Resource effective capacity evaluation and backup configuration method for computer collaboration

Abstract

The present application relates to a kind of resource effective capacity evaluation and backup configuration method for computer collaboration, comprising: based on the physical parameters of each grid flexible resource of access source node, determine the nominal regulation capacity that each resource can provide in the source node;Based on the communication quality index of each terminal of the resource supporting the access source node, determine the effective regulation capacity that the resource can provide in the source node;Based on the effective regulation capacity of each resource and the reachable coefficient of each resource between the source node and target node, determine the transportable effective regulation capacity of each resource from the source node to target node;Based on the nominal regulation capacity, effective regulation capacity, transportable effective regulation capacity of each resource accessing each source node and the regulation backup demand of target node, determine the backup configuration of target node.The method of the present application can solve the problem that the nominal regulation capacity provided by the source network load storage flexible resource in the prior art is inconsistent with the actual effective available capacity.

Description

Technical Field

[0001] This invention relates to the field of new power system planning and operation control technology, and in particular to a method for assessing effective resource capacity and allocating reserves in a computer-based collaborative manner. Background Technology

[0002] With the continuous increase in the proportion of installed capacity of new energy sources, the operational safety, economy, and low-carbon performance of provincial power systems increasingly rely on the coordinated regulation of power generation, grid, load, and storage. Traditional power systems mainly rely on conventional power source ramp-up and spinning reserves to cope with load fluctuations; in new power systems, distributed new energy sources, energy storage, flexible loads, electric vehicles, virtual power plants, interruptible industrial loads, and demand response resources are gradually becoming important regulation resources. Furthermore, with the rapid growth in the scale of new loads such as computing centers, computing loads are gradually becoming an important flexible load resource of the power system, and their operation and regulation depend on the coordinated support of the power network and communication network. These resources are characterized by wide distribution, large quantity, diverse response methods, and high dependence on communication control.

[0003] Existing methods for coordinating energy source, grid, load, and storage typically calculate adjustment potential based on physical installed capacity, rated power, contracted demand response capacity, or historical response capabilities. For example, energy storage is calculated for its chargeable / dischargeable capacity based on rated power and remaining capacity; flexible loads are calculated for their reducible capacity based on contracted capacity; aggregated electric vehicle resources are calculated for their adjustable capacity based on the number of connected units and battery capacity; and distributed power sources are calculated for their up- or down-adjustment capabilities based on their controllable output range. These methods implicitly assume that as long as resources physically exist, they can be observed in real-time, accurately instructed, responded to promptly, and their execution verified by the scheduling platform.

[0004] However, in digital power systems, the above assumptions do not always hold true. The regulation process of flexible resources (source-grid-load-storage), including computing centers, typically relies on communication networks, data acquisition terminals, control master stations, edge gateways, aggregator platforms, and field execution equipment. If the quality of critical communications degrades, problems such as missing telemetry data, delayed command issuance, control confirmation failures, invisible resource status, and increased deviations in aggregated resource execution may occur. In this case, the nominal capacity of the flexible resources still exists, but their effective capacity that can be reliably called upon by the system decreases, thereby compromising the effectiveness and security of system scheduling and affecting the safe and stable operation of the power grid system. Summary of the Invention

[0005] Based on the above analysis, this invention aims to disclose a method for evaluating the effective capacity and configuring backup resources for computer-based collaborative computing. By converting the communication indicators of each resource into communication controllability evaluation values ​​and establishing a communication controllability reduction function, the true available capacity of the resources can be determined. This method addresses the problems in the prior art where the nominal capacity of flexible resources such as source-grid-load-storage are inconsistent with the actual effective available capacity, and where backup capacity is overestimated under communication degradation.

[0006] This invention provides a method for assessing effective resource capacity and configuring backup for computer-based collaborative computing, which specifically includes the following steps: The nominal regulation capacity that each resource can provide at the source node is determined based on the physical parameters of each power grid flexible resource at the access source node. The effective regulation capacity that the resource can provide at the source node is determined based on the communication quality indicators of each terminal supporting the access source node. The effective adjustment capacity of each resource from the source node to the target node is determined based on the effective adjustment capacity of each resource and the reachability coefficient of each resource between the source node and the target node. The backup configuration of the target node is determined based on the nominal adjustment capacity, effective adjustment capacity, and transportable effective adjustment capacity of each resource accessed by each source node, as well as the adjustment backup requirements of the target node.

[0007] Furthermore, the communication quality indicators include telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality. The determination of the effective regulation capacity that the resource can provide at the source node based on the communication quality indicators of each terminal supporting the access source node includes: The communication controllability evaluation value of each terminal is calculated based on the telemetry integrity, command success rate, latency satisfaction, response confirmation rate and key communication quality of each terminal. The resource-level communication controllability evaluation value of the resource at the source node is determined based on the communication controllability evaluation value of each terminal. The communication reduction coefficient of the resource at the source node is calculated based on the resource-level communication controllability evaluation value; The effective regulation capacity that the resource can provide at the source grid node is determined based on the communication reduction factor and nominal regulation capacity of the resource at the source node.

