Power load data processing method and electronic equipment

Abstract

The invention provides a power load data processing method and electronic equipment, and relates to the technical field of data processing. The method comprises the following steps: acquiring power load data of a plurality of load resource objects in the same auxiliary service scene, and determining a data deviation value of the power load data; determining data value evaluation information according to the data deviation value, the value related data, a data quality factor evaluation model, a timeliness factor evaluation model, an internal attribute evaluation model, a value evaluation model and a comprehensive evaluation model; performing value evaluation processing on the power load data according to the data value evaluation information to obtain the data value of the power load data; and determining a transmission sequence of the power load data according to the data value, and sequentially transmitting the power load data according to the transmission sequence. According to the method and the device, the value of the power load data is evaluated, so that the transmission pressure caused by a large amount of concurrent data communication requirements in a communication network is effectively relieved, and the occurrence of communication congestion is prevented.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method and electronic equipment for processing power load data. Background Art

[0002] As the world pays more and more attention to the development of sustainable energy, the proportion of renewable energy in the power system is growing rapidly. However, due to the inherent intermittent and uncertain nature of renewable energy such as wind and solar energy, the stable operation of the power system is challenged, especially in terms of power balance and frequency control. In order to solve this problem and achieve resource regulation, the dispatch center needs to regulate a large number of dispersed demand-side load resources. In this process, multi-point data concurrency and high-frequency data collection will occur, which will in turn generate massive data communication needs.

[0003] However, since demand-side load resources are usually scattered, usually come from different demand-side load resource entities, and are used in different power auxiliary service scenarios, the dispatch center must simultaneously regulate a large number of demand-side load resources. In this process, it is necessary not only to obtain the status information of each load resource in real time, but also to frequently update these states to adapt to the rapidly changing supply and demand situation, resulting in a large number of concurrent data communication needs. The large number of concurrent data communication needs brings transmission pressure to the communication network and easily causes communication congestion. Summary of the invention

[0004] The purpose of this application is to provide a power load data processing method and electronic device to address the deficiencies in the above-mentioned prior art, so as to solve the problem that a large number of concurrent data communication demands in the prior art bring transmission pressure to the communication network and easily cause communication congestion.

[0005] To achieve the above purpose, the technical solution adopted in the embodiment of the present application is as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for processing power load data, the method comprising:

[0007] Obtaining power load data of multiple load resource objects in the same auxiliary service scenario, and determining a data deviation value of the power load data of each of the load resource objects, wherein the data deviation value is a deviation value between initial power load data generated by the load resource object and target power load data obtained by collecting the initial power load data;

[0008] Determine the data value assessment information of each load resource object in the auxiliary service scenario according to the data deviation value and value-related data of the power load data of each load resource object, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model, wherein the value-related data includes: transaction parameters, the scheduling cycle and the collection interval within the scheduling cycle;

[0009] According to the data value evaluation information of each load resource object in the auxiliary service scenario, the power load data of each load resource object is value evaluated to obtain the data value of the power load data of each load resource object;

[0010] According to the data value of the power load data of each load resource object, the transmission order of the power load data of each load resource object is determined, and the power load data of each load resource object is transmitted in sequence according to the transmission order of the power load data of each load resource object.

[0011] As a possible implementation method, the data value evaluation information of each load resource object in the auxiliary service scenario is determined according to the data deviation value of the power load data of each load resource object, the data quality factor evaluation model, the timeliness factor evaluation model, the intrinsic attribute evaluation model, the value evaluation model and the comprehensive evaluation model, including:

[0012] Determining a quality factor evaluation result of each of the load resource objects in the auxiliary service scenario according to the data deviation value and the data quality factor evaluation model;

[0013] Determine a timeliness evaluation result of each of the load resource objects in the auxiliary service scenario according to the data deviation value and the timeliness factor evaluation model;

[0014] Determine an intrinsic attribute evaluation result of each of the load resource objects in the auxiliary service scenario according to the quality factor evaluation result, the timeliness evaluation result and the intrinsic attribute evaluation model;

[0015] Determine, according to the value-related data and the value assessment model, a value assessment result of each of the load resource objects in the auxiliary service scenario;

[0016] The data value assessment information is determined based on the intrinsic attribute assessment result, the value assessment result and the comprehensive assessment model.

[0017] As a possible implementation, the data quality factor evaluation model is represented by a first formula, a second formula and a third formula;

[0018] The first formula is: Among them, q a,w represents the data deviation value, represents the initial power load data generated by the load resource object, represents the target power load data obtained by collecting the initial power load data;

[0019] The second formula is: in, represents the quality factor evaluation result, represents the maximum allowable deviation of the load resource object;

[0020] The third formula is: in, represents the maximum allowable deviation of the load resource object, q a,w represents the data deviation value, σ a represents the variance of the set of data deviation values, μ a Represents the mean of the set of data deviation values.

