Power grid power supply method and system considering differentiated demands of data center in extreme weather

Abstract

The invention discloses a power grid power supply method and system considering differentiated demands of data centers in extreme weather, and the method comprises the steps: firstly constructing a data center cluster power supply optimization model for a cluster micro-grid comprising different scales of data centers with the goal of minimizing the comprehensive power supply cost of a data center cluster; according to the model, differentiated requirements of a data center and the influence of extreme weather on a micro-grid system are considered, a land and underwater combined configuration mode is adopted for the data center, and a cluster micro-grid is a green power supply network combining superior power grid power supply and new energy plant station direct supply; and then, by solving the data center cluster power supply optimization model, obtaining a configuration scheme of the data center and the new energy station and a power grid power supply strategy under differential requirements. The land and underwater differential configuration mode is adopted for data centers of different scales, the supporting capacity of a new energy plant station for loads of the data centers is improved, and the optimal line connection and energy storage configuration operation mode is adopted on the premise that the power supply reliability is guaranteed and green electricity is adopted.

Description

Technical Field

[0001] This invention belongs to the field of data center power grid supply, specifically relating to a power grid supply method and system that takes into account the differentiated needs of data centers under extreme weather conditions. Background Technology

[0002] With the accelerating pace of global digital transformation, particularly the widespread application of advanced technologies such as artificial intelligence, data centers, as critical computing infrastructure, are experiencing rapid expansion in scale and density. This expansion places increasingly stringent demands on power supply capabilities. On the one hand, data centers have become critical loads highly dependent on electricity, requiring a continuous and stable power supply for their operation. On the other hand, the significantly increased power density of individual data center racks has led to a surge in total power demand, posing unprecedented challenges to the capacity, reliability, and power quality of power supply systems. The stability and efficiency of data center power supply have become key factors restricting the healthy development of the computing industry, driving the evolution of power supply systems towards higher standards.

[0003] With the global consensus on jointly addressing climate change and actively promoting a green and low-carbon energy transition, the widespread use of green electricity has become a clear direction for the sustainable development of the data center industry. However, green electricity, such as wind power and solar power, is inherently intermittent and fluctuating in output, and is significantly affected by natural weather conditions. The frequent occurrence and intensification of extreme weather events not only directly restrict the normal output of green electricity such as wind and solar power, leading to a decrease in supply capacity at critical moments, but also significantly increase the cooling load of data centers, further increasing their power consumption.

[0004] The dual challenges of ensuring stable green power supply and meeting the power demands of data centers themselves present complex and severe challenges to their stable operation. How to effectively address the impact of extreme weather and ensure continuous and stable power supply while utilizing a high proportion of green electricity is a core issue that urgently needs to be addressed in the current path of green and low-carbon development for data centers. Summary of the Invention

[0005] The purpose of this invention is to address the aforementioned problems in the prior art by providing a power grid supply method and system that takes into account the differentiated needs of data centers under extreme weather conditions.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] In a first aspect, the present invention proposes a power grid supply method that considers the differentiated needs of data centers under extreme weather conditions, including:

[0008] S1. For cluster microgrids containing data centers of different sizes, with the goal of minimizing the overall power supply cost of the data center cluster, a power supply optimization model for the data center cluster is constructed. This model considers the differentiated needs of the data centers and the impact of extreme weather on the microgrid system. The data centers adopt a combined land and underwater configuration. The cluster microgrid is a green power supply network that combines power supply from the upper-level power grid with direct power supply from new energy power plants.

[0009] S2. Solve the power supply optimization model for the data center cluster to obtain the configuration schemes for the data center and new energy power plants, as well as the power supply strategy for the power grid under differentiated needs.

[0010] In S1, the objective function of the data center cluster power supply optimization model includes:

[0011] ;

[0012] ;

[0013] ;

[0014] ;

[0015] ;

[0016] ;

[0017] In the above formula, For the cost of power supply lines, For energy storage configuration costs, For the discount rate, For the investment period, Cost of supplying electricity to the upper-level power grid Cost of power supply for local renewable energy plants. The cost of purchasing green certificates for data center cluster micronets For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes The length of the power supply channel For nodes With nodes The unit price of power supply lines in inter-channel power supply. For nodes The number of energy storage systems configured at the location The configuration price is for a single energy storage system. This is a typical operating mode for data center cluster micronets, and can be adopted. , , These represent the normal operating mode, the high-temperature weather operating mode, and the low-light weather operating mode, respectively. For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, Operating mode within one year The number of consecutive days, For a unit of time, For time period The price of electricity supplied by the upstream power grid. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, The price of direct power supply for new energy power plants. This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient of the stage, for The price of green certificates at different stages, The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. for The price of green certificates at each stage.

[0018] In S1, the constraints of the data center cluster power supply optimization model include data center differentiated demand constraints:

[0019] ;

[0020] ;

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] In the above formula, For the first The number of modules in each data center For the first Is the data center configured on a terrestrial node? Decision variables at the location, The floor area of ​​a single data center module. For nodes The number of energy storage systems configured at the location The floor area of ​​a single energy storage system. , They are nodes The photovoltaic and wind power capacity configured there, , These refer to the land area occupied per unit capacity of photovoltaic and wind power, respectively. For nodes Available construction area at the location For the first Is the data center configured on an underwater node? Decision variables at the location, For nodes With upstream power node Interconnection variables, For nodes With renewable energy nodes Interconnection variables, For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes Interconnection variables, This refers to the maximum number of power supply lines that a single line corridor can accommodate. For the large M constant, This represents the maximum number of energy storage systems that can be configured. For nodes The location variables of a photovoltaic power plant For nodes The location variables of a wind farm This represents the upper limit for the number of new energy power plants in a microgrid. This represents the total capacity of new energy sources within the microgrid. For nodes With nodes The length of the power supply channel For maximum power supply distance, For nodes Distance to the nearest water source This represents the maximum permissible distance between the data center and the water source.

