A scheduling configuration method and system for flexible and adjustable resources

Abstract

The present invention discloses a scheduling and configuration method and system for flexible adjustable resources. By analyzing the mutual aid channel capacity constraints and the power profit and loss distribution between each area to be configured, and determining the initial resource allocation strategy based on the mutual aid channel capacity constraints and the power profit and loss distribution, the synergy effect between different areas to be configured can be fully considered; in addition, in the process of aggregating flexible adjustable resources, the output regulation response capabilities of different flexible adjustable resources can be fully considered, thereby fully considering the differences in different areas to be configured and different types of flexible adjustable resources, and thus the scheduling and configuration of flexible adjustable resources can be realized comprehensively and accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of power resource configuration, and in particular to a scheduling configuration method and system for flexible and adjustable resources. Background Art

[0002] In the context of energy system transformation and large-scale integration of new energy, the configuration of flexible adjustable resources is directly related to the stable operation of the power system and the efficient use of new energy, and is the core key to achieving energy structure optimization and low-carbon goals. Flexible adjustable resources provide balancing support for the power system through their regulatory capabilities, and their regulatory role is particularly important when the volatility of new energy sources increases. In existing technologies, the scheduling and configuration of flexible adjustable resources usually only focuses on the evaluation of flexible adjustable resources in a single region, ignoring the synergistic effects and differences in flexible adjustable resources between different regions. As a result, existing technologies are unable to fully and accurately realize the scheduling and configuration of flexible adjustable resources. Summary of the Invention

[0003] The present invention provides a method and system for scheduling and configuring flexible adjustable resources, so as to solve the technical problem that it is difficult to comprehensively and accurately realize the scheduling and configuration of flexible adjustable resources in the prior art.

[0004] In order to solve the above technical problems, a first aspect of an embodiment of the present invention provides a scheduling configuration method for flexible adjustable resources, including:

[0005] Determining the mutual aid channel capacity constraints between each of the areas to be configured based on the transmission line parameters between the plurality of substations in each of the areas to be configured;

[0006] Performing power flow calculation on each of the to-be-configured areas according to the transmission line parameters and the mutual aid channel capacity constraints to obtain power profit and loss distribution of each of the to-be-configured areas;

[0007] Perform mutual aid scheduling on each of the areas to be configured according to the mutual aid channel capacity constraint and the power profit and loss distribution to obtain an initial resource allocation strategy;

[0008] According to the initial resource allocation strategy, obtaining the output adjustment response capability of various flexible adjustable resources in each of the areas to be configured;

[0009] According to the output regulation response capability, the flexible adjustable resources of each of the to-be-configured areas are grouped and aggregated to obtain a plurality of resource aggregation groups;

[0010] Obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, so as to schedule the output of the flexible adjustable resources according to the adjusted scheduling priority during the new energy output fluctuation period.

[0011] As a preferred solution, the mutual aid channel capacity constraints between the areas to be configured are determined based on the transmission line parameters between the multiple substations in the areas to be configured, specifically including:

[0012] Determine, based on the transmission line parameters between the plurality of substations in each of the areas to be configured, interconnecting transmission lines between the areas to be configured, as well as transmission section limits, historical transmission loss power time series data, and historical transmission power time series data of the interconnecting transmission lines;

[0013] Obtaining an average line loss rate of the interconnection transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the interconnection transmission line;

[0014] According to the transmission section limit and the average line loss rate, the actual transmission limit of the interconnection transmission line is determined, and the actual transmission limit is used as the capacity constraint of the mutual aid channel.

[0015] As a preferred solution, the power flow calculation is performed on each of the to-be-configured areas according to the transmission line parameters and the mutual aid channel capacity constraint to obtain the power profit and loss distribution of each of the to-be-configured areas, specifically including:

[0016] Determining inter-node injection power restriction conditions between the areas to be configured according to the mutual aid channel capacity constraint;

[0017] According to the transmission line parameters and the inter-node injection power restriction condition, a power flow calculation is performed on each of the areas to be configured using the Newton-Raphson method to obtain the node injection power distribution of each area to be configured;

[0018] According to the transmission line parameters, historical transmission loss power time series data and historical transmission power time series data of the transmission lines between each of the substations in each of the areas to be configured are obtained;

[0019] Determining an average line loss rate of each transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the transmission line;

[0020] Determining the actual power generation power of each of the areas to be configured according to the node injection power distribution and the average line loss rate of the transmission line;

[0021] The power profit and loss distribution of each of the to-be-configured areas is determined according to the actual power generation power and preset load requirements of each of the to-be-configured areas.

[0022] As a preferred solution, performing mutual aid scheduling on each of the to-be-configured areas based on the mutual aid channel capacity constraint and the power profit and loss distribution to obtain an initial resource allocation strategy specifically includes:

[0023] Determining the power deficit value of each of the areas to be configured according to the power profit and loss distribution;

[0024] Taking the mutual aid channel capacity constraint as a constraint condition, and minimizing the power shortage value and transmission loss of each of the to-be-configured areas as the optimization goal, a genetic algorithm is used to perform mutual aid scheduling on each of the to-be-configured areas to obtain the initial resource allocation strategy; wherein, the transmission loss is the product of the transmission power of the interconnecting transmission line and the average line loss rate.

[0025] As a preferred solution, obtaining the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy specifically includes:

[0026] Determining, according to the initial resource allocation strategy, at least one resource allocation time period for each of the to-be-allocated areas and its corresponding output adjustment required power;

[0027] Obtaining the output regulation response power and output regulation response time of various flexible adjustable resources in the to-be-configured area during the resource allocation time period;

[0028] determining an output regulation response rate corresponding to each of the to-be-configured areas according to the output regulation response power and the output regulation required power;

[0029] determining an output regulation response rate of each of the flexible adjustable resources according to the output regulation response power and the output regulation response time;

[0030] The output regulation response capability of each flexible adjustable resource in each of the to-be-configured areas is determined according to the output regulation response time, the output regulation response rate, and the output regulation response speed.

[0031] As a preferred solution, the flexible adjustable resources of each area to be configured are grouped and aggregated according to the output regulation response capability to obtain a plurality of resource aggregation groups, specifically including:

[0032] Grouping and aggregating the various flexible adjustable resources of two adjacent areas to be configured according to the output adjustment response time, the output adjustment response rate, the preset output adjustment response time threshold, and the preset output adjustment response rate threshold to obtain a fast response resource aggregation group and a normal response resource aggregation group;

[0033] Among them, the flexible adjustable resources in the fast response resource aggregation group are flexible adjustable resources whose output regulation response time is less than the preset output regulation response time threshold and whose output regulation response rate is greater than the preset output regulation response rate threshold; the flexible adjustable resources in the conventional response resource aggregation group are flexible adjustable resources whose output regulation response time is greater than or equal to the preset output regulation response time threshold and / or whose output regulation response rate is less than or equal to the preset output regulation response rate threshold.

[0034] As a preferred solution, after determining the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas based on the output regulation response rate and the output regulation response rate, the method further includes:

[0035] When it is detected that the output regulation response rate corresponding to any area to be configured is less than a preset output regulation response rate threshold, obtaining a current resource allocation ratio of various flexible adjustable resources in the area to be configured;

[0036] Adjust the current resource allocation ratio and obtain the output regulation response rate corresponding to any one of the to-be-configured areas after the resource allocation ratio is adjusted; repeat this step until the output regulation response rate corresponding to any one of the to-be-configured areas is greater than or equal to the preset output regulation response rate threshold, and use the current resource allocation ratio as the target resource allocation ratio;

[0037] According to the target resource allocation ratio, resource allocation ratio configuration is performed on various flexible adjustable resources in any one of the areas to be configured.

