Resource scheduling method, device and equipment for multiple types of aggregators to participate in auxiliary service in virtual power plant and readable storage medium

Abstract

The invention relates to a resource scheduling method, device and equipment for multiple types of aggregators to participate in auxiliary service in a virtual power plant, a readable storage medium and a computer program product. The method comprises the following steps: determining a significance level corresponding to a plurality of distributed resources to which a target aggregator belongs in a target service scene, and determining a first resource from the plurality of distributed resources according to the significance level; after a power grid instruction for the target service scene is received, whether the working parameters of the first resource and standard parameters indicated by the power grid instruction meet preset conditions or not is determined; and under the condition that the relationship between the working parameter and the standard parameter meets a preset condition, constructing a battery state-of-charge model equivalent to the charge-discharge state of the first resource based on the first resource, and determining a first working parameter when the first resource responds to the power grid instruction according to the battery state-of-charge model. By adopting the method, long-term operation of the distributed resources to which the power grid aggregator belongs is facilitated, and the safety is improved.

Description

Technical Field

[0001] The present application relates to the field of power grid technology, and in particular to a resource scheduling method, device, equipment and readable storage medium for multiple types of aggregators to participate in auxiliary services in a virtual power plant. Background Art

[0002] Grid aggregators can form a large-scale virtual power plant by integrating resources such as small distributed generation, energy storage and adjustable loads to participate in the electricity market more efficiently.

[0003] In the prior art, when there is demand on the power grid, the power grid aggregator will dispatch its resources to respond to the demand in order to support the stable operation of the power grid.

[0004] However, existing methods do not take into account the technical requirements of grid aggregators for charging and discharging, which is not conducive to the long-term operation of resources belonging to grid aggregators and has low security. Summary of the invention

[0005] Based on this, it is necessary to provide a resource scheduling method, device, equipment and readable storage medium for multiple types of aggregators to participate in auxiliary services in a virtual power plant with higher security in order to address the above technical problems.

[0006] In a first aspect, the present application provides a resource scheduling method for multiple types of aggregators to participate in auxiliary services in a virtual power plant, including:

[0007] Determine a significance level corresponding to a plurality of distributed resources belonging to a target aggregator in a target service scenario, and determine a first resource from the plurality of distributed resources according to the significance level;

[0008] After receiving the power grid instruction for the target service scenario, determining whether the working parameter of the first resource and the standard parameter indicated by the power grid instruction meet a preset condition;

[0009] When the relationship between the working parameter and the standard parameter meets the preset conditions, a battery state of charge model equivalent to the charging and discharging state of the first resource is constructed based on the first resource, and the first working parameter of the first resource when responding to the power grid instruction is determined according to the battery state of charge model.

[0010] In one of the embodiments, the determination of the significance level corresponding to multiple distributed resources belonging to the target aggregator in the target service scenario includes: for each of the multiple distributed resources belonging to the target aggregator, determining the total response volume and the effective response volume of the distributed resource within a preset time period in the target service scenario; determining the significance level corresponding to the distributed resource in the target service scenario based on the total response volume and the effective response volume.

[0011] In one of the embodiments, determining the first resource from the multiple distributed resources according to the significance level includes: determining a distributed resource whose significance level among the multiple distributed resources is greater than a significance level threshold as the first resource.

[0012] In one of the embodiments, determining the first operating parameter of the first resource when responding to the power grid instruction according to the battery state of charge model includes: determining the battery state of charge information of the first resource according to the battery state of charge model; determining the first operating parameter according to the battery state of charge information of the first resource and the power grid instruction.

[0013] In one of the embodiments, the method also includes: when the relationship between the working parameter and the standard parameter does not meet the preset conditions, determining the second working parameter when the first resource responds to the power grid instruction and the third working parameter when the second resource responds to the power grid instruction, the second resource being a distributed resource among the multiple distributed resources other than the first resource.