[0008] Furthermore, the communication controllability evaluation value of each terminal is calculated using the following formula based on the telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality of each terminal: ; Among them, subscript , , , These respectively represent the terminal supporting the flexible resources of the power grid, the flexible resources of the power grid, the node, and the time period; Represents a node China supports the flexible resources of the power grid terminal During the period The communication controllability evaluation value; , , , , These represent nodes. China supports the flexible resources of the power grid terminal During the period Telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality; For the corresponding weights, , .

[0009] Furthermore, the resource-level communication controllability evaluation value of the resource at the source node is determined using the following formula based on the communication controllability evaluation value of each terminal: ; in, Indicating flexible resources of the power grid At the node During the period The resource-level communication controllability evaluation value; Represents a node China supports the flexible resources of the power grid terminal During the period The communication controllability evaluation value; Represents a node China supports the flexible resources of the power grid terminal The association weight.

[0010] Furthermore, the communication reduction factor of the resource at the source node is calculated using the following formula based on the resource-level communication controllability evaluation value: ; ; in, and They are nodes resources During the period The upward and downward communication reduction coefficients; and These represent the minimum upward and minimum downward availability percentages that can be retained even under severe communication degradation, respectively. and Representing resources Sensitivity coefficient to communication degradation; and These represent the communication reduction correction terms after adjusting the resource-level communication controllability evaluation value by the sensitivity coefficients in the upward and downward directions, respectively.

[0011] Furthermore, the effective regulation capacity that the resource can provide at the source node is determined using the following formula based on the communication reduction factor and nominal regulation capacity of the resource at the source node: ; ; in, and They are nodes resources During the period Effective upward and downward capacity adjustments; and They are nodes resources During the period The nominal increase and nominal decrease in capacity.

[0012] Furthermore, the transportable effective adjustment capacity of the resource to the target node is determined using the following formula based on the effective adjustment capacity and the reachability coefficient of the resource between the source node and the target node: ; ; in, and Representing the source node respectively resources For the target node The effective upward transport capacity and the effective downward transport capacity; and Representing resources Upward and downward reachability coefficients between the source and target nodes.

[0013] Furthermore, determining the backup configuration of the target node based on the nominal adjustment capacity, effective adjustment capacity, and transportable effective adjustment capacity of each resource accessed by each source node, as well as the adjustment backup requirements of the target node, includes: The total nominal regulation capacity, total effective regulation capacity, and total transportable effective regulation capacity that can be provided to the target node are calculated based on the nominal regulation capacity, effective regulation capacity, and transportable effective regulation capacity of each resource connected to each source node. The first reserve gap caused by the physical capacity of resources is determined based on the adjustment reserve demand and the total nominal adjustment capacity of the target node; the second reserve gap caused by insufficient communication controllability is determined based on the adjustment reserve demand and the total effective adjustment capacity of the target node; and the third reserve gap caused by insufficient network reachability is determined based on the adjustment reserve demand and the available effective adjustment capacity of the target node. The backup configuration of the target node is determined based on the first backup gap, the second backup gap, and the third backup gap.

[0014] Furthermore, the first reserve gap includes a first upward adjustment of the reserve gap. and the first reduction in reserve gap : ; ; The second reserve gap includes the second upward adjustment of the reserve gap. Second reduction in reserve gap : ; ; The third reserve gap includes the third upward adjustment reserve gap. and the third reduction in reserve gap : ; ; in, and Representing the target node respectively During the period The upward and downward adjustment of reserve requirements; , , , , , Target nodes During the period The nominal increase in capacity, the nominal decrease in capacity, the effective increase in capacity, the effective decrease in capacity, the total effective increase in transportable capacity, and the total effective decrease in transportable capacity.

[0015] Furthermore, the adjustment reserve requirements of the target node are determined based on the target node's security reserve requirements, low-carbon adjustment reserve requirements, and communication risk reserve requirements, including: ; ; in, and These represent the upward and downward adjustment of reserve requirements for the target node, respectively. , , These represent the target node's increased backup requirements for security, increased backup requirements for low-carbon development, and increased backup requirements for communication risks, respectively. , , These represent the target node's security-based backup requirements, low-carbon-based backup requirements, and communication-risk-based backup requirements, respectively.

[0016] The present invention can achieve at least one of the following beneficial effects: By transforming communication indicators such as telemetry integrity, control latency, command success rate, response confirmation rate, and key communication service quality of various flexible resources into node-level or resource-level communication controllability evaluation values, and establishing differentiated communication controllability reduction functions (instead of using a uniform reduction ratio) based on the adjustment characteristics of different resources on the source side, network side, load side, and storage side, and by correcting nominal adjustment capacity to effective upward and downward adjustment capacity, the actual available reserve capacity of different nodes in each time period is calculated. The calculation process shows that the worse the communication quality, the higher the control latency, the lower the telemetry integrity, or the lower the command confirmation rate, the smaller the effective adjustment capacity; conversely, the better the communication quality, the higher the effective adjustment capacity. This avoids the problems in existing technologies where the nominal capacity of source-network-load-storage flexible resources is inconsistent with the actual effective available capacity, and where reserve capacity is overestimated under communication degradation.

[0017] By setting different communication sensitivity coefficients and minimum adjustment availability ratios for different resource types, the effective capacity impact of the same communication quality degradation varies across different resources, thus avoiding the shortcomings of existing methods that apply a "one-size-fits-all" approach to assessing the availability of flexible resources.

