A resource cooperative configuration method and system based on operation characteristic matching

Abstract

The application is suitable for the technical field of distribution network optimization configuration, and provides a resource collaborative configuration method and system based on operation characteristic matching, which comprises the following steps: obtaining operation data and adjustment demand characteristics of each type of power source and adjustable resource in a power system, dividing the adjustment demand characteristics into multiple levels according to the time scale and extracting corresponding technical output characteristic parameters, calculating a characteristic calibration offset by using the deviation between the actual output sequence of the selected reference adjustment resource in the power system and the adjustment demand characteristics, and correcting the adjustment demand characteristics of each level, performing layer-by-layer hierarchical matching on the corrected adjustment demand characteristics for each level, performing output time sequence coupling analysis on the output resource combination, and judging whether there is an adjustment capacity gap, when the gap exists, determining the type and technical specification of the adjustment resource to be added, and incorporating the adjustment resource into the collaborative configuration scheme. The application significantly improves the technical reliability of the resource collaborative configuration scheme.

Description

Technical Field

[0001] This invention relates to the field of power distribution network optimization configuration technology, and in particular to a resource collaborative configuration method and system based on matching operational characteristics. Background Technology

[0002] With the continuous growth of installed capacity of new energy power generation, the power system is facing increasing regulation pressure. In power systems with a high proportion of new energy sources, in order to ensure the safe and stable operation of the system, it is usually necessary to coordinate the allocation of new energy power sources such as wind power and photovoltaic power with adjustable resources such as thermal power, energy storage, and pumped storage. In existing technologies, resource coordination allocation methods typically collect operating data of various power sources and adjustable resources, extract technical output characteristic parameters from them, such as ramp rate, minimum technical output, and response delay, and then match these characteristic parameters with the overall regulation requirements of the system, calculate the degree of matching between each resource and the requirements, sort and filter the resources according to the degree of matching, and finally select the resources with the highest degree of matching to form a coordination allocation scheme.

[0003] Existing methods typically process adjustment needs and resource characteristic parameters at different time scales into the same matching matrix during the matching process, resulting in high computational complexity and difficulty in accurately distinguishing the applicability of each resource at different time scales. At the same time, the system adjustment demand characteristics are usually generated based on load forecasting and new energy output forecasting, which have inherent forecasting biases. This leads to insufficient adjustment capacity or over-configuration of the matching results in actual operation, reducing the technical feasibility of resource allocation schemes under real operating conditions and causing low reliability of resource collaborative allocation. Summary of the Invention

[0004] This invention provides a resource collaborative configuration method and system based on runtime characteristic matching, which addresses the problem that existing matching methods reduce the technical feasibility of resource configuration schemes under real-world operating conditions, leading to low reliability of resource collaborative configuration.

[0005] The first aspect of this invention provides a resource collaborative configuration method based on runtime characteristic matching, comprising: The system acquires operational data of various types of power sources and adjustable resources within the power system, as well as the adjustment demand characteristics of the power system at different time scales. The adjustment demand characteristics are divided into multiple levels according to the time scale, and the technical output characteristic parameters of each resource corresponding to each level are extracted from the operation data. In the power system, multiple flexible regulation resources with complete operating data are selected as benchmark regulation resources. Based on the deviation between the actual output sequence of each benchmark regulation resource at each level and the regulation demand characteristics of that level, the characteristic calibration offset of each level is calculated and the regulation demand characteristics of the corresponding level are corrected. For each level, hierarchical matching is performed using the technical output characteristic parameters of that level and the modified adjustment demand characteristics, and the matching result of the previous level is used as the input range for the matching of the next adjacent level. Perform output time-series coupling analysis on the resource combination of the final output of hierarchical matching, calculate the output complementarity rate and ramp synergy, and determine whether there is a gap in adjustment capacity exceeding a preset threshold. If the aforementioned regulation capacity gap exists, the type and technical specifications of the regulation resources to be added are determined based on the power, duration, and response time parameters corresponding to the regulation capacity gap, and the type and technical specifications of the regulation resources to be added are incorporated into the collaborative configuration scheme.

[0006] Furthermore, the adjustment demand characteristics are divided into multiple levels according to a time scale, and the technical output characteristic parameters of each resource corresponding to each level are extracted from the operational data, including: The aforementioned adjustment demand characteristics are divided into long-cycle balancing layer, intraday adjustment layer and rapid adjustment layer according to the time scale from long to short. For each resource at each level, extract the technical output characteristic parameters of that resource at that level based on the corresponding operational data. The technical output characteristic parameters corresponding to the long-cycle balancing layer include continuous operating time and guaranteed output level; the technical output characteristic parameters corresponding to the intraday adjustment layer include ramp rate and minimum technical output; and the technical output characteristic parameters corresponding to the rapid adjustment layer include response delay and operating condition switching time.

[0007] Furthermore, the calculation of the characteristic calibration offset for each level based on the deviation between the actual output sequence of each reference regulation resource at each level and the regulation demand characteristics of that level includes: For each benchmark adjustment resource, a benchmark adjustment characteristic curve corresponding to each level is constructed based on the historical operating data of the benchmark adjustment resource at each level. For each level, based on the benchmark adjustment characteristic curve corresponding to each benchmark adjustment resource and the adjustment demand characteristics of the level, the adjustment deviation of the benchmark adjustment characteristic curve relative to the adjustment demand characteristics is determined at each time section. For each level, the characteristic calibration offset of the level is calculated based on the adjustment deviation corresponding to multiple reference adjustment resources within the level.

[0008] Furthermore, the modification of the adjustment requirement characteristics at the corresponding level includes: For each level, the characteristic calibration offset of the level is superimposed with the original adjustment demand feature of the level, and the characteristic value of the adjustment demand feature at each time section is corrected using the characteristic calibration offset to obtain the corrected adjustment demand feature.

[0009] Furthermore, the step of performing hierarchical matching of the technical output characteristic parameters of each level with the modified adjustment demand characteristics includes: For each level, the technical output characteristic parameters corresponding to that level are divided into dominant adjustment characteristic parameters and auxiliary adjustment characteristic parameters; Based on the dominant regulation characteristic parameters and the regulation demand characteristics after hierarchical correction, the first-level screening is performed on the resources to be matched at the hierarchical level to obtain the initial screening resource set; Based on the auxiliary adjustment characteristic parameters, a second-level screening is performed on the initial screening resource set to obtain the candidate resource set of the aforementioned level.

