Fusion internet data center adjustable load participation emergency scheduling method and related device

Abstract

The invention belongs to a scheduling method, and provides a method for participating in emergency scheduling by fusing an adjustable load of an interconnected data center and a related device, aiming at the technical problems that an internet data center load assists a power system to carry out voltage regulation research and a power network and an information network are separated from each other. In combination with the voltage out-of-limit condition of any node in the power distribution network and the dynamic sensitivity of the voltage of the node and the injection active power of other associated nodes, the power regulation amount of the node and the associated nodes participating in the voltage regulation of the node is calculated as a power regulation amount instruction, and then the voltage regulation amount of the node is calculated according to the power regulation amount instruction. And carrying out power regulation on each node, so that the power regulation cost is minimum when the power regulation is carried out on each node. Deep coupling of a power network and an information network can be effectively realized to support the two-network integration emergency scheduling service demand, and the flexibility of a voltage out-of-limit problem solution is effectively improved.

Description

Technical Field

[0001] The present application relates to a scheduling method, and more specifically to a method and related apparatus for emergency scheduling of adjustable loads in a converged interconnected data center. Background Art

[0002] Data centers, as the infrastructure for the current digital transformation of society and the economy, are becoming increasingly important loads and energy consumers in the power system due to their computing tasks, which are information system loads that consume electricity. Furthermore, with the increasing penetration of renewable energy, the power system is shifting from a traditional source-load-driven system to a new source-load-interactive system. This is manifesting a new trend of load-to-resource shift in a broad sense, necessitating the unleashing of flexibility in all aspects of the system.

[0003] In recent years, Internet Data Centers (IDCs) have been successfully applied to various power system problems, such as energy management, capacity allocation, demand response, and optimal scheduling. However, there is currently no research on using IDC loads to assist in voltage regulation in power systems. Furthermore, the IDC information load scheduling process fails to consider power conditions, and the IDC information load is also not considered in the power network energy scheduling process, resulting in a disconnect between the power grid and the information network. Summary of the Invention

[0004] The purpose of this application is to solve the different problems currently encountered in the application of Internet data centers in the field of power systems, namely, the lack of research on voltage regulation of Internet data center load-assisted power systems, and the technical problem of mutual separation between the power grid and the information network, and to provide a method and related devices for the participation of adjustable loads in emergency dispatching of integrated interconnected data centers.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions: In a first aspect, the present application proposes a method for converged interconnected data centers to participate in emergency dispatching with adjustable loads, including: Based on the voltage over-limit situation of any node in the distribution network and the dynamic sensitivity of the node's voltage to the active power injected by other associated nodes, the power regulation amount of the node and its associated nodes participating in the voltage regulation of the node is calculated as the power regulation amount instruction; According to the power regulation amount instruction, an emergency joint scheduling strategy for the data center load and the distributed power generation aggregate power is formulated, and the power of each node is adjusted according to the emergency joint scheduling strategy to minimize the power regulation cost when each node performs power regulation.

[0006] Furthermore, before power regulation is performed on each node, a power regulation instruction is sent to the controllers of the distributed power generation aggregation unit, energy storage equipment and Internet data center load connected to the node where the voltage exceeds the limit.

[0007] Furthermore, when the power regulation amount instruction is sent to the controller of the distributed power generation aggregation unit, energy storage device and Internet data center load connected to the node where the voltage exceeds the limit, the optimized sending method includes: A communication path scheduling model is constructed with the optimization goal of minimizing the communication path delay of power regulation instructions and the constraints of the path transmission delay and path reliability of a single emergency dispatch service between nodes. The input of the communication path scheduling model is the number of nodes and the set of emergency dispatch services, and the output is the routing path, path reliability, and shortest path list for each emergency dispatch service. pass Dijkstra The routing algorithm solves the communication path scheduling model and obtains the optimal routing path.

[0008] Furthermore, the communication path scheduling model includes:

[0009] The constraints of the communication path scheduling model include:

[0010]

[0011] in, It is a power line carrier communication path scheduling function driven by real-time reliability requirements. is the transmission delay of a single service path, is the maximum path transmission delay for emergency dispatch services, Reliability requirements for emergency dispatch.

[0012] Furthermore, the method for calculating the dynamic sensitivity of the voltage of the node to the active power injected into other associated nodes includes:

[0013] in, for Moment Active power regulation of each node The dynamic sensitivity of the voltage at each node, for Moment k The real part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, for Moment k The imaginary part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, for Moment The real part of the voltage at each node, , for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, , for Moment k The proportionality coefficient of the voltage of each node to the rated voltage, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, For the k Node and The line impedance between nodes, for Moment The voltage of each node, for Moment Node and The circuit impedance between nodes, for Moment The imaginary part of the voltage at each node, for Moment The reactive power regulation of each node is The dynamic sensitivity of the real part of the voltage at each node, for Moment The voltage of each node, for Moment Active power of each node.

[0014] Furthermore, the method for calculating the power regulation amount of the node and its associated nodes participating in voltage regulation of the node includes:

[0015]

[0016] in, for Moment k The node and all its associated nodes participate in the k The power regulation amount of voltage regulation of each node, For the k The rated voltage of each node, for Moment k The power regulation amount of each node, For the j Nodes participate in k The power regulation amount of voltage regulation of each node, for Moment j The minimum value of the adjustable active power of a node, for Moment j The maximum value of the adjustable active power of the node, is the number of associated nodes that can perform active power regulation, for Moment j The adjustable active power of each node, For the k The associated node set of a node, for Moment k Active power regulation of each node The dynamic sensitivity of the voltage at each node.

[0017] Furthermore, the emergency joint dispatch method includes: According to the power regulation instructions corresponding to each node, the corresponding power regulation minimum cost objective function is constructed; An improved particle swarm optimization algorithm is used to solve the minimum cost objective function of power regulation, and an emergency joint scheduling strategy for data center load and distributed power generation aggregated power driven by voltage overlimit is obtained.

[0018] Furthermore, the power regulation minimum cost objective function includes:

[0019] in, is the minimum cost function for the node to respond to the voltage command, for The power regulation cost of DG can be controlled at all times. for The power regulation cost of energy storage at all times, for The compensation cost for the load shedding of IDC at the moment, for The adjustment compensation cost of IDC adjustable load at the moment, NR is the number of DG aggregations, is the sequence number of the DG aggregation, I is the amount of load that can be removed by IDC, is the serial number of the IDC removable load, J is the number of IDC adjustable loads, It is the serial number of the IDC adjustable load; The constraints of the power regulation minimum cost objective function include:

[0020] in, for The regulated power of DG at the moment, for The IDC can cut off the active power of the load at any time. is the control variable of the IDC adjustable load, is the active power of the IDC adjustable load, is the charge and discharge efficiency of the energy storage unit, for The power of energy storage at all times, is the cuttable rate of IDC cuttable load.

[0021] In a second aspect, the present application proposes a converged interconnected data center load-adjustable emergency dispatch system, comprising: An instruction calculation module is used to calculate the power regulation amount of the node and its associated nodes participating in the voltage regulation of the node, as a power regulation amount instruction, based on the voltage exceeding the limit of any node in the distribution network and the dynamic sensitivity of the node's voltage to the active power injected by other associated nodes; The regulation module is used to formulate an emergency joint scheduling strategy for the data center load and the aggregated power generation power of the distributed power supply according to the power regulation amount instruction, and to adjust the power of each node according to the emergency joint scheduling strategy to minimize the power regulation cost when each node performs power regulation.

[0022] Furthermore, before power regulation is performed on each node, a power regulation instruction is sent to the controllers of the distributed power generation aggregation unit, energy storage equipment and Internet data center load connected to the node where the voltage exceeds the limit.