[0018] By determining the effective transportable regulation capacity of each resource based on the reachability coefficient, it is possible to avoid miscalculating resource capacity limited by line bottlenecks, cross-sectional congestion, or voltage constraints as available reserve at the target node, thus solving the problem of inflated reserve capacity in existing technologies where "resource capacity is sufficient but the grid is inaccessible." This also avoids overestimating the regulation potential of resources simply based on contracted capacity, providing a more reliable basis for flexible resource assessments under different scenarios at different stages of carbon reduction.

[0019] By considering computing centers as flexible load resources in the power system, this approach enables effective capacity assessment and backup configuration for computer-aided collaborative computing. It addresses the issue in computer-aided collaborative computing scenarios where the reliable mobilization of resources such as load regulation, task response, and supporting energy storage in computing centers degrades due to communication quality degradation in the control link, leading to a discrepancy between nominal regulation capacity and actual available mobilization capacity.

[0020] By determining the system's regulatory reserve requirements based on safety reserves, low-carbon regulation reserves, and communication risk reserves, and then determining the reserve gap based on the regulatory reserve requirements and total regulation capacity, the system's reserve configuration is further determined. This satisfies the system's ability to operate safely, operate in a low-carbon manner, and maintain stable operation in response to communication risks. It can cope with fluctuations in renewable energy and peak loads, and also serve renewable energy consumption and high-carbon power purchase substitution. It can analyze reserve gaps caused by different reasons and determine targeted reserve configurations, exhibiting good engineering feasibility. It can be applied to the fields of source-grid-load-storage coordinated optimization, flexible resource assessment of digital distribution networks / provincial power systems, communication-power coupling systems, demand response, low-carbon dispatching, and reserve configuration technology.

[0021] By using an adaptive closed-loop calibration mechanism to perform rolling calibration of the communication sensitivity coefficient and minimum availability ratio, the control strategy can be corrected in real time according to the actual response deviation. This effectively solves the problem of deviation between prediction and actual output caused by communication delay, environmental changes or equipment operating condition fluctuations, reduces the risk of failure in demand response, energy storage, virtual power plants or distributed resource access during critical periods, and significantly improves the accuracy of resource management and operational economy.

[0022] The method of this invention can be applied to scenarios with a high proportion of new energy sources, multi-regional interconnection within provinces, diversified energy storage and flexible load participation in regulation, and power system operation that is highly dependent on communication acquisition and control platforms. Based on the degree of communication controllability degradation, it assesses the effective regulation capacity of flexible resources on the source side, grid side, load side, and storage side, constructs the matching relationship between reserve demand and reserve supply at the node or regional level, and outputs the collaborative optimization results under the constraints of reserve configuration, energy storage layout, available scale of flexible loads, source side regulation demand, and grid carrying capacity. It can support the structural morphology analysis of provincial power systems under different carbon reduction stages.

[0023] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0024] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0025] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0026] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0027] Method Implementation Examples An embodiment of the present invention discloses a method for evaluating the effective capacity of resources and configuring backup for computer-based collaborative computing. The method of the present invention includes steps S1 to S4.

[0028] First, the relevant terms used in this invention will be explained.

[0029] In this invention, a node refers to an electrical connection point in a distribution network that has electrical topological significance and can be monitored, controlled, or configured for resources, including but not limited to bus nodes, transformer substation nodes, feeder segment nodes, load access points, energy storage access points, or equivalent control areas.

[0030] The flexible resources described in this invention refer to various resources in a power system that can flexibly adjust the balance between power supply and demand. Flexible resources include several subcategories, classified according to their distribution within the power system as source-side flexible resources, grid-side flexible resources, load-side flexible resources, and storage-side flexible resources. Source-side flexible resources refer to all resources located on the generation side that can respond to dispatch commands, change active power output, or regulate reactive voltage to provide flexible system regulation capabilities. Source-side flexibility types include conventional power source peak-shaving capabilities, as well as one or more of the following: fast-ramping power sources, controllable new energy sources, distributed power sources, and virtual power plant output regulation capabilities. Grid-side flexible resources refer to various technical means located on the transmission and distribution network side, which improve grid transmission capacity, power flow distribution, and voltage stability by changing the grid operation mode or utilizing power electronic devices. Grid-side flexibility types include one or more of the following: grid topology adjustment, tie-line power transfer, flexible interconnection device regulation, reactive power and voltage control, and cross-sectional mutual assistance capabilities. Load-side flexibility refers to the ability and resources of electricity users (demand side) to flexibly adjust their own power consumption according to the grid demand. Types of load-side flexibility include one or more of the following: interruptible loads, transferable loads, temperature-controlled loads, electric vehicle aggregated loads, industrial demand response, and adjustable capabilities of data centers and computing centers. Flexible energy storage resources refer to the assemblies of various energy storage facilities located on the energy storage side, which provide flexible regulation capabilities to the power system through rapid and precise adjustment of charging and discharging power. Types of flexible energy storage include one or more of electrochemical energy storage, pumped hydro storage, hydrogen energy storage, thermal energy storage, and user-side energy storage.

[0031] The above-mentioned flexible resource types are referred to as resources in this invention.

