Geothermal-based collaborative multi-energy intelligent heating system

Abstract

The present invention discloses a geothermal-based collaborative multi-energy intelligent heating system, including a geothermal heating end, which is used to use geothermal energy as the main line of the heating system for heating and obtain a steady-state range of the geothermal heating capacity; a balancing controller, which is arranged at the geothermal heating end, and is used to control the heating support of the geothermal heating end and the heating elasticity regulation range when using geothermal energy as the main line of the heating system for heating; at least one auxiliary heating end, which is connected to the heating system as auxiliary heating; a heating steady-state model, which connects the geothermal heating end, the auxiliary heating end and the user end, obtains a compensation amount that meets the needs of the user end, and controls the auxiliary heating end by the compensation controller to achieve the heating balance of the heating system with the compensation amount; a control module, which is used to control the balancing controller to be in a restricted controlled state when the heating system enters the heating balance, and to control the connection and exit of the auxiliary heating end by the compensation amount.

Description

Technical Field

[0001] The present invention relates to the field of smart heating technology, and in particular to a geothermal-based collaborative multi-energy smart heating system. Background Art

[0002] The Guanzhong Plain boasts abundant geothermal energy, particularly mid- and deep-seated geothermal resources with distinct regional and zonal distribution patterns. Consequently, many newly constructed communities in the region are now utilizing geothermal heating. However, these resources typically utilize a single well per community, limiting geothermal heating capacity and resulting in suboptimal heating results. Summary of the Invention

[0003] In order to solve the problems of the prior art, the present invention provides a geothermal-based collaborative multi-energy intelligent heating system.

[0004] Its main technical solutions are as follows:

[0005] Geothermal-based collaborative multi-energy smart heating system, including

[0006] The geothermal heating end is used to provide heat using geothermal energy as the main line of the heating system to obtain the steady-state range of geothermal heating capacity;

[0007] a balancing controller, disposed at a geothermal heating end, for controlling, when geothermal heat is used as the main line of the heating system for heating, setting a heating support and a heating elasticity control range of the geothermal heating end; wherein the heating support is obtained from the steady-state interval, and the heating elasticity control range is set based on the heating support;

[0008] At least one auxiliary heating terminal, used as auxiliary heating, connected to the heating system;

[0009] a heating steady-state model, connected to the geothermal heating end, the auxiliary heating end, and the user end, for obtaining a compensation amount that meets the user end's needs through the heating support of the heating system, and establishing a compensation controller at the auxiliary heating end based on the compensation amount, and controlling the auxiliary heating end through the compensation controller to achieve a heating balance of the heating system with the compensation amount;

[0010] The control module is used to control the balancing controller to be in a restricted controlled state when the heating system enters a heating balance, and to control the connection and exit of the auxiliary heating end through the compensation amount.

[0011] Furthermore, the geothermal heating end is provided with a heating capacity determination model, which makes a comprehensive prediction based on the historical production capacity data and heating capacity data of the geothermal heating end to obtain a steady-state range of geothermal heating capacity when the geothermal production capacity is constant.

[0012] Furthermore, the heating capacity determination model has:

[0013] A sampling module, which samples the historical production capacity database and the heating operation database in time sequence, and fills the sampled historical production capacity data and heating capacity historical data into a two-dimensional operation array in sequence;

[0014] A processing module uses the two-dimensional operation array and the statistical model as the core of the training model, configures the two-dimensional operation array to have the same sampling rate for sampling and performs iterative training, and inputs the training results into the statistical model to determine the steady-state range of geothermal heating capacity when the geothermal production capacity is constant.

[0015] Furthermore, the balancing controller is used to determine the stable output of heat supply according to the heat supply support, and at the same time obtain the elastically regulated output on the premise of the stable output of heat supply according to the elastic regulation range of heat supply.

[0016] Furthermore, the heating steady-state model is used to determine the stable heating output according to the heating support, and to obtain the compensation amount that meets the user-side demand according to the user-side demand.