[0038] As a preferred solution, the obtaining of the output regulation response data of the resource aggregation group during the renewable energy output fluctuation period specifically includes:

[0039] Acquire time series data of the new energy output power of the area to be configured, and determine the rate of change of the new energy output power of the area to be configured at each moment based on the time series data of the new energy output power;

[0040] Determining a new energy output fluctuation time period of the area to be configured according to a number of moments when the new energy output power change rate is greater than a preset new energy output power change rate threshold;

[0041] Acquire first output response power time series data of the resource aggregation group corresponding to the area to be configured within the new energy output fluctuation time period;

[0042] determining, according to the interval between the initial output response power value and the maximum output response power value in the first output response power time series data, a response duration of the resource aggregation group within the new energy output fluctuation time period;

[0043] Acquire second output response power time series data of various flexible adjustable resources in the resource aggregation group within the new energy output fluctuation time period;

[0044] Determining, based on the second output response power time series data and the output regulation required power during the new energy output fluctuation period, a response delay time, a response rate, and a response rate of each of the flexible adjustable resources in the resource aggregation group during the new energy output fluctuation period; wherein the response rate is a ratio between a maximum output response power value in the second output response power time series data and the output regulation required power;

[0045] The output regulation response data of the resource aggregation group within the new energy output fluctuation time period is determined according to the response process duration, the response delay time, the response rate, and the response ratio.

[0046] As a preferred solution, adjusting the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data specifically includes:

[0047] When it is detected that the response process duration of any resource aggregation group is greater than a preset response process duration threshold, determining the any resource aggregation group as the resource aggregation group to be optimized;

[0048] Normalizing the response delay time, the response rate, and the response ratio of each of the flexible adjustable resources in the resource aggregation group to be optimized to obtain response feature vectors of each of the flexible adjustable resources;

[0049] Based on the response feature vector, a pre-trained convolutional neural network is used to evaluate the response performance of each of the flexible adjustable resources to obtain a response performance score for each of the flexible adjustable resources; wherein the convolutional neural network is trained using historical output regulation response data of the flexible adjustable resources and corresponding response performance score labels, wherein the historical output regulation response data includes historical response delay time data, historical response rate data, and historical response rate data;

[0050] Determining target scheduling priorities of various flexible adjustable resources according to the response performance score and the score intervals corresponding to the preset plurality of scheduling priorities;

[0051] According to the target scheduling priority, the scheduling priorities of various flexible adjustable resources in the resource aggregation group to be optimized are adjusted.

[0052] A second aspect of an embodiment of the present invention provides a scheduling and configuration system for flexible and adjustable resources, including:

[0053] A mutual aid channel capacity constraint determination module is used to determine the mutual aid channel capacity constraints between each area to be configured based on the transmission line parameters between the multiple substations in each area to be configured;

[0054] A power profit and loss distribution acquisition module is used to perform power flow calculation on each of the areas to be configured according to the transmission line parameters and the mutual aid channel capacity constraints to obtain the power profit and loss distribution of each of the areas to be configured;

[0055] a resource allocation initial strategy acquisition module, configured to perform mutual aid scheduling on each of the to-be-configured areas according to the mutual aid channel capacity constraint and the power profit and loss distribution, and obtain an initial resource allocation strategy;

[0056] An output regulation response capability acquisition module, configured to acquire the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy;

[0057] a flexible adjustable resource aggregation module, configured to group and aggregate the flexible adjustable resources of each of the to-be-configured areas according to the output adjustment response capability to obtain a plurality of resource aggregation groups;

[0058] A flexible adjustable resource scheduling configuration module is used to obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, so as to schedule the output of the flexible adjustable resources according to the adjusted scheduling priority during the new energy output fluctuation period.

[0059] Compared with the existing technology, the beneficial effect of the embodiments of the present invention is that by analyzing the mutual aid channel capacity constraints and the power profit and loss distribution between each area to be configured, and determining the initial resource allocation strategy based on the mutual aid channel capacity constraints and the power profit and loss distribution, the synergy effect between different areas to be configured can be fully considered; in addition, in the process of aggregating flexible adjustable resources, the output regulation response capabilities of different flexible adjustable resources can be fully considered, thereby fully considering the differences between different areas to be configured and different types of flexible adjustable resources, and thus the scheduling and configuration of flexible adjustable resources can be fully and accurately realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 1 is a flow chart of a method for scheduling and configuring flexible adjustable resources in an embodiment of the present invention;

[0061] Figure 2 It is a structural diagram of a scheduling and configuration system for flexible adjustable resources in an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0063] See Figure 1 A first aspect of an embodiment of the present invention provides a method for scheduling and configuring flexible adjustable resources, comprising the following steps S1 to S6:

[0064] Step S1, determining the mutual aid channel capacity constraints between each area to be configured based on the transmission line parameters between a plurality of substations in each area to be configured;

[0065] Step S2, performing power flow calculation on each of the areas to be configured according to the transmission line parameters and the mutual aid channel capacity constraint, to obtain the power profit and loss distribution of each of the areas to be configured;

[0066] Step S3, performing mutual aid scheduling on each of the areas to be configured according to the mutual aid channel capacity constraint and the power profit and loss distribution, to obtain an initial resource allocation strategy;

[0067] Step S4, obtaining the output adjustment response capability of various flexible adjustable resources in each of the areas to be configured according to the initial resource allocation strategy;

[0068] Step S5: grouping and aggregating the flexible adjustable resources of each of the to-be-configured areas according to the output regulation response capability to obtain a plurality of resource aggregation groups;

[0069] Step S6: Obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, so as to schedule the output of the flexible adjustable resources according to the adjusted scheduling priority during the new energy output fluctuation period.

[0070] Specifically, the area to be configured in this embodiment is determined based on the grid partition number. It is understandable that the grid partition number has clarified the boundary information of each numbered area, so that different areas to be configured can be directly distinguished. In order to accurately and comprehensively dispatch and configure flexible adjustable resources, it is necessary to first consider the power mutual assistance between regions. It is understandable that the inherent flexible adjustable resources and adjustment capabilities of different areas to be configured are different, which makes each area to be configured show significant imbalance when facing new energy fluctuations. This imbalance further leads to an increase in the demand for flexible adjustable resource mutual assistance between areas to be configured. However, due to factors such as the transmission line parameters and safety margins between substations, there are mutual assistance channel capacity constraints between each area to be configured. By reasonably controlling the transmission power of the transmission line within the mutual assistance channel capacity constraint, it not only ensures the safe and stable operation of the power grid, but also realizes reliable mutual assistance between areas to be configured.

[0071] Furthermore, in order to determine the differentiated initial resource allocation strategies for each area to be configured, this embodiment performs power flow calculations on each area to be configured based on the transmission line parameters and the mutual aid channel capacity constraints. It can be understood that the power flow calculation simulates the power flow distribution between each area to be configured, thereby determining the power surplus or deficit of each area to be configured, and knowing which areas to be configured need to export power and which areas to be configured need to import power. The distribution of power profits and losses is the prerequisite for mutual aid scheduling, and mutual aid scheduling needs to be carried out under the mutual aid channel capacity constraints to avoid transmission line overload, ensure the safe operation of the power grid, and ultimately obtain the optimal initial resource allocation strategy.