[0032] When resources When it is a single physical resource, it usually corresponds to one access node; when the resource When it is an aggregated resource, it can cover multiple nodes. At the node The nominal adjustment capacity represents the equivalent adjustment capacity allocated to this node. The nominal adjustment capacity refers to the adjustment capacity that can be provided, determined by the physical characteristics of the resource.

[0033] In this invention, a terminal refers to a device used for monitoring, communicating, and controlling resources. One terminal monitors, communicates, and controls one resource, and one resource can be monitored, communicated, and controlled by multiple terminals.

[0034] In this invention, a source node refers to a node that can provide adjustable capacity resources. A target node refers to a node that has adjustable reserve requirements. Neither the source node nor the target node is limited to the source side, grid side, load side, or storage side.

[0035] It should be noted that the operation of a power system can be divided into short-term, medium-term, and long-term stages according to the carbon reduction phase; and according to the operating scenario, it can include high renewable energy output, low renewable energy output, peak load, low load, extreme weather, communication pressure, equipment maintenance, and emergency backup, etc. The source-grid-load-storage effective capacity assessment and backup configuration method that takes into account communication degradation described in this invention is applicable to all carbon reduction stages and all operating scenarios.

[0036] Step S1: Determine the nominal regulation capacity that each resource can provide at the source node based on the physical parameters of each power grid flexible resource at the access source node.

[0037] Specifically, nominal adjustment capacity includes nominal upward adjustment capacity and nominal downward adjustment capacity. Nominal upward adjustment capacity represents the ability of resources to increase power supply to the system or reduce load, while nominal downward adjustment capacity represents the ability of resources to reduce power supply, increase load, or absorb new energy sources. The adjustment capacity described in this invention includes both upward and downward adjustment capacity.

[0038] Specifically, for power resources, the nominal regulating capacity can be determined by the upper and lower limits of output and the ramping capability; for load resources, the nominal regulating capacity can be determined by the scalable capacity, the transferable capacity, and the response duration; for energy storage resources, the nominal regulating capacity can be determined by the rated power, the available power, and the charge and discharge constraints.

[0039] Furthermore, define the flexible resources of the power grid. At the node nominal increase in capacity and nominal reduction in capacity for: ; ; in, Representing resources At the node During the period The running status; Represents the physical parameters of the resource.

[0040] Step S2: Determine the effective adjustment capacity that the resource can provide at the source node based on the communication quality indicators of each terminal supporting the access source node.

[0041] The communication quality indicators include telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality. The determination of the effective regulation capacity that the resource can provide at the source node based on the communication quality indicators of each terminal supporting the access source node includes: The communication controllability evaluation value of each terminal is calculated based on the telemetry integrity, command success rate, latency satisfaction, response confirmation rate and key communication quality of each terminal. ; Among them, subscript , , , These respectively represent the terminal supporting the flexible resources of the power grid, the flexible resources of the power grid, the node, and the time period; Represents a node China supports the flexible resources of the power grid terminal During the period The communication controllability evaluation value; , , , , These represent nodes. China supports the flexible resources of the power grid terminal During the period Telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality; For the corresponding weights, , .

[0042] Furthermore, the values ​​of each weight can be adjusted empirically based on the communication service level, historical response data, and scheduling control requirements. The preferred values ​​in this invention are 0.15, 0.30, 0.25, 0.20, and 0.10, respectively.

[0043] A higher communication controllability rating indicates that the corresponding terminal is more easily observed, instructed, confirmed, and executed reliably.

[0044] It should be noted that the calculation method for the communication controllability evaluation value of each terminal described above also applies to the communication controllability evaluation value of nodes. However, since virtual power plants, electric vehicle aggregators, and interruptible load aggregators may span multiple nodes, flexible resources are not always completely consistent with the communication quality of a single node or terminal. Therefore, it is necessary to calculate resource-level communication controllability evaluation values.

[0045] Furthermore, the resource-level communication controllability evaluation value of the resource at the source node is determined based on the communication controllability evaluation value of each terminal; ; in, Indicating flexible resources of the power grid At the node During the period The resource-level communication controllability evaluation value; Represents a node China supports the flexible resources of the power grid terminal During the period The communication controllability evaluation value; Represents a node China supports the flexible resources of the power grid terminal The association weight is used to represent the relationship weight of a terminal to resources. The degree of contribution of controllability, under optimal conditions It can be determined according to the proportion of the adjustable capacity covered by the terminal to the total adjustable capacity of resources.

[0046] It should be noted that for resources that require multiple control links to be reliable simultaneously, the resource-level communication controllability evaluation value can be taken as the lowest value among the multiple links; for resources with redundant communication links or multiple aggregator access capabilities, the calculation can be performed based on the parallel availability of redundant links.

[0047] Communication controllability evaluation values ​​reflect whether resources are "observable, instructible, responsive, and verifiable." For example, an interruptible load of the same capacity can provide higher backup capacity when the communication link is stable; when the aggregation platform experiences communication interruption or a decrease in control confirmation rate, its effective backup capacity should be reduced.

[0048] Furthermore, different flexible resources exhibit varying degrees of sensitivity to communication degradation. For example, energy storage and electric vehicle aggregation resources typically require real-time or near-real-time control; interruptible industrial loads may have high requirements for acknowledgment feedback; conventional power supply ramp-up capabilities have relatively low communication dependence; and distributed photovoltaics and controllable inverters have high dependence on edge control channels.