[0021] As a possible implementation, the timeliness factor evaluation model is represented by the fourth formula;

[0022] The fourth formula is: in, represents the timeliness assessment result, t rec Indicates the receiving time. represents the scene correlation coefficient, Indicates the maximum allowable deviation of the load resource object.

[0023] As a possible implementation, the intrinsic attribute evaluation model is represented by the fifth formula;

[0024] The fifth formula is: Among them, VoI a,w represents the intrinsic property evaluation result, represents the quality factor evaluation result, represents the timeliness assessment result, represents the coefficient corresponding to the quality factor evaluation result, Represents the coefficient corresponding to the timeliness evaluation result.

[0025] As a possible implementation, the value assessment model is represented by the sixth formula;

[0026] The sixth formula is: Among them, VoE a,w Represents the value assessment result, pa,w represents the transaction parameters, τ w represents the scheduling period, f w represents the collection interval within the scheduling period, and χ represents the unit conversion factor.

[0027] As a possible implementation, the comprehensive evaluation model is represented by the seventh formula;

[0028] The seventh formula is: VoD a,w =VoI a,w V0E a,w , where VoD a,w Indicates the data value assessment information, VoI a,w Indicates the intrinsic attribute evaluation result, VoE a,w Indicates the value assessment result.

[0029] As a possible implementation manner, determining the transmission order of the power load data of each load resource object according to the data value of the power load data of each load resource object includes:

[0030] Determining the priority of the power load data of each of the load resource objects according to the data value of the power load data of each of the load resource objects;

[0031] The transmission order of the power load data of each load resource object is determined according to the priority of the power load data of each load resource object.

[0032] As a possible implementation manner, the method further includes:

[0033] Acquire power load data of a target load resource object in a plurality of auxiliary service scenarios, and determine a data deviation value of the power load data in each of the auxiliary service scenarios, wherein the target load resource object is any one of the plurality of load resource objects;

[0034] Determine the data value assessment information of the power load data of the target load resource object in each of the auxiliary service scenarios according to the data deviation value and value-related data of the power load data in each of the auxiliary service scenarios, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model;

[0035] According to the data value evaluation information of the power load data of the target load resource object in each of the auxiliary service scenarios, value evaluation processing is performed on the power load data in each of the auxiliary service scenarios to obtain the data value of the power load data in each of the auxiliary service scenarios;

[0036] According to the data value of the power load data in each of the auxiliary service scenarios, the transmission order of the power load data in each of the auxiliary service scenarios is determined, and the power load data in each of the auxiliary service scenarios is transmitted sequentially according to the transmission order of the power load data in each of the auxiliary service scenarios.

[0037] In a second aspect, an embodiment of the present application provides a power load data processing device, the device comprising:

[0038] An acquisition module is used to acquire power load data of multiple load resource objects in the same auxiliary service scenario, and determine a data deviation value of the power load data of each of the load resource objects, wherein the data deviation value is a deviation value between initial power load data generated by the load resource object and target power load data obtained by collecting the initial power load data;

[0039] A determination module, configured to determine data value assessment information of each load resource object in the auxiliary service scenario according to data deviation values ​​and value-related data of the power load data of each load resource object, a data quality factor assessment model, a timeliness factor assessment model, an intrinsic attribute assessment model, a value assessment model, and a comprehensive assessment model, wherein the value-related data includes: transaction parameters, a scheduling cycle, and a collection interval within the scheduling cycle;

[0040] A value evaluation module, configured to perform value evaluation processing on the power load data of each load resource object according to the data value evaluation information of each load resource object in the auxiliary service scenario, so as to obtain the data value of the power load data of each load resource object;

[0041] The transmission module is used to determine the transmission order of the power load data of each load resource object according to the data value of the power load data of each load resource object, and transmit the power load data of each load resource object in sequence according to the transmission order of the power load data of each load resource object.

[0042] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the power load data processing method as described in any one of the first aspects above.

[0043] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the power load data processing method as described in any one of the first aspects above are executed.