[0072] Furthermore, based on the initial resource allocation strategy, at least one resource allocation time period for each area to be configured can be clearly defined. It can be understood that the timeliness and accuracy of resource response adjustment are crucial to the balance of power supply and demand in the power grid. Specifically, if the timeliness of resource response adjustment is insufficient, it will not be able to keep up with the rapid fluctuations of new energy when the output of new energy fluctuates; and if the accuracy of resource response adjustment is insufficient, that is, the resource response adjustment amount cannot meet the resource response adjustment demand within the resource allocation time period, then after the resource response adjustment, there will still be an imbalance in power supply and demand in the power grid, which is not conducive to the safe and stable operation of the power grid. Therefore, this embodiment needs to obtain the output adjustment response capabilities of various flexible adjustable resources in each area to be configured within the resource allocation time period.

[0073] Furthermore, this embodiment groups and aggregates flexible adjustable resources based on the output regulation response capabilities of different types of flexible adjustable resources in different areas to be configured, thereby obtaining several resource aggregation groups. It is understood that by integrating flexible adjustable resources in different areas to be configured and grouping flexible adjustable resources with similar regulation characteristics into the same resource aggregation group, it is possible to reduce timing differences in the resource regulation process and avoid the problem of some flexible adjustable resources being overloaded while others are idle. Furthermore, the differences in resource characteristics between different resource aggregation groups can complement each other, helping to enhance the resilience of the power system to fluctuations in the output of renewable energy.

[0074] Furthermore, in order to ensure the output scheduling effect of flexible adjustable resources, it is necessary to further obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period to evaluate the output regulation response performance of the resource aggregation group, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the evaluation results, so that in the actual scheduling process during the new energy output fluctuation period, the flexible adjustable resources are output scheduled according to the adjusted scheduling priority.

[0075] In an optional embodiment, a graph theory algorithm can be used to further construct a power grid topology diagram for the transmission line parameters between several substations in each area to be configured, wherein each substation is regarded as a node, and the transmission line is the edge connecting each node. The transmission line parameters are used as the attribute value of each edge. Based on the power grid topology diagram, the mutual channel capacity constraints between the areas to be configured are analyzed.

[0076] The scheduling and configuration method of flexible adjustable resources provided by an embodiment of the present invention can fully consider the synergy effect between different areas to be configured by analyzing the mutual aid channel capacity constraints and the power profit and loss distribution between each area to be configured, and determining the initial resource allocation strategy based on the mutual aid channel capacity constraints and the power profit and loss distribution; in addition, in the process of aggregating flexible adjustable resources, it can fully consider the output regulation response capabilities of different flexible adjustable resources, thereby fully considering the differences between different areas to be configured and different types of flexible adjustable resources, and thus can comprehensively and accurately realize the scheduling and configuration of flexible adjustable resources.

[0077] As a preferred solution, the mutual aid channel capacity constraints between the areas to be configured are determined based on the transmission line parameters between the multiple substations in the areas to be configured, specifically including:

[0078] Determine, based on the transmission line parameters between the plurality of substations in each of the areas to be configured, interconnecting transmission lines between the areas to be configured, as well as transmission section limits, historical transmission loss power time series data, and historical transmission power time series data of the interconnecting transmission lines;

[0079] Obtaining an average line loss rate of the interconnection transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the interconnection transmission line;

[0080] According to the transmission section limit and the average line loss rate, the actual transmission limit of the interconnection transmission line is determined, and the actual transmission limit is used as the capacity constraint of the mutual aid channel.

[0081] Specifically, the transmission line parameters in this embodiment include at least the transmission voltage, impedance parameters, transmission section limits, historical transmission loss power time series data, and historical transmission power time series data of each transmission line. It is understandable that the impedance parameters of the transmission line reflect the transmission characteristics. Taking a 500 kV transmission line as an example, its impedance value is generally between 0.3 ohms per kilometer and 0.4 ohms per kilometer. For a 100-kilometer transmission line, the total impedance is approximately 35 ohms, which directly affects the capacity level of the transmission channel. The historical transmission power time series data reflects the transmission power fluctuation pattern of different transmission lines, and the transmission power fluctuation pattern is closely related to the power load characteristics of the area to be configured. For example, the transmission power of a 500 kV transmission line during the peak load period during the daytime reaches 2200 MW, which is approximately 78% of its rated capacity, while the transmission power drops to 1100 MW during the low load period at night.

[0082] Furthermore, transmission lines will generate energy loss during the process of electric energy transmission. It is understandable that since current flows through transmission lines with resistance and transmission lines have voltage, and insulation between lines and between lines has leakage, active power loss is caused. At the same time, corona discharge of live parts of overhead transmission lines will also cause active power loss. Therefore, in order to accurately determine the mutual aid channel capacity constraints between each area to be configured, this embodiment also obtains historical transmission loss power time series data to determine the transmission loss power value of the transmission line at different times.

[0083] Furthermore, since the transmission lines for each area to be configured are already clearly defined, the interconnecting transmission lines between the areas to be configured can be directly determined, and based on the transmission line parameters corresponding to the interconnecting transmission lines, the transmission section limit, historical transmission loss power time series data, and historical transmission power time series data can be obtained. Furthermore, although the power load characteristics at different times vary, resulting in different transmission power and transmission loss power for the interconnecting transmission lines at different times, since the impedance parameters of the interconnecting transmission lines are determined, this embodiment uses the historical transmission power time series data and the historical transmission loss power time series data to respectively obtain historical transmission power values ​​and historical transmission loss power values ​​at different times. Then, based on the ratio between the historical transmission loss power value and the historical transmission power value at each time, the line loss rate at each time can be determined. By averaging the line loss rates at each time, the average line loss rate of the interconnecting transmission lines can be obtained.

[0084] Furthermore, the transmission section limit is a key indicator for ensuring system safety. For example, the section composed of 500 kV interconnecting transmission lines between a certain region has a transmission limit of 4,500 MW under normal operation. After considering the N-1 safety check, the transmission section limit is reduced to 3,800 MW. Then, after considering the average line loss rate of the interconnecting transmission line, the loss power of the interconnecting transmission line under the transmission section limit is determined based on the product of the transmission section limit and the average line loss rate. Based on the difference between the transmission section limit and the loss power, the actual transmission limit of the interconnecting transmission line can be obtained, which is the mutual aid channel capacity constraint.

[0085] As a preferred solution, the power flow calculation is performed on each of the to-be-configured areas according to the transmission line parameters and the mutual aid channel capacity constraint to obtain the power profit and loss distribution of each of the to-be-configured areas, specifically including:

[0086] Determining inter-node injection power restriction conditions between the areas to be configured according to the mutual aid channel capacity constraint;

[0087] According to the transmission line parameters and the inter-node injection power restriction condition, a power flow calculation is performed on each of the areas to be configured using the Newton-Raphson method to obtain the node injection power distribution of each area to be configured;

[0088] According to the transmission line parameters, historical transmission loss power time series data and historical transmission power time series data of the transmission lines between each of the substations in each of the areas to be configured are obtained;

[0089] Determining an average line loss rate of each transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the transmission line;

[0090] Determining the actual power generation power of each of the areas to be configured according to the node injection power distribution and the average line loss rate of the transmission line;

[0091] The power profit and loss distribution of each of the to-be-configured areas is determined according to the actual power generation power and preset load requirements of each of the to-be-configured areas.