[0014] In one embodiment, determining the second operating parameter of the first resource when responding to the power grid command and the third operating parameter of the second resource when responding to the power grid command includes: determining the maximum operating parameter of the first resource as the second operating parameter, and determining the third operating parameter based on the second operating parameter and the standard parameter.

[0015] In a second aspect, the present application also provides a resource scheduling device for multiple types of aggregators to participate in auxiliary services in a virtual power plant, including:

[0016] A first determination module, configured to determine a significance level corresponding to a plurality of distributed resources belonging to a target aggregator in a target service scenario, and to determine a first resource from the plurality of distributed resources according to the significance level;

[0017] A second determination module is used to determine whether the working parameters of the first resource and the standard parameters indicated by the grid instruction meet preset conditions after receiving the grid instruction for the target service scenario;

[0018] An execution module is used to construct a battery state of charge model equivalent to the charging and discharging state of the first resource based on the first resource when the relationship between the working parameter and the standard parameter meets a preset condition, and determine the first working parameter of the first resource when responding to the power grid instruction according to the battery state of charge model.

[0019] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in any embodiment of the first aspect when executing the computer program.

[0020] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any one of the embodiments of the first aspect above.

[0021] In a fifth aspect, the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the method described in any embodiment of the first aspect above.

[0022] The resource scheduling, device, computer equipment, computer-readable storage medium and computer program product for multiple types of aggregators participating in auxiliary services in the above-mentioned virtual power plant first determine the significance level corresponding to the multiple distributed resources belonging to the target aggregator in the target service scenario, and determine the first resource from the multiple distributed resources according to the significance level; after receiving the power grid instruction for the target service scenario, determine whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet the preset conditions; when the relationship between the working parameters and the standard parameters meets the preset conditions, construct a battery state of charge model equivalent to the charge and discharge state of the first resource based on the first resource, and determine the first working parameter of the first resource when responding to the power grid instruction according to the battery state of charge model. Since the first working parameter of the first resource in response to the power grid instruction is determined according to the battery state of charge model equivalent to the charge and discharge state of the first resource, the technical requirements of the power grid aggregator for charging and discharging are taken into consideration, so that the battery state of charge is balanced, which is beneficial to the long-term operation of the distributed resources belonging to the power grid aggregator and improves safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 A schematic flow chart of a method for resource scheduling in which multiple types of aggregators participate in auxiliary services in a virtual power plant in one embodiment;

[0025] Figure 2 A flowchart of a method for determining significance levels corresponding to a plurality of distributed resources belonging to a target aggregator in a target service scenario in one embodiment;

[0026] Figure 3 A flowchart of a method for determining a first operating parameter of the first resource when responding to the grid instruction according to the battery state of charge model in one embodiment;

[0027] Figure 4 A schematic flow chart of a method for resource scheduling in which multiple types of aggregators participate in auxiliary services in a virtual power plant in another embodiment;

[0028] Figure 5 A structural block diagram of a resource scheduling device in which multiple types of aggregators participate in auxiliary services in a virtual power plant in one embodiment;

[0029] Figure 6 is an internal structure diagram of a computer device in one embodiment;

[0030] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0032] Grid aggregators can form a large-scale virtual power plant by integrating resources such as small distributed generation, energy storage and adjustable loads to participate in the electricity market more efficiently.

[0033] In the prior art, when there is demand on the power grid, the power grid aggregator will dispatch its resources to respond to the demand in order to support the stable operation of the power grid.

[0034] However, existing methods do not take into account the technical requirements of grid aggregators for charging and discharging, which is not conducive to the long-term operation of resources belonging to grid aggregators and has low security.

[0035] In view of this, the present application provides a resource scheduling method for the participation of multiple types of aggregators in auxiliary services in a virtual power plant, which can balance the charge state of the batteries of the distributed resources belonging to the grid aggregators, thereby facilitating the long-term operation of the distributed resources belonging to the grid aggregators and improving safety.

