Resource scheduling methods, apparatus, equipment, and readable storage media for multiple types of aggregators participating in ancillary services in a virtual power plant.

Abstract

This application relates to a resource scheduling method, apparatus, device, readable storage medium, and computer program product for multiple types of aggregators participating in ancillary services in a virtual power plant. The method includes: determining the salience level of multiple distributed resources belonging to a target aggregator in a target service scenario, and determining a first resource from the multiple distributed resources based on the salience level; upon receiving a grid command for the target service scenario, determining whether the operating parameters of the first resource and the standard parameters indicated by the grid command meet preset conditions; if the relationship between the operating parameters and the standard parameters meets the preset conditions, constructing a battery state-of-charge model equivalent to the charging and discharging state of the first resource based on the first resource, and determining the first operating parameters of the first resource in response to the grid command based on the battery state-of-charge model. This method is beneficial for the long-term operation of distributed resources belonging to grid aggregators and improves security.

Description

Technical Field

[0001] This application relates to the field of power grid technology, and in particular to a resource scheduling method, apparatus, equipment and readable storage medium for multiple types of aggregators participating in ancillary services in a virtual power plant. Background Technology

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

[0003] In existing technologies, when there is demand in the power grid, power grid aggregators will dispatch their 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 the resources owned by grid aggregators and results in low security. Summary of the Invention

[0005] Therefore, it is necessary to provide a resource scheduling method, apparatus, equipment, and readable storage medium for multiple types of aggregators participating in ancillary services in a virtual power plant with high security, in order to address the above-mentioned technical problems.

[0006] Firstly, this application provides a resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant, including:

[0007] Determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and determine the first resource from these multiple distributed resources based on the salience level;

[0008] Upon receiving a power grid instruction for the target service scenario, determine whether the operating parameters of the first resource meet the preset conditions of the standard parameters indicated by the power grid instruction;

[0009] When the relationship between the operating 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 operating parameters of the first resource when responding to the grid command are determined according to the battery state-of-charge model.

[0010] In one embodiment, determining the salience level of the 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 effective response volume of the distributed resource within a preset time period in the target service scenario; and determining the salience level of the distributed resource in the target service scenario based on the total response volume and the effective response volume.

[0011] In one embodiment, determining the first resource from the plurality of distributed resources based on the salience level includes: determining the distributed resources among the plurality of distributed resources whose salience level is greater than a salience level threshold as the first resource.

[0012] In one embodiment, determining the first operating parameters of the first resource in response to the grid command based on the battery state of charge model includes: determining the battery state of charge information of the first resource based on the battery state of charge model; and determining the first operating parameters based on the battery state of charge information of the first resource and the grid command.

[0013] In one embodiment, the method further includes: when the relationship between the operating parameter and the standard parameter does not meet a preset condition, determining a second operating parameter when the first resource responds to the power grid command and a third operating parameter when the second resource responds to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources.

[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] Secondly, this application also provides a resource scheduling device for multiple types of aggregators participating in ancillary services in a virtual power plant, including:

[0016] The first determining module is used to determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and determine the first resource from the multiple distributed resources based on the salience level;

[0017] The second determining module is used to determine, after receiving a power grid instruction for the target service scenario, whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions.

[0018] The 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, provided that the relationship between the working parameters and the standard parameters meets preset conditions, and to determine the first working parameters of the first resource when responding to the grid command based on the battery state-of-charge model.

[0019] Thirdly, this application also provides a computer device, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the method described in any of the embodiments of the first aspect above.

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

[0021] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the embodiments of the first aspect above.

