A method and system for coordinated operation of a data center and district heating system based on carbon emission flow

Abstract

This invention discloses a method and system for the coordinated operation of a data center and a district heating system based on carbon emission flows. The method includes: constructing a coordinated operation framework for the data center and the district heating system; establishing and solving a first operation optimization model for the data center; calculating the carbon emission flow within the data center to obtain the carbon intensity of the heat energy output by the data center, and sending the upper and lower limits of the heat energy and the carbon intensity to the district heating system; establishing and solving a second operation optimization model for the district heating system, and sending the results of heat energy purchases to the data center; iteratively solving the first and second operation optimization models sequentially, and using a bisection method to ensure algorithm convergence. This application quantifies the carbon emissions of both the data center and the district heating system by calculating the carbon emissions inherent in the heat energy output by the data center to the district heating system.

Description

Technical Field

[0001] This invention belongs to the field of data center and district heating system operation and scheduling technology, and particularly relates to a collaborative operation method and system for data centers and district heating systems based on carbon emission flows. Background Technology

[0002] Data center waste heat, as a highly promising thermal resource, has received increasing attention in recent years. By employing heat recovery technology, data centers can convert their waste heat into usable thermal energy and supply it to nearby district heating networks, thereby achieving efficient energy utilization. This integration not only helps improve the energy efficiency of data centers but also provides a stable heat source for district heating systems, reducing reliance on traditional fossil fuels and thus lowering carbon emissions. Furthermore, the synergistic operation of data centers and district heating systems can bring significant economic benefits, such as reduced operating costs and the opening of new business avenues.

[0003] However, existing research and technologies still have some shortcomings in the collaborative operation of data centers and district heating systems. First, current research mainly focuses on developing low-carbon operation plans aimed at minimizing total carbon emissions from energy production. However, this approach ignores the fact that energy production is demand-driven; that is, energy consumers should be considered the primary source of carbon emissions and bear corresponding responsibility for them. Second, as independent entities, data centers and district heating systems need to comprehensively consider their interactions with the power grid and heating system during collaborative operation. However, existing technologies face many challenges in achieving this collaborative operation. For example, waste heat from data centers is usually at low temperatures and needs to be boosted and converted using technologies such as heat pumps, which increases the complexity and cost of the system. Furthermore, data privacy protection is also a significant issue during the collaborative operation of data centers and district heating systems, and existing technologies have not yet fully addressed this problem. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a collaborative operation method for data centers and district heating systems based on carbon emission flows, thereby resolving the issues present in the prior art.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for the coordinated operation of a data center and a district heating system based on carbon emission flows, comprising:

[0006] Construct a collaborative operation framework for data centers and district heating systems;

[0007] Based on the aforementioned collaborative operation framework, a first operation optimization model for the data center is established. By solving the first operation optimization model, the first operation plan and the upper and lower limits of the output thermal energy of the data center are obtained.

[0008] The carbon emission flow within the data center is calculated based on the first operating plan to obtain the carbon intensity of the data center's output heat energy;

[0009] The upper and lower limits of thermal energy and carbon intensity are sent to the district heating system to establish a second operation optimization model for the district heating system. The second operation optimization model is solved to obtain the second operation plan of the district heating system. Based on the second operation plan, the thermal energy purchased by the district heating system from the data center is obtained, and the result of the thermal energy purchase is sent to the data center.

[0010] The first and second running optimization models are solved iteratively in sequence, and the optimization results of the boundary variables are exchanged until the algorithm converges.

[0011] Preferably, the process of obtaining the first operation plan for the data center includes:

[0012] With the goal of minimizing the overall operating cost of the data center, a first operational optimization model for the data center is established;

[0013] The predicted data for the data center for the next day is obtained and used as parameters for the first operation optimization model to solve for the first operation plan of the data center.

[0014] Preferably, the process of obtaining the carbon intensity of the thermal energy output by the data center includes:

[0015] Build a carbon emission flow network within the data center;

[0016] Based on the relationship between energy flow and carbon emission flow in the carbon emission flow network, a carbon intensity calculation model for carbon nodes is established.

[0017] Based on the carbon intensity calculation model and the first operating plan, the carbon intensity of the thermal energy output by the data center is calculated.

[0018] Preferably, the process of obtaining the second operation plan for the district heating system includes:

[0019] A second operational optimization model for the district heating system is established with the goal of minimizing overall operating costs.

[0020] The predicted parameters of the district heating system, the upper and lower limits of the data center's output heat energy, and its carbon intensity are used as inputs to the second operation optimization model to obtain the second operation plan of the district heating system.

[0021] Preferably, the first operational optimization model and the second operational optimization model are solved iteratively using a bisection method until the interaction data between the data center and the district heating system converges.