[0023] Furthermore, when the power regulation amount instruction is sent to the controller of the distributed power generation aggregation unit, energy storage device and Internet data center load connected to the node where the voltage exceeds the limit, the optimized sending method includes: A communication path scheduling model is constructed with the optimization goal of minimizing the communication path delay of power regulation instructions and the constraints of the path transmission delay and path reliability of a single emergency dispatch service between nodes. The input of the communication path scheduling model is the number of nodes and the set of emergency dispatch services, and the output is the routing path, path reliability, and shortest path list for each emergency dispatch service. pass Dijkstra The routing algorithm solves the communication path scheduling model and obtains the optimal routing path.

[0024] Furthermore, the communication path scheduling model includes:

[0025] The constraints of the communication path scheduling model include:

[0026]

[0027] in, It is a power line carrier communication path scheduling function driven by real-time reliability requirements. is the transmission delay of a single service path, is the maximum path transmission delay for emergency dispatch services, Reliability requirements for emergency dispatch.

[0028] Furthermore, the method for calculating the dynamic sensitivity of the voltage of the node to the active power injected into other associated nodes includes:

[0029] in, for Moment Active power regulation of each node The dynamic sensitivity of the voltage at each node, for Moment k The real part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, for Moment k The imaginary part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, for Moment The real part of the voltage at each node, , for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, , for Moment k The proportionality coefficient of the voltage of each node to the rated voltage, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, For the k Node and The line impedance between nodes, for Moment The voltage of each node, for Moment Node and The circuit impedance between nodes, for Moment The imaginary part of the voltage at each node, for Moment The reactive power regulation of each node is The dynamic sensitivity of the real part of the voltage at each node, for Moment The voltage of each node, for Moment Active power of each node.

[0030] Furthermore, the method for calculating the power regulation amount of the node and its associated nodes participating in voltage regulation of the node includes:

[0031]

[0032] in, for Moment kThe node and all its associated nodes participate in the k The power regulation amount of voltage regulation of each node, For the k The rated voltage of each node, for Moment k The power regulation amount of each node, For the j Nodes participate in k The power regulation amount of voltage regulation of each node, for Moment j The minimum value of the adjustable active power of a node, for Moment j The maximum value of the adjustable active power of the node, is the number of associated nodes that can perform active power regulation, for Moment j The adjustable active power of each node, For the k The associated node set of a node, for Moment k Active power regulation of each node The dynamic sensitivity of the voltage at each node.

[0033] Furthermore, the emergency joint dispatch strategy includes: According to the power regulation instructions corresponding to each node, the corresponding power regulation minimum cost objective function is constructed; An improved particle swarm optimization algorithm is used to solve the minimum cost objective function of power regulation, and an emergency joint scheduling strategy for data center load and distributed power generation aggregated power driven by voltage overlimit is obtained.

[0034] Furthermore, the power regulation minimum cost objective function includes:

[0035] in, is the minimum cost function for the node to respond to the voltage command, for The power regulation cost of DG can be controlled at all times. for The power regulation cost of energy storage at all times, for The compensation cost for the load shedding of IDC at the moment, for The adjustment compensation cost of IDC adjustable load at the moment, NR is the number of DG aggregations, is the sequence number of the DG aggregation, I is the amount of load that can be removed by IDC, is the serial number of the IDC removable load, J is the number of IDC adjustable loads, It is the serial number of the IDC adjustable load; The constraints of the power regulation minimum cost objective function include:

[0036] in, for The regulated power of DG at the moment, for The IDC can cut off the active power of the load at any time. is the control variable of the IDC adjustable load, is the active power of the IDC adjustable load, is the charge and discharge efficiency of the energy storage unit, for The power of energy storage at all times, is the cuttable rate of IDC cuttable load.

[0037] In a third aspect, the present application proposes an electronic device comprising: a memory, one or more processors; the memory is coupled to the processor; wherein the memory stores computer program code, the computer program code comprises computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the steps of the above-mentioned method for the converged interconnected data center to participate in emergency dispatching of adjustable loads.

[0038] In a fourth aspect, the present application proposes a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for the participation of adjustable loads in emergency scheduling of converged interconnected data centers are implemented.

[0039] Compared with the prior art, this application has the following beneficial effects: The present application proposes a method for integrating the adjustable load of an interconnected data center to participate in emergency dispatching. Combining the voltage over-limit situation of any node in the distribution network and the dynamic sensitivity of the voltage of the node to the active power injected by other associated nodes, the power regulation amount of the node and its associated nodes participating in the voltage regulation of the node is calculated as the power regulation amount instruction. Then, according to the power regulation amount instruction, power regulation is performed on each node to minimize the power regulation cost when each node performs power regulation. The present application proposes a "power grid-information network" integrated emergency dispatching method that takes into account the adjustable load of the data center. It can effectively realize the deep coupling of the power grid and the information network to support the emergency dispatching business needs of the integration of the two networks. In response to the voltage over-limit problem caused by the large-scale grid connection of distributed energy, based on the voltage-active power sensitivity, the most effective recovery of the over-limit voltage of each node is achieved through the active power regulation of each node, so that the information load of the data center can participate in the emergency dispatching process of the power system, effectively improving the flexibility of the solution to the voltage over-limit problem.

[0040] This application also proposes a converged interconnected data center adjustable load participating emergency dispatch system, an electronic device and a computer storage medium, which have all the advantages of the above-mentioned converged emergency dispatch method. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 This is a schematic diagram of the first flow chart of the method for integrating the adjustable load of the interconnected data center to participate in emergency dispatching in this application; Figure 2 A schematic diagram of an emergency dispatch framework integrating power grid and information network in an embodiment of the present application; Figure 3 This is a second flow chart of the method for integrating the adjustable load of the interconnected data center to participate in emergency dispatching in this application; Figure 4 A voltage diagram of a bus node of a power network before voltage regulation in an embodiment of the present application; Figure 5 A voltage diagram of a bus node of a power network after voltage regulation in an embodiment of the present application; Figure 6 This is a diagram showing the final voltage over-limit control effect when only the DG aggregate power generation regulation capability is considered to regulate the over-limit voltage in the embodiment of this application; Figure 7This is a PLC communication transmission topology diagram on the low-voltage distribution network side in the embodiment of this application; Figure 8 This is a comparison result diagram of emergency dispatch costs under the "power grid-information network" integrated emergency dispatch strategy method taking into account the adjustable load of the data center provided in the embodiment of the present application; Figure 9 This is a cost comparison diagram of power regulation by IDC loads and DG aggregation before and after emergency joint dispatch in the embodiment of the present application, under the premise of ensuring that the voltage of all bus nodes in the power network is regulated within a safe range; Figure 10 This is a schematic diagram of the application of the integrated interconnected data center adjustable load participating in the emergency dispatch system. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0044] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0045] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0046] In the description of the embodiments of the present application, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the accompanying drawings, or the orientation or position relationship in which the product of the invention is usually placed when in use. This is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, it should not be understood as a limitation on the present application. In addition, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0047] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0048] In the description of the embodiments of this application, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art can understand the specific meanings of the above terms in this application based on specific circumstances.