[0034] In S1, the constraints of the data center cluster power supply optimization model also include line load rate constraints under different operating modes:

[0035] ;

[0036] ;

[0037] ;

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] ;

[0044] In the above formula, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For nodes With upstream power grid nodes The number of power supply lines configured in the power supply channel. For the capacity of a single line, This represents the maximum load rate of the line under normal operating conditions. For operating mode Below, time period internal nodes With upstream power grid nodes The load status of the inter-line, For the large M constant, This represents the maximum load rate of the line under heavy load conditions. This is the normal operating mode. This is an extreme weather operation mode, including a high-temperature weather operation mode and a low-sunlight weather operation mode. This refers to the maximum time during which the line can operate under heavy load within a day. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For nodes With new energy plant nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period internal nodes With new energy plant nodes The load status of the inter-line, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, For the upper-level power grid node With renewable energy nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period Inner upper-level power grid node With new energy plant nodes The load status of the inter-line.

[0045] In S1, the constraints of the data center cluster power supply optimization model also include data center cluster microgrid operation constraints:

[0046] ;

[0047] ;

[0048] ;

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] ;

[0054] ;

[0055] In the above formula, For the first Data centers during the time period Internal operating power, For the first Data centers during the time period Internal cooling power, For the first Is the data center configured on a terrestrial node? Decision variables at the location, For the first Is the data center configured on an underwater node? Decision variables at the location, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For operating mode Below, time period internal nodes The power of the energy storage system, For the first Data centers during the time period Internal cooling requirements, The underwater cooling coefficient for data centers. , Operating modes Below, time period Internal renewable energy nodes The output of photovoltaic power plants and wind power plants, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, , Renewable energy nodes The photovoltaic and wind power capacity configured there, , Renewable energy nodes The local light endowment coefficient and wind endowment coefficient, , Operating modes Below, time period Internal renewable energy nodes Based on the output characteristics of photovoltaic and wind power, The installed capacity of a single energy storage system, For nodes The number of energy storage systems configured at the location This represents the percentage change in the maximum electricity volume of the energy storage system in a single hour. For time period internal nodes The power of the energy storage system, , These are the lower and upper limits of the energy state of the energy storage system, respectively. This represents the initial power of a single energy storage system. For a unit of time, As an auxiliary variable, The last period of the day. The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. For a unit of time, Operating mode within one year The number of consecutive days, This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient of the stage, Has the price of green certificates reached [a certain level]? The step coefficient of the stage.

[0056] Secondly, this invention proposes a power grid supply system that considers the differentiated needs of data centers under extreme weather conditions, including a model building module and a model solving module;

[0057] The model building module is used to construct a power supply optimization model for data center clusters with the goal of minimizing the overall power supply cost of data center clusters. The model considers the differentiated needs of data centers and the impact of extreme weather on the microgrid system. It adopts a combined land and underwater configuration for data centers. The cluster microgrid is a green power supply network that combines power supply from the upper-level power grid with direct power supply from new energy power plants.

[0058] The model solving module is used to solve the power supply optimization model of the data center cluster, and obtain the configuration scheme of the data center and the new energy power station, as well as the power supply strategy of the power grid under the differentiated needs.

[0059] The model building module includes an objective function building unit;

[0060] The objective function construction unit is used to construct the objective function of the following data center cluster power supply optimization model:

[0061] ;

[0062] ;

[0063] ;

[0064] ;

[0065] ;

[0066] ;

[0067] In the above formula, For the cost of power supply lines, For energy storage configuration costs, For the discount rate, For the investment period, Cost of supplying electricity to the upper-level power grid Cost of power supply for local renewable energy plants. The cost of purchasing green certificates for data center cluster micronets For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes The length of the power supply channel For nodes With nodes The unit price of power supply lines in inter-channel power supply. For nodes The number of energy storage systems configured at the location The configuration price is for a single energy storage system. This is a typical operating mode for data center cluster micronets, and can be adopted. , , These represent the normal operating mode, the high-temperature weather operating mode, and the low-light weather operating mode, respectively. For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, Operating mode within one year The number of consecutive days, For a unit of time, For time period The price of electricity supplied by the upstream power grid. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, The price of direct power supply for new energy power plants. This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient of the stage, for The price of green certificates at different stages, The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. for The price of green certificates at each stage.

[0068] The model building module also includes a data center differentiated demand constraint building unit;

[0069] The data center differentiated demand constraint construction unit is used to construct the following data center differentiated demand constraints:

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] ;

[0079] ;

[0080] ;

[0081] ;

[0082] ;

[0083] ;

[0084] In the above formula, For the first The number of modules in each data center For the first Is the data center configured on a terrestrial node? Decision variables at the location, The floor area of ​​a single data center module. For nodes The number of energy storage systems configured at the location The floor area of ​​a single energy storage system. , They are nodes The photovoltaic and wind power capacity configured there, , These refer to the land area occupied per unit capacity of photovoltaic and wind power, respectively. For nodes Available construction area at the location For the first Is the data center configured on an underwater node? Decision variables at the location, For nodes With upstream power node Interconnection variables, For nodes With renewable energy nodes Interconnection variables, For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes Interconnection variables, This refers to the maximum number of power supply lines that a single line corridor can accommodate. For the large M constant, This represents the maximum number of energy storage systems that can be configured. For nodes The location variables of a photovoltaic power plant For nodes The location variables of a wind farm This represents the upper limit for the number of new energy power plants in a microgrid. This represents the total capacity of new energy sources within the microgrid. For nodes With nodes The length of the power supply channel For maximum power supply distance, For nodes Distance to the nearest water source This represents the maximum permissible distance between the data center and the water source.

[0085] The model building module also includes line load rate constraint building units under different operating modes;

[0086] The line load rate constraint construction unit under different operating modes is used to construct line load rate constraints under the following different operating modes:

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] ;

[0093] ;

[0094] ;

[0095] ;

[0096] In the above formula, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For nodes With upstream power grid nodes The number of power supply lines configured in the power supply channel. For the capacity of a single line, This represents the maximum load rate of the line under normal operating conditions. For operating mode Below, time period internal nodes With upstream power grid nodes The load status of the inter-line, For the large M constant, This represents the maximum load rate of the line under heavy load conditions. This is the normal operating mode. This is an extreme weather operation mode, including a high-temperature weather operation mode and a low-sunlight weather operation mode. This refers to the maximum time during which the line can operate under heavy load within a day. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For nodes With new energy plant nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period internal nodes With new energy plant nodes The load status of the inter-line, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, For the upper-level power grid node With renewable energy nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period Inner upper-level power grid node With new energy plant nodes The load status of the inter-line.