[0022] Secondly, the present invention also provides a collaborative operation system for data centers and district heating systems based on carbon emission flows, comprising:

[0023] The framework building module is used to build a collaborative operation framework between data centers and district heating systems.

[0024] The first acquisition module is used to establish a first operation optimization model of the data center based on the collaborative operation framework, solve the first operation optimization model, and obtain the first operation plan and upper and lower limits of the output thermal energy of the data center.

[0025] A carbon emission flow calculation module is used to calculate the carbon emission flow within the data center based on the first operating plan, and to obtain the carbon intensity of the heat energy output by the data center;

[0026] The second acquisition module is used to send the upper and lower limits of thermal energy and carbon intensity to the district heating system, establish a second operation optimization model of the district heating system, solve the second operation optimization model, obtain a second operation plan of the district heating system, obtain the thermal energy purchased by the district heating system from the data center based on the second operation plan, and send the result of the thermal energy purchase to the data center.

[0027] The data iteration module is used to iteratively solve the first and second running optimization models in sequence, and to exchange the optimization results of boundary variables until the algorithm converges.

[0028] Thirdly, the present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.

[0029] Fourthly, the present invention also discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0030] Fifthly, the present invention also discloses a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in the first aspect.

[0031] Compared with the prior art, the present invention has the following advantages and technical effects:

[0032] This invention provides a method for the coordinated operation of a data center and a district heating system based on carbon emission flows. First, a coordinated operation framework for the data center and the district heating system is constructed. Second, based on the framework, a first operational optimization model for the data center is established, and the first operational optimization model is solved to obtain a first operational plan and upper and lower limits for the output heat energy of the data center. Next, based on the first operational plan, the carbon emission flow within the data center is calculated to obtain the carbon intensity of the output heat energy of the data center. Further, the upper and lower limits of the heat energy and the carbon intensity are sent to the district heating system to establish a second operational optimization model for the district heating system. The second operational optimization model is solved to obtain a second operational plan for the district heating system. Based on the second operational plan, the heat energy purchased by the district heating system from the data center is obtained, and the purchase result is sent to the data center. Finally, the first and second operational optimization models are iteratively solved sequentially, and the optimization results of the boundary variables are exchanged until the algorithm converges.

[0033] This invention, based on a proposed collaborative operation framework, quantifies the carbon emissions of each entity by calculating the carbon emissions inherent in the heat energy output from a data center to a district heating system. Furthermore, it effectively protects data privacy by requiring only the results of interaction boundary variables. Based on carbon emission flow theory, it analyzes the carbon emission flow within the data center and proposes a calculation model for the carbon intensity of the heat energy output from the data center, thus quantifying the carbon emissions inherent in the heat energy output from the data center. Attached Figure Description

[0034] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0035] Figure 1 This is a schematic diagram of the topology of a data center and a district heating system according to an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the collaborative operation framework between a data center and a district heating system according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the energy flow and carbon emission flow inside a data center according to an embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the iterative solution convergence process based on the bisection method in an embodiment of the present invention; (a) is the iterative solution convergence process of data center 1, and (b) is the iterative solution convergence process of data center 2.

[0039] Figure 5This is a schematic diagram of the thermal energy output from the data center to the district heating system according to an embodiment of the present invention; wherein, (a) is a schematic diagram of the thermal energy output from data center 1, (b) is a schematic diagram of the thermal energy output from data center 2, (c) is a schematic diagram of the thermal energy output from data center 3, and (d) is a schematic diagram of the thermal energy output from the cogeneration equipment.

[0040] Figure 6 This is a schematic diagram illustrating the carbon emission results from a data center to a district heating system according to an embodiment of the present invention. Detailed Implementation

[0041] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0042] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0043] Example 1

[0044] like Figure 1-2 As shown, this embodiment provides a method for the coordinated operation of a data center and a district heating system based on carbon emission flows, including:

[0045] Step 1: Construct a collaborative operation framework between the data center and the district heating system;

[0046] This embodiment employs a district heating system with three data centers and 23 nodes, such as Figure 1 As shown.

[0047] A collaborative operation framework for data centers and district heating systems, such as Figure 2 As shown.

[0048] Step 2: Based on the aforementioned collaborative operation framework, establish a first operation optimization model for the data center, solve the first operation optimization model, and obtain the first operation plan and upper and lower limits of the output thermal energy of the data center;

[0049] Furthermore, the process of obtaining the first operational plan for the data center includes:

[0050] With the goal of minimizing the overall operating cost of the data center, a first operational optimization model for the data center is established;

[0051] The predicted data for the data center for the next day is obtained and used as parameters for the first operation optimization model to solve for the first operation plan of the data center.