[0010] Furthermore, the first-level screening of the resources to be matched at the aforementioned level yields a preliminary set of resources, including: Obtain the dominant regulation characteristic threshold corresponding to the level; The dominant regulation characteristic parameter of each resource to be matched at the level is compared with the dominant regulation characteristic threshold. Resources to be matched that do not meet the dominant regulation characteristic threshold are removed to obtain the initial screening resource set; Specifically, when the dominant regulation characteristic parameter of the resource to be matched is missing at the level, the dominant regulation characteristic parameter is supplemented based on the statistical characteristic value of the operating resources of the same type as the resource to be matched in the power system, and the supplemented resource is marked before the comparison is performed.

[0011] Furthermore, the second-level screening of the initial resource set to obtain the candidate resource set at the next level includes: For each resource in the initial screening resource set, the hierarchical fit between the resource and the hierarchical adjusted adjustment demand characteristics is calculated based on the auxiliary adjustment characteristic parameters of the resource at the level. According to the order of the hierarchical adaptability from high to low, a preset number of resources are selected from the initial screening resource set to form the candidate resource set of the level.

[0012] Furthermore, the step of performing output time-series coupling analysis on the resource combination of the final output of hierarchical matching, and calculating the output complementarity rate and climbing synergy, includes: Obtain the output time sequence of each resource in the resource combination at each sampling point within a preset time period; The output complementarity rate of the resource combination is calculated as follows: in: For the power complementarity rate, The total number of resources in the resource portfolio. This represents the total number of sampling points within a preset time period. For the first The resource in the first The actual output value of each sampling point For the first The average output value of each resource within a preset time period. This represents the average total output of the resource combination over a preset time period. The climbing synergy of the resource combination is calculated as follows: in: For climbing coordination, For the first time period within the preset time period From the sampling point to the... The change in the regulation demand of the power system between the sampling points For the first The change in output of each resource within the corresponding sampling interval.

[0013] Furthermore, determining the type and technical specifications of the additional regulation resources needed based on the power, duration, and response time parameters corresponding to the regulation capacity gap includes: Obtain the power deficit value, duration threshold, and response time upper limit corresponding to the regulation capacity gap; Based on the upper limit of response time, at least one candidate adjustment resource type that meets the upper limit of response time is selected from the preset adjustment resource type library; Based on the power deficit value and the duration threshold, the type of regulation resource to be added is determined from the at least one candidate regulation resource type, and the power specification and capacity specification corresponding to the type of regulation resource to be added are determined.

[0014] A second aspect of the present invention provides a resource collaborative configuration system based on runtime characteristic matching, comprising: The operation data and regulation demand characteristics acquisition module is used to acquire the operation data of various types of power sources and adjustable resources in the power system, as well as the regulation demand characteristics of the power system at different time scales. The technical output characteristic parameter extraction module is used to divide the adjustment demand characteristics into multiple levels according to the time scale, and extract the technical output characteristic parameters of each resource corresponding to each level from the operation data. The characteristic calibration offset calculation module is used to select multiple flexible regulation resources with complete operating data as reference regulation resources in the power system, and calculate the characteristic calibration offset of each level and correct the regulation demand characteristics of the corresponding level based on the deviation between the actual output sequence of each reference regulation resource at each level and the regulation demand characteristics of that level. The hierarchical matching module is used to perform hierarchical matching for each level by using the technical output characteristic parameters of that level and the modified adjustment demand characteristics, and the matching result of the previous level is used as the input range for the matching of the next adjacent level. The output complementarity rate and ramp synergy calculation module is used to perform output time-series coupling analysis on the resource combination of the final output of hierarchical matching, calculate the output complementarity rate and ramp synergy, and determine whether there is a gap in adjustment capacity exceeding a preset threshold. The collaborative configuration scheme determination module is used to determine the type and technical specifications of the additional regulation resources to be added based on the power, duration and response time parameters corresponding to the regulation capacity gap if the gap exists, and to incorporate the type and technical specifications of the additional regulation resources to be added into the collaborative configuration scheme.

[0015] As can be seen from the above technical solutions, the present invention has the following advantages: This invention acquires operational data of various types of power sources and adjustable resources within the power system, as well as regulation demand characteristics at different time scales. It then divides these regulation demand characteristics into multiple levels according to time scale and extracts corresponding technical output characteristic parameters. Using the deviation between the actual output sequence of selected benchmark adjustable resources in the power system and the regulation demand characteristics, it calculates characteristic calibration offsets and corrects the regulation demand characteristics at each level. For each level, it performs hierarchical matching using the corrected regulation demand characteristics. Finally, it performs output time-series coupling analysis on the output resource combination and determines whether there is a regulation capacity gap. When a gap exists, it determines the type and technical specifications of the adjustable resources that need to be added and incorporates them into the collaborative configuration scheme. This invention achieves hierarchical matching of regulation demand characteristics across time scales, decoupling regulation demands and resource characteristic parameters layer by layer. This reduces computational complexity and improves matching efficiency. By introducing benchmark regulation resources to calibrate and correct deviations in system regulation demand characteristics, the inherent biases in load forecasting and renewable energy output forecasting are eliminated, ensuring reliable regulation capabilities of the matched resource combinations under real-world operating conditions. Furthermore, through quantitative identification of regulation capacity gaps and determination of additional resource types and technical specifications, the collaborative configuration scheme can compensate for structural regulation capacity deficiencies in the system. This enables precise collaborative configuration of multiple power sources and adjustable resources across multiple time scales, significantly improving the technical reliability of the resource collaborative configuration scheme. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a resource collaborative configuration method based on runtime characteristic matching in this invention. Figure 2 This is a schematic diagram of the process for calculating the characteristic calibration offset of each level in this invention; Figure 3 This is a schematic diagram of the hierarchical matching process in this invention; Figure 4 This is a schematic diagram of the first-level screening process in this invention; Figure 5 This is a schematic diagram of the second-level screening process in this invention; Figure 6 This is a flowchart illustrating the process of determining the type and technical specifications of the adjustment resources that need to be added in this invention. Detailed Implementation

[0017] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “corresponding to,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0018] Example 1 Please see Figure 1 The resource collaborative configuration method based on runtime characteristic matching provided in this application includes the following steps: S1. Obtain operational data of various types of power sources and adjustable resources within the power system, as well as the characteristics of the power system's regulation demand at different time scales; The power sources include both renewable energy sources and conventional power sources. Renewable energy sources specifically include wind turbines and photovoltaic arrays, while conventional power sources include thermal power units and hydropower units. Adjustable resources include energy storage devices and pumped-storage units. Energy storage devices specifically include electrochemical energy storage systems and compressed air energy storage systems. Operational data is collected from monitoring and data acquisition systems, energy management systems, or power prediction systems connected to each type of power source and adjustable resource, according to a specific data acquisition cycle. The operational data includes the actual output sequence and corresponding predicted output sequence of renewable energy sources within a certain historical period; the ramp rate, start-up and shutdown time, and minimum technical output of thermal power units; the output adjustment range and operating condition transition time of hydropower units; the charging and discharging power range, continuous charging and discharging duration, and response delay of energy storage devices; and the pumping-to-generation conversion efficiency and continuous operating time of pumped-storage units.