[0097] The model building module also includes a data center cluster microgrid operation constraint building unit;

[0098] The data center cluster micronet operation constraint construction unit is used to construct the following data center cluster micronet operation constraints:

[0099] ;

[0100] ;

[0101] ;

[0102] ;

[0103] ;

[0104] ;

[0105] ;

[0106] ;

[0107] ;

[0108] In the above formula, For the first Data centers during the time period Internal operating power, For the first Data centers during the time period Internal cooling power, For the first Is the data center configured on a terrestrial node? Decision variables at the location, For the first Is the data center configured on an underwater node? Decision variables at the location, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For operating mode Below, time period internal nodes The power of the energy storage system, For the first Data centers during the time period Internal cooling requirements, The underwater cooling coefficient for data centers. , Operating modes Below, time period Internal renewable energy nodes The output of photovoltaic power plants and wind power plants, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, , Renewable energy nodes The photovoltaic and wind power capacity configured there, , Renewable energy nodes The local light endowment coefficient and wind endowment coefficient, , Operating modes Below, time period Internal renewable energy nodes Based on the output characteristics of photovoltaic and wind power, The installed capacity of a single energy storage system, For nodes The number of energy storage systems configured at the location This represents the percentage change in the maximum electricity volume of the energy storage system in a single hour. For time period internal nodes The power of the energy storage system, , These are the lower and upper limits of the energy state of the energy storage system, respectively. This represents the initial power of a single energy storage system. For a unit of time, As an auxiliary variable, The last period of the day. The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. For a unit of time, Operating mode within one year The number of consecutive days, This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient of the stage, Has the price of green certificates reached [a certain level]? The step coefficient of the stage.

[0109] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0110] 1. This invention proposes a power grid supply method and system that considers the differentiated needs of data centers under extreme weather conditions. The method first constructs a power supply optimization model for data center clusters containing data centers of different sizes, aiming to minimize the overall power supply cost of the data center cluster. This model considers the differentiated needs of data centers and the impact of extreme weather on the microgrid system, and adopts a combined land and underwater configuration for the data centers. The cluster microgrid is a green electricity supply network combining power supply from the upper-level power grid and direct supply from renewable energy plants. Then, by solving the data center cluster power supply optimization model, the configuration schemes for data centers and renewable energy plants, as well as the power grid supply strategy under differentiated needs, are obtained. On the one hand, this method constructs a green electricity supply network combining power supply from the upper-level power grid and direct supply from renewable energy plants for cluster microgrids containing data centers of different sizes, considering the direct connection between power supply from the upper-level power grid and green electricity within the microgrid, ensuring 100% green electricity for the data center cluster. On the other hand, this method takes into account the impact of extreme weather on microgrid systems, forms a typical operating mode for data center cluster microgrids, improves the support capacity of new energy power plants for data center loads, and minimizes the overall power supply cost of data center clusters by adopting the optimal line connection and energy storage configuration operation mode under the premise of ensuring power supply reliability and using green electricity.

[0111] 2. This invention proposes a power grid supply method and system that takes into account the differentiated needs of data centers under extreme weather conditions. This method adopts a land-based and underwater differentiated configuration for data centers of different sizes, making full use of the low heat dissipation load of underwater data centers to reduce the cooling power consumption of microgrids.

[0112] 3. This invention proposes a power grid supply method and system that considers the differentiated needs of data centers under extreme weather conditions. Based on the differences in geographical environment and resource endowment within the area where the data center cluster microgrid is located, this method optimizes the site selection of data centers, photovoltaic power plants, and wind power plants. On the one hand, it considers the distance constraints of each node to avoid low voltage problems, and also considers the distance between the data center site and the water source to ensure the supply of water resources necessary for data center cooling. On the other hand, it constructs power balance constraints for new energy plant nodes to fully utilize the output of all new energy plants and maximize the output of new energy plants, taking into account the differences in sunlight and wind power endowment of different nodes. Attached Figure Description

[0113] Figure 1 This is a schematic diagram of the structure of the example described in Example 1.

[0114] Figure 2 The output characteristics of photovoltaic and wind power in the example described in Example 1 are shown in the diagram.

[0115] Figure 3 This is an overall flowchart of the method described in this invention.

[0116] Figure 4 This is a schematic diagram of the cluster micronet structure described in Example 1.

[0117] Figure 5 This is a schematic diagram of the configuration scheme of the data center and new energy power station described in Example 1.

[0118] Figure 6 This is a structural diagram of the system described in this invention. Detailed Implementation

[0119] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings.

[0120] This invention proposes a power grid supply method and system that considers the differentiated needs of data centers under extreme weather conditions. It constructs a power supply optimization model for data center clusters, comprehensively considering the joint configuration and operation of multiple data centers, new energy power plants, and energy storage systems. It adopts a power supply method that directly connects the upstream power grid to green points within the microgrid, ensuring that the data center cluster's electricity consumption is 100% green electricity. Taking into account the impact of extreme weather on the microgrid system, it establishes normal operation modes, high-temperature weather operation modes, and low-light weather operation modes for the data center microgrid cluster. It employs differentiated configurations for data centers of different sizes, using both land and underwater methods, fully utilizing the lower heat dissipation load requirements of underwater data centers. Under the premise of ensuring power supply reliability and using green electricity, it adopts optimal line connections and energy storage configurations to minimize the overall power supply cost of the data center cluster.