[0092] Specifically, this embodiment first uses the mutual aid channel capacity constraints between each area to be configured as the node-to-node injection power restriction conditions between each area to be configured, and then based on the transmission line parameters, it can determine the conductance and susceptance of each transmission line in the area to be configured for power flow calculation, and then uses the Newton-Raphson method to solve the node power balance equation to perform power flow calculation on each area to be configured, until the iterative calculation error reaches the convergence criterion condition or the number of convergences reaches the maximum. For example, the iterative error is set to 0.0001 and the number of convergences is set to 10 times. This embodiment does not make specific limitations here, so as to obtain the node injection power distribution of each area to be configured. Since the transmission line is an electric energy transmission channel for connecting two nodes, the transmission power distribution of each transmission line can be known based on the node injection power distribution.

[0093] Furthermore, based on the transmission line parameters, the historical transmission loss power time series data and the historical transmission power time series data of the transmission lines between the substations in the area to be configured can be directly obtained, so that the historical transmission loss power value and the historical transmission power value of each transmission line at different times can be obtained respectively. Then, based on the ratio between the historical transmission loss power value and the historical transmission power value at each time, the line loss rate of each transmission line at each time can be determined. By averaging the line loss rates at each time, the average line loss rate of each transmission line can be obtained.

[0094] Since the transmission power distribution of each transmission line has been determined through power flow calculation, the actual transmission power of each transmission line can be determined based on the average line loss rate of each transmission line, and thus the actual power generation power of each area to be configured can be determined.

[0095] Furthermore, based on the actual power generation and preset load demand of each area to be allocated, the power surplus or deficit at different times can be calculated for each area to be allocated, that is, the power surplus and deficit distribution. For example, the actual power generation of a certain area to be allocated is 3100 MW, while the load demand during peak hours is 4100 MW, resulting in a power deficit of 1000 MW. Meanwhile, the actual power generation of an adjacent area is 5600 MW, while the load demand during this period is only 3800 MW, resulting in a power surplus of 1800 MW.

[0096] As a preferred solution, performing mutual aid scheduling on each of the to-be-configured areas based on the mutual aid channel capacity constraint and the power profit and loss distribution to obtain an initial resource allocation strategy specifically includes:

[0097] Determining the power deficit value of each of the areas to be configured according to the power profit and loss distribution;

[0098] Taking the mutual aid channel capacity constraint as a constraint condition, and minimizing the power shortage value and transmission loss of each of the to-be-configured areas as the optimization goal, a genetic algorithm is used to perform mutual aid scheduling on each of the to-be-configured areas to obtain the initial resource allocation strategy; wherein, the transmission loss is the product of the transmission power of the interconnecting transmission line and the average line loss rate.

[0099] Specifically, this embodiment first determines the power shortage value of each area to be configured at different times according to the distribution of power profit and loss, and then takes the minimum power shortage value of each area to be configured and the minimum transmission loss as the optimization goal, constructs the optimization objective function, and takes the mutual aid channel capacity constraint as the constraint condition, randomly generates a number of individuals, each individual corresponds to the resource allocation amount of each area to be configured in each time period, and the resource allocation amount corresponding to each individual must comply with the mutual aid channel capacity constraint, and then designs a fitness function that is inversely related to the optimization objective function, and uses a genetic algorithm to repeatedly select, cross and mutate each individual to iteratively optimize the mutual aid scheduling of each area to be configured, until the number of iterations reaches the preset maximum. The maximum number of iterations, or the change between the fitness values ​​of N consecutive generations is less than the preset change threshold. It is worth noting that the parameter "N" here can be set according to actual application requirements, such as setting it to 2, 3, 4, 5, etc. In addition, the maximum number of iterations, population size, crossover probability and mutation probability can all be set according to actual application requirements. For example, the maximum number of iterations is set to 200, the population size is set to 100, the crossover probability is set to 0.8, and the mutation probability is set to 0.05. This embodiment is not specifically limited here. The individual with the highest fitness finally output is used as the initial resource allocation strategy, which includes at least one resource allocation time period for each area to be configured and its corresponding output regulation demand power.

[0100] As a preferred solution, obtaining the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy specifically includes:

[0101] Determining, according to the initial resource allocation strategy, at least one resource allocation time period for each of the to-be-allocated areas and its corresponding output adjustment required power;

[0102] Obtaining the output regulation response power and output regulation response time of various flexible adjustable resources in the to-be-configured area during the resource allocation time period;

[0103] determining an output regulation response rate corresponding to each of the to-be-configured areas according to the output regulation response power and the output regulation required power;

[0104] determining an output regulation response rate of each of the flexible adjustable resources according to the output regulation response power and the output regulation response time;

[0105] The output regulation response capability of each flexible adjustable resource in each of the to-be-configured areas is determined according to the output regulation response time, the output regulation response rate, and the output regulation response speed.

[0106] Specifically, based on the initial resource allocation strategy, at least one resource allocation time period of each to-be-configured area and its corresponding output regulation demand power can be determined, and then the output regulation response power and output regulation response time of various flexible adjustable resources in the to-be-configured area in the resource allocation time period are obtained. According to the ratio between the output regulation response power and the output regulation demand power, the output regulation response rate corresponding to each to-be-configured area can be determined. It can be understood that the output regulation response rate reflects the output regulation accuracy of the to-be-configured area, that is, whether its actual maximum output regulation response power reaches the output regulation demand power, and the output regulation response time is the time required to increase from the initial power value to the maximum output regulation response power, which reflects the timeliness of the flexible adjustable resource's response to the resource scheduling instruction. Therefore, according to the ratio between the output regulation response power and the output regulation response time, the output regulation response rate of each flexible adjustable resource can be determined, and then the output regulation response capability of various flexible adjustable resources in each to-be-configured area can be clarified.

[0107] As a preferred solution, the flexible adjustable resources of each area to be configured are grouped and aggregated according to the output regulation response capability to obtain a plurality of resource aggregation groups, specifically including:

[0108] Grouping and aggregating the various flexible adjustable resources of two adjacent areas to be configured according to the output adjustment response time, the output adjustment response rate, the preset output adjustment response time threshold, and the preset output adjustment response rate threshold to obtain a fast response resource aggregation group and a normal response resource aggregation group;

[0109] Among them, the flexible adjustable resources in the fast response resource aggregation group are flexible adjustable resources whose output regulation response time is less than the preset output regulation response time threshold and whose output regulation response rate is greater than the preset output regulation response rate threshold; the flexible adjustable resources in the conventional response resource aggregation group are flexible adjustable resources whose output regulation response time is greater than or equal to the preset output regulation response time threshold and / or whose output regulation response rate is less than or equal to the preset output regulation response rate threshold.

[0110] Specifically, in order to group and aggregate flexible adjustable resources with similar response characteristics, this embodiment pre-sets an output regulation response time threshold and an output regulation response rate threshold. For example, taking the flexible adjustable resources in a certain area to be configured as an example, it includes an energy storage power station, a pumped storage power station, an industrial load, and an electric vehicle charging station. Among them, the maximum output regulation response rate of the energy storage power station reaches 90% of its rated capacity per minute, and the output regulation response time is less than 100 milliseconds, while the maximum output regulation response rate of the pumped storage power station is 15% of its rated capacity per minute, and the output regulation response time is within 3 minutes. Therefore, the response characteristics of these two types of flexible adjustable resources have large differences. Based on the preset output regulation response time threshold and the preset output regulation response rate threshold, this embodiment divides various flexible adjustable resources in two adjacent areas to be configured into a fast response resource aggregation group and a conventional response resource aggregation group. This grouping method gives full play to the advantages of different types of flexible adjustable resources.