[0019] Regulation demand characteristics refer to the regulation capacity requirements of a power system for various types of power sources and adjustable resources at different time scales in order to maintain active power balance and frequency stability. Different time scales can be divided into long-cycle balance layer, intraday regulation layer, and fast regulation layer according to regulation response speed and duration. The long-cycle balance layer corresponds to monthly or quarterly time scales, reflecting the power system's demand for power balance and capacity adequacy regulation under seasonal changes in energy output and load. The intraday regulation layer corresponds to 15-minute to hourly time scales, reflecting the power system's peak-shaving and ramp-up regulation needs under intraday load peak-valley changes and fluctuations in renewable energy output. The fast regulation layer corresponds to second- to minute-level time scales, reflecting the power system's rapid power support needs during primary frequency regulation and transient stabilization processes. Specifically, load forecast data, renewable energy output forecast data, and system reserve capacity requirements of the power system are obtained. Combined with regulation capacity calculation models for each time scale, regulation demand characteristics corresponding to each level are generated. These characteristics can include the regulation power demand, regulation duration requirements, and response time requirements at each sampling point.

[0020] S2. Divide the adjustment demand characteristics into multiple levels according to the time scale, and extract the technical output characteristic parameters of each resource corresponding to each level from the operational data; Because the regulation needs of power systems vary significantly across different time scales—for example, seasonal changes in energy output require long-term, continuous regulation capabilities, while transient frequency fluctuations require millisecond-level rapid response capabilities—it is necessary to stratify the regulation demand characteristics according to time scales. This allows for targeted matching of regulation needs at different levels with the technical characteristics of resources at different time scales. Specifically, this includes the following: 1. Divide the adjustment demand characteristics into long-cycle balancing layer, intraday adjustment layer and rapid adjustment layer according to the time scale from long to short; 2. For the operational data of each resource at each level, extract the technical output characteristic parameters of that resource at that level; among them, the technical output characteristic parameters corresponding to the long-cycle balance layer include continuous running time and guaranteed output level, the technical output characteristic parameters corresponding to the intraday adjustment layer include ramp rate and minimum technical output, and the technical output characteristic parameters corresponding to the rapid adjustment layer include response delay and operating condition transition time.

[0021] Specifically, the long-cycle balancing layer corresponds to a monthly or quarterly time scale, reflecting the power system's demand for power balance and capacity adequacy regulation under seasonal changes in energy output and load. When extracting the technical output characteristic parameters of resources at this level, their continuous operating time and guaranteed output level can be statistically analyzed from their historical operating data. Continuous operating time refers to the longest continuous operating time that the resource can maintain above its rated output or a specified output level after a single startup. Guaranteed output level refers to the power value that the resource can guarantee with a specified probability within a preset statistical period. These two parameters reflect the resource's ability to provide continuous power support under a long-cycle time scale. The intraday regulation layer corresponds to a 15-minute to hourly time scale, reflecting the power system's peak-shaving and ramp-up regulation needs under intraday load peak-valley changes and fluctuations in new energy output. When extracting the technical output characteristic parameters of a resource at this level, its ramp rate and minimum technical output can be extracted from its historical operating data. The ramp rate refers to the change in output of the resource per unit time, specifically including upward and downward ramp rates, reflecting the resource's ability to track load changes and fluctuations in renewable energy output. The minimum technical output refers to the lowest output level that the resource can maintain under stable operating conditions, reflecting the resource's downward adjustment potential during periods of low system load. The rapid adjustment layer corresponds to a time scale of seconds to minutes, reflecting the power system's rapid power support requirements during primary frequency regulation and transient stabilization processes. When extracting the technical output characteristic parameters of a resource at this level, its response delay and operating condition transition time can be obtained from the historical operating data of the resource. Response delay refers to the time interval between the resource receiving the regulation command and the start of the output change. Operating condition transition time refers to the time required for the resource to switch between different operating conditions, such as the time for energy storage equipment to switch from charging to discharging, or the time for pumped storage units to switch from pumping to generating. These parameters determine the resource's ability to provide immediate power support in the fast regulation layer.

[0022] Through the above-described hierarchical extraction process, the technical output characteristic parameters of each resource at each level are organized into corresponding parameter sets, which serve as the basis for subsequent hierarchical matching processing.

[0023] S3. Select multiple flexible regulation resources with complete operating data in the power system as benchmark regulation resources. Based on the deviation between the actual output sequence of each benchmark regulation resource at each level and the regulation demand characteristics of that level, calculate the characteristic calibration offset of each level and correct the regulation demand characteristics of the corresponding level. Benchmark regulation resources refer to flexible regulation resources that have been operating stably in the power system for a long time, with complete operational data records and verified regulation characteristics. Examples include hydropower units that have been in operation for many years and have complete operational records, electrochemical energy storage power stations that have completed performance testing and are continuously monitored, and thermal power units that participate in deep peak shaving and have complete operational data. Since system regulation demand characteristics are generated based on load forecasting and renewable energy output forecasting, inherent biases in the forecast data can lead to differences between demand characteristics and actual system operating demand. Benchmark regulation resources, as operational resources that actually participate in system regulation, can accurately reflect the system's demand for regulation capacity at different times through their actual output sequences. Therefore, the actual operational data of benchmark regulation resources can be used to calibrate and correct the forecasted demand characteristics, eliminating the impact of forecast bias on the subsequent matching process. Please refer to [link to relevant documentation]. Figure 2 The following is a detailed explanation of each step: S31. For each benchmark adjustment resource, construct the benchmark adjustment characteristic curve corresponding to each level based on the historical operating data of the benchmark adjustment resource at each level; The baseline regulation characteristic curve reflects the actual regulation capability of the baseline regulation resource at each time scale over time. Specifically, for each baseline regulation resource, the actual output sequence of that resource at each level within a preset historical period is obtained. For the long-cycle balancing layer, the daily average output sequence of the baseline regulation resource within a preset historical year or quarter can be obtained; for the intraday regulation layer, the output sequence of the baseline regulation resource every 15 minutes or hour within a preset historical period can be obtained; for the fast regulation layer, the high-resolution output sequence of the baseline regulation resource at the second or minute level within a preset historical period can be obtained. The obtained actual output sequences are cleaned to remove abnormal operating conditions and missing points caused by communication interruptions, and the missing points are filled in using interpolation methods to obtain the baseline regulation characteristic curve corresponding to each level. The baseline regulation characteristic curve can be represented as: in: Indicates the first The benchmark adjustment resources in the first The reference adjustment characteristic curve of the hierarchy, The value can be selected as a long-term balancing layer, an intraday adjustment layer, or a rapid adjustment layer. This represents the total number of sampling points at this level. Indicates the first The benchmark adjustment resources in the first Level 1 The actual output value of each sampling point.