[0036] The resource scheduling method for the participation of multiple types of aggregators in auxiliary services in a virtual power plant provided in the present application can be executed by a computer device, which can be a terminal or a server.

[0037] In an exemplary embodiment, Figure 1 As shown, a resource scheduling method for multiple types of aggregators to participate in auxiliary services in a virtual power plant is provided, and the method includes the following steps:

[0038] Step 101: determine the significance levels of a plurality of distributed resources belonging to a target aggregator in a target service scenario, and determine a first resource from the plurality of distributed resources according to the significance levels.

[0039] Optionally, the target service scenario refers to an auxiliary service market scenario in which the target aggregator participates. Specifically, the target service scenario may include energy frequency regulation auxiliary services in which the target aggregator participates, peak load regulation auxiliary services in which the target aggregator participates, and day-ahead energy auxiliary services in which the target aggregator participates.

[0040] The significance level refers to the ratio of the actual working parameters of the distributed resource when responding to the grid command in the target service scenario to the working parameters under normal conditions. Specifically, it can be the ratio of the actual output power of the distributed resource when responding to the grid command in the target service scenario to the output power that should be output. This significance level can be used to characterize the working performance of the distributed resource in the target service scenario.

[0041] In some exemplary embodiments, the significance levels of multiple distributed resources belonging to the target aggregator in each service scenario may be first determined, and then the first resource in each service scenario may be determined from the multiple distributed resources based on the significance levels.

[0042] For example, if the service scenarios include scenario A, scenario B, and scenario C, then the significance level A1 corresponding to the multiple distributed resources belonging to the target aggregator in scenario A, the significance level B1 corresponding to the multiple distributed resources belonging to the target aggregator in scenario B, and the significance level C1 corresponding to the multiple distributed resources belonging to the target aggregator in scenario C can be determined first. Then, the first resource in scenario A is determined from the multiple distributed resources according to A1, the first resource in scenario B is determined from the multiple distributed resources according to B1, and the first resource in scenario C is determined from the multiple distributed resources according to C1.

[0043] That is, multiple service scenarios may be determined as target service scenarios in sequence, and the corresponding significance levels and first resources may be determined respectively.

[0044] Exemplarily, the attribute information of the multiple distributed resources and the target service scenario can be input into a pre-trained significance level determination model in sequence to obtain the significance levels corresponding to the multiple distributed resources belonging to the target aggregator in the target service scenario.

[0045] It is also possible to first determine the total response volume and effective response volume of each of the multiple distributed resources within a preset time period under the target service scenario; and determine the significance level corresponding to the distributed resource in the target service scenario based on the total response volume and the effective response volume.

[0046] The significance levels of the multiple distributed resources belonging to the target aggregator in the target service scenario may also be determined based on the hierarchical analysis algorithm.

[0047] As described above, after determining the significance levels corresponding to the multiple distributed resources belonging to the target aggregator in the target service scenario, the first resource can also be determined from the multiple distributed resources based on the significance levels corresponding to the multiple distributed resources in the target service scenario.

[0048] Optionally, the first resource refers to a resource among multiple distributed resources that meets the requirements of the target service scenario. Exemplarily, the performance of the first resource can meet the requirements of the target service scenario.

[0049] In some exemplary embodiments, a significance level threshold is set for each service scenario, and the first resource can be determined from the multiple distributed resources based on the significance levels corresponding to the multiple distributed resources in the target service scenario and the significance level threshold corresponding to the target service scenario.

[0050] In other exemplary embodiments, a significance level range is set for each service scenario, and the first resource can be determined from the multiple distributed resources based on the significance levels corresponding to the multiple distributed resources in the target service scenario and the significance level range corresponding to the target service scenario.

[0051] Step 102: After receiving the power grid instruction for the target service scenario, determine whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions.

[0052] Optionally, the operating parameter may be the output power of the first resource, and the standard parameter refers to the output power required by the power grid. The preset condition may be pre-set by a technician according to actual needs. The preset condition may be that the operating parameter is greater than the standard parameter, or that the difference between the operating parameter and the standard parameter is less than a preset range.