[0049] Driven by policies such as new infrastructure, digital transformation, and the Digital China vision, the data center market, with telecom operators as a prime example, has shown sustained and rapid growth. Data centers, as essential infrastructure for the digital transformation of our society and economy, are increasingly becoming critical loads and a major source of energy consumption in the power system due to their computing tasks, which consume electricity as information system loads. Furthermore, with the increasing penetration of renewable energy in the power system, the power system is undergoing a profound transformation from the traditional "source follows load" model to a new "source-load interaction" model. This transformation is manifesting in a new trend of shifting loads to resources in the power system, making it increasingly urgent to unlock flexibility in all links. Unlike traditional power loads, data center loads possess dual flexibility in both time and space. Leveraging this unique advantage, data center loads can serve as a vastly adjustable resource, participating in the optimized scheduling of new power systems. This initiative not only provides strong support for enhancing grid scheduling flexibility but also represents a key approach to reducing the high energy consumption of data centers.

[0050] In recent years, Internet Data Centers (IDCs) have demonstrated significant application value in power systems, successfully penetrating multiple core processes, including energy management, capacity allocation, demand response, and optimized scheduling, providing strong support for improving grid efficiency and flexibility. However, current research still faces two key gaps: First, in the critical grid control area of ​​voltage regulation, the potential of IDCs as auxiliary load regulators has not been fully explored, failing to integrate their rapid response characteristics with voltage stability requirements. Second, existing research lacks a coordinating mechanism between information load scheduling and energy scheduling. Specifically, the information load scheduling process fails to fully consider the actual operational constraints of the power grid, such as line capacity and generation costs, while energy scheduling strategies fail to incorporate the information processing requirements of IDCs, such as computing task migration and data storage distribution, into optimization models. This results in the formation of independently operating "information islands" between the power grid and the information network. This bidirectional disconnect not only limits the comprehensive effectiveness of IDCs in the power grid but also hinders the development of new power systems in the context of deep power-information integration.

[0051] Based on the above situation, the present application proposes a method and related devices for emergency dispatching of adjustable loads in converged interconnected data centers. The present application is described in detail below with reference to embodiments and drawings.

[0052] like Figure 1 As shown, this is a first flow chart of the method for the converged interconnected data center to participate in emergency dispatching with adjustable loads, which may include: S101, combining the voltage over-limit situation of any node in the distribution network and the dynamic sensitivity of the voltage of the node to the active power injected by other associated nodes, calculate the power adjustment amount of the node and its associated nodes participating in the voltage regulation of the node as a power adjustment amount instruction.

[0053] This application breaks through the limitation of traditional voltage regulation that only focuses on the voltage amplitude of a single node. By constructing a dynamic sensitivity matrix of node voltage and active power injected by associated nodes, the power-voltage coupling relationship between each node is quantified. For example, when a node's voltage exceeds the limit, not only the reactive compensation equipment adjustment of the node is considered, but also the set of associated nodes that have the most significant impact on the node voltage is identified through sensitivity analysis, such as adjacent distributed power access points or Internet data center power supply buses. Based on the weighted allocation of adjustment tasks based on the sensitivity coefficient, the power adjustment amount instruction can satisfy the voltage recovery constraint while avoiding power backflow or equipment overload caused by over-regulation.

[0054] S102, based on the power regulation amount instruction, formulate an emergency joint scheduling strategy for the data center load and the aggregated power generation power of the distributed power supply, and perform power regulation on each node according to the emergency joint scheduling strategy to minimize the power regulation cost when each node performs power regulation.

[0055] This application addresses the disconnect between the power grid and the information network in traditional scheduling by innovatively proposing a two-tiered scheduling architecture. At the physical layer, the output characteristics of distributed power sources (such as photovoltaics and energy storage) are aggregated with adjustable resources such as IT loads and cooling systems in internet data centers (IDCs) to form a virtual power plant unit. At the information layer, edge computing provides real-time perception of the voltage status of each node and pre-reserves regulation capacity based on a predictive model. For example, before a voltage overshoot occurs, the computing task distribution of the IDC server cluster can be pre-adjusted, migrating non-real-time tasks to nodes with sufficient voltage margin. Simultaneously, the energy storage system's charging and discharging strategy can be adjusted to achieve spatiotemporal decoupling of power regulation. When regulating power at each node, the optimal regulation strategy can be determined by constructing a multi-objective function that incorporates network loss costs, equipment loss costs, and penalty costs for internet data center service interruptions. For example, during voltage regulation, resources with low regulation costs (such as adjusting the power factor of IDC servers) are prioritized. When regulation margin is insufficient, higher-cost measures (such as starting diesel generators) are gradually activated. At the same time, considering the delay sensitivity of Internet data center loads, dynamic priority queue management is used to ensure power regulation while ensuring the continuity of critical services.

[0056] This application builds a "power grid-information network" integrated emergency dispatch framework taking into account the adjustable load of the data center. Figure 2, which is a schematic diagram of the power grid-information network integrated emergency dispatch framework in an embodiment of the present application. In the event of voltage over-limit in the distribution network, the emergency power support strategy of the present application is used to obtain the power adjustment amount required for each node to be restored to the normal voltage range at the over-limit voltage node. At the same time, the data center adjustable power and distributed power aggregate power generation combined with the communication transmission path scheduling method driven by the joint emergency dispatch service demand of the present application are combined to obtain the optimal communication transmission path that meets the real-time and reliability requirements of the emergency dispatch service. The dispatch control center uses the required power adjustment amount information as a power adjustment amount instruction and sends it to the central coordinator (CCO) via the wide area network. The CCO further sends the instruction to the agent coordinator, station (STA), and data acquisition devices such as electric meters connected to each node of the power grid through the local communication network in a PLC (Power Line Carrier) communication manner. The power adjustment amount instruction is sent to the controllers of each DG (Distributed Generation) aggregation unit, energy storage device, and IDC (Internet Data Center) load connected to the node in the power grid according to the optimal communication transmission path selected by the information network. These controllers will adjust their respective outputs based on the power regulation amount instructions and the joint scheduling method of this application with the goal of minimizing regulation costs, thereby quickly regulating the voltage back to a safe range.

[0057] In this application, the information network part mainly considers the local communication network. In this embodiment, the integrated emergency dispatch strategy framework includes two parts: the information network and the power grid. Among them, the information network CCO is the center. The CCO transmits and interacts data with the distribution communication master station through the remote communication network. The distribution communication master station is the distribution master station layer in the dispatching control center that is responsible for communicating with the power grid and is integrated in the dispatching control center. Data exchange between each node in the network (each node in the power grid) and the fusion terminal (referring to the data acquisition equipment such as the electric meter connected to the node in the power grid, the connecting line is the green dotted line part in the figure) is realized through PLC communication. The power grid supplies power to the IDC load of the information network, and according to the IDC adjustable capacity and loss information provided by the information network, combined with the DG aggregated power generation power, the two-network fusion emergency dispatch is realized. Figure 3 As shown, it is a second flow chart of the method for the converged interconnected data center to participate in emergency dispatching of adjustable loads in this application, which may include: S201, formulate an emergency power support strategy when the power grid voltage exceeds the limit, and achieve the most effective recovery of the over-limit voltage at each node by adjusting the active power of each node.

[0058] In this embodiment, this can be achieved by the following steps: (1), node voltage-active power dynamic sensitivity algorithm.

[0059] According to the dynamic power flow of the power grid, the voltage-active power sensitivity relationship is determined as follows: (1) in, represents the dynamic sensitivity matrix, represents the node active power matrix of the power grid, represents the node voltage matrix of the power grid, to Represents the 1st to the The active power of each node, to Represents the 1st to the The voltage value of a node.