[0044] According to the power load data processing method and electronic device of the embodiment of the present application, the power load data of multiple load resource objects in the same auxiliary service scenario are obtained, and the data deviation value between the initial power load data of each load resource object and the target power load data obtained by the collection is determined. According to the data deviation value, value-related data, data quality factor evaluation model, timeliness factor evaluation model, intrinsic attribute evaluation model, value evaluation model and comprehensive evaluation model of each load resource object, the data value evaluation information of each load resource object in the auxiliary service scenario is evaluated, and then the power load data of each load resource object is value evaluated according to the data value evaluation information, and the data value of the power load data of each load resource object is obtained. The transmission order is determined according to the data value of the power load data of each load resource object, so as to transmit the power load data of each load resource object in sequence according to the transmission order, so as to ensure that high-value data is transmitted and utilized first. According to the embodiment of the present application, by performing value evaluation on the power load data and determining the data transmission order according to the value evaluation result, it is ensured that the key data is transmitted first and the transmission delay of the key data is reduced. And the priority of network transmission is determined according to the value of the data, and the communication resources are reasonably allocated to avoid the network congestion caused by all the power load data competing for bandwidth at the same time. Therefore, the present application can effectively alleviate the transmission pressure caused by a large number of concurrent data communication demands in the communication network and prevent the occurrence of communication congestion, thereby improving the transmission efficiency and utilization value of power load data in auxiliary service scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A schematic diagram of a flow chart of a method for processing power load data provided in an embodiment of the present application is shown;

[0047] Figure 2 A schematic diagram of a process for determining data value assessment information provided by an embodiment of the present application is shown;

[0048] Figure 3A data value distribution diagram of different load resource objects in the same auxiliary service scenario provided by an embodiment of the present application is shown;

[0049] Figure 4 A schematic diagram showing a flow chart of another method for processing power load data provided in an embodiment of the present application is shown;

[0050] Figure 5 A data value distribution diagram of the same load resource object in different auxiliary service scenarios provided by an embodiment of the present application is shown;

[0051] Figure 6 A schematic diagram of the structure of a power load data processing device provided in an embodiment of the present application is shown;

[0052] Figure 7 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0053] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0054] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0055] In order to enable those skilled in the art to use the contents of this application, the following implementation method is given in combination with the specific application scenario "Data value assessment method for flexible resource regulation on the demand side of the power grid in ancillary service scenarios". For those skilled in the art, the general principles defined here can be applied to other embodiments and application scenarios without departing from the spirit and scope of this application. Although this application is mainly described around the power load data processing method, it should be understood that this is only an exemplary embodiment.

[0056] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0057] Figure 1 A schematic diagram of a process flow of a power load data processing method provided by an embodiment of the present application is shown. Figure 1 As shown, the method specifically comprises the following steps:

[0058] S101. Obtain power load data of multiple load resource objects in the same auxiliary service scenario, and determine a data deviation value of the power load data of each load resource object.

[0059] Optionally, multiple load resource objects can be used as different data sources, and the load resource objects can be power sales companies, power purchasing departments of a factory, electric car owners, etc. Ancillary service scenarios include but are not limited to: frequency regulation scenarios, primary backup scenarios, and secondary backup scenarios.

[0060] Optionally, the data deviation value is the deviation value between the initial power load data generated by the load resource object and the target power load data obtained by collecting the initial power load data. The deviation value reflects the accuracy of the power load data collection process, and the smaller the deviation value, the more reliable the data. The whole process from the generation to the application of power load data involves multiple links, including but not limited to: the load resource object generates power load data, the measurement equipment collects power load data, and the communication network transmits power load data. In this process, it is inevitable to generate data consistency deviation between the initial real data and the final collected data. Therefore, the process of obtaining power load data of multiple load resource objects in the same auxiliary service scenario in the present application includes obtaining the initial power load data generated by each load resource object and the target power load data obtained by the measurement equipment collecting the initial power load data generated by each load resource object, and determining the data deviation value based on the initial power load data and the target power load data.

[0061] Optionally, data deviation values ​​of multiple load resource objects are shown in Table 1 below:

[0062] Table 1 Data deviation values

[0063]

[0064]

[0065] S102. Determine the data value assessment information of each load resource object in the auxiliary service scenario based on the data deviation value and value-related data of the power load data of each load resource object, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model.

[0066] Optionally, the value-related data includes: transaction parameters, scheduling cycle, and collection interval within the scheduling cycle. Data value assessment information mainly includes assessment information on the intrinsic attributes and value of the data. The data value of different load resource objects is determined by comprehensively considering multiple factors, thereby providing a basis for data priority sorting and transmission.

[0067] Optionally, the present application provides various models for evaluating data value, including a data quality factor evaluation model, a timeliness factor evaluation model, an intrinsic attribute evaluation model, a value evaluation model, and a comprehensive evaluation model. Among them, the data quality factor evaluation model is used to evaluate the quality of the data, the timeliness factor evaluation model is used to evaluate the timeliness of the data, the intrinsic attribute evaluation model is used to evaluate the characteristics of the data itself, the value evaluation model is used to evaluate the value of the data, and the comprehensive evaluation model is used to comprehensively evaluate the value of the data based on multiple factors. The data value evaluation information of each load resource object in the auxiliary service scenario is determined by the above-mentioned multiple evaluation models, so as to use the data value evaluation information to guide the priority sorting of power load data, thereby optimizing data transmission, avoiding congestion of the communication network, and improving data utilization efficiency.