[0053] In some exemplary embodiments, after receiving the grid instruction for the target service scenario, a first resource adapted to the target service scenario may be obtained first, and then it may be determined whether the working parameters of the first resource and the standard parameters indicated by the grid instruction meet the preset conditions. Specifically, it may be determined whether the output power of the first resource is greater than the power required by the grid indicated by the grid instruction.

[0054] Step 103: When the relationship between the operating parameter and the standard parameter meets a preset condition, a battery state of charge model equivalent to the charging and discharging state of the first resource is constructed based on the first resource, and a first operating parameter of the first resource when responding to the grid instruction is determined according to the battery state of charge model.

[0055] The first operating parameter indication is an actual operating parameter of each distributed resource in the first resource when responding to a power grid instruction, for example, an actual output power of each distributed resource in the first resource when responding to a power grid instruction.

[0056] In some exemplary embodiments, when the relationship between the working parameter and the standard parameter meets the preset conditions, it can be determined that the first resource can meet the grid demand, and a battery state of charge (SOC, State of Charge) model equivalent to the charge and discharge state of the first resource is first constructed based on the first resource. The SOC model can be used to allocate the output power of the first resource. Specifically, for resources in the first resource that do not have an obvious iterative relationship, such as electric vehicles, the SOC model is not constructed; for energy storage resources in the first resource, the SOC model is determined using the ampere-hour integration method; for temperature-controlled load resources in the first resource, the SOC model is ,in, , are the highest and lowest temperatures acceptable to users in the temperature control load resources, for Typical indoor temperature at the time. The typical indoor temperature is the temperature of the temperature-controlled load resource simulated by the target aggregator through reinforcement learning after responding to the grid command.

[0057] Furthermore, after constructing the SOC model, it is also necessary to determine the first operating parameter of the first resource when responding to the grid instruction according to the battery state of charge model. Exemplarily, the first operating parameter of the first resource when responding to the grid instruction can be determined based on a pre-trained first operating parameter determination model and the battery state of charge model. The battery state of charge information of the first resource can also be determined according to the battery state of charge model; and then the first operating parameter can be determined according to the battery state of charge information of the first resource and the grid instruction.

[0058] The resource scheduling method for multiple types of aggregators participating in auxiliary services in the above virtual power plant first determines the significance level corresponding to the multiple distributed resources belonging to the target aggregator in the target service scenario, and determines the first resource from the multiple distributed resources according to the significance level; after receiving the power grid instruction for the target service scenario, determines whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet the preset conditions; when the relationship between the working parameters and the standard parameters meets the preset conditions, a battery state of charge model equivalent to the charging and discharging state of the first resource is constructed based on the first resource, and the first working parameter of the first resource when responding to the power grid instruction is determined according to the battery state of charge model equivalent to the charging and discharging state of the first resource. Since the first working parameter of the first resource in response to the power grid instruction is determined according to the battery state of charge model equivalent to the charging and discharging state of the first resource, the technical requirements of the power grid aggregator for charging and discharging are taken into consideration, so that the battery state of charge is balanced, which is beneficial to the long-term operation of the distributed resources belonging to the power grid aggregator and improves safety.

[0059] In an exemplary embodiment, Figure 2 As shown, determining the significance levels of multiple distributed resources belonging to the target aggregator in the target service scenario includes the following steps:

[0060] Step 201: For each of the multiple distributed resources belonging to the target aggregator, determine the total response volume and the effective response volume of the distributed resource within a preset time period in the target service scenario.

[0061] The total response volume refers to the actual workload of the distributed resource within a preset time period under the target service scenario.