[0049] Based on the resource-level communication controllability evaluation value, the nominal adjustment capacity of each resource needs to be differentially reduced in order to obtain the effective upward and downward adjustment capacity of each resource. Therefore, it is necessary to calculate the communication reduction coefficients in the upward and downward adjustment directions.

[0050] Specifically, the communication reduction factor of the resource at the source node is calculated using the following formula based on the resource-level communication controllability evaluation value; ; ; in, and They are nodes resources During the period The upward and downward communication reduction coefficients; and These represent the minimum up-adjustment and minimum down-adjustment availability percentages that can be retained even under severe communication degradation, respectively, and are preset values ​​determined based on resource characteristics and experience; and Representing resources The sensitivity coefficient to communication degradation is a preset value determined based on resource characteristics and experience; and These represent the communication reduction correction terms after adjusting the resource-level communication controllability evaluation value for upward and downward direction sensitivity coefficients, respectively. These terms are determined through communication system reliability assessment (communication system reliability assessment is a mature application in the power industry and will not be discussed further in this invention). Different resource types can be configured with different terms. This is because the same communication degradation can produce different reduction effects on different resources, such as energy storage, flexible loads, distributed power sources, virtual power plants, and grid-side mutual assistance resources. Its value is set according to the resource's dependence on remote communication control; specifically, it applies to resources with local autonomous control capabilities. and Smaller resources that rely on aggregators or remote scheduling instructions and Relatively large.

[0051] Furthermore, based on the communication reduction factor and nominal regulation capacity of the resource at the source node, the effective regulation capacity that the resource can provide at the source grid node is determined, and the calculation formula is as follows: ; ; in, and They are nodes resources During the period Effective upward and downward capacity adjustments; and They are nodes resources During the period The nominal increase and nominal decrease in capacity.

[0052] It should be noted that if resources If the resource-level communication controllability evaluation value is lower than the minimum call threshold for that resource, then the resource will not enter the backup configuration candidate pool, or will only retain the minimum locally autonomous executable adjustment capability. Furthermore, the minimum call threshold can be determined based on resource type, response time limit, historical execution rate, contract reliability requirements, and backup service level.

[0053] This embodiment transforms communication indicators such as telemetry integrity, control latency, command success rate, response confirmation rate, and the quality of key communication services into node-level or resource-level communication controllability evaluation values. It also establishes differentiated communication controllability reduction functions (instead of using a uniform reduction ratio) based on the adjustment characteristics of different resources on the source, network, load, and storage sides. Furthermore, it corrects the nominal adjustment capacity to effective upward and downward adjustment capacities, calculating the actual available backup capacity of different nodes in each time period. The calculation process shows that the worse the communication quality, the higher the control latency, the lower the telemetry integrity, or the lower the command confirmation rate, the smaller the effective adjustment capacity; conversely, the better the communication quality, the higher the effective adjustment capacity. This avoids the problems in existing technologies where the nominal capacity of flexible resources in the source, network, load, and storage sides is inconsistent with the actual effective available capacity, and where backup capacity is overestimated under communication degradation.

[0054] By setting different communication sensitivity coefficients and minimum adjustable availability ratios for different resource types, the effective capacity impact of the same communication quality degradation varies across different resources, thus avoiding the shortcomings of existing methods that apply a "one-size-fits-all" approach to assessing the availability of flexible resources. Specifically, computing centers can be considered as flexible load resources (load-side flexible resources) in the power system, enabling effective capacity assessment and backup configuration for computer-computer collaboration. This addresses the issue in computer-computer collaboration scenarios where the reliable access to resources such as load regulation, task response, and supporting energy storage in computing centers deteriorates due to communication quality degradation in the control link, leading to a discrepancy between nominal and actual available capacity.

[0055] Step S3: Determine the effective adjustment capacity of each resource from the source node to the target node based on the effective adjustment capacity of each resource and the reachability coefficient of each resource between the source node and the target node.

[0056] In the actual operation of a power system, even if a resource has effective adjustable capacity, if line, section, or voltage constraints do not allow the adjustable capacity to be transferred to the target node, then the capacity cannot be fully included in the target node's reserve supply.

[0057] Assume the resource is located on the node The target node is Define resources From node To the node The upward adjustment coefficient and lower reachability coefficient The value ranges from 0 to 1.

[0058] The reachability factor can be determined by power flow sensitivity, cross-sectional margin, node voltage margin, line thermal stability margin, and regional mutual assistance capability. For example, the reachability factor can be defined as the proportion of the effective regulated capacity that resources can actually transmit from the current node to the target node, relative to its communication-reduced effective capacity, under the conditions of satisfying line capacity, cross-sectional limits, and voltage constraints. When there are no network constraints, the reachability factor is 1; when network constraints exist, the reachability factor is less than 1.

[0059] Specifically, the effective adjustable capacity for each resource to be transported from the source node to the target node is determined using the following formula: ; ; in, and Representing the source node respectively resources For the target node The effective upward transport capacity and the effective downward transport capacity; and Representing resources Upward and downward reachability coefficients between the source and target nodes.