[0024] S32. For each level, based on the benchmark adjustment characteristic curve corresponding to each benchmark adjustment resource and the adjustment demand characteristics of the level, determine the adjustment deviation of the benchmark adjustment characteristic curve relative to the adjustment demand characteristics at each time section. Specifically, for each level Obtain the original adjustment demand characteristic curve for this level. The regulation demand characteristic curve can be represented as a sequence of regulation power demand at each sampling point: in: Indicates the first The level is at the The adjustment power requirement of each sampling point This represents the total number of sampling points at this level.

[0025] For each benchmark adjustment resource Reference adjustment characteristic curve at this level The difference between the benchmark regulation characteristic curve and the regulation demand characteristic curve at each sampling point is calculated to obtain the regulation deviation of the benchmark regulation resource at each sampling point. The formula for calculating the regulation deviation is: in: Indicates the first The benchmark adjustment resources in the first Level 1 The adjustment deviation of each sampling point. If A positive value indicates that the actual output of the benchmark regulation resource at that sampling point is higher than the predicted regulation demand; a negative value indicates that the actual output is lower than the predicted regulation demand. The [number]th [item / section]... The adjustment deviation of each reference adjustment resource at all sampling points in this level is organized into a sequence of adjustment deviations corresponding to that reference adjustment resource: .

[0026] S33. For each level, calculate the characteristic calibration offset of the level based on the adjustment deviation corresponding to multiple benchmark adjustment resources within the level.

[0027] Since the regulation deviation of a single benchmark regulation resource may be affected by its own operating conditions or local grid constraints, to obtain more representative system-level deviation characteristics, it is necessary to perform a fusion calculation of the regulation deviations of multiple benchmark regulation resources within the same level. Specifically, for the level... Get all items within this level. Each benchmark adjustment resource corresponds to a sequence of adjustment deviations. For the same sampling point The characteristic calibration offset of this level at this sampling point is obtained by weighted averaging of the adjustment deviations of multiple benchmark adjustment resources. The weighted calculation formula is as follows: in: Indicates the first The level is at the Characteristic calibration offset of each sampling point For the first The total number of baseline adjustment resources within the tier. For the first The benchmark adjustment resources in the first The weighting coefficients for each level. The weights can be determined based on the operational reliability indicators of each benchmark adjustment resource at that level. For example, the historical operational availability rate of the benchmark adjustment resource at that level can be used as the weight, with higher operational availability rates assigning greater weights. This makes the fusion calculation results more reflective of the reliability level of deviations from the actual adjustment demands of the system. This leads to the... The hierarchical characteristic calibration offset sequence is .

[0028] In this embodiment, the correction of the adjustment demand characteristics of the corresponding level includes: for each level, superimposing the characteristic calibration offset of the level with the original adjustment demand characteristics of the level, and using the characteristic calibration offset to correct the characteristic values ​​of the adjustment demand characteristics at each time section to obtain the corrected adjustment demand characteristics.

[0029] For hierarchy Obtain the original adjustment demand characteristic curve for this level. and the calculated characteristic calibration offset sequence The two are superimposed and corrected at each sampling point, and the corrected adjustment demand characteristics are obtained. The calculation formula is: That is, for each sampling point The revised regulation power requirement is: ;in, Indicates the first The level is at the The adjusted power demand after correction at each sampling point This represents the original regulating power demand. The offset is used to calibrate the characteristics of this level at this sampling point.

[0030] Through the above calibration and correction process, the original regulation demand characteristics generated based on the predicted data are corrected by the measured operating data. The corrected regulation demand characteristics can more accurately reflect the real regulation demand of the power system at different time scales, providing a more reliable demand benchmark for subsequent hierarchical matching at each level, thereby improving the technical feasibility of resource collaborative allocation schemes under actual operating conditions.

[0031] S4. For each level, use the technical output characteristic parameters of that level and the modified adjustment demand characteristics to perform hierarchical matching, and use the matching result of the previous level as the input range for the matching of the next adjacent level. Because the requirements for resource adjustment capabilities differ fundamentally across different time scales, mixing multi-level needs with resource characteristics for matching can easily lead to key adjustment capabilities at one level being masked by secondary characteristics at other levels, thus identifying resources that cannot meet the hard adjustment constraints at a particular level. Furthermore, directly performing multi-dimensional, detailed calculations on all resources would result in excessive computational overhead during the matching process. Therefore, a hierarchical matching strategy is adopted. Within each level, a coarse screening is first performed using key hard indicators, followed by a finer selection using auxiliary quality indicators. The results of the upper-level screening are then passed down to the lower level as input, gradually narrowing the matching range and achieving decoupling and efficient screening of multi-timescale adjustment needs. Please refer to [link / reference]. Figures 3 to 5 The following provides a detailed explanation of each step: S41. For each level, the technical output characteristic parameters corresponding to the level are divided into dominant adjustment characteristic parameters and auxiliary adjustment characteristic parameters; Dominant regulation characteristic parameters refer to the hard technical indicators that directly affect whether resources can be used for regulation at the corresponding level and determine whether resources have basic regulation availability. Auxiliary regulation characteristic parameters refer to the optimization technical indicators that affect the quality and efficiency of resource regulation while meeting basic regulation availability. For the long-cycle balancing layer, dominant regulation characteristic parameters include continuous operating time, and auxiliary regulation characteristic parameters include guaranteed output level. For the intraday regulation layer, dominant regulation characteristic parameters include ramp rate and minimum technical output, and auxiliary regulation characteristic parameters may include output regulation range. For the rapid regulation layer, dominant regulation characteristic parameters include response delay, and auxiliary regulation characteristic parameters include operating condition transition time. Dividing characteristic parameters into dominant and auxiliary categories ensures that the hard regulation capability of resources meets the basic operating requirements of the system during subsequent screening. Resources that meet the basic requirements are then selected for quality optimization, avoiding the introduction of resources with substandard regulation capabilities due to interference from the weighting of auxiliary indicators.