[0060] Similarly, according to the voltage-active power sensitivity relationship, calculate the h Active power regulation of each node k Dynamic sensitivity of the voltage of a node: (2) in, for Moment Active power regulation of each node The dynamic sensitivity of the voltage at each node, for Moment k The real part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, for Moment k The imaginary part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, for Moment The real part of the voltage at each node, , for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, , for Moment k The proportionality coefficient of the voltage of each node to the rated voltage, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, For the k Node and The line impedance between nodes, for Moment The voltage of each node, for Moment Node and The circuit impedance between nodes, for Moment The imaginary part of the voltage at each node, for Moment The reactive power regulation of each node is The dynamic sensitivity of the real part of the voltage at each node, for Moment The voltage of each node, for Moment Active power of each node.

[0061] (2) Power regulation distribution.

[0062] According to k The voltage limit of each node, and the k The voltage of the node is dynamically sensitive to the active power injected by all associated nodes. k The node and all its associated nodes participate in the k The power regulation amount of voltage regulation of each node: (3) (4) in, for Moment k The node and all its associated nodes participate in the k The power regulation amount of voltage regulation of each node, For the k The rated voltage of each node, for Moment k The voltage of each node, for Moment k The power regulation amount of each node, For the j Nodes participate in k The power regulation amount of voltage regulation of each node, For the j The minimum value of the adjustable active power of a node, For the j The maximum value of the adjustable active power of the node, is the number of associated nodes that can perform active power regulation, For the j The adjustable active power of each node.

[0063] In the emergency power support strategy, To adjust the target, It is an emergency power support strategy and serves as a power adjustment instruction issued by the dispatching control center.

[0064] S202, formulate an emergency joint dispatch strategy for data center load and distributed power generation aggregated power under voltage over-limit driving, aiming to meet the emergency power support needs of each node under voltage over-limit with the minimum power regulation cost.

[0065] In this embodiment, this can be achieved specifically through the following methods: (1) Establishment of emergency joint dispatch model.

[0066] In order to respond to the emergency power support strategy of each node under voltage over-limit, this application performs joint emergency power dispatch on the DG aggregated power generation power and IDC adjustable load connected to each node at the minimum power regulation cost. k The emergency joint dispatch strategy is studied by taking a node as an example. It is assumed that the node is connected with a distributed generation aggregation unit, energy storage equipment and a switchable and adjustable IDC adjustable load.

[0067] According to k The power regulation of the voltage regulation of each node , the objective function of power regulation minimum cost is constructed as: (5) The constraints of the objective function of formula (5) are: (6) in, is the minimum cost function for the node to respond to the voltage command, for The power regulation cost of DG can be controlled at all times. for The power regulation cost of energy storage at all times, for The compensation cost for the load shedding of IDC at the moment, for The adjustment compensation cost of IDC adjustable load at the moment, NR is the number of DG aggregations, is the sequence number of the DG aggregation, I is the amount of load that can be removed by IDC, is the serial number of the IDC removable load, J is the number of IDC adjustable loads, It is the serial number of the IDC adjustable load. for The regulated power of DG at the moment, for The IDC can cut off the active power of the load at any time. is the control variable of the IDC adjustable load, is the active power of the IDC adjustable load, is the charge and discharge efficiency of the energy storage unit, for The power of energy storage at all times, is the cuttable rate of IDC cuttable load.

[0068] The specific calculation methods or constraints for the above parameters include: Power regulation cost of controllable DG The constraints are: (7) in, 、 and All are coefficients.

[0069] DG regulation power The constraints are: (8) The operating ramp rate constraint is: (9) in, For DG Power changes within.

[0070] Power regulation costs of energy storage The constraints are: (10) Energy storage charging and discharging power The constraints are: (11) Energy storage charge capacity The constraints are: (12) in, is the adjustment cost coefficient of energy storage.

[0071] In information networks, IDC workloads can be divided into two categories: online and offline loads, based on task priority and response time characteristics. Online loads, given their high-priority processing requirements and stringent requirements for computing reliability and real-time performance, can be considered uncontrollable critical loads in the power grid, and their power demands must be met first to ensure system stability. In contrast, offline loads exhibit lower priority and latency sensitivity, allowing their processing to be reasonably decomposed into multiple subtasks and executed step by step according to a preset logical sequence. For loads with earlier subtasks, their power consumption has a certain elasticity at a given moment due to their shorter delays, allowing for flexible adjustment based on system needs, thus being defined as adjustable loads. For loads with later subtasks, their power consumption can be considered non-critical during specific periods due to their longer delay tolerance. If necessary, they can be quickly reduced or completely removed to meet the system's emergency dispatch needs. These loads are classified as interruptible or shelvable loads in the power grid. Therefore, the power regulation cost of IDC loads can be specifically defined as: (13) (14) in, For shear load i Removal compensation costs, For shear load i The scheduling cost coefficient, is the grid electricity price, For shear load i Rated power, is the power regulation cost of the adjustable load, is the control variable of IDC adjustable load.

[0072] The constraints for IDC load power regulation can be defined as: (15) (16) Wherein, formula (15) is the power regulation constraint of the shelved load, and are the minimum and maximum cuttable rates of the cuttable load, respectively. Formula (15) is the operating constraint of the adjustable load. For the The total operating time of an IDC adjustable load, For the The starting operation time of an IDC adjustable load, For the The end time of the IDC adjustable load. The adjustable load can only run within the given time window and cannot be stopped before the task is completed.

[0073] (2) Solution of the emergency joint dispatch model: According to the predicted power demand of DG aggregated power generation, IDC key load and switchable and adjustable load, the improved particle swarm optimization algorithm is used to obtain the emergency joint dispatch strategy of IDC load and DG aggregation under voltage over-limit driving.

[0074] The specific steps of the improved particle swarm optimization algorithm may include: (1) Problem definition: The problem is to build an emergency joint dispatch model for IDC load and DG aggregated power generation under voltage over-limit driving.

[0075] (2) Define the fitness function: Incorporate the constraints into the definition of the fitness function. The fitness function considers the value of the objective function and the degree of constraint violation. A penalty function or penalty factor method can be used to penalize solutions that violate the constraints, so that the fitness function can quantify the quality of the solution and the degree of constraint violation.

[0076] (3) Initialize the particle swarm: As with the traditional particle swarm optimization algorithm, a group of particles is randomly generated, and each particle includes position and velocity attributes.

[0077] (4) Calculate the fitness value: Calculate the fitness value of each particle based on the objective function and constraints.

[0078] (5) Update the best individual position and best group position of the particle: According to the fitness value, update the historical best position and global best position of each particle.

[0079] (6) Update the speed and position of particles: As with the traditional particle swarm optimization algorithm, the speed and position of particles are adjusted according to the speed and position update formula.

[0080] It can be updated according to the following formula: (17) (18) in, is the particle velocity, is a random number between (0,1), is the current position of the particle, and are learning factors, The maximum value of (greater than 0), if ,but . For the The optimal position of the individual in the population searched by particles, The optimal position of the particles to search for in the population.

[0081] (7) Constraint processing: After updating the particle position, constraint processing is performed to ensure that the solution satisfies the constraints. Correction operators or projection operators can be used to adjust solutions that exceed the constraint range back to the legal range.

[0082] (8) Check the stopping condition: Determine whether the stopping condition is met. If so, the algorithm ends and returns the global best position as the optimal solution; otherwise, continue iterating.

[0083] In this embodiment, the improved particle swarm algorithm can be written and tested by MATLAB. In order to verify the effectiveness of the proposed emergency joint dispatch strategy for data center load and distributed power generation under voltage over-limit driving on voltage over-limit regulation, as shown in the following example: Figure 4 As shown in the figure, it is the voltage diagram of the bus node of the power network before voltage regulation, as shown in the figure. Figure 5 The figure shows the voltage diagram of the busbar node of the power network after voltage regulation. It should be noted that Figure 4 and Figure 5 In the figure, lines of different colors represent different nodes.