[0062] In some exemplary embodiments, the target service scenario is a peak-shaving auxiliary service in which a target aggregator participates. In this service scenario, the preset time period is the peak-shaving duration. For each of the multiple distributed resources belonging to the target aggregator, the total response volume of the distributed resource within the peak-shaving duration is determined based on historical data and the peak-shaving duration. Specifically, the total response volume ,in, for Distributed resources The actual capacity may be determined based on historical data. To regulate the gap, is the corresponding peak load duration.

[0063] Furthermore, the effective response volume refers to the effective workload of the distributed resource within a preset time period in the target service scenario. ,in for Distributed resources Available capacity that meets the requirements of the target service scenario.

[0064] Step 202: Determine the significance level of the distributed resource in the target service scenario according to the total response volume and the effective response volume.

[0065] In some exemplary embodiments, after determining the total response volume and the effective response volume for each distributed resource, the significance level corresponding to the distributed resource in the target service scenario is determined according to the total response volume and the effective response volume. Specifically, the significance level .

[0066] In an exemplary embodiment, it is characterized in that determining the first resource from the multiple distributed resources according to the significance level includes: determining a distributed resource whose significance level is greater than a significance level threshold among the multiple distributed resources as the first resource.

[0067] Optionally, the significance level threshold may be preset by a technician according to actual needs.

[0068] In some exemplary embodiments, after obtaining the significance levels corresponding to the multiple distributed resources, a distributed resource whose significance level among the multiple distributed resources is greater than the significance level threshold may be determined as the first resource;

[0069] Further, a distributed resource among the multiple distributed resources whose significance level is less than the significance level threshold is determined as a second resource.

[0070] In an exemplary embodiment, Figure 3 As shown, determining the first operating parameter of the first resource when responding to the grid instruction according to the battery state of charge model includes the following steps:

[0071] Step 301, determining the battery state of charge information of the first resource according to the battery state of charge model; Step 302, determining the first operating parameter according to the battery state of charge information of the first resource and the power grid instruction.

[0072] Optionally, the first operating parameter may be actual output power of the first resource when responding to a grid instruction.

[0073] In some exemplary embodiments, after the battery state of charge model is determined, the battery state of charge information of the first resource may be determined based on the battery state of charge model.

[0074] Furthermore, the first operating parameter, that is, the actual output power of the first resource when responding to the grid instruction, can be determined according to the battery charge state information of the first resource and the grid instruction. Specifically, ,in, , is the number of first resources, is the battery charge state information of the distributed resource i in the first resource (if it cannot be calculated, let it be When 0, 1 when is the average state of charge information of the first resource.

[0075] In an exemplary embodiment, when the relationship between the operating parameter and the standard parameter does not satisfy a preset condition, the method further includes: determining a second operating parameter when the first resource responds to the grid command and a third operating parameter when the second resource responds to the grid command.

[0076] The second resource is a distributed resource among the multiple distributed resources except the first resource.

[0077] Optionally, the second operating parameter may be the actual output power of the first resource when responding to the grid instruction, and the third operating parameter may be the actual output power of the second resource when responding to the grid instruction.

[0078] In some exemplary embodiments, when the relationship between the working parameter and the standard parameter does not satisfy the preset condition, that is, when the working parameter is less than the standard parameter, it can be explained that the output power of the first resource cannot meet the required power indicated by the grid instruction. Therefore, the first resource and the second resource are required to jointly respond to the grid instruction.

[0079] In an exemplary embodiment, determining the second operating parameter of the first resource when responding to the power grid command and the third operating parameter of the second resource when responding to the power grid command includes: determining the maximum operating parameter of the first resource as the second operating parameter, and determining the third operating parameter based on the second operating parameter and the standard parameter.

[0080] In some exemplary embodiments, when the relationship between the operating parameter and the standard parameter does not meet the preset condition, the first resource can respond to the grid instruction according to the maximum output power, and the second resource can be sorted according to the significance level and output in ascending order. Specifically, the insufficient part can be determined according to the second operating parameter of the first resource and the standard parameter indicated by the grid instruction, and then the second resource can be sorted according to the significance level, and the second resource makes up for the insufficient part in ascending order.