[0032] S42. Based on the dominant regulation characteristic parameters and the regulation demand characteristics after hierarchical correction, perform the first-level screening of the resources to be matched at each level to obtain the initial screening resource set; The purpose of the first-level screening is to quickly remove resources that cannot meet the basic adjustment capability requirements from the pool of resources to be matched, based on the hard thresholds corresponding to the dominant adjustment characteristic parameters of each level. Specifically: S421. Obtain the threshold value of the dominant regulation characteristic corresponding to the level; The dominant regulation characteristic threshold is a pre-determined technical parameter limit based on the basic regulation capability requirements of the target power system at each level. This threshold characterizes the minimum technical performance standard that resources must meet to participate in regulation at the corresponding level. Specifically, it involves obtaining the minimum regulation capability indicators specified in the operating procedures or safety and stability guidelines of the target power system at the corresponding level. For example, the maximum allowable delay of primary frequency regulation on resource response time in the fast regulation level, the minimum requirement of peak shaving on resource ramp rate in the intraday regulation level, and the minimum requirement of seasonal power balance on continuous resource operation time in the long-cycle balance level. Combined with the corrected regulation demand characteristics of the target power system at that level, the technical requirements implied by the regulation demand characteristics at each sampling point are statistically analyzed. For example, the minimum required ramp rate or the maximum required response delay of the corrected regulation demand characteristics at each sampling point is taken as the dominant regulation characteristic threshold for that level.

[0033] S422. Compare the dominant regulation characteristic parameter of each resource to be matched with the dominant regulation characteristic threshold at the level; For hierarchy Assuming its dominant regulatory characteristic parameters include The corresponding threshold for the dominant regulatory characteristic of this indicator is: For each resource to be matched Extract its hierarchical structure of The dominant regulating characteristic parameter value Each parameter is compared with its corresponding threshold. The comparison method is determined based on the parameter type: for parameters with larger values ​​indicating stronger adjustment capabilities, such as ramp rate and continuous running time, the parameter value is checked to see if it is greater than or equal to the corresponding lower threshold; for parameters with smaller values ​​indicating stronger adjustment capabilities, such as response delay and minimum technical output, the parameter value is checked to see if it is less than or equal to the corresponding upper threshold.

[0034] S423. Eliminate resources to be matched whose dominant regulation characteristic parameters do not meet the dominant regulation characteristic threshold to obtain the initial screening resource set; wherein, when the dominant regulation characteristic parameters of the resource to be matched are missing at the level, the dominant regulation characteristic parameters are supplemented based on the statistical characteristic values ​​of the operating resources of the same type as the resource to be matched in the power system, and the supplemented resources are marked before comparison is performed.

[0035] For resources to be matched If all of them If all dominant regulation characteristic parameters meet the corresponding dominant regulation characteristic thresholds, the resource to be matched is retained in the initial screening resource set. If any dominant regulation characteristic parameter does not meet the corresponding threshold, the resource to be matched is removed and not processed further. When the dominant regulation characteristic parameters of the resource to be matched are missing at the hierarchical level due to insufficient operational data, a statistical completion strategy of the same type is adopted: identify operational resources in the target power system that belong to the same resource type as the resource to be matched and have accumulated complete operational data; extract the statistical feature value of the same dominant regulation characteristic parameter at the corresponding level from the operational data of the operational resources. The statistical feature value can be the mean of the corresponding parameter of the operational resources of this type; use the statistical feature value as the completion value of the missing parameter and generate a completion tag for the resource to be matched. The completion tag is used to indicate that the dominant regulation characteristic parameter of the resource at the hierarchical level is obtained through statistical estimation rather than actual operational measurement value. After the parameter completion is completed, the resource to be matched participates in the above threshold comparison process together with other resources to be matched with complete parameter values.

[0036] Through the first-level screening, resources whose dominant regulatory characteristic parameters meet the hard threshold requirements are retained among the resources to be matched, forming a preliminary set of resources.

[0037] S43. Based on the auxiliary adjustment characteristic parameters, perform a second-level screening on the initial screening resource set to obtain a hierarchical candidate resource set.

[0038] The purpose of the second-level screening is to quantitatively evaluate and prioritize the resources that have passed the first-level screening, selecting a predetermined number of resources from the initial screening set that best match the revised adjustment requirements at this level as a candidate resource set. Specifically: S431. For each resource in the initial screening resource set, calculate the hierarchical fit between the resource and the hierarchical-corrected adjustment demand characteristics based on the auxiliary adjustment characteristic parameters of the resource at the hierarchical level. Hierarchical fit is used to comprehensively measure the degree of matching between the auxiliary adjustment characteristic parameters of resources at a hierarchy and the modified adjustment demand characteristics. For hierarchy... The revised regulation demand characteristics are used to extract the reference value of the auxiliary regulation characteristics at this level; for each resource in the initial screening resource set... Extract its hierarchical structure The auxiliary adjustment characteristic parameter values ​​are used to calculate the deviation between each auxiliary adjustment characteristic parameter value and the corresponding demand reference value. Then, a weighted sum of each deviation is performed to obtain the hierarchical adaptability of the resource at that level. The formula for calculating the hierarchical adaptability can be expressed as: in: Representing resources In the The level of adaptation ranges from 0 to 1, with the value closer to 1 indicating a higher degree of adaptation. The number of auxiliary adjustment characteristic parameters at this level; Representing resources In the Level 1 The actual values ​​of the auxiliary adjustment characteristic parameters; Indicates the first The hierarchical adjustment demand characteristics are in the first place. The required reference value for auxiliary regulation characteristics can be determined based on the statistical values ​​of each sampling point in the modified regulation demand characteristics. For the first Level 1 The weighting coefficients of the auxiliary regulation characteristic parameters are determined based on the degree of emphasis the target power system places on each auxiliary characteristic under the current operating scenario.

[0039] S432. Select a preset number of resources from the initial screening resource set in descending order of hierarchical suitability to form a hierarchical candidate resource set.

[0040] Specifically, the initial screening resources will be pooled together and all resources will be categorized according to their hierarchical level. Hierarchical adaptability Sort the values ​​in descending order, and select the top-ranked resources from the sorted sequence in sequence. Each resource is used to form a candidate resource set for that level. The preset number of resources is... The minimum number of regulation resources required by the target power system at this level is estimated by combining the peak power demand of the revised regulation demand characteristics of this level with the average rated power of each resource. This ensures that the total capacity of the selected resources can cover the revised regulation power demand of this level while reserving a set proportion of regulation margin. For levels with insufficient resources or significantly low level fit, a prompt can be made in the candidate resource set for that level to indicate that the technical output characteristic parameters of the resource are estimated values ​​and its actual regulation performance needs to be verified by field testing.