[0121] Example 1:

[0122] This embodiment takes a 15-node data center candidate configuration area as the research object, and its structure is as follows: Figure 1 As shown, the output characteristics of photovoltaic and wind power used in the example are as follows: Figure 2 As shown. The parameters in the example are set as follows: discount rate of 0.05, investment period of 10 years, configuration price of a single energy storage system of 1 million yuan, direct power supply price of new energy power plants of 0.5 yuan per kilowatt-hour, floor area of ​​a single data center module and energy storage system of 500 square meters and 100 square meters respectively, maximum configuration of 200 energy storage systems, installation capacity of a single energy storage system of 1 megawatt-hour, capacity of a single line of 100 megawatts, maximum power supply distance of 30 kilometers, maximum allowable distance of the data center from the water source of 10 kilometers, unit time of 1 hour, maximum number of power supply lines that a single line corridor can accommodate is 4, underwater cooling coefficient of the data center of 0.2, maximum hourly power change ratio of the energy storage system of 0.4, lower limit and upper limit of energy state of the energy storage system of 0.1 and 0.9 respectively, initial power of a single energy storage system of 0.8 megawatt-hours, maximum load rate of the line under normal operation and heavy load conditions of 0.8 and 1 respectively, and the maximum time that the line can operate under heavy load in a day is 4 hours.

[0123] like Figure 3 As shown, the power supply method for data centers considering the differentiated needs under extreme weather conditions is carried out in the following steps:

[0124] 1. For cluster microgrids containing data centers of different sizes, with the goal of minimizing the overall power supply cost of the data center cluster, a power supply optimization model for the data center cluster is constructed. This model considers the differentiated needs of the data centers and the impact of extreme weather on the microgrid system. The data centers adopt a combined land and underwater configuration. The cluster microgrid is a green power supply network that combines power supply from the upper-level power grid with direct power supply from new energy power plants.

[0125] For data center cluster microgrids consisting of multiple data centers of varying sizes, a green power supply network combining power from the upper-level power grid and direct power from renewable energy plants was constructed. Its structure is as follows: Figure 4 As shown, a power supply method considering direct connection between the upstream power grid and the microgrid's internal green electricity is taken into account. The data center receives a portion of its green electricity directly from renewable energy plants, while the upstream power grid supplies the remainder. A tiered pricing system is used to purchase green certificates for grid-supplied loads, ensuring that the data center cluster's electricity consumption is 100% green. The impact of extreme weather on the microgrid system is also considered: high temperatures increase cooling demands for the data center, while low sunlight reduces photovoltaic output, affecting the renewable energy plants' ability to support the data center load. Based on this, typical operating modes for the data center cluster microgrid are established, including a normal operating mode, a high-temperature weather operating mode, and a low-sunlight weather operating mode.

[0126] Considering the joint configuration and operation of multiple data centers, new energy power plants, and energy storage systems, a power supply optimization model for data center clusters is constructed. Under the premise of ensuring power supply reliability and using green electricity, the optimal line interconnection and energy storage configuration and operation mode are obtained to minimize the overall power supply cost of the data center cluster. Furthermore, differentiated configurations for land-based and underwater data centers of different sizes are adopted, fully utilizing the lower heat dissipation load requirements of underwater data centers to reduce the cooling power consumption of the microgrid.

[0127] The objective function of the data center cluster power supply optimization model considers the costs of power supply lines, energy storage configuration, upstream power grid, local renewable energy plant, and the cost of purchasing green certificates for the data center cluster microgrid, including:

[0128] ;

[0129] ;

[0130] ;

[0131] ;

[0132] ;

[0133] ;

[0134] In the above formula, For the cost of power supply lines, For energy storage configuration costs, For the discount rate, For the investment period, Cost of supplying electricity to the upper-level power grid Cost of power supply for local renewable energy plants. The cost of purchasing green certificates for data center cluster micronets For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes The length of the power supply channel For nodes With nodes The unit price of power supply lines in inter-channel power supply. For nodes The number of energy storage systems configured at the location The configuration price is for a single energy storage system. This is a typical operating mode for data center cluster micronets, and can be adopted. , , These represent the normal operating mode, the high-temperature weather operating mode, and the low-light weather operating mode, respectively. For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, Operating mode within one year The number of consecutive days, For a unit of time, For time period The price of electricity supplied by the upstream power grid. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, The price of direct power supply for new energy power plants. This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient (binary) for each stage; when it is 1, the price of a green certificate reaches [a certain value]. Stage, or conversely, not reached. for The price of green certificates at different stages, The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. for The price of green certificates at each stage.

[0135] The constraints of the data center cluster power supply optimization model include the data center's differentiated demand constraints, the line load rate constraints under different operating modes, and the data center cluster microgrid operation constraints.

[0136] Specifically, based on the differences in geographical constraints and resource endowments within the microgrid's region, the site selection for data centers, photovoltaic power plants, and wind power plants is optimized. The differentiated demand constraints for data centers include:

[0137] Available construction area constraints for land nodes:

[0138] ;

[0139] The configuration of data centers is constrained; a single data center can only be configured on either a land-based node or an underwater node.

[0140] ;

[0141] Line connection constraints:

[0142] ;

[0143] ;

[0144] Due to power supply constraints at renewable energy power plants, a single data center is only allowed to be directly powered by a maximum of one renewable energy power plant.

[0145] ;

[0146] The number of power supply lines is constrained, taking into account the capacity of the power supply line corridor:

[0147] ;

[0148] Energy storage configuration constraints:

[0149] ;

[0150] ;

[0151] New energy vehicle configuration constraints:

[0152] ;

[0153] ;

[0154] ;

[0155] ;

[0156] Power supply distance constraints are considered, taking into account the distance constraints of upstream power grid nodes, data center nodes, and new energy power plants, in order to avoid low voltage problems:

[0157] ;

[0158] Water source distance constraints were considered, taking into account the distance between the data center location and the water source to ensure the necessary water supply for cooling.