[0111] In addition, different flexible adjustable resources within the same resource aggregation group can form a complementary effect within the group through coordinated adjustment. For example, during a certain period of photovoltaic output fluctuation, the fast-response resource aggregation group includes energy storage power stations and electric vehicle charging stations. The energy storage power stations provide fast adjustment with an average response time of 80 milliseconds and an adjustment accuracy of 95%. The electric vehicle charging stations provide continuous adjustment capabilities by adjusting the charging power, thereby ensuring a fast response of output adjustment during the period of photovoltaic output fluctuation.

[0112] Furthermore, the fast-response resource aggregation group and the conventional response resource aggregation group can complement each other in the output regulation timing. When the output of new energy fluctuates rapidly, the fast-response resource aggregation group undertakes the initial output regulation task. The flexible adjustable resources with a response time of less than 100 milliseconds account for 80%. After the conventional response resource aggregation group is adjusted in place, it gradually withdraws from the regulation, realizing the dynamic switching of output regulation resources.

[0113] As a preferred solution, after determining the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas based on the output regulation response rate and the output regulation response rate, the method further includes:

[0114] When it is detected that the output regulation response rate corresponding to any area to be configured is less than a preset output regulation response rate threshold, obtaining a current resource allocation ratio of various flexible adjustable resources in the area to be configured;

[0115] Adjust the current resource allocation ratio and obtain the output regulation response rate corresponding to any one of the to-be-configured areas after the resource allocation ratio is adjusted; repeat this step until the output regulation response rate corresponding to any one of the to-be-configured areas is greater than or equal to the preset output regulation response rate threshold, and use the current resource allocation ratio as the target resource allocation ratio;

[0116] According to the target resource allocation ratio, resource allocation ratio configuration is performed on various flexible adjustable resources in any one of the areas to be configured.

[0117] Specifically, since different types of flexible adjustable resources have different output regulation response performance, the allocation ratio of different types of flexible adjustable resources will directly affect the resource regulation response performance of the current area to be configured. In order to ensure the resource regulation response effect of each area to be configured, this embodiment compares the output regulation response rate corresponding to the area to be configured during each resource adjustment process with the preset output regulation response rate threshold to determine whether the output regulation response rate corresponding to a certain area to be configured is too low. When it is detected that the output regulation response rate corresponding to any area to be configured is less than the preset output regulation response rate threshold, it indicates that the allocation ratio of the flexible adjustable resources in the area to be configured needs to be reallocated to improve the overall resource regulation response performance, and obtain the current resource allocation ratio of various flexible adjustable resources in the area to be configured. It is worth noting that the resource allocation ratio of various flexible adjustable resources directly affects the participation of the flexible adjustable resources in the output regulation response process. By adjusting the current resource allocation ratio and obtaining the output regulation response rate of the area to be configured in the same resource regulation process after the resource allocation ratio is adjusted, this step is repeated until the output regulation response rate corresponding to the area to be configured is greater than or equal to the preset output regulation response rate threshold, indicating that the resource allocation ratio obtained by the current adjustment can meet the current resource regulation response requirements, thereby reallocating the resource allocation ratio of the area to be configured.

[0118] As a preferred solution, the obtaining of the output regulation response data of the resource aggregation group during the renewable energy output fluctuation period specifically includes:

[0119] Acquire time series data of the new energy output power of the area to be configured, and determine the rate of change of the new energy output power of the area to be configured at each moment based on the time series data of the new energy output power;

[0120] Determining a new energy output fluctuation time period of the area to be configured according to a number of moments when the new energy output power change rate is greater than a preset new energy output power change rate threshold;

[0121] Acquire first output response power time series data of the resource aggregation group corresponding to the area to be configured within the new energy output fluctuation time period;

[0122] determining, according to the interval between the initial output response power value and the maximum output response power value in the first output response power time series data, a response duration of the resource aggregation group within the new energy output fluctuation time period;

[0123] Acquire second output response power time series data of various flexible adjustable resources in the resource aggregation group within the new energy output fluctuation time period;

[0124] Determining, based on the second output response power time series data and the output regulation required power during the new energy output fluctuation period, a response delay time, a response rate, and a response rate of each of the flexible adjustable resources in the resource aggregation group during the new energy output fluctuation period; wherein the response rate is a ratio between a maximum output response power value in the second output response power time series data and the output regulation required power;

[0125] The output regulation response data of the resource aggregation group within the new energy output fluctuation time period is determined according to the response process duration, the response delay time, the response rate, and the response ratio.

[0126] Specifically, this embodiment is based on the new energy output power time series data of the area to be configured, and can determine the new energy output power change rate of the area to be configured at each moment through the new energy output power change values ​​at two adjacent moments. It is worth noting that the new energy output fluctuation characteristics directly affect the stability of the power grid operation. Taking a photovoltaic power station as an example, its output power time series data shows that during the period of rapid cloud changes, the output power change per unit time reaches 35% of its rated capacity, and the new energy output power change rate exceeds 300 megawatts per minute. This embodiment pre-sets the new energy output power change rate threshold, thereby judging several new energy output fluctuation time periods in which flexible adjustable resources need to be aggregated for output regulation response.

[0127] Furthermore, first output response power time series data of the resource aggregation group corresponding to the area to be configured during the renewable energy output fluctuation period is obtained. This first output response power time series data reflects the regulation capability of the resource aggregation group during renewable energy output fluctuations. Based on the interval between the initial output response power value and the maximum output response power value in the first output response power time series data, the duration of the response process of the resource aggregation group during the renewable energy output fluctuation period is determined. It can be understood that the duration of the response process is a key indicator for measuring regulation performance, which reflects whether the current resource aggregation group can respond quickly and promptly during the renewable energy output fluctuation period. For example, an energy storage power station, as a fast-response resource, has a startup time of no more than 50 milliseconds after receiving a dispatch instruction, and its output response power curve shows that the process from zero output to full power lasts 200 milliseconds. In contrast, the startup time of the demand-side response resource is between 5 and 10 seconds, and its output response power curve shows that the process from zero output to full power lasts 30 seconds, forming a clear response time gradient.

[0128] Furthermore, this embodiment also obtains the second output response power timing data of various flexible adjustable resources in the resource aggregation group during the new energy output fluctuation time period and the output regulation demand power during the new energy output fluctuation time period, and then determines the response delay time of various flexible adjustable resources during the new energy output fluctuation time period based on the interval time between the initial output response power value and the maximum output response power value in the second output response power timing data; based on the ratio of the difference between the maximum output response power value and the initial output response power value and the response delay time, the response rate of various flexible adjustable resources during the new energy output fluctuation time period can be determined; based on the ratio between the maximum output response power value and the output regulation demand power during the new energy output fluctuation time period, the response rate of various flexible adjustable resources during the new energy output fluctuation time period can be determined.

[0129] As a preferred solution, adjusting the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data specifically includes:

[0130] When it is detected that the response process duration of any resource aggregation group is greater than a preset response process duration threshold, determining the any resource aggregation group as the resource aggregation group to be optimized;

[0131] Normalizing the response delay time, the response rate, and the response ratio of each of the flexible adjustable resources in the resource aggregation group to be optimized to obtain response feature vectors of each of the flexible adjustable resources;

[0132] Based on the response feature vector, a pre-trained convolutional neural network is used to evaluate the response performance of each of the flexible adjustable resources to obtain a response performance score for each of the flexible adjustable resources; wherein the convolutional neural network is trained using historical output regulation response data of the flexible adjustable resources and corresponding response performance score labels, wherein the historical output regulation response data includes historical response delay time data, historical response rate data, and historical response rate data;

[0133] Determining target scheduling priorities of various flexible adjustable resources according to the response performance score and the score intervals corresponding to the preset plurality of scheduling priorities;

[0134] According to the target scheduling priority, the scheduling priorities of various flexible adjustable resources in the resource aggregation group to be optimized are adjusted.