[0041] Through the first and second level screenings described above, a hierarchical matching process is completed for each level. The matching process at each level is executed sequentially in the order of long-cycle balancing layer, intraday adjustment layer, and fast adjustment layer. The candidate resource set output by the previous level serves as the input range for the matching resources in the next adjacent level. This hierarchical transfer between levels narrows the matching range layer by layer, ultimately outputting resource combinations that meet the adjustment capability requirements and have superior adjustment quality at each level.

[0042] S5. Perform output time-series coupling analysis on the resource combination of the final output of hierarchical matching, calculate the output complementarity rate and ramp synergy, and determine whether there is a gap in adjustment capacity exceeding the preset threshold. Output timing coupling analysis refers to the joint simulation of the output timing of each resource in the resource combination finally output by hierarchical matching on the same time axis. This is to examine the complementary effects between the outputs of each resource in the resource combination during the common operating period, as well as the degree of synergy between the overall ramp-up capability and the system regulation requirements. Since the hierarchical matching process is carried out independently at each level, although the final output resource combination meets the regulation requirements at each individual level, the output timing of each resource may overlap and fluctuate, or the ramp-up capability may not match the system requirements during actual operation. Therefore, coupling verification needs to be performed under a unified time series. The specific analysis steps are as follows: 1. Obtain the output time sequence of each resource in the resource combination at each sampling point within a preset time period; 2. Calculate the output complementarity rate of the resource combination as follows: in: For the power complementarity rate, The total number of resources in the resource portfolio. This represents the total number of sampling points within a preset time period. For the first The resource in the first The actual output value of each sampling point For the first The average output value of each resource within a preset time period. This represents the average total output of the resource combination over a preset time period. 3. Calculate the ramp-up synergy of the resource combination as follows: in: For climbing coordination, For the first time period within the preset time period From the sampling point to the... The change in the regulation demand of the power system between the sampling points For the first The change in output of each resource within the corresponding sampling interval.

[0043] After calculating the power complementarity rate and ramp-up coordination, it is necessary to determine whether there is a regulation capacity gap exceeding a preset threshold. The preset threshold is a pre-determined technical indicator based on the minimum complementarity level and minimum coordination level required for the safe and stable operation of the target power system. Power complementarity rate threshold. Based on the maximum permissible range of active power fluctuations in the target power system, and considering the statistical characteristics of load fluctuations and renewable energy output fluctuations, an upper limit for the total output fluctuation level that the system can accept is determined. The complementarity rate calculated from this upper limit is then used as the output complementarity rate threshold. (Ramp-up coordination threshold) Based on the maximum allowable limits of frequency deviation and ramping deficit of the target power system, and combined with the maximum single load change and the maximum single new energy output drop of the system within a preset time period, the minimum ramping following capability required by the system is determined, and the degree of coordination corresponding to the minimum ramping following capability is used as the ramping coordination threshold.

[0044] Specifically, the calculated output complementarity rate is compared with the output complementarity rate threshold, and the calculated climbing synergy is compared with the climbing synergy threshold. If both conditions are met... and This indicates that the complementary output level and the coordinated ramp-up level of this resource combination meet the basic operational requirements of the system, and there is no gap in regulation capacity. If or This indicates that the resource combination has a capacity gap in actual operation, and the existing resource combination's capacity is insufficient to meet the system's adjustment needs during certain periods; specifically, when When this occurs, it indicates insufficient complementarity in the output of the resource combination, and the fluctuation range of the total output exceeds the acceptable range of the system. At this time, the gap power value can be quantified based on the magnitude of the deviation of the total output from the average output at each sampling point; when This indicates that the ramp-up coordination capability of the resource combination is insufficient, and there is a non-negligible deviation between the total ramp-up amount of the combination and the change in system adjustment demand. At this time, it is possible to determine the appropriate approach based on the data within each sampling interval. The portion exceeding the allowable deviation determines the power deficit value and duration threshold corresponding to the regulation capacity gap. The response time parameter of the regulation capacity gap can be determined according to the time level to which the gap belongs in the output time-series coupling analysis. For example, a gap belonging to the fast regulation level corresponds to a second-level response time requirement, and a gap belonging to the intraday regulation level corresponds to a minute-level response time requirement.

[0045] S6. When there is a regulation capacity gap, the type and technical specifications of the regulation resources to be added shall be determined according to the power, duration and response time parameters corresponding to the regulation capacity gap, and the type and technical specifications of the regulation resources to be added shall be incorporated into the collaborative configuration scheme.

[0046] Please see Figure 6 The following section provides a detailed explanation of the specific implementation methods for each step, using steps S61 to S63 as examples: S61. Obtain the power deficit value, duration threshold, and response time upper limit corresponding to the regulation capacity gap; The parameters corresponding to the regulation capacity gap are extracted from the output timing coupling analysis results of S5. The power deficit value refers to the power difference that the resource combination cannot meet the system regulation demand within a preset time period. Specifically, it can be extracted from sampling points or sampling intervals where the output complementarity rate or ramp synergy does not meet the threshold. When the output complementarity rate does not meet the threshold, the power deficit value can be the statistical value of the excess portion of the total output of the resource combination deviating from the average total output at each sampling point, such as the maximum value or a specified quantile of the excess portion at each sampling point. When the ramp synergy does not meet the threshold, the power deficit value can be the statistical value of the deviation between the change in regulation demand and the change in the total output of the resource combination within each sampling interval. The duration threshold refers to the longest continuous duration required for the power deficit to exist within the preset time period, which can be determined by multiplying the number of sampling points that continuously fail to meet the threshold by the sampling interval. The upper limit of response time refers to the maximum allowable delay time from receiving the adjustment command to the output reaching the target value when additional resources are allocated to make up for the gap. The upper limit of response time is determined according to the time level to which the gap belongs in the output timing coupling analysis. The upper limit of response time for gaps belonging to the fast adjustment level is in the second level, the upper limit of response time for gaps belonging to the intraday adjustment level is in the minute level, and the upper limit of response time for gaps belonging to the long-cycle balancing level is in the hour level or longer.