[0052] Specifically, the objective function of the data center operation optimization model is as follows:

[0053]

[0054] The constraints of the data center operation optimization model are as follows:

[0055] (1) IT equipment operation constraints:

[0056]

[0057]

[0058] (2) UPS energy storage operation constraints:

[0059]

[0060] (3) Operating constraints of the refrigeration system:

[0061]

[0062] (4) Power balance constraints:

[0063]

[0064] (5) Data center thermal output constraints:

[0065]

[0066]

[0067] Step 3: Calculate the carbon emission flow within the data center based on the first operating plan to obtain the carbon intensity of the data center's output heat energy;

[0068] Furthermore, the process of obtaining the carbon intensity of the thermal energy output by the data center includes:

[0069] Build a carbon emission flow network within the data center;

[0070] Based on the relationship between energy flow and carbon emission flow in the carbon emission flow network, a carbon intensity calculation model for carbon nodes is established.

[0071] Based on the carbon intensity calculation model and the first operating plan, the carbon intensity of the thermal energy output by the data center is calculated.

[0072] Specifically, a carbon emission flow network is constructed within the data center, comprising seven nodes, such as... Figure 3As shown. Based on the relationship between energy flow and carbon emission flow within the data center, a carbon intensity calculation model for carbon nodes is established to determine the carbon intensity of the data center's output heat energy. First, the carbon intensity of the sup node is calculated, as shown in the following formula:

[0073]

[0074] The carbon strength of the bt node is calculated using the following formula:

[0075]

[0076] The carbon intensity of other nodes is calculated according to the following formula:

[0077]

[0078] Finally, the carbon intensity of the thermal energy output by the data center is calculated using the following formula.

[0079]

[0080] Step 4: Send the upper and lower limits of thermal energy and carbon intensity to the district heating system, establish a second operation optimization model for the district heating system, solve the second operation optimization model, and obtain the second operation plan for the district heating system; based on the second operation plan, obtain the thermal energy purchased by the district heating system from the data center, and send the result of the thermal energy purchase to the data center.

[0081] Furthermore, the process of obtaining the second operating plan for the district heating system includes:

[0082] A second operational optimization model for the district heating system is established with the goal of minimizing overall operating costs.

[0083] The predicted parameters of the district heating system, the upper and lower limits of the data center's output heat energy, and its carbon intensity are used as inputs to the second operation optimization model to obtain the second operation plan of the district heating system.

[0084] Specifically, the objectives of the district heating system operation optimization model are as follows:

[0085]

[0086] The constraints of the district heating system operation optimization model are as follows:

[0087]

[0088] Step 5: Iterate through the first and second running optimization models sequentially, and exchange the optimization results of the boundary variables until the algorithm converges.

[0089] Furthermore, the first operational optimization model and the second operational optimization model are solved iteratively using a bisection method algorithm until the interaction data between the data center and the district heating system converges. Then, the iteration stops, and the operational plan of the data center and the district heating system is output.

[0090] To address the potential oscillations that may occur during the iterative solution process for data centers and district heating systems, an iterative solution algorithm based on the bisection method is proposed, as detailed below:

[0091]

[0092] The results of the iterative solution process based on the bisection method are as follows: Figure 4 As shown.

[0093] The results of the heat energy output from the data center to the district heating system are as follows Figure 5 As shown.

[0094] The carbon emissions associated with heat energy flowing from data centers to district heating systems are as follows: Figure 6 As shown.

[0095] The operating cost results for data centers and district heating systems are shown in Table 1.

[0096] Table 1

[0097]

[0098] Beneficial effects of this embodiment:

[0099] This embodiment proposes a collaborative operation method for data centers and district heating systems based on carbon emission flows. The method aims to minimize the overall cost of the data center and constructs a low-carbon economic operation optimization model for the data center. Based on carbon emission flow theory, the carbon intensity of the data center's output heat energy is calculated according to its operation plan, and the result is sent to the district heating system. Simultaneously, an optimization model for the district heating system is established with the goal of minimizing overall operating costs. This model determines the heat energy purchased by the district heating system from the data center through solution calculation and feeds the result back to the data center. To address the potential oscillation problem that may occur during the iterative solution process between the data center and the district heating system, this embodiment proposes an iterative solution algorithm based on the bisection method.

[0100] Example 2

[0101] Based on the same inventive concept, this embodiment also provides a collaborative operation system for data centers and district heating systems based on carbon emission flows, including:

[0102] The framework building module is used to build a collaborative operation framework between data centers and district heating systems.

[0103] The first acquisition module is used to acquire the first operation plan and the upper and lower limits of the output thermal energy of the data center based on the collaborative operation framework.

[0104] A carbon emission flow calculation module is used to calculate the carbon emission flow within the data center based on the first operating plan, and to obtain the carbon intensity of the heat energy output by the data center;

[0105] The second acquisition module is used to send the upper and lower limits of thermal energy and carbon intensity to the district heating system, acquire the second operation plan of the district heating system, obtain the thermal energy purchased by the district heating system from the data center based on the second operation plan, and send the result of the thermal energy purchase to the data center.