[0135] Specifically, in this embodiment, when it is detected that the response process duration of any resource aggregation group is greater than a preset response process duration threshold, it indicates that the regulation performance of the resource aggregation group needs to be further optimized, and the resource aggregation group is determined to be a resource aggregation group to be optimized.

[0136] Furthermore, since the response delay time, response rate, and response rate all have different dimensions, this embodiment normalizes the response delay time, response rate, and response rate of various flexible adjustable resources in the resource aggregation group to be optimized to eliminate the dimensionality effect and obtain response feature vectors for the various flexible adjustable resources. Based on the response feature vectors, a pre-trained convolutional neural network is then used to evaluate the response performance of the various flexible adjustable resources. It is understood that the response feature vectors in this embodiment include response delay time features, response rate features, and response rate features, and the convolutional neural network is trained using historical output regulation response data of the flexible adjustable resources and their corresponding response performance score labels. The historical output regulation response data includes historical response delay time data, historical response rate data, and historical response rate data of the flexible adjustable resources during historical periods of different renewable energy output fluctuations. The historical response delay time data, historical response rate data, and historical response rate data are normalized separately, and combined with the response performance score labels corresponding to each set of normalized historical output regulation response data to obtain a training dataset for the convolutional neural network. The convolutional neural network is trained using the training data set, so that the convolutional neural network can learn the relationship between the response delay time characteristics, response rate characteristics, response rate characteristics and response performance scores. The weight parameters of the response delay time characteristics, response rate characteristics and response rate characteristics are continuously optimized through training to achieve the training of the convolutional neural network.

[0137] Furthermore, after obtaining the response performance scores of various flexible adjustable resources, based on the response performance scores and the score intervals corresponding to several preset scheduling priorities, illustratively, the response performance scores of the flexible adjustable resources are between 0 and 1. In this embodiment, the score interval corresponding to the first-level scheduling priority is preset to be greater than 0.8 and less than or equal to 1, the score interval corresponding to the second-level scheduling priority is preset to be greater than or equal to 0.6 and less than or equal to 0.8, and the score interval corresponding to the third-level scheduling priority is preset to be less than 0.6 and greater than or equal to 0. This allows the various flexible adjustable resources within the resource aggregation group to be optimized to be divided into different scheduling priorities. During actual scheduling, when the output of renewable energy sources fluctuates drastically, the flexible adjustable resources in the first-level scheduling priority sequence respond first, providing rapid adjustment support. The flexible adjustable resources in the second-level scheduling priority sequence are put into adjustment after the flexible adjustable resources in the first-level scheduling priority sequence respond. The flexible adjustable resources in the third-level scheduling priority sequence serve as backup resources, ensuring the tiered entry and orderly exit of adjustment resources and ensuring that flexible adjustable resources with better adjustment performance are scheduled first during the scheduling process, effectively improving the overall adjustment performance of the resource aggregation group.

[0138] See Figure 2 A second aspect of an embodiment of the present invention provides a scheduling and configuration system for flexible and adjustable resources, including:

[0139] A mutual aid channel capacity constraint determination module 11 is configured to determine the mutual aid channel capacity constraints between each area to be configured based on the transmission line parameters between the multiple substations in each area to be configured;

[0140] The power profit and loss distribution acquisition module 12 is used to perform power flow calculation on each of the areas to be configured according to the transmission line parameters and the mutual aid channel capacity constraints to obtain the power profit and loss distribution of each of the areas to be configured;

[0141] The resource allocation initial strategy acquisition module 13 is used to perform mutual assistance scheduling on each of the areas to be configured according to the mutual assistance channel capacity constraint and the power profit and loss distribution, and obtain an initial resource allocation strategy;

[0142] The output regulation response capability acquisition module 14 is configured to acquire the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy;

[0143] The flexible adjustable resource aggregation module 15 is configured to group and aggregate the flexible adjustable resources of each of the to-be-configured areas according to the output adjustment response capability to obtain a plurality of resource aggregation groups;

[0144] The flexible adjustable resource scheduling configuration module 16 is used to obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, so as to schedule the output of the flexible adjustable resources according to the adjusted scheduling priority during the new energy output fluctuation period.

[0145] As a preferred solution, the mutual aid channel capacity constraint determination module 11 is used to determine the mutual aid channel capacity constraints between each of the areas to be configured based on the transmission line parameters between the multiple substations in each area to be configured, specifically including:

[0146] Determine, based on the transmission line parameters between the plurality of substations in each of the areas to be configured, interconnecting transmission lines between the areas to be configured, as well as transmission section limits, historical transmission loss power time series data, and historical transmission power time series data of the interconnecting transmission lines;

[0147] Obtaining an average line loss rate of the interconnection transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the interconnection transmission line;

[0148] According to the transmission section limit and the average line loss rate, the actual transmission limit of the interconnection transmission line is determined, and the actual transmission limit is used as the capacity constraint of the mutual aid channel.

[0149] As a preferred solution, the power profit and loss distribution acquisition module 12 is used to perform power flow calculation on each of the to-be-configured areas according to the transmission line parameters and the mutual aid channel capacity constraints, and obtain the power profit and loss distribution of each of the to-be-configured areas, specifically including:

[0150] Determining inter-node injection power restriction conditions between the areas to be configured according to the mutual aid channel capacity constraint;

[0151] According to the transmission line parameters and the inter-node injection power restriction condition, a power flow calculation is performed on each of the areas to be configured using the Newton-Raphson method to obtain the node injection power distribution of each area to be configured;

[0152] According to the transmission line parameters, historical transmission loss power time series data and historical transmission power time series data of the transmission lines between each of the substations in each of the areas to be configured are obtained;

[0153] Determining an average line loss rate of each transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the transmission line;

[0154] Determining the actual power generation power of each of the areas to be configured according to the node injection power distribution and the average line loss rate of the transmission line;

[0155] The power profit and loss distribution of each of the to-be-configured areas is determined according to the actual power generation power and preset load requirements of each of the to-be-configured areas.

[0156] As a preferred solution, the resource allocation initial strategy acquisition module 13 is used to perform mutual assistance scheduling on each of the to-be-configured areas according to the mutual assistance channel capacity constraint and the power profit and loss distribution, and obtain the initial resource allocation strategy, which specifically includes:

[0157] Determining the power deficit value of each of the areas to be configured according to the power profit and loss distribution;

[0158] Taking the mutual aid channel capacity constraint as a constraint condition, and minimizing the power shortage value and transmission loss of each of the to-be-configured areas as the optimization goal, a genetic algorithm is used to perform mutual aid scheduling on each of the to-be-configured areas to obtain the initial resource allocation strategy; wherein, the transmission loss is the product of the transmission power of the interconnecting transmission line and the average line loss rate.

[0159] As a preferred solution, the output regulation response capability acquisition module 14 is used to acquire the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy, specifically including:

[0160] Determining, according to the initial resource allocation strategy, at least one resource allocation time period for each of the to-be-allocated areas and its corresponding output adjustment required power;

[0161] Obtaining the output regulation response power and output regulation response time of various flexible adjustable resources in the to-be-configured area during the resource allocation time period;

[0162] determining an output regulation response rate corresponding to each of the to-be-configured areas according to the output regulation response power and the output regulation required power;

[0163] determining an output regulation response rate of each of the flexible adjustable resources according to the output regulation response power and the output regulation response time;

[0164] The output regulation response capability of each flexible adjustable resource in each of the to-be-configured areas is determined according to the output regulation response time, the output regulation response rate, and the output regulation response speed.