[0084] In order to verify the necessity of introducing data center load, the same emergency dispatch strategy is adopted, and only the DG aggregate power generation regulation capability is considered to regulate the over-limit voltage, such as Figure 6 As shown in Figure 1, the final voltage over-limit control effect diagram is obtained by adjusting the over-limit voltage by only considering the DG aggregate power generation regulation capability. Figures 4 to 6 The comparison results show that by introducing IDC adjustable loads to achieve emergency joint dispatch, the voltage of most bus nodes in the power network with serious voltage over-limit can be adjusted to the safe range [0.95, 1.05] pu. At the same time, the flexibility of IDC information load is fully utilized, that is, the over-limit voltage can still be effectively adjusted when the DG aggregate power generation regulation capacity is insufficient, thus verifying the effectiveness of the "power grid-information network" integrated emergency dispatch for voltage over-limit regulation.

[0085] S203, constructing a communication transmission path scheduling method driven by joint emergency dispatch service needs to meet the real-time and reliability requirements of power regulation instructions under voltage over-limit conditions on communication transmission.

[0086] (1) Reliability analysis and calculation of power line carrier communication.

[0087] (1.1) Reliability analysis of power line carrier communication.

[0088] like Figure 7 The figure shows the PLC communication transmission topology diagram on the low voltage distribution network side. Figure 7 The real-time and reliability analysis of the PLC communication transmission topology on the low-voltage distribution network side is shown in the figure. Node 1 in the figure corresponds to the dispatch center, while the IDC load and DG aggregate power generation controller correspond to nodes 5, 7, 12, and 15 in the communication topology, respectively. Based on this, a communication transmission path scheduling strategy driven by joint emergency dispatch business needs is proposed to determine the optimal communication transmission path to ensure the real-time and reliability requirements of power grid dispatch.

[0089] Comprehensively consider the impact of the three characteristic parameters of the power line channel, "attenuation, impedance, and noise", on the reliability of the PLC link.

[0090] The impact of channel attenuation on link reliability is as follows: PLC channel fading It conforms to the lognormal distribution, and its probability density function is: (19) in, For, parameter and They are normal random variables If the unit energy of the channel gain is 1, then .

[0091] The impact of channel "impedance" on link reliability is as follows: Assume that the path loss per unit distance of the power line is ,node i With transmission power To Node j Transmit signal, then the receiving node j Signal power for: (20) in, is a node i With node j The path distance between them. The possible value range after actual measurement is usually 10-100 dB / km.

[0092] The impact of channel "noise" on link reliability is as follows: Assume PLC noise is background noise and impulse noise The mixture obeys the Bernoulli-Gaussian model, as follows: (twenty one) in, and Independently subject to mean 0 and variance and Gaussian distribution, is a Bernoulli random variable (equal to 1 with probability , the probability of being equal to 0 is ). is the standard deviation of the background noise, is the standard deviation of the impulse noise.

[0093] is the average noise power, which can be expressed as: (twenty two) in, .

[0094] In summary, when the node i With transmission power To Node j Send data, receive node j Signal-to-noise ratio It can be expressed as: (twenty three) in, is a node i With node j The channel gain between follows an exponential distribution with parameter 1.

[0095] Assuming that the modulation mode used in the PLC communication link is QPSK modulation, the bit error rate during data transmission can be expressed as: (twenty four) in, It is a node in the PLC communication link i To Node j The bit error rate of the transmission, Gauss Q function.

[0096] Assumptions It is Emergency dispatch services The number of bits required to be transmitted, then the emergency dispatch service At the node i and nodes j The probability of successful transmission is: (25) in, Node on the PLC communication link i To Node j send The probability of successful transmission of bit data. The larger its value, the stronger the reliability of the PLC communication link. Therefore, it can be set as a link reliability index that comprehensively considers the three influencing factors of the PLC channel.

[0097] (1.2) Calculation of path reliability for power line carrier communication transmission.

[0098] The PLC communication transmission path needs to comprehensively consider the specific values ​​of all links that make up the path. Therefore, its path reliability can be expressed by the product of the reliabilities of all links through which the communication transmission passes, that is: (26) in, It refers to the k Control instructions The reliability of the path. If the probability of successful transmission of the path is greater than or equal to the service If the required success transmission probability is higher than the specified value, the control instruction transmitted through the path is considered valid; otherwise, the transmission is considered failed. In this embodiment, the emergency dispatch reliability requirement is set to 99.999%.

[0099] (2) Real-time analysis and calculation of power line carrier communication.

[0100] (2.1) Real-time analysis of power line carrier communication.

[0101] The size of the signal transmission delay mainly depends on the signal propagation speed and the length of the communication transmission link, plus other delays , specifically expressed as follows: (27) in, is a node i and nodes j The link delay time between is a node i With node j The link distance between Is the signal in this link For PLC communication, The speed of light is 2 / 3. Other delays typically include processing delays, waiting delays, interference, and retransmission delays during the communication transmission process. Since the analysis of link delay in this embodiment focuses on transmission delay, other delays can be simplified to fixed values.

[0102] (2.2) Real-time calculation of PLC communication transmission path.

[0103] Business The number of routing hops that the communication transmission passes through is q Based on the above calculations of link reliability and real-time performance, it can be seen that the transmission system from the source node to the destination node is a series system composed of all links. Therefore, the transmission path delay can be expressed as the sum of the delays of all links passed through. The specific formula is as follows: (28) in, For the k Control instructions The path delay is Less than or equal to emergency dispatch business Maximum delay tolerated for communication , then it is considered that this business meets the real-time requirements; otherwise, it is considered that the instruction has not been issued in time and the business transmission has failed.

[0104] (3) Communication transmission path scheduling strategy driven by joint emergency dispatch business needs.

[0105] (3.1) Communication path scheduling strategy model driven by real-time reliability requirements.

[0106] According to the real-time and reliability analysis and calculation process of PLC communication in steps (1) and (2), the low-voltage distribution network side communication network is used as the research scenario, and the required transmission Emergency dispatch services Taking the minimum PLC communication path delay as the optimization goal and the path transmission delay and path reliability of a single emergency dispatch service as the constraint conditions, a PLC communication path scheduling model driven by real-time reliability requirements is established. The specific expression is as follows: (29) (30) (31) in, PLC communication path scheduling function driven by real-time reliability requirements, is the transmission delay of a single service path, The maximum path transmission delay for emergency dispatch services can be set to 0.2s. Reliability requirements for emergency dispatch.

[0107] (3.2) Communication transmission path scheduling algorithm driven by joint emergency dispatch business needs: According to the set scenario, there are Emergency dispatch services are initiated at the same time, and the reliability and real-time requirements of these services are the same. Dijkstra The routing algorithm selects the optimal path for the service. The improved algorithm steps are as follows: Input: Number of nodes in the communication network , emergency dispatch business collection .

[0108] Output: Routing path for each emergency dispatch service and path reliability , the shortest path list .

[0109] (a) Clarify the communication requirements for emergency dispatch services, namely, the service latency requirement is less than or equal to 200ms and the reliability requirement is greater than 99.999%.

[0110] (b) Initialization node reliability and delay, determining the source node s , create a node collection S and node collection U ,in S Contains only source nodes, U Including s Other nodes outside.

[0111] (c) Calculate the reliability of the path With delay , determine the node with the shortest delay k The shortest path.

[0112] (d) Calculation through nodes k To adjacent nodes j New path delay ,Compare With the size of the current recorded delay, if If the delay is smaller than the currently recorded delay, proceed to the next step; otherwise, reselect the adjacent node and repeat this step until all new path delays are compared.