[0017] Furthermore, a monitoring module is also provided in the heating steady-state model, and the monitoring module is used to monitor the heating balance state. When the heating balance state cannot be sustained under the control of the control module, the monitoring module sends a release instruction to the control module to release the restricted controlled state of the balancing controller. The control module controls the balancing controller to enter the adaptive control state based on the release instruction. In the adaptive control state, the heating capacity of the geothermal heating end is increased by controlling the elastic selection of the balancing controller to flexibly control the output to re-satisfy the heating balance state.

[0018] Furthermore, the balancing controller is provided with a program instruction for triggering the release of the restricted controlled state of the balancing controller. After the release instruction is input into the balancing controller, the program instruction is triggered. On the one hand, the program instruction switches the balancing controller from the restricted controlled state to the adaptive control state. On the other hand, a feedback instruction is sent to the monitoring module. Based on the feedback instruction, the monitoring module obtains the elastic control compensation amount obtained by the heating steady-state model to satisfy the heating balance state, and transmits the elastic control compensation amount to the balancing controller. The balancing controller compares the amount with the elastic control output and then performs control in the adaptive control state. During control, the elastic control compensation amount is increased by controlling the balancing controller to elastically select the elastic control compensation amount to achieve the re-satisfaction of the heating balance state.

[0019] Furthermore, the control module controls the connection and exit of the auxiliary heating end through a compensation controller.

[0020] The present application proposes an intelligent system capable of combining auxiliary heat sources such as air source heat pumps, natural gas boilers, and solar auxiliary heat sources for combined heating. In this system, a steady-state range of geothermal heating capacity when geothermal capacity is constant is obtained based on historical geothermal production capacity data and historical geothermal heating operation data. A heating support, i.e., a lower limit of the steady-state range, is obtained within the steady-state range. Furthermore, the heating elasticity control range is obtained based on the steady-state support and the steady-state range. When geothermal heat is the primary source of heating, the balancing controller is controlled to be in a restricted controlled state. At this time, the balancing controller controls the geothermal heating end to provide heating according to the steady-state support. At this time, the geothermal heating end is constant. When user demand increases, the auxiliary heating end is connected and controlled under the control of a control module. A required compensation amount is calculated based on the user demand obtained from a heating steady-state model and the heating capacity of the geothermal heating end. The compensation amount is used to control at least one auxiliary heating end to provide heating compensation, thereby achieving a balanced heating state. When climatic conditions change significantly, such as a temperature increase, user demand decreases, and the auxiliary heating end can be controlled to exit. When the temperature drops sharply, if a heat supply balance cannot be achieved under the auxiliary heating and steady-state heating modes, the geothermal production capacity can be adjusted and the heating capacity of the geothermal heating end can be controlled based on the set heating elasticity control range to achieve a balance. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is a schematic diagram of the system framework provided by the present invention;

[0023] Figure 2 It is a system framework principle diagram of the heating capacity determination model provided by the present invention. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0025] Reference Figure 1 and Figure 2 , the present invention provides a geothermal-based collaborative multi-energy intelligent heating system, including a geothermal heating end for supplying heat using geothermal energy as the main line of the heating system, and obtaining a steady-state range of the geothermal heating capacity;

[0026] a balancing controller, disposed at a geothermal heating end, for controlling, when geothermal heat is used as the main line of the heating system for heating, setting a heating support and a heating elasticity control range of the geothermal heating end; wherein the heating support is obtained from the steady-state interval, and the heating elasticity control range is set based on the heating support;

[0027] At least one auxiliary heating terminal, used as auxiliary heating, connected to the heating system;

[0028] a heating steady-state model, connected to the geothermal heating end, the auxiliary heating end, and the user end, for obtaining a compensation amount that meets the user end's needs through the heating support of the heating system, and establishing a compensation controller at the auxiliary heating end based on the compensation amount, and controlling the auxiliary heating end through the compensation controller to achieve a heating balance of the heating system with the compensation amount;

[0029] The control module is used to control the balancing controller to be in a restricted controlled state when the heating system enters a heating balance, and to control the connection and exit of the auxiliary heating end through the compensation amount.

