Cooperative operation method and system of data center and regional heat supply system based on carbon emission flow

Abstract

The invention discloses a cooperative operation method and system of a data center and a regional heat supply system based on carbon emission flow. The method comprises the steps that a cooperative operation framework of the data center and the regional heat supply system is constructed; establishing a first operation optimization model for the data center, and solving the first operation optimization model; then, calculating a carbon emission flow in 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 a regional heat supply system; a second operation optimization model for the regional heat supply system is established and solved, and a heat energy purchasing result is sent to the data center; and iteratively solving the first operation optimization model and the second operation optimization model in sequence, and ensuring algorithm convergence by adopting a bisection method. According to the method, the carbon emission contained in the heat energy output by the data center to the regional heat supply system is calculated, so that the carbon emission of the data center and the regional heat supply system is quantified.

Description

Technical Field

[0001] The present invention belongs to the technical field of operation scheduling of data centers and regional heating systems, and in particular, relates to a coordinated operation method and system of a data center and a regional heating system based on carbon emission flow. Background Art

[0002] As a highly potential thermal resource, waste heat from data centers has received increasing attention in recent years. By adopting heat recovery technology, data centers can convert waste heat generated into useful thermal energy and transmit it to nearby district heating networks, thereby achieving efficient use of energy. This integration not only helps to improve the energy efficiency of data centers, but also provides a stable heat source for district heating systems, reducing dependence on traditional fossil fuels and thus reducing carbon emissions. In addition, the coordinated operation of data centers and district heating systems can also bring significant economic benefits, such as reducing operating costs and opening up new business avenues.

[0003] However, existing research and technology still have some shortcomings in the coordinated operation of data centers and district heating systems. First, current research mainly focuses on formulating low-carbon operation plans with the goal of minimizing the total carbon emissions on the energy production side, but this approach ignores the fact that energy production is driven by demand, that is, energy consumers should be regarded as the main source of carbon emissions and bear the corresponding carbon emission responsibilities. Secondly, as independent operating entities, data centers and district heating systems need to fully consider the interactive relationship with the power grid and heating system during the coordinated operation process, but existing technologies face many challenges in achieving such coordinated operation. For example, the waste heat of data centers is usually in a low-temperature state and needs to be improved and converted through technologies such as heat pumps, which increases the complexity and cost of the system. In addition, in the interactive process of the coordinated operation of data centers and district heating systems, data privacy protection is also an issue that cannot be ignored, and existing technologies have not yet fully addressed this issue. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a coordinated operation method of a data center and a regional heating system based on carbon emission flow to solve the problems existing in the above-mentioned prior art.

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

[0006] Build a collaborative operation framework between data centers and district heating systems;

[0007] Based on the collaborative operation framework, a first operation optimization model of the data center is established, and the first operation optimization model is solved to obtain a first operation plan of the data center and upper and lower limits of output heat energy;

[0008] Calculating the carbon emission flow in the data center based on the first operation plan to obtain the carbon intensity of the heat energy output by the data center;

[0009] Send the upper and lower limits of thermal energy and carbon intensity to the regional heating system, establish a second operation optimization model of the regional heating system, solve the second operation optimization model, and obtain a second operation plan of the regional heating system; based on the second operation plan, obtain the thermal energy purchased by the regional heating system from the data center, and send the result of the purchased thermal energy to the data center;

[0010] The first operation optimization model and the second operation optimization model are solved iteratively in sequence, and the optimization results of the boundary variables are exchanged until the algorithm reaches convergence.

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

[0012] With the goal of minimizing the comprehensive operating cost of the data center, the first operation optimization model of the data center is established;

[0013] The forecast data of the data center for the next day is obtained as the parameter of the first operation optimization model, and the first operation plan of the data center is obtained by solving the model.

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

[0015] Build a network of carbon emission flows within data centers;

[0016] According to the relationship between energy flow and carbon emission flow in the carbon emission flow network, a carbon intensity calculation model of the carbon node is established;

[0017] The carbon intensity of the thermal energy output by the data center is calculated according to the carbon intensity calculation model and the first operation plan.

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

[0019] The second operation optimization model of the district heating system is established with the goal of minimizing the comprehensive operation cost;

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

[0021] Preferably, the first operation optimization model and the second operation optimization model are iteratively solved in sequence by using a binary search iterative solution algorithm until the interaction data between the data center and the regional heating system converges.

[0022] In a second aspect, the present invention further provides a coordinated operation system of a data center and a regional heating system based on a carbon emission flow, comprising:

[0023] Framework building module, used to build a collaborative operation framework between data centers and district heating systems;

[0024] A 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 a first operation plan of the data center and upper and lower limits of output heat energy;

[0025] a carbon emission flow calculation module, configured to calculate the carbon emission flow in the data center based on the first operation plan to obtain the carbon intensity of the heat energy output by the data center;

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

[0027] The data iteration module is used to iteratively solve the first operation optimization model and the second operation optimization model in sequence and exchange the optimization results of the boundary variables until the algorithm reaches convergence.

[0028] In a third aspect, the present invention further discloses a computer device, comprising 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] In a fourth aspect, the present invention further discloses a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when executed by a processor.

