustering result; Establishing a first objective function and a second objective function according to the operating state; Solve the first objective function to obtain the number of startups of each group in the next period; Solving the second objective function to obtain the start and stop status of each heat pump in each group; The start-up number of each group and the start-up and stop status of the heat pumps in each group are controlled according to the start-up and stop status of each heat pump in each group and the start-up number of each group in the next period.

2. An electric heating cluster control method according to claim 1, It is characterized in that The establishment of the first objective function comprises the following steps: Calculate the number of machines started in the previous period in each group according to the operating status; The power of a single machine when it is running is obtained, and according to the power of the single machine when it is running and the number of machines started in each group in the previous period, a first objective function is established with the goal of minimizing total power and minimizing power fluctuation.

3. The electric heating cluster control method according to claim 1, It is characterized in that The second objective function is established according to the operating state with the goal of minimizing state changes.

4. The electric heating cluster control method according to claim 1, It is characterized in that The first objective function satisfies a first temperature constraint; The establishment of the first temperature constraint comprises the following steps: Get environmental data and outdoor temperature; Calculate the average room temperature in the group in the previous period based on the indoor temperature; The indoor temperature of the group in the next period is calculated based on the number of powered-on devices in each group in the next period, the average room temperature in the group in the previous period, the outdoor temperature and environmental data; If the indoor temperature in the next time period group belongs to [minimum temperature, maximum temperature], the first temperature constraint is satisfied.

5. The electric heating cluster control method according to claim 1, It is characterized in that The second objective function satisfies a second temperature constraint; The establishment of the second temperature constraint comprises the following steps: Obtain environmental data and outdoor temperature for each household; Calculate the average room temperature of each household in the group in the previous period based on the indoor temperature; The indoor temperature of each household in the group in the next period is calculated based on the start and stop status of each heat pump in each group, the average room temperature of each household in the group in the previous period, the outdoor temperature and the environmental data of each household; If the indoor temperature of each household in the group in the next time period belongs to [minimum temperature, maximum temperature], the second temperature constraint is met.

6. The electric heating cluster control method according to claim 4, It is characterized in that The environmental data include: average thermal resistance of houses in the group, average thermal capacity of houses in the group and control interval.

7. The electric heating cluster control method according to claim 1, It is characterized in that The start and stop states of the heat pumps in each group and the number of units started in each group in the next period satisfy the on / off number constraint, that is, the number of units started in each group in the next period is greater than or equal to the sum of the start and stop states of the heat pumps in the group.

8. An electric heating cluster control device, It is characterized in that include: Data acquisition module: used to obtain the operating status and indoor temperature in the preset area; Grouping module: used to cluster according to the indoor temperature in the preset area, and group the electric heating in the preset area according to the clustering results; Establishment module: used for establishing the first objective function and the second objective function according to the operation state; The first solution module is used to solve the first objective function to obtain the number of startups of each group in the next period; The second solution module is used to solve the second objective function to obtain the start and stop status of each heat pump in each group; Control module: used to control the startup quantity of each group and the startup and stop status of the heat pumps in each group according to the startup and stop status of each heat pump in each group and the startup quantity of each group in the next period.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, an electric heating cluster control method described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program. It is characterized in that When the computer program is executed by a processor, an electric heating cluster control method according to any one of claims 1 to 7 is implemented.

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