[0030] In the above, the steady-state interval of geothermal heating capacity when geothermal production capacity is constant is obtained based on the historical data of geothermal production capacity and the historical data of geothermal heating operation, and the heating support is obtained within the steady-state interval, that is, the lower limit of the steady-state interval, and the heating elasticity control range is obtained through the steady-state support and the steady-state interval; when geothermal heat is used as the main line for heating, the balancing controller is controlled to be in a restricted controlled state. At this time, the balancing controller controls the geothermal heating end to provide heating according to the steady-state support. At this time, the geothermal heating end is constant. When the demand at the user end increases, at this time, the auxiliary heating end is connected and controlled under the control of the control module, and the required compensation amount is converted according to the user end demand obtained by the heating steady-state model and the heating capacity of the geothermal heating end, so as to control at least one auxiliary heating end to perform heating compensation through the compensation amount to achieve a heating balance state.

[0031] In the above, the steady-state interval of geothermal heat is obtained by the following method: the geothermal heating end is provided with a heating capacity determination model, and the heating capacity determination model makes a comprehensive prediction through the historical production capacity data and heating capacity historical data of the geothermal heating end to obtain the steady-state interval of geothermal heating capacity when the geothermal production capacity is constant.

[0032] The heating capacity determination model comprises: a sampling module, which samples correspondingly in time from a historical production capacity database and a heating operation database, and sequentially fills the sampled historical production capacity data and historical heating capacity data into a two-dimensional operation array; a processing module, which uses the two-dimensional operation array and a statistical model as the core of a training model, and configures the two-dimensional operation array to have the same sampling rate for sampling and performs iterative training, and inputs the training results into the statistical model to determine the steady-state range of geothermal heating capacity when the geothermal production capacity is constant.

[0033] The sampling module is configured to have a first sampling unit and a second sampling unit, and the first sampling unit is configured to be connected to the production capacity database and the first axis of the two-dimensional operation array, and the second sampling unit is configured to be connected to the heating operation database and the second axis of the two-dimensional operation array; and the first sampling unit and the second sampling unit are set to have the same sampling rate, and the first axis of the two-dimensional operation array corresponds to the historical production capacity data and samples are sequentially sampled according to the set time nodes, and then the two-dimensional operation array performs production capacity prediction to obtain a production capacity prediction value at a time node; the second axis of the two-dimensional operation array corresponds to the historical heating capacity data and samples are sequentially sampled according to the set time nodes, and then the two-dimensional operation array performs heating capacity prediction to obtain a heating capacity prediction value at a time node; the obtained production capacity prediction value and the corresponding heating capacity prediction value are sequentially input into the statistical model according to the time nodes, and optimization selection is performed in the statistical model to obtain a steady-state interval of geothermal heating capacity under a constant geothermal production capacity state.

[0034] In the above, the geothermal production capacity historical data and the heating capacity historical data are sampled according to the time axis, that is, under the same time, the data generated by the historical operating status corresponding to the geothermal production capacity. In this application, in order to increase the effectiveness of training, historical data are extracted according to the set time as a time node. For example, in 10 days, the geothermal heating operation data corresponding to the geothermal production capacity. A large amount of data makes the training prediction more accurate. A time node forms a stable production capacity data interval and operation data interval. The production capacity prediction value and heating capacity are obtained by averaging. The power prediction value is input into the plane coordinate axis for marking, and then multiple capacity prediction values ​​and heating capacity prediction values ​​are connected with smooth curves to obtain the heating capacity steady-state curve and the capacity steady-state curve. The capacity stability data value can be obtained through the capacity steady-state curve. Similarly, according to the steady-state curve of the heating capacity, the steady-state support formed in the heating steady-state interval and based on the heating steady-state interval can be obtained. The steady-state support can be understood as the curve after the steady-state curve of the heating capacity is corrected. Any point on the curve represents the lower limit of the geothermal heating capacity.

[0035] In the above, when the steady-state curve of heating capacity is corrected, a coefficient, such as 0.9, is set to shift the steady-state curve of heating capacity downward as a whole by the coefficient, wherein the coefficient is converted by the difference between the average value of the lower limit value of the steady-state interval and the median value of the steady-state interval.