[0060] This embodiment, by determining the effective transportable regulation capacity of each resource based on the reachability coefficient, avoids miscalculating resource capacity limited by line bottlenecks, cross-sectional congestion, or voltage constraints as available reserve at the target node, thus solving the problem of inflated reserve capacity in existing technologies where "resource capacity is sufficient but the grid is inaccessible." It also avoids overestimating the regulation potential of resources simply based on contracted capacity, providing a more reliable basis for flexible resource assessment in different scenarios under different carbon reduction stages.

[0061] Step S4: Determine the standby configuration of the target node based on the nominal adjustment capacity, effective adjustment capacity, and transportable effective adjustment capacity of each resource accessed by each source node, as well as the adjustment standby requirements of the target node. Step S4 includes S41 to S43.

[0062] S41. Calculate the total nominal adjustment capacity, total effective adjustment capacity, and total transmittable effective adjustment capacity that can be provided to the target node based on the nominal adjustment capacity, effective adjustment capacity, and transmittable effective adjustment capacity of each resource accessed by each source node.

[0063] S42. Based on the target node's adjustment reserve requirements and the total nominal adjustment capacity, determine the first reserve gap caused by the physical capacity of resources; based on the target node's adjustment reserve requirements and the total effective adjustment capacity, determine the second reserve gap caused by insufficient communication controllability; based on the target node's adjustment reserve requirements and the available effective adjustment capacity, determine the third reserve gap caused by insufficient network reachability.

[0064] S43. Determine the backup configuration of the target node based on the first backup gap, the second backup gap, and the third backup gap.

[0065] Specifically, in step S41, The nominal increase and decrease in total capacity can be expressed as follows: ; .

[0066] The total effective upward adjustment and the total effective downward adjustment of capacity can be expressed as: ; .

[0067] The total effective upward transport capacity and the total effective downward transport capacity can be expressed as: ; .

[0068] Specifically, in step S42, the adjustment reserve requirements of the target node are determined based on the target node's security reserve requirements, low-carbon adjustment reserve requirements, and communication risk reserve requirements, including: ; ; in, and These represent the upward and downward adjustment of reserve requirements for the target node, respectively. , , These represent the target node's increased backup requirements for security, increased backup requirements for low-carbon development, and increased backup requirements for communication risks, respectively. , , These represent the target node's security-based backup requirements, low-carbon-based backup requirements, and communication-risk-based backup requirements, respectively.

[0069] Furthermore, safety reserve requirements can be determined by net load forecasting errors, contingency reserves, and frequency security requirements; low-carbon regulation reserve requirements can be determined by carbon emission factors from electricity purchases, surplus renewable energy, and curtailment risks; and communication risk reserve requirements are used to compensate for the decline in the reliability of reserve supply caused by the degradation of communication controllability, and are determined based on historical data and experience.

[0070] Specifically, in step S42, The first reserve gap includes the first upward adjustment of the reserve gap. and the first reduction in reserve gap : ; ; The second reserve gap includes the second upward adjustment of the reserve gap. Second reduction in reserve gap : ; ; The third reserve gap includes the third upward adjustment reserve gap. and the third reduction in reserve gap : ; ; in, and Representing the target node respectively During the period The upward and downward adjustment of reserve requirements; , , , , , Target nodes During the period The nominal increase in capacity, the nominal decrease in capacity, the effective increase in capacity, the effective decrease in capacity, the total effective increase in transportable capacity, and the total effective decrease in transportable capacity.

[0071] In step S43, the backup configuration of the target node is determined based on the first backup gap, the second backup gap, and the third backup gap.

[0072] Specifically, when the first reserve gap is greater than 0, it is determined that the reserve gap mainly stems from insufficient physical capacity of resources. Different reserve configuration suggestions are generated for different resources: if the reserve gap mainly stems from insufficient storage capacity, suggestions for energy storage supplementary nodes and capacity ranges are generated; if the reserve gap mainly stems from insufficient load-side adjustable resources, suggestions for flexible load access scale and available scale are generated; if the reserve gap mainly stems from insufficient source-side regulation capacity, suggestions for supplementing regulation capacity with distributed power sources, conventional power sources, or low-carbon alternative power sources are generated.

[0073] When the first backup gap is 0 and the second backup gap is greater than 0, it indicates that the nominal adjustment capacity can meet the backup requirements, but the effective adjustment capacity after communication reduction is insufficient to meet the backup requirements. Therefore, the backup gap is determined to mainly stem from insufficient communication controllability. In this case, an enhanced solution is generated for communication links, control terminals, edge gateways, or aggregation platforms, or resources with higher communication controllability are prioritized for backup.

[0074] When the first and second backup gaps are 0, and the third backup gap is greater than 0, it indicates that the effective regulation capacity after communication reduction can meet the backup requirements, but the available effective regulation capacity is insufficient to meet the backup requirements. Therefore, it is determined that the backup gap mainly stems from insufficient network accessibility. In this case, solutions are generated to supplement local backup resources, enhance transferable channels, adjust tie switches, or improve the transmission capacity of critical sections.

[0075] This embodiment determines the system's regulatory reserve requirements based on safety reserves, low-carbon regulation reserves, and communication risk reserves. It then determines the reserve gap based on these requirements and the total regulation capacity, further defining the system's reserve configuration. This satisfies the system's ability to operate safely, operate in a low-carbon manner, and maintain stable operation while mitigating communication risks. It can cope with fluctuations in renewable energy and peak loads, while also supporting renewable energy consumption and high-carbon power purchase substitution. It can analyze reserve gaps caused by different factors and determine targeted reserve configurations, demonstrating good engineering feasibility. It can be applied to technologies such as source-grid-load-storage coordinated optimization, flexible resource assessment of digital distribution networks / provincial power systems, communication-power coupling systems, demand response, low-carbon dispatching, and reserve configuration.