[0030] In a fifth aspect, the present invention further discloses a computer program product, including a computer program, which implements the steps of the method described in the first aspect when executed by a processor.

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

[0032] The present invention provides a method for coordinated operation of a data center and a regional heating system based on a carbon emission flow. First, a coordinated operation framework of the data center and the regional heating system is constructed. Secondly, based on the coordinated operation framework, a first operation optimization model of the data center is established, and the first operation optimization model is solved to obtain a first operation plan of the data center and upper and lower limits of output heat energy. Then, based on the first operation plan, the carbon emission flow in the data center is calculated to obtain the carbon intensity of the heat energy output by the data center. Further, the upper and lower limits of the heat energy and the carbon intensity are sent to the regional heating system, a second operation optimization model of the regional heating system is established, and the second operation optimization model is solved to obtain a second operation plan of the regional heating system. Based on the second operation plan, the heat energy purchased by the regional heating system from the data center is obtained, and the result of the purchased heat energy is sent to the data center. Finally, the first operation optimization model and the second operation optimization model are solved iteratively in sequence, and the optimization results of the boundary variables are interacted until the algorithm converges.

[0033] Based on the proposed collaborative operation framework, this invention realizes the quantification of carbon emissions of each subject by calculating the carbon emissions contained in the heat energy output by the data center to the regional heating system, and only requires the operation results of the interactive boundary variables, which effectively protects data privacy. In addition, based on the carbon emission flow theory, the carbon emission flow inside the data center is analyzed, and a calculation model for the carbon intensity of the heat energy output by the data center is proposed, which realizes the quantification of the carbon emissions contained in the heat energy output by the data center. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0035] Figure 1 A schematic diagram of the topological structure 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 a collaborative operation framework of a data center and a regional heating system according to an embodiment of the present invention;

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

[0038] Figure 4 Schematic diagram of the iterative solution convergence process based on the bisection method according to 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 5Schematic diagram of heat energy output from a data center to a regional heating system according to an embodiment of the present invention; wherein (a) is a schematic diagram of heat energy output from data center 1, (b) is a schematic diagram of heat energy output from data center 2, (c) is a schematic diagram of heat energy output from data center 3, and (d) is a schematic diagram of heat energy output from a cogeneration device;

[0040] Figure 6 This is a schematic diagram of carbon emissions results from a data center to a district heating system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

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

[0043] Embodiment 1

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

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

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

[0047] The collaborative operation framework between data centers and district heating systems, such as Figure 2 shown.

[0048] Step 2: Based on the collaborative operation framework, a first operation optimization model of the data center is established, and the first operation optimization model is solved to obtain a first operation plan of the data center and upper and lower limits of output heat energy;

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

[0050] With the goal of minimizing the comprehensive operating cost of the data center, the first operation optimization model of the data center is established;

[0051] The forecast data of the data center for the next day is obtained as the parameter of the first operation optimization model, and the first operation plan of the data center is obtained by solving the model.

[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) Refrigeration system operation constraints:

[0061]

[0062] (4) Power balance constraints:

[0063]

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

[0065]

[0066]

[0067] Step 3: Calculate the carbon emission flow in the data center based on the first operation plan to obtain the carbon intensity of the heat energy output by the data center;

[0068] Further, the process of obtaining the carbon intensity of the data center's thermal output includes:

[0069] Build a network of carbon emission flows within data centers;

[0070] According to the relationship between energy flow and carbon emission flow in the carbon emission flow network, a carbon intensity calculation model of the carbon node is established;

[0071] The carbon intensity of the thermal energy output by the data center is calculated according to the carbon intensity calculation model and the first operation plan.

[0072] Specifically, a carbon emission flow network inside the data center is constructed, including 7 nodes, such as Figure 3As shown. According to the relationship between the energy flow and carbon emission flow within the data center, a carbon intensity calculation model for the carbon node is established to determine the carbon intensity of the heat output of the data center. First, the carbon intensity of the sup node is calculated, as shown in the following formula:

[0073]

[0074] The carbon intensity of the bt node is calculated according to 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 data center's thermal output 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 of the district heating system, solve the second operation optimization model, and obtain a second operation plan of 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 purchasing thermal energy to the data center;

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

[0082] The second operation optimization model of the district heating system is established with the goal of minimizing the comprehensive operation cost;

[0083] The predicted parameters of the district heating system, the upper and lower limits of the heat output of the data center and its carbon intensity are used as inputs of the second operation optimization model to solve 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: Iteratively solve the first operation optimization model and the second operation optimization model in sequence, and exchange the optimization results of boundary variables until the algorithm reaches convergence.

[0089] Furthermore, through the iterative solution algorithm of the binary search method, the first operation optimization model and the second operation optimization model are iteratively solved in turn until the interaction data of the data center and the regional heating system converge, the iteration is stopped, and the operation plans of the data center and the regional heating system are output.

[0090] Aiming at the oscillation phenomenon that may occur in the iterative solution process of the data center and the district heating system, an iterative solution algorithm based on the dichotomy method is proposed, as shown below:

[0091]

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

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

[0094] The results for the carbon emissions embodied in the heat energy flowing from the data center to the district heating system are as follows: Figure 6 shown.