[0047] S62. Based on the upper limit of response time, select at least one candidate adjustment resource type that meets the upper limit of response time from the preset adjustment resource type library; The pre-defined regulating resource type library is a dataset pre-established based on the technical characteristics of various types of adjustable resources already applied or planned in the target power system. The library records typical technical characteristic parameters for each type of regulating resource, including at least typical response delay time, typical power range, and typical continuous charge / discharge or continuous operating duration. Resource types in the library can include electrochemical energy storage, compressed air energy storage, pumped hydro storage, concentrated solar power (CSP), flexible thermal power, and hydropower units. Specifically, the typical response delay time for each type of regulating resource in the library is extracted, and regulating resource types with typical response delay times less than or equal to the upper limit of response time are identified as candidate regulating resource types. If no single regulating resource type meets the upper limit of response time, combinations of multiple regulating resource types with shorter response times can be used as candidate schemes to meet the response time requirements.

[0048] S63. Based on the power deficit value and duration threshold, determine the type of regulation resource that needs to be added from at least one candidate regulation resource type, and determine the power specification and capacity specification corresponding to the type of regulation resource that needs to be added.

[0049] For at least one candidate regulation resource type selected in S62, the typical power range and typical continuous charge / discharge or continuous operating time of each candidate regulation resource type are further obtained. The power deficit value is compared with the typical power range of each candidate regulation resource type, and the duration threshold is compared with the typical continuous charge / discharge or continuous operating time of each candidate regulation resource type. Candidate regulation resource types whose typical power of a single unit or station can cover the power deficit value and whose typical continuous charge / discharge or continuous operating time can cover the duration threshold are preferentially selected as the regulation resource types to be added. If multiple candidate regulation resource types meet the above conditions, further optimization is performed based on technical characteristics such as typical operating condition transition time or typical availability rate of each candidate regulation resource type. For example, types with shorter typical operating condition transition times or higher typical availability rates are preferred.

[0050] After determining the types of regulatory resources that need to be added, their corresponding technical specifications are further determined. Power specifications can be determined based on the power deficit value and a preset power margin coefficient. For example, the power deficit value multiplied by the power margin coefficient can be used as the rated power specification for the type of regulatory resource to be added. The power margin coefficient can be determined based on the target power system's requirements for operating reserve capacity, and its value can range from 1.1 to 1.5. Capacity specifications can be determined by multiplying the duration threshold by the power specification. That is, the rated storage capacity or regulation capacity that the type of regulatory resource to be added should have is equal to the power specification multiplied by the duration threshold. For resource types such as pumped storage and energy storage, which use energy storage as the main means of regulation, this capacity specification reflects the required energy storage. For resource types such as thermal power and hydropower, which use fuel or water energy reserves as the main means of regulation, this capacity specification can be converted into the corresponding fuel reserve or water volume regulation range.

[0051] The identified types of regulatory resources requiring additional allocation, along with their power and capacity specifications, are included as allocation items in the collaborative configuration scheme. The collaborative configuration scheme contains both the configuration information of each resource in the final resource combination output by hierarchical matching and the types and technical specifications of the additional regulatory resources. This ensures that the final output collaborative configuration scheme simultaneously covers the combination of existing available resources and the additional resource information needed to compensate for the system's structural regulatory capacity deficiencies.

[0052] Example 2 An embodiment of a resource collaborative configuration system based on runtime characteristic matching provided by the present invention includes the following: The module for acquiring operational data and regulation demand characteristics is used to acquire operational data of various types of power sources and adjustable resources within the power system, as well as the regulation demand characteristics of the power system at different time scales. The technical output characteristic parameter extraction module is used to divide the adjustment demand characteristics into multiple levels according to the time scale, and extract the technical output characteristic parameters of each resource corresponding to each level from the operation data. The characteristic calibration offset calculation module is used to select multiple flexible regulation resources with complete operating data in the power system as benchmark regulation resources. Based on the deviation between the actual output sequence of each benchmark regulation resource at each level and the regulation demand characteristics of that level, the module calculates the characteristic calibration offset of each level and corrects the regulation demand characteristics of the corresponding level. The hierarchical matching module is used to perform hierarchical matching for each level by using the technical output characteristic parameters of that level and the modified adjustment demand characteristics, and the matching result of the previous level is used as the input range for the matching of the next adjacent level. The output complementarity rate and ramp synergy calculation module is used to perform output time-series coupling analysis on the resource combination of the final output of hierarchical matching, calculate the output complementarity rate and ramp synergy, and determine whether there is a gap in adjustment capacity exceeding a preset threshold. The collaborative configuration scheme determination module is used to determine the type and technical specifications of the additional regulation resources to be added based on the power, duration and response time parameters corresponding to the regulation capacity gap if there is a gap, and to incorporate the type and technical specifications of the additional regulation resources to be added into the collaborative configuration scheme.

[0053] For specific limitations regarding the system, please refer to the method limitations described above, which will not be repeated here. Each module in the above system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0054] It is understood that those skilled in the art can combine various implementation methods in the above embodiments under the guidance of the above examples to obtain technical solutions with multiple implementation methods.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A resource collaborative configuration method based on runtime characteristic matching, characterized in that, include: Acquire operational data of various types of power sources and adjustable resources within the power system, as well as the adjustment demand characteristics of the power system at different time scales; The adjustment demand characteristics are divided into multiple levels according to the time scale, and the technical output characteristic parameters of each resource corresponding to each level are extracted from the operation data. In the power system, multiple flexible regulation resources with complete operating data are selected as benchmark regulation resources. Based on the deviation between the actual output sequence of each benchmark regulation resource at each level and the regulation demand characteristics of that level, the characteristic calibration offset of each level is calculated and the regulation demand characteristics of the corresponding level are corrected. For each level, hierarchical matching is performed using the technical output characteristic parameters of that level and the modified adjustment demand characteristics, and the matching result of the previous level is used as the input range for the matching of the next adjacent level. Perform output time-series coupling analysis on the resource combination of the final output of hierarchical matching, calculate the output complementarity rate and ramp synergy, and determine whether there is a gap in adjustment capacity exceeding the preset threshold. If the aforementioned regulation capacity gap exists, the type and technical specifications of the regulation resources to be added are determined based on the power, duration, and response time parameters corresponding to the regulation capacity gap, and the type and technical specifications of the regulation resources to be added are incorporated into the collaborative configuration scheme.

2. The resource collaborative configuration method based on runtime characteristic matching according to claim 1, characterized in that, The adjustment demand characteristics are divided into multiple levels according to the time scale, and the technical output characteristic parameters of each resource corresponding to each level are extracted from the operational data, including: The aforementioned adjustment demand characteristics are divided into long-cycle balancing layer, intraday adjustment layer and rapid adjustment layer according to the time scale from long to short. For each resource at each level, extract the technical output characteristic parameters of that resource at that level based on the corresponding operational data. The technical output characteristic parameters corresponding to the long-cycle balancing layer include continuous operating time and guaranteed output level; the technical output characteristic parameters corresponding to the intraday adjustment layer include ramp rate and minimum technical output; and the technical output characteristic parameters corresponding to the rapid adjustment layer include response delay and operating condition switching time.