[0113] (e) Determine whether the new path meets the reliability requirements. If so, update the node j Otherwise, no update.

[0114] (f) Repeat steps (c)-(e) until the shortest paths for all nodes are determined. Return the shortest path list and the corresponding path transmission delay and path reliability, and the algorithm ends.

[0115] In this embodiment, the software MATLAB is used to complete DijkstraWriting and testing the routing algorithm. To verify the effectiveness of the proposed joint emergency dispatch service demand-driven communication transmission path scheduling method for the real-time reliability requirements of emergency dispatch instructions, Tables 1 and 2 show the real-time and reliability results under any selected communication transmission path and under the communication transmission path scheduling strategy, respectively.

[0116] Table 1 Real-time and reliability results under any selected communication transmission path

[0117] Table 2 Real-time and reliability results under any selected communication transmission path

[0118] Comparing the latency and reliability in Tables 1 and 2 shows that the reliability of communication transmission paths 1-14-5 and 1-14-12-6-15 in Table 1 is 99.9989% and 99.9979%, respectively, which cannot meet the minimum reliability requirements of emergency dispatch services. Furthermore, the transmission delay of communication path 1-14-12-9-3-7 is 0.21s, exceeding the real-time requirements of emergency dispatch services. Without the communication transmission path scheduling strategy, the real-time and reliability requirements cannot be met. This is primarily because emergency dispatch instructions must be transmitted from the dispatch center to each IDC load and DG aggregation controller via the communication network. The latency and reliability of arbitrarily selected communication transmission paths cannot meet emergency dispatch requirements, affecting the real-time and accuracy of emergency dispatch instructions. This, in turn, reduces the accuracy of power regulation for IDC loads and DG aggregation, resulting in overvoltage and undervoltage issues at some nodes even after the "power grid-information network" integrated emergency dispatch. However, the real-time and reliability requirements of the communication transmission path scheduling strategy can meet the minimum requirements.

[0119] In response to the problem that the quality of communication network services in low-voltage power grids is difficult to guarantee, this application proposes a communication transmission path scheduling method driven by joint emergency dispatch business needs based on the coupling relationship of "power grid-information network" and the real-time and reliability indicators of PLC communication methods, so as to meet the real-time and reliability requirements of communication transmission for emergency power dispatch instructions under voltage over-limit.

[0120] In summary, this application verifies the effectiveness of voltage over-limit regulation based on the proposed emergency joint dispatch strategy for data center load and distributed power generation under voltage over-limit driving, combined with the communication transmission path scheduling strategy under the joint emergency dispatch business requirements. Figure 8 As shown in FIG, a comparison result diagram of emergency dispatch cost under the “power grid-information network” integrated emergency dispatch strategy method taking into account the adjustable load of the data center provided in this embodiment. Figure 8 The results show that the “power grid-information network” integrated emergency dispatch strategy proposed in this application taking into account IDC load can adjust the voltage of all bus nodes with serious voltage limit violations to the safe range [0.95, 1.05] pu. Figure 5 and Figure 8 It can be seen that the use of the communication transmission path scheduling strategy proposed in this application for emergency joint scheduling of the two networks can effectively solve the delay and reliability issues that may be encountered when the dispatch center uses the communication network to issue adjustment instructions in real-world scenarios, thereby enhancing the regulation effect of over-limit voltage. In summary, the effectiveness of the method proposed in this application in voltage over-limit regulation has been verified, thereby ensuring the real-time and reliability of the emergency scheduling service of the two-network integration.

[0121] In order to verify that the emergency joint dispatch of IDC load and DG aggregated power generation can achieve efficient regulation of multiple nodes with severe voltage limit violations at the lowest cost. Figure 9 As shown in the figure, under the premise of ensuring that the voltage of all bus nodes in the power network is adjusted to a safe range, the cost comparison result of power regulation by IDC load and DG aggregation before and after the emergency joint dispatch of this application is adopted. Figure 9 It can be seen that the power optimization dynamic adjustment method proposed in this application can significantly reduce the operating cost of the power network.

[0122] This application covers three strategies: (1) Emergency power support strategy: In the event of voltage over-limit in the distribution network, the dispatching and control center can obtain the power adjustment amount required for each node to restore the over-limit voltage node to the normal voltage range through this strategy, and use it as the dispatching instruction for the latter two strategies. (2) Joint dispatching strategy of data center adjustable load and distributed power generation aggregate power: Under the dispatching instruction of the first strategy, the output of the DG aggregation unit, energy storage equipment and IDC load adjustable resources connected to each over-limit node is optimized, so as to meet the adjustment instruction of the first strategy with the minimum operating cost, and thus effectively restore the voltage over-limit. (3) Joint emergency dispatching business demand-driven communication transmission path scheduling strategy: This strategy studies the delay and reliability issues that may be encountered in the process of the dispatching and control center issuing dispatching instructions. This strategy and the second strategy jointly respond to the adjustment instructions of the first strategy from the communication level and the power grid business level, respectively, to ensure the real-time and accuracy of the distribution network voltage over-limit adjustment.

[0123] This application first constructs a "power grid-information network" integrated emergency dispatch framework that takes into account the adjustable load of the data center, where the information network portion mainly considers the local communication network. Based on this, an emergency power support strategy for power network voltage over-limit is proposed, aiming to achieve the most effective recovery of each node's over-limit voltage by adjusting the active power of each node. Furthermore, an emergency joint dispatch strategy for data center load and distributed power generation aggregated power driven by voltage over-limit is proposed, aiming to meet the emergency power support needs of each node under voltage over-limit with minimal power regulation cost. Finally, a communication transmission path scheduling method driven by joint emergency dispatch business needs is proposed, aiming to meet the real-time and reliability requirements of communication transmission for emergency power dispatch instructions under voltage over-limit. This application can effectively utilize the adjustable capacity of the information network data center load and enable it to flexibly participate in the safe and economic dispatch of the power grid, while effectively reducing the impact of the communication network's arbitrary selection of communication transmission paths for issuing instructions on the power grid's emergency dispatch business, ensuring the real-time and reliability of the emergency dispatch business of the two networks.

[0124] like Figure 10 FIG. 1 is a schematic diagram of the integrated interconnected data center load-adjustable emergency dispatch system proposed in this application, which may include: An instruction calculation module is used to calculate the power regulation amount of the node and its associated nodes participating in the voltage regulation of the node, as a power regulation amount instruction, based on the voltage exceeding the limit of any node in the distribution network and the dynamic sensitivity of the node's voltage to the active power injected by other associated nodes; The regulation module is used to formulate an emergency joint scheduling strategy for the data center load and the aggregated power generation power of distributed power sources according to the power regulation instruction, and to regulate the power of each node to minimize the power regulation cost when each node performs power regulation.

[0125] In some embodiments of the present application in which the adjustable load of an integrated interconnected data center participates in an emergency dispatch system, before power regulation is performed on each node, a power regulation instruction is sent to the controllers of the distributed power generation aggregation unit, energy storage equipment and Internet data center load connected to the node where the voltage exceeds the limit.

[0126] In some embodiments of the present application of the integrated interconnected data center adjustable load participating in the emergency dispatch system, when the power adjustment amount instruction is sent to the distributed power generation aggregation unit, energy storage device and Internet data center load controller connected to the node where the voltage exceeds the limit, the optimized sending method includes: A communication path scheduling model is constructed with the optimization goal of minimizing the communication path delay of power regulation instructions and the constraints of the path transmission delay and path reliability of a single emergency dispatch service between nodes. The input of the communication path scheduling model is the number of nodes and the set of emergency dispatch services, and the output is the routing path, path reliability, and shortest path list for each emergency dispatch service. pass Dijkstra The routing algorithm solves the communication path scheduling model and obtains the optimal routing path.