[0159] ;

[0160] In the above formula, For the first The number of modules in each data center For the first Is the data center configured on a terrestrial node? The decision variable (binary) at position 1, when it is 1, is the first... Each data center is configured on a terrestrial node. If it is not configured, then it is not configured. The floor area of ​​a single data center module. For nodes The number of energy storage systems configured at the location The floor area of ​​a single energy storage system. , They are nodes The photovoltaic and wind power capacity configured there, , These refer to the land area occupied per unit capacity of photovoltaic and wind power, respectively. For nodes Available construction area at the location For the first Is the data center configured on an underwater node? The decision variable (binary) at position 1, when it is 1, is the first... One data center is configured on an underwater node. If it is not configured, then it is not configured. For nodes With upstream power node The communication variable (binary) between nodes indicates that two nodes are connected via a line when the value is 1, otherwise there is no connection. For nodes With renewable energy nodes The communication variable (binary) between nodes indicates that two nodes are connected via a line when the value is 1, otherwise there is no connection. For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes Interconnection variables, This refers to the maximum number of power supply lines that a single line corridor can accommodate. For the large M constant, This represents the maximum number of energy storage systems that can be configured. For nodes The location variable (binary) for the photovoltaic power plant, when it is 1, indicates the node A photovoltaic power plant is located there. For nodes The location variable (binary) for the wind farm, when it is 1, indicates the node A wind power plant is located there. This represents the upper limit for the number of new energy power plants in a microgrid. This represents the total capacity of new energy sources within the microgrid. For nodes With nodes The length of the power supply channel For maximum power supply distance, For nodes Distance to the nearest water source This represents the maximum permissible distance between the data center and the water source.

[0161] Considering power supply capacity under both normal and extreme conditions, line load factor constraints under different operating modes include:

[0162] Line load factor constraints between data center nodes and upstream power grid nodes under normal operating conditions:

[0163] ;

[0164] ;

[0165] ;

[0166] Line load factor constraints between data center nodes and upstream power grid nodes under high-temperature weather operation mode:

[0167] ;

[0168] ;

[0169] ;

[0170] Line load factor constraints between data center nodes and upstream power grid nodes under low-light weather operation mode:

[0171] ;

[0172] ;

[0173] ;

[0174] In the above formula, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For nodes With upstream power grid nodes The number of power supply lines configured in the power supply channel. For the capacity of a single line, This represents the maximum load rate of the line under normal operating conditions. For operating mode Below, time period internal nodes With upstream power grid nodes The load rate status (binary) of the line indicates that the line is under heavy load when it is 1, and under normal operation when it is 0. For the large M constant, This represents the maximum load rate of the line under heavy load conditions. This is the normal operating mode. This is an extreme weather operation mode, including a high-temperature weather operation mode and a low-sunlight weather operation mode. This refers to the maximum time during which the line can operate under heavy load within a day. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For nodes With new energy plant nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period internal nodes With new energy plant nodes The load rate status (binary) of the line indicates that the line is under heavy load when it is 1, and under normal operation when it is 0. For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, For the upper-level power grid node With renewable energy nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period Inner upper-level power grid node With new energy plant nodes The load rate status (binary) of the line indicates that the line is under heavy load when it is 1 and under normal operation when it is 0.

[0175] Considering three operating modes—normal operation, high-temperature operation, and low-light operation—the operational constraints of the data center cluster micronet include:

[0176] Power balance constraints for data center nodes:

[0177] ;

[0178] Cooling constraints of data centers:

[0179] ;

[0180] The power balance constraint of renewable energy power plant nodes requires that the output of all renewable energy power plants be utilized, taking into account the differences in solar and wind power endowments at different nodes, and maximizing the output of renewable energy power plants:

[0181] ;

[0182] ;

[0183] ;

[0184] Energy storage operation constraints:

[0185] ;

[0186] ;

[0187] Constraints on purchasing green certificates for data center cluster micronets:

[0188] ;

[0189] ;

[0190] In the above formula, For the first Data centers during the time period Internal operating power, For the first Data centers during the time period Internal cooling power, For the first Is the data center configured on a terrestrial node? Decision variables at the location, For the first Is the data center configured on an underwater node? Decision variables at the location, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For operating mode Below, time period internal nodes The power of the energy storage system, For the first Data centers during the time period Internal cooling requirements, The underwater cooling coefficient for data centers refers to the proportion of heat dissipation achieved through water cooling in underwater data centers. , Operating modes Below, time period Internal renewable energy nodes The output of photovoltaic power plants and wind power plants, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, , Renewable energy nodes The photovoltaic and wind power capacity configured there, , Renewable energy nodes The local light endowment coefficient and wind endowment coefficient, , Operating modes Below, time period Internal renewable energy nodes Based on the output characteristics of photovoltaic and wind power, The installed capacity of a single energy storage system, For nodes The number of energy storage systems configured at the location This represents the percentage change in the maximum electricity volume of the energy storage system in a single hour. For time period internal nodes The power of the energy storage system, , These are the lower and upper limits of the energy state of the energy storage system, respectively. This represents the initial power of a single energy storage system. For a unit of time, As an auxiliary variable, The last period of the day. The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. For a unit of time, Operating mode within one year The number of consecutive days, This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient (binary) for each stage; when it is 1, the price of a green certificate reaches [a certain value]. Stage, or conversely, not reached. Has the price of green certificates reached [a certain level]? The step coefficient (binary) for each stage; when it is 1, the price of a green certificate reaches [a certain value]. The stage is reached if it is not reached, otherwise it is not reached.

[0191] 2. Simulations were performed using the MATLAB / CPLEX platform to solve the power supply optimization model for the data center cluster, obtaining configuration schemes for the data center and new energy power plants, as well as power grid supply strategies under differentiated requirements. The configuration schemes for the data center and new energy power plants are as follows: Figure 5 As shown;

[0192] The hardware parameters for the simulation platform are set as follows: Intel Core i7-9750H, 32GB RAM, 2.6GHz.

[0193] To verify the effectiveness of this scheme, a power supply method that relies entirely on the upstream power grid (Method 2) was introduced, and a power supply method that considers the differentiated needs of data centers under extreme weather conditions (Method 1) was introduced. Both were applied to the candidate configuration area structure of a 15-node data center for comparison. The comprehensive power supply cost of the microgrid for the two methods is shown in Table 1.

[0194] Table 1. Cost breakdown of the two methods

[0195] ;

[0196] Table 1 lists the annualized facility investment, annual electricity cost, and annual microgrid integrated power supply cost calculated based on the configurations and power supply schemes of the two methods. Comparing Method 1 and Method 2, it can be seen that Method 1 reduces the annualized facility investment by 10.79%, the annual electricity cost by 29.76%, and the annual microgrid integrated power supply cost by 25.34% compared to Method 2. These results demonstrate that the proposed power grid supply method, which considers the differentiated needs of data centers under extreme weather conditions, achieves the effect of minimizing the integrated power supply cost of the data center cluster microgrid while ensuring power supply reliability and using green electricity.