[0022] In the aforementioned virtual power plant, the resource scheduling, devices, computer equipment, computer-readable storage media, and computer program products of various aggregators participating in ancillary services first determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and then determine the first resource from these multiple distributed resources based on the salience level. Upon receiving a grid command for the target service scenario, it is determined whether the operating parameters of the first resource and the standard parameters indicated by the grid command meet preset conditions. If the relationship between the operating parameters and the standard parameters meets the preset conditions, a battery state-of-charge (POC) model equivalent to the charging and discharging state of the first resource is constructed based on the first resource, and the first operating parameters of the first resource in response to the grid command are determined based on the battery POC model. Since the first operating parameters of the first resource in response to the grid command are determined based on the battery POC model equivalent to the charging and discharging state of the first resource, the technical requirements for charging and discharging of the grid aggregator are considered, resulting in a balanced battery POC, which is beneficial to the long-term operation of the distributed resources belonging to the grid aggregator and improves security. Attached Figure Description

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. 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 any creative work.

[0024] Figure 1 This is a flowchart illustrating a resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant, as shown in one embodiment.

[0025] Figure 2 This is a flowchart illustrating a method for determining the salience level of multiple distributed resources belonging to a target aggregator in a target service scenario, as shown in one embodiment.

[0026] Figure 3 This is a flowchart illustrating a method for determining the first operating parameters of a first resource in response to a power grid command based on the battery state of charge model in one embodiment.

[0027] Figure 4 This is a flowchart illustrating a resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant, as described in another embodiment.

[0028] Figure 5 This is a structural block diagram of a resource scheduling device in a virtual power plant where multiple types of aggregators participate in ancillary services, as shown in one embodiment.

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

[0030] Figure 7 This is a diagram of the internal structure of a computer device in another embodiment. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

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

[0033] In existing technologies, when there is demand in the power grid, power grid aggregators will dispatch their 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 the resources owned by grid aggregators and results in low security.

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

[0036] The resource scheduling method for multiple aggregators participating in ancillary services in a virtual power plant provided in this application can be executed by computer equipment, which can be a terminal or a server.

[0037] In one exemplary embodiment, such as Figure 1 As shown, a resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant is provided. The method includes the following steps:

[0038] Step 101: Determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and determine the first resource from these multiple distributed resources based on the salience level.

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

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

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

[0042] For example, if the service scenarios include scenarios A, B, and C, we can first determine the salience level A1 of the multiple distributed resources belonging to the target aggregator in scenario A, the salience level B1 of the multiple distributed resources belonging to the target aggregator in scenario B, and the salience level C1 of the multiple distributed resources belonging to the target aggregator in scenario C. Then, based on A1, we determine the first resource in scenario A from the multiple distributed resources; based on B1, we determine the first resource in scenario B from the multiple distributed resources; and based on C1, we determine the first resource in scenario C from the multiple distributed resources.

[0043] In other words, multiple service scenarios can be sequentially identified as target service scenarios, and their corresponding salience levels and primary resources can be determined respectively.

[0044] For example, the attribute information of the multiple distributed resources and the target service scenario can be sequentially input into a pre-trained saliency level determination model to obtain the saliency level of the multiple distributed resources to which the target aggregator belongs under the target service scenario.

[0045] Alternatively, 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 can be determined first; based on the total response volume and the effective response volume, the salience level of the distributed resource under the target service scenario can be determined.

[0046] Furthermore, the salience levels of multiple distributed resources belonging to the target aggregator in the target service scenario can be determined based on the analytic hierarchy process algorithm.

[0047] As mentioned above, after determining the salience levels of multiple distributed resources belonging to the target aggregator in the target service scenario, the first resource can be determined from these multiple distributed resources based on their salience levels 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. For example, the performance of the first resource may be sufficient to meet the requirements of the target service scenario.

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

[0050] In some other exemplary embodiments, each service scenario is provided with a corresponding salience level range, and the first resource can be determined from the multiple distributed resources based on the salience levels of the multiple distributed resources in the target service scenario and the salience level range of 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 the preset conditions.

[0052] Optionally, the operating parameter can 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 can be pre-set by technicians according to actual needs. The preset condition can be that the operating parameter is greater than the standard parameter, or the difference between the operating parameter and the standard parameter can be less than a preset range.

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

[0054] Step 103: When the relationship between the working parameters and the standard parameters meets the preset conditions, construct a battery state-of-charge model that is 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 grid command based on the battery state-of-charge model.