3. The resource collaborative configuration method based on runtime characteristic matching according to claim 1, characterized in that, The calculation of the characteristic calibration offset for each level, based on the deviation between the actual output sequence of each reference regulation resource at each level and the regulation demand characteristics of that level, includes: For each benchmark adjustment resource, a benchmark adjustment characteristic curve corresponding to each level is constructed based on the historical operating data of the benchmark adjustment resource at each level. For each level, based on the benchmark adjustment characteristic curve corresponding to each benchmark adjustment resource and the adjustment demand characteristics of the level, the adjustment deviation of the benchmark adjustment characteristic curve relative to the adjustment demand characteristics is determined at each time section. For each level, the characteristic calibration offset of the level is calculated based on the adjustment deviation corresponding to multiple reference adjustment resources within the level.

4. The resource collaborative configuration method based on runtime characteristic matching according to claim 3, characterized in that, The modified adjustment requirements at the corresponding level include: For each level, the characteristic calibration offset of the level is superimposed with the original adjustment demand feature of the level, and the characteristic value of the adjustment demand feature at each time section is corrected using the characteristic calibration offset to obtain the corrected adjustment demand feature.

5. The resource collaborative configuration method based on runtime characteristic matching according to claim 1, characterized in that, The step of hierarchically matching each level with the modified adjustment demand characteristics using the technical output characteristic parameters of that level, includes: For each level, the technical output characteristic parameters corresponding to that level are divided into dominant adjustment characteristic parameters and auxiliary adjustment characteristic parameters; Based on the dominant regulation characteristic parameters and the regulation demand characteristics after hierarchical correction, the first-level screening is performed on the resources to be matched at the hierarchical level to obtain the initial screening resource set; Based on the auxiliary adjustment characteristic parameters, a second-level screening is performed on the initial screening resource set to obtain the candidate resource set of the aforementioned level.

6. The resource collaborative configuration method based on runtime characteristic matching according to claim 5, characterized in that, The first-level filtering of the resources to be matched at the aforementioned level yields a preliminary set of resources, including: Obtain the dominant regulation characteristic threshold corresponding to the level; The dominant regulation characteristic parameter of each resource to be matched at the level is compared with the dominant regulation characteristic threshold. Resources to be matched that do not meet the dominant regulation characteristic threshold are removed to obtain the initial screening resource set; Specifically, when the dominant regulation characteristic parameter of the resource to be matched is missing at the level, the dominant regulation characteristic parameter is supplemented based on the statistical characteristic value of the operating resources of the same type as the resource to be matched in the power system. After the supplemented resource is marked, the comparison is then performed.

7. The resource collaborative configuration method based on runtime characteristic matching according to claim 5, characterized in that, The second-level screening of the initial resource set to obtain the candidate resource set at the next level includes: For each resource in the initial screening resource set, the hierarchical fit between the resource and the hierarchical adjusted adjustment demand characteristics is calculated based on the auxiliary adjustment characteristic parameters of the resource at the level. According to the order of the hierarchical adaptability from high to low, a preset number of resources are selected from the initial screening resource set to form the candidate resource set of the level.

8. The resource collaborative configuration method based on runtime characteristic matching according to claim 1, characterized in that, The step involves performing a time-series coupling analysis on the resource combination output from the hierarchical matching process, calculating the output complementarity rate and the climbing synergy, including: Obtain the output time sequence of each resource in the resource combination at each sampling point within a preset time period; The output complementarity rate of the resource combination is calculated as follows: in: For the power complementarity rate, The total number of resources in the resource portfolio. This represents the total number of sampling points within a preset time period. For the first The resource in the first The actual output value of each sampling point For the first The average output value of each resource within a preset time period. This represents the average total output of the resource combination over a preset time period. The climbing synergy of the resource combination is calculated as follows: in: For climbing coordination, For the first time period within the preset time period From the sampling point to the... The change in the regulation demand of the power system between the sampling points For the first The change in output of each resource within the corresponding sampling interval.

9. The resource collaborative configuration method based on runtime characteristic matching according to claim 1, characterized in that, The step of determining the type and technical specifications of the additional regulation resources to be allocated based on the power, duration, and response time parameters corresponding to the regulation capacity gap includes: Obtain the power deficit value, duration threshold, and response time upper limit corresponding to the regulation capacity gap; Based on the upper limit of response time, at least one candidate adjustment resource type that meets the upper limit of response time is selected from the preset adjustment resource type library; Based on the power deficit value and the duration threshold, the type of regulation resource to be added is determined from the at least one candidate regulation resource type, and the power specification and capacity specification corresponding to the type of regulation resource to be added are determined.

10. A resource collaborative configuration system based on runtime characteristic matching, characterized in that, The resource collaborative configuration method based on runtime characteristic matching as described in any one of claims 1 to 9 includes: The operation data and regulation demand characteristics acquisition module is used to acquire operation data of various types of power sources and adjustable resources in the power system, as well as the regulation demand characteristics of the power system at different time scales. The technical output characteristic parameter extraction module is used to divide the adjustment demand characteristics into multiple levels according to the time scale, and extract the technical output characteristic parameters of each resource corresponding to each level from the operation data. The characteristic calibration offset calculation module is used to select multiple flexible regulation resources with complete operating data as reference regulation resources in the power system, and calculate the characteristic calibration offset of each level and correct the regulation demand characteristics of the corresponding level based on the deviation between the actual output sequence of each reference regulation resource at each level and the regulation demand characteristics of that level. The hierarchical matching module is used to perform hierarchical matching for each level by using the technical output characteristic parameters of that level and the modified adjustment demand characteristics, and the matching result of the previous level is used as the input range for the matching of the next adjacent level. The output complementarity rate and ramp synergy calculation module is used to perform output time-series coupling analysis on the resource combination of the final output of hierarchical matching, calculate the output complementarity rate and ramp synergy, and determine whether there is a gap in adjustment capacity exceeding a preset threshold. The collaborative configuration scheme determination module is used to determine the type and technical specifications of the additional regulation resources to be added based on the power, duration and response time parameters corresponding to the regulation capacity gap if the gap exists, and to incorporate the type and technical specifications of the additional regulation resources to be added into the collaborative configuration scheme.

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