[0197] Example 2:

[0198] like Figure 6 As shown, a power grid supply system considering the differentiated needs of data centers under extreme weather conditions is included, comprising a model building module and a model solving module.

[0199] The model building module is used to construct a power supply optimization model for data center clusters with the goal of minimizing the overall power supply cost of data center clusters. The model considers the differentiated needs of data centers and the impact of extreme weather on the microgrid system. It adopts a combined land and underwater configuration for data centers. The cluster microgrid is a green power supply network that combines power supply from the upper-level power grid with direct power supply from new energy power plants.

[0200] The model solving module is used to solve the power supply optimization model of the data center cluster, and obtain the configuration scheme of the data center and the new energy power station, as well as the power supply strategy of the power grid under the differentiated needs.

[0201] The model building module includes an objective function building unit, a data center differentiated demand constraint building unit, a line load rate constraint building unit under different operating modes, and a data center cluster micronet operating constraint building unit.

[0202] The objective function construction unit is used to construct the objective function of the following data center cluster power supply optimization model:

[0203] ;

[0204] ;

[0205] ;

[0206] ;

[0207] ;

[0208] ;

[0209] In the above formula, For the cost of power supply lines, For energy storage configuration costs, For the discount rate, For the investment period, Cost of supplying electricity to the upper-level power grid Cost of power supply for local renewable energy plants. The cost of purchasing green certificates for data center cluster micronets For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes The length of the power supply channel For nodes With nodes The unit price of power supply lines in inter-channel power supply. For nodes The number of energy storage systems configured at the location The configuration price is for a single energy storage system. This is a typical operating mode for data center cluster micronets, and can be adopted. , , These represent the normal operating mode, the high-temperature weather operating mode, and the low-light weather operating mode, respectively. For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, Operating mode within one year The number of consecutive days, For a unit of time, For time period The price of electricity supplied by the upstream power grid. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, The price of direct power supply for new energy power plants. This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient of the stage, for The price of green certificates at different stages, The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. for The price of green certificates at each stage.

[0210] The data center differentiated demand constraint construction unit is used to construct the following data center differentiated demand constraints:

[0211] ;

[0212] ;

[0213] ;

[0214] ;

[0215] ;

[0216] ;

[0217] ;

[0218] ;

[0219] ;

[0220] ;

[0221] ;

[0222] ;

[0223] ;

[0224] ;

[0225] In the above formula, For the first The number of modules in each data center For the first Is the data center configured on a terrestrial node? Decision variables at the location, The floor area of ​​a single data center module. For nodes The number of energy storage systems configured at the location The floor area of ​​a single energy storage system. , They are nodes The photovoltaic and wind power capacity configured there, , These refer to the land area occupied per unit capacity of photovoltaic and wind power, respectively. For nodes Available construction area at the location For the first Is the data center configured on an underwater node? Decision variables at the location, For nodes With upstream power node Interconnection variables, For nodes With renewable energy nodes Interconnection variables, For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes Interconnection variables, This refers to the maximum number of power supply lines that a single line corridor can accommodate. For the large M constant, This represents the maximum number of energy storage systems that can be configured. For nodes The location variables of a photovoltaic power plant For nodes The location variables of a wind farm This represents the upper limit for the number of new energy power plants in a microgrid. This represents the total capacity of new energy sources within the microgrid. For nodes With nodes The length of the power supply channel For maximum power supply distance, For nodes Distance to the nearest water source This represents the maximum permissible distance between the data center and the water source.

[0226] The line load rate constraint construction unit under different operating modes is used to construct line load rate constraints under the following different operating modes:

[0227] ;

[0228] ;

[0229] ;

[0230] ;

[0231] ;

[0232] ;

[0233] ;

[0234] ;

[0235] ;

[0236] In the above formula, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For nodes With upstream power grid nodes The number of power supply lines configured in the power supply channel. For the capacity of a single line, This represents the maximum load rate of the line under normal operating conditions. For operating mode Below, time period internal nodes With upstream power grid nodes The load status of the inter-line, For the large M constant, This represents the maximum load rate of the line under heavy load conditions. This is the normal operating mode. This is an extreme weather operation mode, including a high-temperature weather operation mode and a low-sunlight weather operation mode. This refers to the maximum time during which the line can operate under heavy load within a day. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For nodes With new energy plant nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period internal nodes With new energy plant nodes The load status of the inter-line, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, For the upper-level power grid node With renewable energy nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period Inner upper-level power grid node With new energy plant nodes The load status of the inter-line.

[0237] The data center cluster micronet operation constraint construction unit is used to construct the following data center cluster micronet operation constraints:

[0238] ;

[0239] ;

[0240] ;

[0241] ;

[0242] ;

[0243] ;

[0244] ;

[0245] ;

[0246] ;

[0247] In the above formula, For the first Data centers during the time period Internal operating power, For the first Data centers during the time period Internal cooling power, For the first Is the data center configured on a terrestrial node? Decision variables at the location, For the first Is the data center configured on an underwater node? Decision variables at the location, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For operating mode Below, time period internal nodes The power of the energy storage system, For the first Data centers during the time period Internal cooling requirements, The underwater cooling coefficient for data centers. , Operating modes Below, time period Internal renewable energy nodes The output of photovoltaic power plants and wind power plants, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, , Renewable energy nodes The photovoltaic and wind power capacity configured there, , Renewable energy nodes The local light endowment coefficient and wind endowment coefficient, , Operating modes Below, time period Internal renewable energy nodes Based on the output characteristics of photovoltaic and wind power, The installed capacity of a single energy storage system, For nodes The number of energy storage systems configured at the location This represents the percentage change in the maximum electricity volume of the energy storage system in a single hour. For time period internal nodes The power of the energy storage system, , These are the lower and upper limits of the energy state of the energy storage system, respectively. This represents the initial power of a single energy storage system. For a unit of time, As an auxiliary variable, The last period of the day. The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. For a unit of time, Operating mode within one year The number of consecutive days, This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of green certificates reached [a certain level]? The step coefficient of the stage, Has the price of green certificates reached [a certain level]? The step coefficient of the stage.