[0055] The first operating parameter indicates the actual operating parameters of each distributed resource in the first resource when responding to a grid command. For example, the actual output power of each distributed resource in the first resource when responding to a grid command.

[0056] In some exemplary embodiments, if the relationship between the operating parameters and the standard parameters meets preset conditions, it can be determined that the first resource can meet the grid demand. Therefore, a battery state of charge (SOC) model equivalent to the charge / discharge state of the first resource is first constructed. This 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 a clear iterative relationship, such as electric vehicles, no SOC model is constructed; for energy storage resources in the first resource, the SOC model is determined using the ampere-hour integral method; for temperature-controlled load resources in the first resource, the SOC model is... Among them, T max T min These represent the highest and lowest acceptable temperatures for users within the temperature-controlled load resources, T. r (t) represents the typical indoor temperature at time t. 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 parameters of the first resource in response to the grid command based on the battery state of charge model. For example, the first operating parameters of the first resource in response to the grid command can be determined based on a pre-trained first operating parameter determination model and the battery state of charge model. Alternatively, the battery state of charge information of the first resource can be determined based on the battery state of charge model; then, the first operating parameters can be determined based on the battery state of charge information of the first resource and the grid command.

[0058] The resource scheduling method for multiple aggregators participating in ancillary services in the aforementioned virtual power plant first determines the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and then determines a first resource from these distributed resources based on the salience level. Upon receiving a grid command for the target service scenario, it determines whether the operating parameters of the first resource and the standard parameters indicated by the grid command meet preset conditions. If the relationship between the operating parameters and the standard parameters meets the preset conditions, a battery state-of-charge (POC) model equivalent to the charging and discharging state of the first resource is constructed based on the first resource, and the first operating parameters of the first resource in response to the grid command are determined based on the battery POC model. Since the first operating parameters of the first resource in response to the grid command are determined based on the battery POC model equivalent to the charging and discharging state of the first resource, the technical requirements for charging and discharging by the grid aggregator are considered, resulting in a balanced battery POC. This is beneficial for the long-term operation of the distributed resources belonging to the grid aggregator and improves security.

[0059] In one exemplary embodiment, such as Figure 2 As shown, determining the salience level 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 effective response volume of the distributed resource within a preset time period under 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 illustrated using a peak-shaving auxiliary service involving a target aggregator. In this service scenario, a 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 that distributed resource within the peak-shaving duration is determined based on historical data and the peak-shaving duration. Specifically, this total response volume... Among them, Q i (t) represents the actual capacity of distributed resource i within [t t+Δt], which can be determined based on historical data, Δ t The interval is the control gap, and T is the corresponding peak shaving duration.

[0063] Furthermore, the effective response volume refers to the effective workload of the distributed resource within a preset time period under the target service scenario. in Let i be the available capacity of the distributed resource i within [t t+Δt] to meet the requirements of the target service scenario.

[0064] Step 202: Determine the salience level of the distributed resource in the target service scenario based on the total response volume and the effective response volume.

[0065] In some exemplary embodiments, after determining the total response volume and effective response volume for each distributed resource, the salience level of that distributed resource in the target service scenario is determined based on the total response volume and the effective response volume. Specifically, this salience level...

[0066] In an exemplary embodiment, the method of determining a first resource from the plurality of distributed resources based on the salience level includes: determining the distributed resources among the plurality of distributed resources whose salience level is greater than a salience level threshold as the first resource.

[0067] Optionally, the significance level threshold can be preset by technicians according to actual needs.

[0068] In some exemplary embodiments, after obtaining the salience levels corresponding to the plurality of distributed resources, the distributed resources among the plurality of distributed resources whose salience levels are greater than the salience level threshold can be identified as the first resource;

[0069] Furthermore, the distributed resources among the multiple distributed resources whose salience level is less than the salience level threshold are identified as the second resource.

[0070] In one exemplary embodiment, such as Figure 3 As shown, determining the first operating parameters of the first resource in response to the grid command based on the battery state-of-charge model includes the following steps:

[0071] Step 301: Determine the battery state of charge information of the first resource based on the battery state of charge model; Step 302: Determine the first operating parameters based on the battery state of charge information of the first resource and the power grid command.