[0081] In an exemplary embodiment, Figure 4 As shown, another resource scheduling method for multi-type aggregators to participate in auxiliary services in a virtual power plant is provided, and the method includes the following steps:

[0082] Step 401: for each of the multiple distributed resources belonging to the target aggregator, determine the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario;

[0083] Step 402: determining the significance level of the distributed resource in the target service scenario according to the total response amount and the effective response amount; determining a distributed resource whose significance level is greater than a significance level threshold among the multiple distributed resources as the first resource;

[0084] Step 403: after receiving the power grid instruction for the target service scenario, determine whether the working parameter of the first resource and the standard parameter indicated by the power grid instruction meet the preset conditions;

[0085] Step 404: when the relationship between the operating parameter and the standard parameter meets a preset condition, a battery state of charge model equivalent to the charge and discharge state of the first resource is constructed based on the first resource, and the battery state of charge information of the first resource is determined according to the battery state of charge model; the first operating parameter is determined according to the battery state of charge information of the first resource and the power grid instruction;

[0086] Step 405: When the relationship between the working parameter and the standard parameter does not meet the preset conditions, the maximum working parameter of the first resource is determined as the second working parameter, and the third working parameter is determined based on the second working parameter and the standard parameter. The second resource is a distributed resource among the multiple distributed resources except the first resource.

[0087] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0088] Based on the same inventive concept, the embodiment of the present application also provides a resource scheduling device for multiple types of aggregators participating in auxiliary services in a virtual power plant for implementing the resource scheduling method for multiple types of aggregators participating in auxiliary services in a virtual power plant involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the resource scheduling device for multiple types of aggregators participating in auxiliary services in one or more virtual power plants provided below can be referred to the limitations of the resource scheduling method for multiple types of aggregators participating in auxiliary services in a virtual power plant above, and will not be repeated here.

[0089] In an exemplary embodiment, Figure 5 As shown, a resource scheduling device 500 for multiple types of aggregators to participate in auxiliary services in a virtual power plant is provided, comprising: a first determination module 501, a second determination module 502 and an execution module 503, wherein:

[0090] A first determination module 501 is used to determine the significance level of a plurality of distributed resources belonging to a target aggregator in a target service scenario, and determine a first resource from the plurality of distributed resources according to the significance level;

[0091] A second determination module 502 is used to determine whether the working parameters of the first resource and the standard parameters indicated by the grid instruction meet a preset condition after receiving the grid instruction for the target service scenario;

[0092] The execution module 503 is used to construct a battery state of charge model equivalent to the charging and discharging state of the first resource based on the first resource when the relationship between the working parameter and the standard parameter meets the preset conditions, and determine the first working parameter of the first resource when responding to the power grid instruction according to the battery state of charge model.

[0093] In one embodiment, the first determination module 501 is specifically used to determine, for each of the multiple distributed resources belonging to the target aggregator, a total response volume and an effective response volume of the distributed resource within a preset time period under the target service scenario; and determine the significance level corresponding to the distributed resource under the target service scenario based on the total response volume and the effective response volume.

[0094] In an embodiment, the first determination module 501 is specifically configured to determine a distributed resource whose significance level is greater than a significance level threshold among the multiple distributed resources as the first resource.

[0095] In one embodiment, the execution module 503 is specifically configured to determine the battery state of charge information of the first resource according to the battery state of charge model; and determine the first operating parameter according to the battery state of charge information of the first resource and the grid instruction.

[0096] In one embodiment, the execution module 503 is also used to determine the second working parameter of the first resource when responding to the power grid instruction and the third working parameter of the second resource when responding to the power grid instruction when the relationship between the working parameter and the standard parameter does not meet the preset conditions, and the second resource is a distributed resource among the multiple distributed resources other than the first resource.

[0097] In one embodiment, the execution module 503 is specifically configured to determine the maximum operating parameter of the first resource as the second operating parameter, and determine the third operating parameter according to the second operating parameter and the standard parameter.