Claims

1. A power grid supply method considering the differentiated needs of data centers under extreme weather conditions, characterized in that, The method includes: S1. For cluster microgrids containing data centers of different sizes, with the goal of minimizing the overall power supply cost of the data center cluster, a power supply optimization model for the data center cluster is constructed. This model considers the differentiated needs of the data centers and the impact of extreme weather on the microgrid system. The data centers adopt a combined land and underwater configuration. The cluster microgrid is a green power supply network that combines power supply from the upper-level power grid with direct power supply from new energy power plants. S2. Solve the power supply optimization model for the data center cluster to obtain the configuration schemes for the data center and new energy power plants, as well as the power supply strategy for the power grid under differentiated needs.

2. The power grid supply method for considering the differentiated needs of data centers under extreme weather conditions according to claim 1, characterized in that, In S1, the objective function of the data center cluster power supply optimization model includes: ； ； ； ； ； ； In the above formula, For the cost of power supply lines, For energy storage configuration costs, For the discount rate, For the investment period, Cost of supplying electricity to the upper-level power grid Cost of power supply for local renewable energy plants. The cost of purchasing green certificates for data center cluster micronets For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes The length of the power supply channel For nodes With nodes The unit price of power supply lines in inter-channel power supply. For nodes The number of energy storage systems configured at the location The configuration price is for a single energy storage system. This is a typical operating mode for data center cluster micronets, and can be adopted. , , These represent the normal operating mode, the high-temperature weather operating mode, and the low-light weather operating mode, respectively. For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, Operating mode within one year The number of consecutive days, For a unit of time, For time period The price of electricity supplied by the upstream power grid. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, The price of direct power supply for new energy power plants. This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of the green certificate reached [a certain level]? The step coefficient of the stage, for The price of green certificates at different stages, The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. for The price of green certificates at each stage.

3. The power grid supply method for considering the differentiated needs of data centers under extreme weather conditions according to claim 1, characterized in that, In S1, the constraints of the data center cluster power supply optimization model include data center differentiated demand constraints: ； ； ； ； ； ； ； ； ； ； ； ； ； ； In the above formula, For the first The number of modules in each data center For the first Is the data center configured on a terrestrial node? Decision variables at the location, The floor area of ​​a single data center module. For nodes The number of energy storage systems configured at the location The floor area of ​​a single energy storage system. , They are nodes The photovoltaic and wind power capacity configured there, , These refer to the land area occupied per unit capacity of photovoltaic and wind power, respectively. For nodes Available construction area at the location For the first Is the data center configured on an underwater node? Decision variables at the location, For nodes With upstream power node Interconnection variables, For nodes With renewable energy nodes Interconnection variables, For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes Interconnection variables, This refers to the maximum number of power supply lines that a single line corridor can accommodate. For the large M constant, This represents the maximum number of energy storage systems that can be configured. For nodes The location variables of a photovoltaic power plant For nodes The location variables of a wind farm This represents the upper limit for the number of new energy power plants in a microgrid. This represents the total capacity of new energy sources within the microgrid. For nodes With nodes The length of the power supply channel For maximum power supply distance, For nodes Distance to the nearest water source This represents the maximum permissible distance between the data center and the water source.

4. The power grid supply method for considering the differentiated needs of data centers under extreme weather conditions according to claim 1, characterized in that, In S1, the constraints of the data center cluster power supply optimization model also include line load rate constraints under different operating modes: ； ； ； ； ； ； ； ； ； In the above formula, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For nodes With upstream power grid nodes The number of power supply lines configured in the power supply channel. For the capacity of a single line, This represents the maximum load rate of the line under normal operating conditions. For operating mode Below, time period internal nodes With upstream power grid nodes The load status of the inter-line, For the large M constant, This represents the maximum load rate of the line under heavy load conditions. This is the normal operating mode. This is an extreme weather operation mode, including a high-temperature weather operation mode and a low-sunlight weather operation mode. This refers to the maximum time during which the line can operate under heavy load within a day. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For nodes With new energy plant nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period internal nodes With new energy plant nodes The load status of the inter-line, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, For the upper-level power grid node With renewable energy nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period Inner upper-level power grid node With new energy plant nodes The load status of the inter-line.

5. The power grid supply method for considering the differentiated needs of data centers under extreme weather conditions according to claim 1, characterized in that, In S1, the constraints of the data center cluster power supply optimization model also include data center cluster microgrid operation constraints: ； ； ； ； ； ； ； ； ； In the above formula, For the first Data centers during the time period Internal operating power, For the first Data centers during the time period Internal cooling power, For the first Is the data center configured on a terrestrial node? Decision variables at the location, For the first Is the data center configured on an underwater node? Decision variables at the location, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For operating mode Below, time period internal nodes The power of the energy storage system, For the first Data centers during the time period Internal cooling requirements, The underwater cooling coefficient for data centers. , Operating modes Below, time period Internal renewable energy nodes The output of photovoltaic power plants and wind power plants, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, , Renewable energy nodes The photovoltaic and wind power capacity configured there, , Renewable energy nodes The local light endowment coefficient and wind endowment coefficient, , Operating modes Below, time period Internal renewable energy nodes Based on the output characteristics of photovoltaic and wind power, The installed capacity of a single energy storage system, For nodes The number of energy storage systems configured at the location This represents the percentage change in the maximum electricity volume of the energy storage system in a single hour. For time period internal nodes The power of the energy storage system, , These are the lower and upper limits of the energy state of the energy storage system, respectively. This represents the initial power of a single energy storage system. For a unit of time, As an auxiliary variable, The last period of the day. The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. For a unit of time, Operating mode within one year The number of consecutive days, This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of the green certificate reached [a certain level]? The step coefficient of the stage, Has the price of the green certificate reached [a certain level]? The step coefficient of the stage.

6. A power grid supply system that considers the differentiated needs of data centers under extreme weather conditions, characterized in that: The system includes a model building module and a model solving module; The model building module is used to construct a power supply optimization model for data center clusters with the goal of minimizing the overall power supply cost of data center clusters. The model considers the differentiated needs of data centers and the impact of extreme weather on the microgrid system. It adopts a combined land and underwater configuration for data centers. The cluster microgrid is a green power supply network that combines power supply from the upper-level power grid with direct power supply from new energy power plants. The model solving module is used to solve the power supply optimization model of the data center cluster, and obtain the configuration scheme of the data center and the new energy power station, as well as the power supply strategy of the power grid under the differentiated needs.