[0127] In some embodiments of the integrated emergency dispatch system of the present application, the communication path scheduling model includes:

[0128] The constraints of the communication path scheduling model include:

[0129]

[0130] in, It is a power line carrier communication path scheduling function driven by real-time reliability requirements. is the transmission delay of a single service path, is the maximum path transmission delay for emergency dispatch services, Reliability requirements for emergency dispatch.

[0131] In some embodiments of the present application of the integrated interconnected data center adjustable load participation emergency dispatch system, the method for calculating the dynamic sensitivity of the voltage of the node to the active power injected by other associated nodes includes:

[0132] in, for Moment Active power regulation of each node The dynamic sensitivity of the voltage at each node, for Moment k The real part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, for Moment k The imaginary part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, for Moment The real part of the voltage at each node, , for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, , for Moment k The proportionality coefficient of the voltage of each node to the rated voltage, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, For the k Node and The line impedance between nodes, for Moment The voltage of each node, for Moment Node and The circuit impedance between nodes, for Moment The imaginary part of the voltage at each node, for Moment The reactive power regulation of each node is The dynamic sensitivity of the real part of the voltage at each node, for Moment The voltage of each node, for Moment Active power of each node.

[0133] In some embodiments of the system for enabling adjustable loads to participate in emergency dispatching of a converged interconnected data center of the present application, the method for calculating the power adjustment amount of the node and its associated nodes participating in voltage regulation of the node includes:

[0134]

[0135] in, for Moment k The node and all its associated nodes participate in the kThe power regulation amount of voltage regulation of each node, For the k The rated voltage of each node, for Moment k The power regulation amount of each node, For the j Nodes participate in k The power regulation amount of voltage regulation of each node, for Moment j The minimum value of the adjustable active power of a node, for Moment j The maximum value of the adjustable active power of the node, is the number of associated nodes that can perform active power regulation, for Moment j The adjustable active power of each node, For the k The associated node set of a node, for Moment k Active power regulation of each node The dynamic sensitivity of the voltage at each node.

[0136] In some embodiments of the present application's integrated interconnected data center adjustable load participation emergency dispatch system, the emergency joint dispatch strategy includes: According to the power regulation instructions corresponding to each node, the corresponding power regulation minimum cost objective function is constructed; An improved particle swarm optimization algorithm is used to solve the minimum cost objective function of power regulation, and an emergency joint scheduling strategy for data center load and distributed power generation aggregated power driven by voltage overlimit is obtained.

[0137] In some embodiments of the present application of the integrated interconnected data center adjustable load participating in the emergency dispatch system, the power regulation minimum cost objective function includes:

[0138] in, is the minimum cost function for the node to respond to the voltage command, for The power regulation cost of DG can be controlled at all times. for The power regulation cost of energy storage at all times, for The compensation cost for the load shedding of IDC at the moment, for The adjustment compensation cost of IDC adjustable load at the moment, NR is the number of DG aggregations, is the sequence number of the DG aggregation, I is the amount of load that can be removed by IDC, is the serial number of the IDC removable load, J is the number of IDC adjustable loads, It is the serial number of the IDC adjustable load; The constraints of the power regulation minimum cost objective function include:

[0139] in, for The regulated power of DG at the moment, for The IDC can cut off the active power of the load at any time. is the control variable of the IDC adjustable load, is the active power of the IDC adjustable load, is the charge and discharge efficiency of the energy storage unit, for The power of energy storage at all times, is the cuttable rate of IDC cuttable load.

[0140] It should be noted that in the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of each module is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules can be combined or integrated into another device, or some features can be ignored or not executed. The modules described as separate components may or may not be physically separated. The components displayed as modules may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed in multiple different places. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0141] In addition, the modules in the various embodiments of the present invention may be integrated into a single processing unit, each module may exist physically separately, or two or more modules may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0142] An embodiment of the present application also provides an electronic device, which may include one or more processors, memories, and communication interfaces.

[0143] The memory, the communication interface, and the processor are coupled together. For example, the memory, the communication interface, and the processor may be coupled together via a bus.

[0144] The communication interface is used to transmit data with other devices. The memory stores computer program code. The computer program code includes computer instructions that, when executed by a processor, cause the electronic device to execute the steps of the above-described method for enabling converged interconnected data centers to participate in emergency dispatch with adjustable loads.

[0145] Among them, the processor can be a processor or a controller, for example, a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute the various exemplary logic blocks, modules and circuits described in conjunction with the contents of this disclosure. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The processor can be used to support electronic devices in executing the method steps provided in the above embodiments.

[0146] The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The above buses may be divided into an address bus, a data bus, a control bus, etc.

[0147] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for the converged interconnected data center to participate in emergency scheduling of adjustable loads are implemented.

[0148] The computer-readable storage medium involved in this application includes random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD ROMs, or any other form of storage medium known in the technical field.

[0149] The above are merely preferred embodiments of the present application and are not intended to limit the present application. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for emergency dispatching of adjustable loads in a converged interconnected data center, characterized in that: include: Based on the voltage over-limit situation of any node in the distribution network and the dynamic sensitivity of the node's voltage to the active power injected by other associated nodes, the power regulation amount of the node and its associated nodes participating in the voltage regulation of the node is calculated as the power regulation amount instruction; According to the power regulation amount instruction, an emergency joint scheduling strategy for the data center load and the distributed power generation aggregate power is formulated, and the power of each node is adjusted according to the emergency joint scheduling strategy to minimize the power regulation cost when each node performs power regulation.

2. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 1, characterized in that: Before power regulation is performed on each node, a power regulation instruction is sent to the controllers of the distributed power generation aggregation unit, energy storage equipment and Internet data center load connected to the node where the voltage exceeds the limit.

3. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 2, characterized in that: When the power regulation amount instruction is sent to the controller of the distributed power generation aggregation unit, energy storage device and Internet data center load connected to the node where the voltage exceeds the limit, the optimized sending method includes: A communication path scheduling model is constructed with the optimization goal of minimizing the communication path delay of power regulation instructions and the constraints of the path transmission delay and path reliability of a single emergency dispatch service between nodes. The input of the communication path scheduling model is the number of nodes and the set of emergency dispatch services, and the output is the routing path, path reliability, and shortest path list for each emergency dispatch service. pass Dijkstra The routing algorithm solves the communication path scheduling model and obtains the optimal routing path.

4. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 3, characterized in that: The communication path scheduling model includes: The constraints of the communication path scheduling model include: in, It is a power line carrier communication path scheduling function driven by real-time reliability requirements. is the transmission delay of a single service path, is the maximum path transmission delay for emergency dispatch services, Reliability requirements for emergency dispatch.

5. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 1, characterized in that: The method for calculating the dynamic sensitivity of the voltage of the node to the active power injected into other associated nodes includes: in, for Moment Active power regulation of each node The dynamic sensitivity of the voltage at each node, for Moment k The real part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, for Moment k The imaginary part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, for Moment The real part of the voltage at each node, , for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, , for Moment k The proportionality coefficient of the voltage of each node to the rated voltage, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, For the k Node and The line impedance between nodes, for Moment The voltage of each node, for Moment Node and The circuit impedance between nodes, for Moment The imaginary part of the voltage at each node, for Moment The reactive power regulation of each node is The dynamic sensitivity of the real part of the voltage at each node, for Moment The voltage of each node, for Moment Active power of each node.

6. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 5, characterized in that: The method for calculating the power regulation amount of the node and its associated nodes participating in voltage regulation of the node includes: in, for Moment k The node and all its associated nodes participate in the k The power regulation amount of voltage regulation of each node, For the k The rated voltage of each node, for Moment k The power regulation amount of each node, For the j Nodes participate in k The power regulation amount of voltage regulation of each node, for Moment j The minimum value of the adjustable active power of a node, for Moment j The maximum value of the adjustable active power of the node, is the number of associated nodes that can perform active power regulation, for Moment j The adjustable active power of each node, For the k The associated node set of a node, for Moment k Active power regulation of each node The dynamic sensitivity of the voltage at each node.

7. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 1, characterized in that: The emergency joint dispatch strategy includes: According to the power regulation instructions corresponding to each node, the corresponding power regulation minimum cost objective function is constructed; An improved particle swarm optimization algorithm is used to solve the minimum cost objective function of power regulation, and an emergency joint scheduling strategy for data center load and distributed power generation aggregated power driven by voltage overlimit is obtained.

8. The method for emergency dispatching of adjustable loads in converged interconnected data centers according to claim 7, characterized in that: The power regulation minimum cost objective function includes: in, is the minimum cost function for the node to respond to the voltage command, for The power regulation cost of DG can be controlled at all times. for The power regulation cost of energy storage at all times, for The compensation cost for the load shedding of IDC at the moment, for The adjustment compensation cost of IDC adjustable load at the moment, NR is the number of DG aggregations, is the sequence number of the DG aggregation, I is the amount of load that can be removed by IDC, is the serial number of the IDC removable load, J is the number of IDC adjustable loads, It is the serial number of the IDC adjustable load; The constraints of the power regulation minimum cost objective function include: in, for The regulated power of DG at the moment, for The IDC can cut off the active power of the load at any time. is the control variable of the IDC adjustable load, is the active power of the IDC adjustable load, is the charge and discharge efficiency of the energy storage unit, for The power of energy storage at all times, is the cuttable rate of IDC cuttable load.

9. A converged interconnected data center load-adjustable emergency dispatch system, characterized in that: include: An instruction calculation module is used to calculate the power regulation amount of the node and its associated nodes participating in the voltage regulation of the node, as a power regulation amount instruction, based on the voltage exceeding the limit of any node in the distribution network and the dynamic sensitivity of the node's voltage to the active power injected by other associated nodes; The regulation module is used to formulate an emergency joint scheduling strategy for the data center load and the aggregated power generation power of the distributed power supply according to the power regulation amount instruction, and to adjust the power of each node according to the emergency joint scheduling strategy to minimize the power regulation cost when each node performs power regulation.

10. The converged interconnected data center adjustable load participation emergency dispatch system according to claim 9, characterized in that: Before power regulation is performed on each node, a power regulation instruction is sent to the controllers of the distributed power generation aggregation unit, energy storage equipment and Internet data center load connected to the node where the voltage exceeds the limit.

11. The converged interconnected data center load-adjustable emergency dispatching system according to claim 10, characterized in that: When the power regulation amount instruction is sent to the controller of the distributed power generation aggregation unit, energy storage device and Internet data center load connected to the node where the voltage exceeds the limit, the optimized sending method includes: A communication path scheduling model is constructed with the optimization goal of minimizing the communication path delay of power regulation instructions and the constraints of the path transmission delay and path reliability of a single emergency dispatch service between nodes. The input of the communication path scheduling model is the number of nodes and the set of emergency dispatch services, and the output is the routing path, path reliability, and shortest path list for each emergency dispatch service. pass Dijkstra The routing algorithm solves the communication path scheduling model and obtains the optimal routing path.

12. The converged interconnected data center adjustable load participation emergency dispatch system according to claim 11, characterized in that: The communication path scheduling model includes: The constraints of the communication path scheduling model include: in, It is a power line carrier communication path scheduling function driven by real-time reliability requirements. is the transmission delay of a single service path, is the maximum path transmission delay for emergency dispatch services, Reliability requirements for emergency dispatch.

13. The converged interconnected data center load-adjustable emergency dispatch system according to claim 9, characterized in that: The method for calculating the dynamic sensitivity of the voltage of the node to the active power injected into other associated nodes includes: in, for Moment Active power regulation of each node The dynamic sensitivity of the voltage at each node, for Moment k The real part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, for Moment k The imaginary part of the voltage at each node, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, for Moment The real part of the voltage at each node, , for Moment Active power regulation of each node The dynamic sensitivity of the real part of the voltage at each node, , for Moment k The proportionality coefficient of the voltage of each node to the rated voltage, for Moment Active power regulation of each node The dynamic sensitivity of the imaginary part of the voltage at each node, For the k Node and The line impedance between nodes, for Moment The voltage of each node, for Moment Node and The circuit impedance between nodes, for Moment The imaginary part of the voltage at each node, for Moment The reactive power regulation of each node is The dynamic sensitivity of the real part of the voltage at each node, for Moment The voltage of each node, for Moment Active power of each node.

14. The converged interconnected data center load-adjustable emergency dispatching system according to claim 13, characterized in that: The method for calculating the power regulation amount of the node and its associated nodes participating in voltage regulation of the node includes: in, for Moment k The node and all its associated nodes participate in the k The power regulation amount of voltage regulation of each node, For the k The rated voltage of each node, for Moment k The power regulation amount of each node, For the j Nodes participate in k The power regulation amount of voltage regulation of each node, for Moment j The minimum value of the adjustable active power of a node, for Moment j The maximum value of the adjustable active power of the node, is the number of associated nodes that can perform active power regulation, for Moment j The adjustable active power of each node, For the k The associated node set of a node, for Moment k Active power regulation of each node The dynamic sensitivity of the voltage at each node.

15. The converged interconnected data center load-adjustable emergency dispatch system according to claim 9, characterized in that: The emergency joint dispatch strategy includes: According to the power regulation instructions corresponding to each node, the corresponding power regulation minimum cost objective function is constructed; An improved particle swarm optimization algorithm is used to solve the minimum cost objective function of power regulation, and an emergency joint scheduling strategy for data center load and distributed power generation aggregated power driven by voltage overlimit is obtained.

16. The converged interconnected data center load-adjustable emergency dispatching system according to claim 15, characterized in that: The power regulation minimum cost objective function includes: in, is the minimum cost function for the node to respond to the voltage command, for The power regulation cost of DG can be controlled at all times. for The power regulation cost of energy storage at all times, for The compensation cost for the load shedding of IDC at the moment, for The adjustment compensation cost of IDC adjustable load at the moment, NR is the number of DG aggregations, is the sequence number of the DG aggregation, I is the amount of load that can be removed by IDC, is the serial number of the IDC removable load, J is the number of IDC adjustable loads, It is the serial number of the IDC adjustable load; The constraints of the power regulation minimum cost objective function include: in, for The regulated power of DG at the moment, for The IDC can cut off the active power of the load at any time. is the control variable of the IDC adjustable load, is the active power of the IDC adjustable load, is the charge and discharge efficiency of the energy storage unit, for The power of energy storage at all times, is the cuttable rate of IDC cuttable load.

17. An electronic device, characterized in that: include: A memory, one or more processors; the memory is coupled to the processor; wherein the memory stores computer program code, the computer program code includes computer instructions, and when the computer instructions are executed by the processor, the electronic device performs the steps of the method for emergency dispatch of adjustable loads in a converged interconnected data center as described in any one of claims 1 to 8.

18. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for participating in emergency dispatch of adjustable loads in a converged interconnected data center as claimed in any one of claims 1 to 8.

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