[0165] As a preferred solution, the flexible adjustable resource aggregation module 15 is used to group and aggregate the flexible adjustable resources of each of the to-be-configured areas according to the output adjustment response capability to obtain a plurality of resource aggregation groups, specifically including:

[0166] Grouping and aggregating the various flexible adjustable resources of two adjacent areas to be configured according to the output adjustment response time, the output adjustment response rate, the preset output adjustment response time threshold, and the preset output adjustment response rate threshold to obtain a fast response resource aggregation group and a normal response resource aggregation group;

[0167] Among them, the flexible adjustable resources in the fast response resource aggregation group are flexible adjustable resources whose output regulation response time is less than the preset output regulation response time threshold and whose output regulation response rate is greater than the preset output regulation response rate threshold; the flexible adjustable resources in the conventional response resource aggregation group are flexible adjustable resources whose output regulation response time is greater than or equal to the preset output regulation response time threshold and / or whose output regulation response rate is less than or equal to the preset output regulation response rate threshold.

[0168] As a preferred solution, the system further includes a resource allocation ratio configuration module, which is used to:

[0169] When it is detected that the output regulation response rate corresponding to any area to be configured is less than a preset output regulation response rate threshold, obtaining a current resource allocation ratio of various flexible adjustable resources in the area to be configured;

[0170] Adjust the current resource allocation ratio and obtain the output regulation response rate corresponding to any one of the to-be-configured areas after the resource allocation ratio is adjusted; repeat this step until the output regulation response rate corresponding to any one of the to-be-configured areas is greater than or equal to the preset output regulation response rate threshold, and use the current resource allocation ratio as the target resource allocation ratio;

[0171] According to the target resource allocation ratio, resource allocation ratio configuration is performed on various flexible adjustable resources in any one of the areas to be configured.

[0172] As a preferred solution, the flexible adjustable resource scheduling configuration module 16 is used to obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, specifically including:

[0173] Acquire time series data of the new energy output power of the area to be configured, and determine the rate of change of the new energy output power of the area to be configured at each moment based on the time series data of the new energy output power;

[0174] Determining a new energy output fluctuation time period of the area to be configured according to a number of moments when the new energy output power change rate is greater than a preset new energy output power change rate threshold;

[0175] Acquire first output response power time series data of the resource aggregation group corresponding to the area to be configured within the new energy output fluctuation time period;

[0176] determining, according to the interval between the initial output response power value and the maximum output response power value in the first output response power time series data, a response duration of the resource aggregation group within the new energy output fluctuation time period;

[0177] Acquire second output response power time series data of various flexible adjustable resources in the resource aggregation group within the new energy output fluctuation time period;

[0178] Determining, based on the second output response power time series data and the output regulation required power during the new energy output fluctuation period, a response delay time, a response rate, and a response rate of each of the flexible adjustable resources in the resource aggregation group during the new energy output fluctuation period; wherein the response rate is a ratio between a maximum output response power value in the second output response power time series data and the output regulation required power;

[0179] The output regulation response data of the resource aggregation group within the new energy output fluctuation time period is determined according to the response process duration, the response delay time, the response rate, and the response ratio.

[0180] As a preferred solution, the flexible adjustable resource scheduling configuration module 16 is configured to adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, specifically including:

[0181] When it is detected that the response process duration of any resource aggregation group is greater than a preset response process duration threshold, determining the any resource aggregation group as the resource aggregation group to be optimized;

[0182] Normalizing the response delay time, the response rate, and the response ratio of each of the flexible adjustable resources in the resource aggregation group to be optimized to obtain response feature vectors of each of the flexible adjustable resources;

[0183] Based on the response feature vector, a pre-trained convolutional neural network is used to evaluate the response performance of each of the flexible adjustable resources to obtain a response performance score for each of the flexible adjustable resources; wherein the convolutional neural network is trained using historical output regulation response data of the flexible adjustable resources and corresponding response performance score labels, wherein the historical output regulation response data includes historical response delay time data, historical response rate data, and historical response rate data;

[0184] Determining target scheduling priorities of various flexible adjustable resources according to the response performance score and the score intervals corresponding to the preset plurality of scheduling priorities;

[0185] According to the target scheduling priority, the scheduling priorities of various flexible adjustable resources in the resource aggregation group to be optimized are adjusted.

[0186] The scheduling and configuration system for flexible adjustable resources provided by an embodiment of the present invention can fully consider the synergy effect between different areas to be configured by analyzing the mutual aid channel capacity constraints and the power profit and loss distribution between each area to be configured, and determining the initial resource allocation strategy based on the mutual aid channel capacity constraints and the power profit and loss distribution; in addition, in the process of aggregating flexible adjustable resources, it can fully consider the output regulation response capabilities of different flexible adjustable resources, thereby fully considering the differences between different areas to be configured and different types of flexible adjustable resources, and thus can comprehensively and accurately realize the scheduling and configuration of flexible adjustable resources.

[0187] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for scheduling and configuring flexible adjustable resources, characterized in that: include: Determining the mutual aid channel capacity constraints between each of the areas to be configured based on the transmission line parameters between the plurality of substations in each of the areas to be configured; Performing power flow calculation on each of the to-be-configured areas according to the transmission line parameters and the mutual aid channel capacity constraints to obtain power profit and loss distribution of each of the to-be-configured areas; Perform mutual aid scheduling on each of the areas to be configured according to the mutual aid channel capacity constraint and the power profit and loss distribution to obtain an initial resource allocation strategy; According to the initial resource allocation strategy, obtaining the output adjustment response capability of various flexible adjustable resources in each of the areas to be configured; According to the output regulation response capability, the flexible adjustable resources of each of the to-be-configured areas are grouped and aggregated to obtain a plurality of resource aggregation groups; Obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, so as to schedule the output of the flexible adjustable resources according to the adjusted scheduling priority during the new energy output fluctuation period.

2. The method for scheduling and configuring flexible adjustable resources according to claim 1, wherein: Determining the mutual aid channel capacity constraints between the areas to be configured based on the transmission line parameters between the plurality of substations in the areas to be configured specifically includes: Determine, based on the transmission line parameters between the plurality of substations in each of the areas to be configured, interconnecting transmission lines between the areas to be configured, as well as transmission section limits, historical transmission loss power time series data, and historical transmission power time series data of the interconnecting transmission lines; Obtaining an average line loss rate of the interconnection transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the interconnection transmission line; According to the transmission section limit and the average line loss rate, the actual transmission limit of the interconnection transmission line is determined, and the actual transmission limit is used as the capacity constraint of the mutual aid channel.

3. The method for scheduling and configuring flexible adjustable resources according to claim 1, wherein: The step of performing power flow calculation on each of the to-be-configured areas according to the transmission line parameters and the mutual aid channel capacity constraint to obtain power profit and loss distribution of each of the to-be-configured areas specifically includes: Determining inter-node injection power restriction conditions between the areas to be configured according to the mutual aid channel capacity constraint; According to the transmission line parameters and the inter-node injection power restriction condition, a power flow calculation is performed on each of the areas to be configured using the Newton-Raphson method to obtain the node injection power distribution of each area to be configured; According to the transmission line parameters, historical transmission loss power time series data and historical transmission power time series data of the transmission lines between each of the substations in each of the areas to be configured are obtained; Determining an average line loss rate of each transmission line according to the historical transmission loss power time series data and the historical transmission power time series data of the transmission line; Determining the actual power generation power of each of the areas to be configured according to the node injection power distribution and the average line loss rate of the transmission line; The power profit and loss distribution of each of the to-be-configured areas is determined according to the actual power generation power and preset load requirements of each of the to-be-configured areas.