[0072] Optionally, the first operating parameter can be the actual output power when the first resource responds to a grid command.

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

[0074] Furthermore, the first operating parameter, which is the actual output power of the first resource in response to the grid command, can be determined based on the battery state-of-charge information of the first resource and the grid command. in,

[0075] N is the number of primary resources, SOC i (t) represents the battery state-of-charge information of distributed resource i in the first resource (if it cannot be calculated, let it be in P). ref When (t) > 0, take the value 0, P ref When (t) < 0, take 1), SOC mean (t) represents the average state of charge information of the first resource.

[0076] In an exemplary embodiment, if the relationship between the operating parameter and the standard parameter does not meet a preset condition, the method further includes: determining a second operating parameter when the first resource responds to the power grid command and a third operating parameter when the second resource responds to the power grid command.

[0077] The second resource is any distributed resource other than the first resource among the plurality of distributed resources.

[0078] Optionally, the second operating parameter may be the actual output power of the first resource when responding to the grid command, and the third operating parameter may be the actual output power of the second resource when responding to the grid command.

[0079] In some exemplary embodiments, if the relationship between the operating parameter and the standard parameter does not meet the preset conditions, that is, if the operating parameter is less than the standard parameter, it can be said that the output power of the first resource cannot meet the power required by the power grid command. Therefore, the first resource and the second resource need to jointly respond to the power grid command.

[0080] 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.

[0081] In some exemplary embodiments, when the relationship between the operating parameters and the standard parameters does not meet preset conditions, the first resource can respond to the grid command with maximum output power, and the second resource can be sorted according to salience level and output in ascending order. Specifically, the deficient part can be determined first based on the second operating parameters of the first resource and the standard parameters indicated by the grid command, and then the second resource can be sorted according to salience level, and the second resource can supplement the deficient part in ascending order.

[0082] In one exemplary embodiment, such as Figure 4 As shown, another resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant is provided. This method includes the following steps:

[0083] Step 401: For each of the multiple distributed resources belonging to the target aggregator, determine the total response volume and effective response volume of the distributed resource within a preset time period under the target service scenario;

[0084] Step 402: Determine the salience level of the distributed resource in the target service scenario based on the total response volume and the effective response volume; determine the distributed resource with a salience level greater than the salience level threshold among the multiple distributed resources as the first resource;

[0085] Step 403: 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.

[0086] Step 404: When the relationship between the working parameter and the standard parameter meets the preset conditions, construct a battery state-of-charge model that is equivalent to the charging and discharging state of the first resource based on the first resource, and determine the battery state-of-charge information of the first resource according to the battery state-of-charge model; determine the first working parameter according to the battery state-of-charge information of the first resource and the power grid command.

[0087] Step 405: If 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 according to the second working parameter and the standard parameter. The second resource is the distributed resource other than the first resource among the multiple distributed resources.

[0088] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0089] Based on the same inventive concept, this application also provides a resource scheduling apparatus for multiple types of aggregators participating in ancillary services in a virtual power plant, used to implement the resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant as described above. The solution provided by this apparatus is similar to the implementation described in the above method. Therefore, the specific limitations in one or more embodiments of the resource scheduling apparatus for multiple types of aggregators participating in ancillary services in a virtual power plant provided below can be found in the limitations of the resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant described above, and will not be repeated here.

[0090] In one exemplary embodiment, such as Figure 5 As shown, a resource scheduling device 500 for multiple types of aggregators participating in ancillary services in a virtual power plant is provided, comprising: a first determining module 501, a second determining module 502, and an execution module 503, wherein:

[0091] The first determining module 501 is used to determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and determine the first resource from the multiple distributed resources based on the salience level.

[0092] The second determining module 502 is used to determine, after receiving a power grid instruction for the target service scenario, whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions.

[0093] 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, and determine the first operating parameters of the first resource when responding to the grid command based on the battery state-of-charge model, provided that the relationship between the operating parameters and the standard parameters meets the preset conditions.