[0076] Furthermore, the method of this invention can be applied to scenarios with a high proportion of new energy sources, multi-regional interconnection within provinces, diversified energy storage and flexible load participation in regulation, and power system operation that is highly dependent on communication acquisition and control platforms. Based on the degree of communication controllability degradation, it assesses the effective regulation capacity of flexible resources on the source side, grid side, load side, and storage side, constructs the matching relationship between reserve demand and reserve supply at the node or regional level, and outputs the collaborative optimization results under the constraints of reserve configuration, energy storage layout, available scale of flexible loads, source side regulation demand, and grid carrying capacity. It can support the structural morphology analysis of provincial power systems under different carbon reduction stages.

[0077] In one embodiment of the present invention, the source-grid-load-storage effective capacity assessment and backup configuration method taking into account communication degradation further includes: real-time correction and updating of calculation parameters based on actual response effects and communication status.

[0078] Specifically, if a certain type of resource still frequently experiences insufficient response even when the communication controllability evaluation is high, then the communication sensitivity coefficient of that resource should be increased. and ) or reduce the minimum available ratio ( and If a certain type of resource can still reliably respond through local control even under communication degradation, its minimum availability ratio can be appropriately increased. and ).

[0079] Assume the actual response capacity of the resource is the actual value. The predicted effective capacity is Response bias It can be represented as:

[0080] Parameters such as communication sensitivity coefficient and minimum availability ratio can be calibrated on a rolling basis based on response deviation. When the actual response capacity is lower than the predicted effective capacity and the deviation exceeds the threshold, the communication sensitivity coefficient of this type of resource is increased or the minimum availability ratio is decreased; when the actual response capacity consistently reaches or exceeds the predicted effective capacity, the communication sensitivity coefficient is decreased or the minimum availability ratio is increased. The calibration cycle can be determined based on the scheduling cycle, daily operation statistics, or rolling optimization cycle.

[0081] In this embodiment, the communication sensitivity coefficient and minimum availability ratio are calibrated in a rolling manner through an adaptive closed-loop calibration mechanism. The control strategy can be corrected in real time according to the actual response deviation, which effectively solves the problem of deviation between prediction and actual output caused by communication delay, environmental changes or equipment operating condition fluctuations. It reduces the risk of failure in demand response, energy storage, virtual power plants or distributed resource call during critical periods, and significantly improves the precise control capability and operating economy of resources.

[0082] System Implementation Examples One embodiment of the present invention discloses a source-network-load-storage effective capacity assessment and standby configuration system that takes into account communication degradation, including... The flexible resource nominal capacity calculation module is used to determine the nominal regulation capacity that each flexible resource can provide at the source node based on the physical parameters of each power grid flexible resource at the access source node.

[0083] An effective adjustment capacity reduction module is used to determine the effective adjustment capacity that the resource can provide at the source node based on the communication quality indicators of each terminal supporting the access source node.

[0084] The power grid reachability verification module is used to determine the effective regulation capacity that each resource can transmit from the source node to the target node based on the effective regulation capacity of each resource and the reachability coefficient of each resource between the source node and the target node.

[0085] The dynamic standby requirement configuration module is used to determine the standby configuration of the target node based on the nominal adjustment capacity, effective adjustment capacity, and transportable effective adjustment capacity of each resource of each source node and the adjustment standby requirement of the target node.

[0086] Furthermore, it may also include a rolling calibration module and an alarm module.

[0087] The rolling calibration module is used to correct and update the calculated parameters in real time based on the actual response effect and communication status.

[0088] The alarm module is used to send alarms when the communication controllability evaluation value is lower than the threshold, the backup gap exceeds the threshold, or the network accessibility is insufficient.

[0089] Compared with the prior art, the beneficial effects of the source-network-load-storage effective capacity assessment and backup configuration system that takes into account communication degradation provided in this embodiment are basically the same as those provided in the method embodiment, and will not be described in detail here.

[0090] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for assessing effective resource capacity and allocating reserve resources for computer-based collaborative computing, characterized in that, Includes the following steps: The nominal regulation capacity that each resource can provide at the source node is determined based on the physical parameters of each power grid flexible resource at the access source node. The effective regulation capacity that the resource can provide at the source node is determined based on the communication quality indicators of each terminal supporting the access source node. The effective adjustment capacity of each resource from the source node to the target node is determined based on the effective adjustment capacity of each resource and the reachability coefficient of each resource between the source node and the target node. The backup configuration of the target node is determined based on the nominal adjustment capacity, effective adjustment capacity, and transportable effective adjustment capacity of each resource accessed by each source node, as well as the adjustment backup requirements of the target node.