[0098] Each module in the resource scheduling device for the participation of multiple types of aggregators in auxiliary services in the virtual power plant can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0099] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a resource scheduling method for multiple types of aggregators to participate in auxiliary services in a virtual power plant is implemented.

[0100] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 7As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (Near Field Communication, NFC) or other technologies. When the computer program is executed by the processor, a resource scheduling method for multiple types of aggregators to participate in auxiliary services in a virtual power plant is implemented.

[0101] Those skilled in the art will understand that Figure 6 and Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0102] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0103] Determine the significance levels corresponding to multiple distributed resources belonging to the target aggregator in the target service scenario, and determine a first resource from the multiple distributed resources based on the significance level; after receiving a power grid instruction for the target service scenario, determine whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions; when the relationship between the working parameters and the standard parameters meets the preset conditions, construct a battery state of charge model equivalent to the charging and discharging state of the first resource based on the first resource, and determine the first working parameters of the first resource when responding to the power grid instruction based on the battery state of charge model.

[0104] In one embodiment, when the processor executes the computer program, the following steps are also implemented: for each of the multiple distributed resources belonging to the target aggregator, the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario are determined; based on the total response volume and the effective response volume, the significance level corresponding to the distributed resource in the target service scenario is determined.

[0105] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining a distributed resource among the multiple distributed resources whose significance level is greater than a significance level threshold as the first resource.

[0106] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining the battery state of charge information of the first resource according to the battery state of charge model; and determining the first operating parameter according to the battery state of charge information of the first resource and the grid instruction.

[0107] In one embodiment, when the processor executes the computer program, the following steps are also implemented: when the relationship between the working parameter and the standard parameter does not meet the preset conditions, determine the second working parameter when the first resource responds to the power grid instruction and the third working parameter when the second resource responds to the power grid instruction, and the second resource is a distributed resource among the multiple distributed resources except the first resource.

[0108] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining the maximum operating parameter of the first resource as the second operating parameter, and determining the third operating parameter according to the second operating parameter and the standard parameter.

[0109] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0110] Determine the significance levels corresponding to multiple distributed resources belonging to the target aggregator in the target service scenario, and determine a first resource from the multiple distributed resources based on the significance level; after receiving a power grid instruction for the target service scenario, determine whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions; when the relationship between the working parameters and the standard parameters meets the preset conditions, construct a battery state of charge model equivalent to the charging and discharging state of the first resource based on the first resource, and determine the first working parameters of the first resource when responding to the power grid instruction based on the battery state of charge model.

[0111] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: for each of the multiple distributed resources belonging to the target aggregator, the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario are determined; based on the total response volume and the effective response volume, the significance level corresponding to the distributed resource in the target service scenario is determined.

[0112] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: a distributed resource whose significance level is greater than a significance level threshold among the multiple distributed resources is determined as the first resource.

[0113] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the battery state of charge information of the first resource according to the battery state of charge model; and determining the first operating parameter according to the battery state of charge information of the first resource and the grid instruction.

[0114] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the relationship between the working parameter and the standard parameter does not meet the preset conditions, determine the second working parameter of the first resource when responding to the power grid instruction and the third working parameter of the second resource when responding to the power grid instruction, and the second resource is a distributed resource among the multiple distributed resources except the first resource.

[0115] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining the maximum operating parameter of the first resource as the second operating parameter, and determining the third operating parameter according to the second operating parameter and the standard parameter.

[0116] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0117] Determine the significance levels corresponding to multiple distributed resources belonging to the target aggregator in the target service scenario, and determine a first resource from the multiple distributed resources based on the significance level; after receiving a power grid instruction for the target service scenario, determine whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions; when the relationship between the working parameters and the standard parameters meets the preset conditions, construct a battery state of charge model equivalent to the charging and discharging state of the first resource based on the first resource, and determine the first working parameters of the first resource when responding to the power grid instruction based on the battery state of charge model.