[0106] The data iteration module is used to iteratively solve the first operating plan and the second operating plan in sequence, and to continue the data interaction between the data center and the district heating system until the algorithm converges.

[0107] The collaborative operation system of data center and district heating system based on carbon emission flow provided in this embodiment has all the advantages of the collaborative operation method of data center and district heating system based on carbon emission flow provided in Embodiment 1.

[0108] Example 3

[0109] This embodiment also discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in Embodiment 1.

[0110] Example 4

[0111] This embodiment also discloses a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in Embodiment 1.

[0112] Example 5

[0113] This embodiment also discloses a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in Embodiment 1.

[0114] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for coordinated operation of a data center and district heating system based on carbon emission flow, characterized in that, The method comprises the following steps: a coordination operation framework of the data center and the district heating system is constructed; a first operation optimization model of the data center is established based on the coordination operation framework, the first operation optimization model is solved, and a first operation plan of the data center and upper and lower limits of output heat energy are obtained; an objective function of the first operation optimization model is as follows: ； carbon intensity of the output heat energy of the data center is calculated based on the first operation plan, and the carbon intensity of the output heat energy of the data center is obtained; a calculation formula of the carbon intensity of the output heat energy of the data center is as follows: carbon intensity of the sup node is calculated first, and is as follows: ； carbon intensity of the bt node is calculated according to the following formula: ； carbon intensity of other nodes is calculated according to the following formula: ； finally, carbon intensity of the output heat energy of the data center is calculated according to the following formula: ； the upper and lower limits of the heat energy and the carbon intensity are sent to the district heating system, a second operation optimization model of the district heating system is established, the second operation optimization model is solved, and a second operation plan of the district heating system is obtained; based on the second operation plan, heat energy purchased by the district heating system from the data center is obtained, and a result of the purchased heat energy is sent to the data center; an objective function of the second operation optimization model is as follows: ； the first operation optimization model and the second operation optimization model are iteratively solved in sequence, and an optimization result of a boundary variable is interacted until the algorithm converges.

2. The method of claim 1, wherein the process of obtaining the first operation plan of the data center comprises: a first operation optimization model of the data center is established with the objective of minimizing the comprehensive operation cost of the data center; predicted data of the data center for the next day is obtained as a parameter of the first operation optimization model, and the first operation plan of the data center is obtained by solving.

3. The method of claim 1, wherein the process of obtaining the carbon intensity of the output heat energy of the data center comprises: a carbon emission flow network inside the data center is constructed; a carbon intensity calculation model of a carbon node is established according to a relationship between energy flow and carbon emission flow in the carbon emission flow network; the carbon intensity of the output heat energy of the data center is calculated according to the carbon intensity calculation model and the first operation plan.

4. The method of claim 1, wherein the process of obtaining the second operation plan of the district heating system comprises: a second operation optimization model of the district heating system is established with the objective of minimizing the comprehensive operation cost; predicted parameters of the district heating system, the upper and lower limits of the output heat energy of the data center, and the carbon intensity thereof are taken as inputs of the second operation optimization model, and the second operation plan of the district heating system is obtained by solving.

5. The method of claim 1, wherein the first operation optimization model and the second operation optimization model are iteratively solved in sequence by a bisection iterative solving algorithm until interactive data of the data center and the district heating system converges.

6. A system for coordinated operation of a data center and district heating system based on carbon emission flow, for implementing the method of any one of claims 1-5, characterized in that, The system comprises: a framework construction module configured to construct a coordination operation framework of a data center and a district heating system; The first obtaining module is configured to establish a first operation optimization model of the data center based on the collaborative operation framework, solve the first operation optimization model, and obtain a first operation plan of the data center and an upper and lower limit of output heat energy; The carbon emission flow calculation module is configured to calculate carbon emission flow in the data center based on the first operation plan, and obtain carbon intensity of the output heat energy of the data center; The second obtaining module is configured to send the upper and lower limit of the heat energy and the carbon intensity to the district heating system, establish a second operation optimization model of the district heating system, solve the second operation optimization model, obtain a second operation plan of the district heating system, obtain heat energy purchased by the district heating system from the data center based on the second operation plan, and send a result of the purchased heat energy to the data center; The data iteration module is configured to iteratively solve the first operation optimization model and the second operation optimization model in sequence, and exchange optimization results of boundary variables until the algorithm converges.

7. A computer apparatus comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program, when executed by the processor, causes the processor to perform the method of any one of claims 1 to 6. The processor executes the computer program to implement the steps of the method of any one of claims 1-5.

8. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1-5.

9. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1-5.

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