2. The method for assessing effective resource capacity and configuring reserve according to claim 1, characterized in that, The communication quality indicators include telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality. The determination of the effective regulation capacity that the resource can provide at the source node based on the communication quality indicators of each terminal supporting the access source node includes: The communication controllability evaluation value of each terminal is calculated based on the telemetry integrity, command success rate, latency satisfaction, response confirmation rate and key communication quality of each terminal. The resource-level communication controllability evaluation value of the resource at the source node is determined based on the communication controllability evaluation value of each terminal. The communication reduction coefficient of the resource at the source node is calculated based on the resource-level communication controllability evaluation value; The effective regulation capacity that the resource can provide at the source grid node is determined based on the communication reduction factor and nominal regulation capacity of the resource at the source node.

3. The method for assessing effective resource capacity and allocating reserves according to claim 2, characterized in that, The following formula is used to calculate the communication controllability evaluation value for each terminal based on telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality: ； Among them, subscript , , , These respectively represent the terminal supporting the flexible resources of the power grid, the flexible resources of the power grid, the node, and the time period; Represents a node China supports the flexible resources of the power grid terminal During the period The communication controllability evaluation value; , , , , These represent nodes. China supports the flexible resources of the power grid terminal During the period Telemetry integrity, command success rate, latency satisfaction, response confirmation rate, and key communication quality; For the corresponding weights, , .

4. The method for assessing effective resource capacity and configuring reserve according to claim 2, characterized in that, The resource-level communication controllability evaluation value of this resource at the source node is determined using the following formula based on the communication controllability evaluation value of each terminal: ； in, Indicating flexible resources of the power grid At the node During the period The resource-level communication controllability evaluation value; Represents a node China supports the flexible resources of the power grid terminal During the period The communication controllability evaluation value; Represents a node China supports the flexible resources of the power grid terminal The association weight.

5. The method for assessing effective resource capacity and configuring backup as described in claim 4, characterized in that, The communication reduction factor for this resource at the source node is calculated using the following formula based on the resource-level communication controllability evaluation value: ； ； in, and They are nodes resources During the period The upward and downward communication reduction coefficients; and These represent the minimum upward and minimum downward availability percentages that can be retained even under severe communication degradation, respectively. and Representing resources Sensitivity coefficient to communication degradation; and These represent the communication reduction correction terms after adjusting the resource-level communication controllability evaluation value by the sensitivity coefficients in the upward and downward directions, respectively.

6. The method for assessing effective resource capacity and configuring reserve according to claim 5, characterized in that, The effective regulation capacity that the resource can provide at the source node is determined using the following formula, based on the communication reduction factor and nominal regulation capacity of the resource at the source node: ； ； in, and They are nodes resources During the period Effective upward and downward capacity adjustments; and They are nodes resources During the period The nominal increase and nominal decrease in capacity.

7. The method for assessing effective resource capacity and configuring reserve according to claim 6, characterized in that, The transportable effective regulation capacity of the resource to the target node is determined using the following formula, based on the effective regulation capacity and the reachability coefficient of the resource between the source node and the target node: ； ； in, and Representing the source node respectively resources For the target node The effective upward transport capacity and the effective downward transport capacity; and Representing resources Upward and downward reachability coefficients between the source and target nodes.

8. The method for assessing effective resource capacity and configuring reserve according to claim 1, characterized in that, The determination of the backup configuration of the target node based on the nominal adjustment capacity, effective adjustment capacity, transportable effective adjustment capacity, and adjustment backup requirements of each resource accessed by each source node includes: The total nominal regulation capacity, total effective regulation capacity, and total transportable effective regulation capacity that can be provided to the target node are calculated based on the nominal regulation capacity, effective regulation capacity, and transportable effective regulation capacity of each resource connected to each source node. The first reserve gap caused by the physical capacity of resources is determined based on the adjustment reserve demand and the total nominal adjustment capacity of the target node; the second reserve gap caused by insufficient communication controllability is determined based on the adjustment reserve demand and the total effective adjustment capacity of the target node; and the third reserve gap caused by insufficient network reachability is determined based on the adjustment reserve demand and the available effective adjustment capacity of the target node. The backup configuration of the target node is determined based on the first backup gap, the second backup gap, and the third backup gap.

9. The method for assessing effective resource capacity and configuring reserve according to claim 8, characterized in that, The first reserve gap includes the first upward adjustment of the reserve gap. and the first reduction in reserve gap : ; ; The second reserve gap includes the second upward adjustment of the reserve gap. Second reduction in reserve gap : ; ; The third reserve gap includes the third upward adjustment reserve gap. and the third reduction in reserve gap : ; ; in, and Representing the target node respectively During the period The upward and downward adjustment of reserve requirements; , , , , , Target nodes During the period The nominal increase in capacity, the nominal decrease in capacity, the effective increase in capacity, the effective decrease in capacity, the total effective increase in transportable capacity, and the total effective decrease in transportable capacity.

10. The method for assessing effective resource capacity and configuring reserve according to claim 1, characterized in that, The adjustment reserve requirements of the target node are determined based on the target node's security reserve requirements, low-carbon adjustment reserve requirements, and communication risk reserve requirements, including: ； ； in, and These represent the upward and downward adjustment of reserve requirements for the target node, respectively. , , These represent the target node's increased backup requirements for security, increased backup requirements for low-carbon development, and increased backup requirements for communication risks, respectively. , , These represent the target node's security-based backup requirements, low-carbon-based backup requirements, and communication-risk-based backup requirements, respectively.

Images