[0095] The operating cost results for the data center and district heating system are shown in Table 1.

[0096] Table 1

[0097]

[0098] Beneficial effects of this embodiment:

[0099] This embodiment proposes a method for the coordinated operation of a data center and a regional heating system based on carbon emission flow. This method aims to minimize the comprehensive cost of the data center and constructs a low-carbon economic operation optimization model for the data center. Based on the carbon emission flow theory, the carbon intensity of the output heat energy of the data center is calculated according to the data center operation plan, and the result is sent to the regional heating system. At the same time, an optimization model for the regional heating system is established with the goal of minimizing the comprehensive operating cost. The amount of heat energy purchased by the regional heating system from the data center is determined by solving the problem, and the result is fed back to the data center. In order to solve the oscillation problem that may occur in the iterative solution process between the data center and the regional heating system, this embodiment proposes an iterative solution algorithm based on the dichotomy method.

[0100] Embodiment 2

[0101] Based on the same inventive concept, this embodiment also provides a coordinated operation system of a data center and a regional heating system based on carbon emission flow, including:

[0102] Framework building module, used to build a collaborative operation framework between data centers and district heating systems;

[0103] A first acquisition module, configured to acquire a first operation plan of the data center and upper and lower limits of output heat energy based on the collaborative operation framework;

[0104] a carbon emission flow calculation module, configured to calculate the carbon emission flow in the data center based on the first operation plan to obtain the carbon intensity of the heat energy output by the data center;

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

[0106] A data iteration module is used to iteratively solve the first operation plan and the second operation plan in sequence, and continue the data interaction between the data center and the regional heating system until the algorithm reaches convergence.

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

[0108] Embodiment 3

[0109] This embodiment further 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 embodiment.

[0110] Embodiment 4

[0111] This embodiment further discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in the first embodiment are implemented.

[0112] Embodiment 5

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

[0114] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for coordinated operation of a data center and a district heating system based on carbon emission flow, characterized in that: The following steps are involved: Build a collaborative operation framework between data centers and district heating systems; Based on the collaborative operation framework, a first operation optimization model of the data center is established, and the first operation optimization model is solved to obtain a first operation plan of the data center and upper and lower limits of output heat energy; Calculating the carbon emission flow in the data center based on the first operation plan to obtain the carbon intensity of the heat energy output by the data center; Sending the upper and lower limits of thermal energy and the carbon intensity to the regional heating system, establishing a second operation optimization model of the regional heating system, solving the second operation optimization model, and obtaining a second operation plan of the regional heating system; Based on the second operation plan, obtaining the heat energy purchased by the regional heating system from the data center, and sending the result of the purchased heat energy to the data center; The first operation optimization model and the second operation optimization model are solved iteratively in sequence, and the optimization results of the boundary variables are exchanged until the algorithm reaches convergence.

2. The method according to claim 1, characterized in that The process of obtaining the first operation plan of the data center includes: With the goal of minimizing the comprehensive operating cost of the data center, the first operation optimization model of the data center is established; The forecast data of the data center for the next day is obtained as the parameter of the first operation optimization model, and the first operation plan of the data center is obtained by solving the model.

3. The method according to claim 1, characterized in that The process for deriving the carbon intensity of a data center’s thermal output involves: Build a network of carbon emission flows within data centers; According to the relationship between energy flow and carbon emission flow in the carbon emission flow network, a carbon intensity calculation model of the carbon node is established; The carbon intensity of the thermal energy output by the data center is calculated according to the carbon intensity calculation model and the first operation plan.

4. The method according to claim 1, characterized in that The process of obtaining the second operation plan of the district heating system includes: The second operation optimization model of the district heating system is established with the goal of minimizing the comprehensive operation cost; The predicted parameters of the district heating system, the upper and lower limits of the heat output of the data center and its carbon intensity are used as inputs of the second operation optimization model to solve the second operation plan of the district heating system.

5. The method according to claim 1, characterized in that The first operation optimization model and the second operation optimization model are iteratively solved in sequence through a binary search iterative solution algorithm until the interaction data between the data center and the regional heating system converges.

6. A coordinated operation system of a data center and a regional heating system based on carbon emission flow, characterized in that: include: Framework building module, used to build a collaborative operation framework between data centers and district heating systems; A 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 a first operation plan of the data center and upper and lower limits of output heat energy; a carbon emission flow calculation module, configured to calculate the carbon emission flow in the data center based on the first operation plan to obtain the carbon intensity of the heat energy output by the data center; A second acquisition module is used to send the upper and lower limits of thermal energy and the carbon intensity to the regional heating system, establish a second operation optimization model of the regional heating system, solve the second operation optimization model, and obtain a second operation plan of the regional heating system; Based on the second operation plan, obtaining the heat energy purchased by the regional heating system from the data center, and sending the result of the purchased heat energy to the data center; The data iteration module is used to iteratively solve the first operation optimization model and the second operation optimization model in sequence and exchange the optimization results of the boundary variables until the algorithm reaches convergence.

7. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 5.

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

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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