[0094] In one embodiment, the first determining module 501 is specifically used to determine, for each of the multiple distributed resources to which the target aggregator belongs, the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario; and to determine the salience level of the distributed resource under the target service scenario based on the total response volume and the effective response volume.

[0095] In one embodiment, the first determining module 501 is specifically used to determine the distributed resource among the plurality of distributed resources whose salience level is greater than the salience level threshold as the first resource.

[0096] In one embodiment, the execution module 503 is specifically used to determine the battery state of charge information of the first resource based on the battery state of charge model; and to determine the first operating parameters based on the battery state of charge information of the first resource and the power grid command.

[0097] In one embodiment, the execution module 503 is further configured to determine, when the relationship between the working parameters and the standard parameters does not meet the preset conditions, a second working parameter when the first resource responds to the power grid command and a third working parameter when the second resource responds to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources.

[0098] 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 to determine the third operating parameter based on the second operating parameter and the standard parameter.

[0099] In the aforementioned virtual power plant, the various modules within the resource scheduling device for ancillary services involving multiple types of aggregators can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, facilitating processor execution of the corresponding operations.

[0100] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant.

[0101] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a resource scheduling method for ancillary services involving multiple types of aggregators in a virtual power plant.

[0102] Those skilled in the art will understand that Figure 6 and Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0103] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0104] The salience levels of multiple distributed resources belonging to the target aggregator in the target service scenario are determined, and a first resource is determined from these multiple distributed resources based on the salience levels. After receiving a power grid instruction for the target service scenario, it is determined whether the operating parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions. If the relationship between the operating 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 operating parameters of the first resource in response to the power grid instruction are determined based on the battery state-of-charge model.

[0105] In one embodiment, when the processor executes the computer program, it further performs the following steps: for each of the multiple distributed resources to which the target aggregator belongs, determine the total response volume and effective response volume of the distributed resource within a preset time period under the target service scenario; and determine the salience level of the distributed resource under the target service scenario based on the total response volume and the effective response volume.

[0106] In one embodiment, when the processor executes the computer program, it further performs the following step: identifying the distributed resource among the plurality of distributed resources whose salience level is greater than a salience level threshold as the first resource.

[0107] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the battery state of charge information of the first resource based on the battery state of charge model; and determining the first operating parameter based on the battery state of charge information of the first resource and the power grid instruction.

[0108] In one embodiment, when the processor executes the computer program, it further performs the following steps: when the relationship between the operating parameters and the standard parameters does not meet the preset conditions, it determines the second operating parameters of the first resource when responding to the power grid command and the third operating parameters of the second resource when responding to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources.

[0109] In one embodiment, when the processor executes the computer program, it further performs the following steps: 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.

[0110] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0111] The salience levels of multiple distributed resources belonging to the target aggregator in the target service scenario are determined, and a first resource is determined from these multiple distributed resources based on the salience levels. After receiving a power grid instruction for the target service scenario, it is determined whether the operating parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions. If the relationship between the operating 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 operating parameters of the first resource in response to the power grid instruction are determined based on the battery state-of-charge model.

[0112] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: for each of the multiple distributed resources to which the target aggregator belongs, determine the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario; and determine the salience level of the distributed resource under the target service scenario based on the total response volume and the effective response volume.

[0113] In one embodiment, when the computer program is executed by the processor, it further performs the following step: identifying the distributed resource among the plurality of distributed resources whose salience level is greater than a salience level threshold as the first resource.

[0114] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the battery state of charge information of the first resource based on the battery state of charge model; and determining the first operating parameter based on the battery state of charge information of the first resource and the power grid command.

[0115] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: when the relationship between the operating parameters and the standard parameters does not meet the preset conditions, determining the second operating parameters of the first resource when responding to the power grid command and the third operating parameters of the second resource when responding to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources.

[0116] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: 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.

[0117] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0118] The salience levels of multiple distributed resources belonging to the target aggregator in the target service scenario are determined, and a first resource is determined from these multiple distributed resources based on the salience levels. After receiving a power grid instruction for the target service scenario, it is determined whether the operating parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions. If the relationship between the operating 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 operating parameters of the first resource in response to the power grid instruction are determined based on the battery state-of-charge model.