[0118] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: for each of the multiple distributed resources belonging to the target aggregator, the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario are determined; based on the total response volume and the effective response volume, the significance level corresponding to the distributed resource in the target service scenario is determined.

[0119] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: a distributed resource whose significance level is greater than a significance level threshold among the multiple distributed resources is determined as the first resource.

[0120] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the battery state of charge information of the first resource according to the battery state of charge model; and determining the first operating parameter according to the battery state of charge information of the first resource and the grid instruction.

[0121] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the relationship between the working parameter and the standard parameter does not meet the preset conditions, determine the second working parameter of the first resource when responding to the power grid instruction and the third working parameter of the second resource when responding to the power grid instruction, and the second resource is a distributed resource among the multiple distributed resources except the first resource.

[0122] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining the maximum operating parameter of the first resource as the second operating parameter, and determining the third operating parameter according to the second operating parameter and the standard parameter.

[0123] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0124] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0125] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A resource scheduling method for multi-type aggregators to participate in auxiliary services in a virtual power plant, characterized in that: The method comprises: Determine a significance level corresponding to a plurality of distributed resources belonging to a target aggregator in a target service scenario, and determine a first resource from the plurality of distributed resources according to the significance level; After receiving the grid instruction for the target service scenario, determining whether the working parameters of the first resource and the standard parameters indicated by the grid instruction meet preset conditions; When the relationship between the working parameters and the standard parameters meets the preset conditions, a battery state of charge model equivalent to the charging and discharging state of the first resource is constructed based on the first resource, and the first working parameters of the first resource when responding to the grid instruction are determined according to the battery state of charge model.

2. The method according to claim 1, characterized in that The determining of the significance levels of the plurality of distributed resources belonging to the target aggregator in the target service scenario includes: For each of the multiple distributed resources belonging to the target aggregator, determine the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario; The significance level corresponding to the distributed resource in the target service scenario is determined according to the total response volume and the effective response volume.

3. The method according to claim 1, characterized in that The determining a first resource from the plurality of distributed resources according to the significance level comprises: A distributed resource among the multiple distributed resources whose significance level is greater than a significance level threshold is determined as the first resource.

4. The method according to claim 1, characterized in that: The determining, according to the battery state of charge model, a first operating parameter of the first resource when responding to the grid instruction comprises: determining the battery state of charge information of the first resource according to the battery state of charge model; The first operating parameter is determined according to the battery state of charge information of the first resource and the grid instruction.

5. The method according to claim 1, characterized in that The method further comprises: When the relationship between the working parameter and the standard parameter does not meet the preset conditions, determine the second working parameter of the first resource when responding to the power grid command and the third working parameter of the second resource when responding to the power grid command, and the second resource is a distributed resource among the multiple distributed resources except the first resource.

6. The method according to claim 5, characterized in that The determining of a second operating parameter when the first resource responds to the power grid instruction and a third operating parameter when the second resource responds to the power grid instruction includes: The maximum operating parameter of the first resource is determined as the second operating parameter, and the third operating parameter is determined according to the second operating parameter and the standard parameter.

7. A resource scheduling device for multiple types of aggregators to participate in auxiliary services in a virtual power plant, characterized in that: The device comprises: A first determination module, configured to determine a significance level corresponding to a plurality of distributed resources belonging to a target aggregator in a target service scenario, and to determine a first resource from the plurality of distributed resources according to the significance level; A second determination module is used to determine whether the working parameters of the first resource and the standard parameters indicated by the grid instruction meet preset conditions after receiving the grid instruction for the target service scenario; An execution module is used to construct a battery state of charge model equivalent to the charging and discharging state of the first resource based on the first resource when the relationship between the working parameter and the standard parameter meets a preset condition, and determine the first working parameter of the first resource when responding to the power grid instruction according to the battery state of charge model.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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