4. The method for scheduling and configuring flexible adjustable resources according to claim 2, wherein: The mutual aid scheduling is performed on each of the to-be-configured areas according to the mutual aid channel capacity constraint and the power profit and loss distribution to obtain an initial resource allocation strategy, specifically including: Determining the power deficit value of each of the areas to be configured according to the power profit and loss distribution; Taking the mutual aid channel capacity constraint as a constraint condition, and minimizing the power shortage value and transmission loss of each of the to-be-configured areas as the optimization goal, a genetic algorithm is used to perform mutual aid scheduling on each of the to-be-configured areas to obtain the initial resource allocation strategy; wherein, the transmission loss is the product of the transmission power of the interconnecting transmission line and the average line loss rate.

5. The method for scheduling and configuring flexible adjustable resources according to claim 1, wherein: The step of obtaining the output adjustment response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy specifically includes: Determining, according to the initial resource allocation strategy, at least one resource allocation time period for each of the to-be-allocated areas and its corresponding output adjustment required power; Obtaining the output regulation response power and output regulation response time of various flexible adjustable resources in the to-be-configured area during the resource allocation time period; determining an output regulation response rate corresponding to each of the to-be-configured areas according to the output regulation response power and the output regulation required power; determining an output regulation response rate of each of the flexible adjustable resources according to the output regulation response power and the output regulation response time; The output regulation response capability of each flexible adjustable resource in each of the to-be-configured areas is determined according to the output regulation response time, the output regulation response rate, and the output regulation response speed.

6. The method for scheduling and configuring flexible adjustable resources according to claim 5, wherein: The step of grouping and aggregating the flexible adjustable resources of each of the to-be-configured areas according to the output regulation response capability to obtain a plurality of resource aggregation groups specifically includes: Grouping and aggregating the various flexible adjustable resources of two adjacent areas to be configured according to the output adjustment response time, the output adjustment response rate, the preset output adjustment response time threshold, and the preset output adjustment response rate threshold to obtain a fast response resource aggregation group and a normal response resource aggregation group; Among them, the flexible adjustable resources in the fast response resource aggregation group are flexible adjustable resources whose output regulation response time is less than the preset output regulation response time threshold and whose output regulation response rate is greater than the preset output regulation response rate threshold; the flexible adjustable resources in the conventional response resource aggregation group are flexible adjustable resources whose output regulation response time is greater than or equal to the preset output regulation response time threshold and / or whose output regulation response rate is less than or equal to the preset output regulation response rate threshold.

7. The method for scheduling and configuring flexible adjustable resources according to claim 6, wherein: After determining the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the output regulation response rate and the output regulation response rate, the method further includes: When it is detected that the output regulation response rate corresponding to any area to be configured is less than a preset output regulation response rate threshold, obtaining a current resource allocation ratio of various flexible adjustable resources in the area to be configured; Adjust the current resource allocation ratio and obtain the output regulation response rate corresponding to any one of the to-be-configured areas after the resource allocation ratio is adjusted; repeat this step until the output regulation response rate corresponding to any one of the to-be-configured areas is greater than or equal to the preset output regulation response rate threshold, and use the current resource allocation ratio as the target resource allocation ratio; According to the target resource allocation ratio, resource allocation ratio configuration is performed on various flexible adjustable resources in any one of the areas to be configured.

8. The method for scheduling and configuring flexible adjustable resources according to claim 1, wherein: The obtaining of the output regulation response data of the resource aggregation group during the renewable energy output fluctuation period specifically includes: Acquire time series data of the new energy output power of the area to be configured, and determine the rate of change of the new energy output power of the area to be configured at each moment based on the time series data of the new energy output power; Determining a new energy output fluctuation time period of the area to be configured according to a number of moments when the new energy output power change rate is greater than a preset new energy output power change rate threshold; Acquire first output response power time series data of the resource aggregation group corresponding to the area to be configured within the new energy output fluctuation time period; determining, according to the interval between the initial output response power value and the maximum output response power value in the first output response power time series data, a response duration of the resource aggregation group within the new energy output fluctuation time period; Acquire second output response power time series data of various flexible adjustable resources in the resource aggregation group within the new energy output fluctuation time period; Determining, based on the second output response power time series data and the output regulation required power during the new energy output fluctuation period, a response delay time, a response rate, and a response rate of each of the flexible adjustable resources in the resource aggregation group during the new energy output fluctuation period; wherein the response rate is a ratio between a maximum output response power value in the second output response power time series data and the output regulation required power; The output regulation response data of the resource aggregation group within the new energy output fluctuation time period is determined according to the response process duration, the response delay time, the response rate, and the response ratio.

9. The method for scheduling and configuring flexible adjustable resources according to claim 8, wherein: The adjusting the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data specifically includes: When it is detected that the response process duration of any resource aggregation group is greater than a preset response process duration threshold, determining the any resource aggregation group as the resource aggregation group to be optimized; Normalizing the response delay time, the response rate, and the response ratio of each of the flexible adjustable resources in the resource aggregation group to be optimized to obtain response feature vectors of each of the flexible adjustable resources; Based on the response feature vector, a pre-trained convolutional neural network is used to evaluate the response performance of each of the flexible adjustable resources to obtain a response performance score for each of the flexible adjustable resources; wherein the convolutional neural network is trained using historical output regulation response data of the flexible adjustable resources and corresponding response performance score labels, wherein the historical output regulation response data includes historical response delay time data, historical response rate data, and historical response rate data; Determining target scheduling priorities of various flexible adjustable resources according to the response performance score and the score intervals corresponding to the preset plurality of scheduling priorities; According to the target scheduling priority, the scheduling priorities of various flexible adjustable resources in the resource aggregation group to be optimized are adjusted.

10. A flexible and adjustable resource scheduling and configuration system, characterized in that: include: A mutual aid channel capacity constraint determination module is used to determine the mutual aid channel capacity constraints between each area to be configured based on the transmission line parameters between the multiple substations in each area to be configured; A power profit and loss distribution acquisition module is used to perform power flow calculation on each of the areas to be configured according to the transmission line parameters and the mutual aid channel capacity constraints to obtain the power profit and loss distribution of each of the areas to be configured; a resource allocation initial strategy acquisition module, configured to perform mutual aid scheduling on each of the to-be-configured areas according to the mutual aid channel capacity constraint and the power profit and loss distribution, and obtain an initial resource allocation strategy; An output regulation response capability acquisition module, configured to acquire the output regulation response capability of various flexible adjustable resources in each of the to-be-configured areas according to the initial resource allocation strategy; a flexible adjustable resource aggregation module, configured to group and aggregate the flexible adjustable resources of each of the to-be-configured areas according to the output adjustment response capability to obtain a plurality of resource aggregation groups; A flexible adjustable resource scheduling configuration module is used to obtain the output regulation response data of the resource aggregation group during the new energy output fluctuation period, and adjust the scheduling priority of the flexible adjustable resources in the resource aggregation group based on the output regulation response data, so as to schedule the output of the flexible adjustable resources according to the adjusted scheduling priority during the new energy output fluctuation period.

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