[0036] In the above, the sampling rate is expressed as obtaining the production capacity data or heating operation number generated in the historical geothermal heating operation cycle in the production capacity database or heating operation database according to the set time node.

[0037] In the above, the balancing controller is used to determine the stable output of heat supply according to the heat supply support, and at the same time obtain the elastically regulated output on the premise of the stable output of heat supply according to the elastic regulation range of heat supply.

[0038] In the above, the heating steady-state model is used to determine the stable heating output according to the heating support, and to obtain the compensation amount that meets the user-side demand according to the user-side demand.

[0039] In the above, a monitoring module is also provided in the heating steady-state model, and the monitoring module is used to monitor the heating balance state. When the heating balance state cannot be sustained under the control of the control module, the monitoring module sends a release instruction to the control module to release the restricted controlled state of the balancing controller. The control module controls the balancing controller to enter the adaptive control state based on the release instruction. In the adaptive control state, the heating capacity of the geothermal heating end is increased by controlling the elastic selection of the balancing controller to flexibly control the output to re-satisfy the heating balance state.

[0040] In the above, the balancing controller is provided with a program instruction for triggering the release of the restricted controlled state of the balancing controller. After the release instruction is input into the balancing controller, the program instruction is triggered. On the one hand, the program instruction switches the balancing controller from the restricted controlled state to the adaptive control state. On the other hand, a feedback instruction is sent to the monitoring module, and based on the feedback instruction, the monitoring module obtains the elastic control compensation amount obtained by the heating steady-state model to meet the heating balance state, and transmits the elastic control compensation amount to the balancing controller. The balancing controller compares the amount with the elastic control output and then performs control in the adaptive control state. During the control, the elastic control compensation amount is increased by controlling the balancing controller to elastically select the elastic control compensation amount to increase the heating capacity of the geothermal heating end so as to re-meet the heating balance state.

[0041] Furthermore, the control module controls the connection and exit of the auxiliary heating end through a compensation controller.

[0042] The principle of the present application is as follows: based on historical geothermal production capacity data and historical geothermal heating operation data, a steady-state interval of geothermal heating capacity when geothermal production capacity is constant is obtained. Specifically, the sampling module is configured to have a first sampling unit and a second sampling unit, and the first sampling unit is configured to be connected to the production capacity database and the first axis of the two-dimensional operation array, and the second sampling unit is configured to be connected to the heating operation database and the second axis of the two-dimensional operation array; and the first sampling unit and the second sampling unit are set to have the same sampling rate. The first axis of the two-dimensional operation array corresponds to the historical production capacity data and samples are sequentially sampled according to set time nodes. Then, the two-dimensional operation array performs production capacity prediction to obtain a production capacity prediction value for a time node. The second axis of the two-dimensional operation array corresponds to the historical heating capacity data and samples are sequentially sampled according to set time nodes. Then, the two-dimensional operation array performs heating capacity prediction to obtain a heating capacity prediction value for a time node. The obtained production capacity prediction value and the corresponding heating capacity prediction value are sequentially input into a statistical model according to the time nodes, and an optimization selection is performed in the statistical model to obtain a steady-state interval of geothermal heating capacity when geothermal production capacity is constant. And obtain the heating support within the steady-state interval, that is, the lower limit of the steady-state interval, and obtain the heating elasticity control range through the steady-state support and the steady-state interval; when geothermal heat is used as the main line for heating, the balance controller is controlled to be in a restricted controlled state. At this time, the balance controller controls the geothermal heating end to provide heating according to the steady-state support. At this time, the geothermal heating end is constant. When the demand of the user end increases, at this time, under the control of the control module, the auxiliary heating end is connected and controlled, and the required compensation amount is converted according to the user end demand obtained by the heating steady-state model and the heating capacity of the geothermal heating end. In this way, the compensation amount is used to control at least one auxiliary heating end to perform heating compensation and achieve a heating balance state. When the climate conditions change significantly, such as when the temperature rises, the demand of the user end decreases. At this time, the auxiliary heating end can be controlled to exit. When the temperature drops suddenly, and the heating balance state cannot be reached under the auxiliary heating and steady-state heating modes, the geothermal production capacity can be adjusted, and the heating capacity of the geothermal heating end can be controlled based on the set heating elasticity control range to achieve a balance state.