7. The power grid supply system considering the differentiated needs of data centers under extreme weather conditions according to claim 6, characterized in that, The model building module includes an objective function building unit; The objective function construction unit is used to construct the objective function of the following data center cluster power supply optimization model: ； ； ； ； ； ； In the above formula, For the cost of power supply lines, For energy storage configuration costs, For the discount rate, For the investment period, Cost of supplying electricity to the upper-level power grid Cost of power supply for local renewable energy plants. The cost of purchasing green certificates for data center cluster micronets For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes The length of the power supply channel For nodes With nodes The unit price of power supply lines in inter-channel power supply. For nodes The number of energy storage systems configured at the location The configuration price is for a single energy storage system. This is a typical operating mode for data center cluster micronets, and can be adopted. , , These represent the normal operating mode, the high-temperature weather operating mode, and the low-light weather operating mode, respectively. For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, Operating mode within one year The number of consecutive days, For a unit of time, For time period The price of electricity supplied by the upstream power grid. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, The price of direct power supply for new energy power plants. This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of the green certificate reached [a certain level]? The step coefficient of the stage, for The price of green certificates at different stages, The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. for The price of green certificates at each stage.

8. The power grid supply system considering the differentiated needs of data centers under extreme weather conditions according to claim 6, characterized in that, The model building module also includes a data center differentiated demand constraint building unit; The data center differentiated demand constraint construction unit is used to construct the following data center differentiated demand constraints: ； ； ； ； ； ； ； ； ； ； ； ； ； ； In the above formula, For the first The number of modules in each data center For the first Is the data center configured on a terrestrial node? Decision variables at the location, The floor area of ​​a single data center module. For nodes The number of energy storage systems configured at the location The floor area of ​​a single energy storage system. , They are nodes The photovoltaic and wind power capacity configured there, , These refer to the land area occupied per unit capacity of photovoltaic and wind power, respectively. For nodes Available construction area at the location For the first Is the data center configured on an underwater node? Decision variables at the location, For nodes With upstream power node Interconnection variables, For nodes With renewable energy nodes Interconnection variables, For nodes With nodes The number of power supply lines configured in the power supply channel. For nodes With nodes Interconnection variables, This refers to the maximum number of power supply lines that a single line corridor can accommodate. For the large M constant, This represents the maximum number of energy storage systems that can be configured. For nodes The location variables of a photovoltaic power plant For nodes The location variables of a wind farm This represents the upper limit for the number of new energy power plants in a microgrid. This represents the total capacity of new energy sources within the microgrid. For nodes With nodes The length of the power supply channel For maximum power supply distance, For nodes Distance to the nearest water source This represents the maximum permissible distance between the data center and the water source.

9. The power grid supply system considering the differentiated needs of data centers under extreme weather conditions according to claim 6, characterized in that, The model building module also includes line load rate constraint building units under different operating modes; The line load rate constraint construction unit under different operating modes is used to construct line load rate constraints under the following different operating modes: ； ； ； ； ； ； ； ； ； In the above formula, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For nodes With upstream power grid nodes The number of power supply lines configured in the power supply channel. For the capacity of a single line, This represents the maximum load rate of the line under normal operating conditions. For operating mode Below, time period internal nodes With upstream power grid nodes The load status of the inter-line, For the large M constant, This represents the maximum load rate of the line under heavy load conditions. This is the normal operating mode. This is an extreme weather operation mode, including a high-temperature weather operation mode and a low-sunlight weather operation mode. This refers to the maximum time during which the line can operate under heavy load within a day. For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For nodes With new energy plant nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period internal nodes With new energy plant nodes The load status of the inter-line, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, For the upper-level power grid node With renewable energy nodes The number of power supply lines configured in the power supply channel. For operating mode Below, time period Inner upper-level power grid node With new energy plant nodes The load status of the inter-line.

10. The power grid supply system considering the differentiated needs of data centers under extreme weather conditions according to claim 6, characterized in that, The model building module also includes a data center cluster microgrid operation constraint building unit; The data center cluster micronet operation constraint construction unit is used to construct the following data center cluster micronet operation constraints: ； ； ； ； ； ； ； ； ； In the above formula, For the first Data centers during the time period Internal operating power, For the first Data centers during the time period Internal cooling power, For the first Is the data center configured on a terrestrial node? Decision variables at the location, For the first Is the data center configured on an underwater node? Decision variables at the location, For operating mode Below, time period internal nodes With upstream power grid nodes Electrical power interaction, For operating mode Below, time period internal nodes With new energy plant nodes Electrical power interaction, For operating mode Below, time period internal nodes The power of the energy storage system, For the first Data centers during the time period Internal cooling requirements, The underwater cooling coefficient for data centers. , Operating modes Below, time period Internal renewable energy nodes The output of photovoltaic power plants and wind power plants, For operating mode Below, time period Inner upper-level power grid node With renewable energy nodes Electrical power interaction, , Renewable energy nodes The photovoltaic and wind power capacity configured there, , Renewable energy nodes The local light endowment coefficient and wind endowment coefficient, , Operating modes Below, time period Internal renewable energy nodes Based on the output characteristics of photovoltaic and wind power, The installed capacity of a single energy storage system, For nodes The number of energy storage systems configured at the location This represents the percentage change in the maximum electricity volume of the energy storage system in a single hour. For time period internal nodes The power of the energy storage system, , These are the lower and upper limits of the energy state of the energy storage system, respectively. This represents the initial power of a single energy storage system. For a unit of time, As an auxiliary variable, The last period of the day. The total amount of electricity purchased from the upper-level power grid for the data center cluster microgrid. For a unit of time, Operating mode within one year The number of consecutive days, This refers to the electricity volume covered by the tiered pricing system for single-stage green certificates. Has the price of the green certificate reached [a certain level]? The step coefficient of the stage, Has the price of the green certificate reached [a certain level]? The step coefficient of the stage.

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