[0119] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: for each of the multiple distributed resources to which the target aggregator belongs, determine the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario; and determine the salience level of the distributed resource under the target service scenario based on the total response volume and the effective response volume.

[0120] In one embodiment, when the computer program is executed by the processor, it further performs the following step: identifying the distributed resource among the plurality of distributed resources whose salience level is greater than a salience level threshold as the first resource.

[0121] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the battery state of charge information of the first resource based on the battery state of charge model; and determining the first operating parameter based on the battery state of charge information of the first resource and the power grid command.

[0122] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: when the relationship between the operating parameters and the standard parameters does not meet the preset conditions, determining the second operating parameters of the first resource when responding to the power grid command and the third operating parameters of the second resource when responding to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources.

[0123] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: 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.

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this 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. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0125] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0126] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A resource scheduling method for multiple types of aggregators participating in ancillary services in a virtual power plant, characterized in that, The method includes: Determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and determine the first resource from the multiple distributed resources based on the salience level; Upon receiving a power grid instruction for the target service scenario, determine whether the operating parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions; When the relationship between the operating 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 operating parameters of the first resource when responding to the power grid command are determined according to the battery state-of-charge model. If the relationship between the operating parameters and the standard parameters does not meet the preset conditions, determine the second operating parameters when the first resource responds to the power grid command and the third operating parameters when the second resource responds to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources; Determining the salience level of 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 effective response volume of the distributed resource within a preset time period in the target service scenario; and determining the salience level of the distributed resource in the target service scenario based on the total response volume and the effective response volume.

2. The method according to claim 1, characterized in that, The step of determining the first resource from the plurality of distributed resources based on the salience level includes: The distributed resources with a significance level greater than a significance level threshold among the plurality of distributed resources are identified as the first resource.

3. The method according to claim 1, characterized in that, The step of determining the first operating parameters of the first resource in response to the grid command based on the battery state-of-charge model includes: The battery state of charge information of the first resource is determined based on the battery state of charge model. The first operating parameters are determined based on the battery state of charge information of the first resource and the power grid command.

4. The method according to claim 1, characterized in that, The determination of the second operating parameters when the first resource responds to the power grid command and the third operating parameters when the second resource responds to the power grid command includes: The maximum operating parameter of the first resource is determined as the second operating parameter, and the third operating parameter is determined based on the second operating parameter and the standard parameter.

5. The method according to claim 1, characterized in that, The operating parameter is the output power of the first resource, and the standard parameter is the output power required by the power grid.

6. The method according to claim 1, characterized in that, The preset condition is whether the working parameter is greater than the standard parameter.

7. A resource scheduling device for ancillary services involving multiple types of aggregators in a virtual power plant, characterized in that, The device includes: The first determining module is used to determine the salience level of multiple distributed resources belonging to the target aggregator in the target service scenario, and to determine the first resource from the multiple distributed resources based on the salience level; The second determining module is used to determine, after receiving a power grid instruction for the target service scenario, whether the working parameters of the first resource and the standard parameters indicated by the power grid instruction meet preset conditions. An execution module is configured to, when the relationship between the operating parameters and the standard parameters satisfies a preset condition, construct a battery state-of-charge model equivalent to the charge-discharge state of the first resource based on the first resource, and determine the first operating parameters of the first resource when responding to the power grid command based on the battery state-of-charge model; and, when the relationship between the operating parameters and the standard parameters does not satisfy a preset condition, determine the second operating parameters of the first resource when responding to the power grid command and the third operating parameters of the second resource when responding to the power grid command, wherein the second resource is a distributed resource other than the first resource among the plurality of distributed resources; The first determining module is specifically used to determine, for each of the multiple distributed resources to which the target aggregator belongs, the total response volume and the effective response volume of the distributed resource within a preset time period under the target service scenario; and to determine the salience level of the distributed resource under the target service scenario based on the total response volume and the effective response volume.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

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

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

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