[0043] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A geothermal-based, multi-energy intelligent heating system, characterized by: include The geothermal heating end is used to provide heat using geothermal energy as the main line of the heating system to obtain the steady-state range of geothermal heating capacity; a balancing controller, disposed at a geothermal heating end, for controlling, when geothermal heat is used as the main line of the heating system for heating, setting a heating support and a heating elasticity control range of the geothermal heating end; wherein the heating support is obtained from the steady-state interval, and the heating elasticity control range is set based on the heating support; At least one auxiliary heating terminal, used as auxiliary heating, connected to the heating system; a heating steady-state model, connected to the geothermal heating end, the auxiliary heating end, and the user end, for obtaining a compensation amount that meets the user end's needs through the heating support of the heating system, and establishing a compensation controller at the auxiliary heating end based on the compensation amount, and controlling the auxiliary heating end through the compensation controller to achieve a heating balance of the heating system with the compensation amount; a control module, configured to control the balancing controller to be in a restricted controlled state when the heating system reaches a heat supply balance, and to control the connection and exit of the auxiliary heating end by means of the compensation amount; The geothermal heating end is provided with a heating capacity determination model, which performs a comprehensive prediction based on the historical data of the production capacity and the heating capacity of the geothermal heating end to obtain a steady-state range of the geothermal heating capacity when the geothermal production capacity is constant; The heating capacity determination model has: A sampling module, which samples the historical production capacity database and the heating operation database in time sequence, and fills the sampled historical production capacity data and heating capacity historical data into a two-dimensional operation array in sequence; A processing module uses the two-dimensional operation array and the statistical model as the core of the training model, configures the two-dimensional operation array to have the same sampling rate for sampling and performs iterative training, and inputs the training results into the statistical model to determine the steady-state range of geothermal heating capacity when the geothermal production capacity is constant.

2. The geothermal-based collaborative multi-energy intelligent heating system according to claim 1 is characterized in that: The balancing controller is used to determine the stable output of heat supply according to the heat supply support, and at the same time obtain the elastically regulated output on the premise of the stable output of heat supply according to the elastic regulation range of heat supply.

3. The geothermal-based collaborative multi-energy intelligent heating system according to claim 1 is characterized in that: The heating steady-state model is used to determine the stable output of heating according to the heating support, and to obtain the compensation amount that meets the user-side demand according to the user-side demand.

4. The geothermal-based collaborative multi-energy intelligent heating system according to claim 1 is characterized in that: A monitoring module is also provided in the heating steady-state model. The monitoring module is used to monitor the heating balance state. When the heating balance state cannot be sustained under the control of the control module, the monitoring module sends a release instruction to the control module to release the restricted controlled state of the balancing controller. The control module controls the balancing controller to enter an adaptive control state based on the release instruction. In the adaptive control state, the heating capacity of the geothermal heating end is increased by elastically controlling the output through elastically controlling the balancing controller to re-satisfy the heating balance state.

5. The geothermal-based collaborative multi-energy intelligent heating system according to claim 4 is characterized in that: The balancing controller is provided with a program instruction for triggering the release of the restricted controlled state of the balancing controller. After the release instruction is input into the balancing controller, the program instruction is triggered. On the one hand, the program instruction switches the balancing controller from the restricted controlled state to the adaptive control state. On the other hand, a feedback instruction is sent to the monitoring module. Based on the feedback instruction, the monitoring module obtains the elastic control compensation amount obtained by the heating steady-state model to meet the heating balance state, and transmits the elastic control compensation amount to the balancing controller. The balancing controller compares the amount with the elastic control output and then performs control in the adaptive control state. During control, the elastic control compensation amount is increased by controlling the balancing controller to elastically select the elastic control compensation amount to achieve the re-satisfaction of the heating balance state.

6. The geothermal-based collaborative multi-energy intelligent heating system according to claim 1 is characterized in that: The control module controls the connection and exit of the auxiliary heating end through a compensation controller.

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