[0068] S103. Perform value evaluation on the power load data of each load resource object according to the data value evaluation information of each load resource object in the auxiliary service scenario to obtain the data value of the power load data of each load resource object.

[0069] Optionally, the power load data of each load resource object is comprehensively evaluated through multiple evaluation models to obtain preliminary data value evaluation information. On this basis, the power load data of each load resource object is further value evaluated, and the specific data value of the power load data of each load resource object is obtained by using various indicators in the data value evaluation information. The specific data value can reflect the data value of the power load data, and can also further reflect the importance and priority of each load resource object in a specific auxiliary service scenario.

[0070] S104. Determine the transmission order of the power load data of each load resource object according to the data value of the power load data of each load resource object, and transmit the power load data of each load resource object in sequence according to the transmission order of the power load data of each load resource object.

[0071] Optionally, the value of the power load data affects the transmission order of the power load data. Specifically, the power load data with higher data value will be transmitted first, while the power load data with lower data value will be transmitted with a delay, so as to ensure that important data can be transmitted first when facing a large number of concurrent data transmission requirements, thereby improving the efficiency of data utilization. In addition, once the transmission order is determined, the power load data of each load resource object is transmitted in sequence according to the transmission order, that is, starting from the data with the highest value to the data with the lowest value, so as to ensure that the high-value data will not be delayed in transmission due to network congestion and other reasons, and at the same time, it can also reasonably utilize network resources and avoid unnecessary data congestion.

[0072] Based on this, according to the power load data processing method provided in the embodiment of the present application, by conducting a value assessment on the power load data and determining the data transmission order based on the value assessment results, it is ensured that critical data is transmitted first and the transmission delay of critical data is reduced. In addition, the priority of network transmission is determined according to the value of the data, and communication resources are reasonably allocated to avoid network congestion caused by all power load data competing for bandwidth at the same time. Therefore, the present application can effectively alleviate the transmission pressure caused by a large number of concurrent data communication demands in the communication network, and prevent the occurrence of communication congestion, thereby improving the transmission efficiency and utilization value of power load data in auxiliary service scenarios.

[0073] Figure 2 A flow chart of a method for determining data value assessment information provided by an embodiment of the present application is shown. Figure 2 As shown, the method specifically comprises the following steps:

[0074] S201. Determine a quality factor evaluation result of each load resource object in an auxiliary service scenario according to a data deviation value and a data quality factor evaluation model.

[0075] Optionally, the data quality factor evaluation model is represented by a first formula, a second formula and a third formula, wherein the first formula is shown in the following formula (1), the second formula is shown in the following formula (2), and the third formula is shown in the following formula (3):

[0076]

[0077] Among them, q a,w Indicates the data deviation value, Represents the initial power load data generated by the load resource object. It represents the target power load data obtained by collecting the initial power load data.

[0078]

[0079] in, represents the quality factor evaluation result, Indicates the maximum allowable deviation of the load resource object.

[0080] For example, the quality factor evaluation result shown in the above formula (2) is The calculation of can be equivalent to the following formula (3):

[0081]

[0082] in, Indicates the maximum allowable deviation of the load resource object, q a,w Represents the data deviation value, σ a Represents the variance of the set of data deviation values, μ a The mean of the set of deviation values ​​representing the data.

[0083] For example, the data deviation value q a,w a represents the load resource object, w represents the auxiliary service scenario, and any data deviation value q a,w All belong to the data in the data deviation value set, that is, Q a,w In addition, the initial power load data generated by multiple load resource objects also belong to the data in the initial data set, that is, represents the initial data set, and the target power load data also belongs to the data collected by the measuring equipment in the final data set, that is, Represents the final collection data set.

[0084] Exemplarily, in combination with the data deviation values ​​shown in Table 1 above, for load resource object 1, the set of data deviation values ​​based on multiple data deviation values ​​is {-0.2169, -0.0570, -0.0723, -0.0848, -0.1379, -0.0604, -0.0543, -0.0472, -0.0316, -0.0090, -0.0118, 0.0243, 0.0390, -0.0183, -0.0335, 0.0118, -0.0042, -0.0048, -0.0143, -0.0080, 0.0145, 0.0078, -0.0166, -0.0435}, and the variance σ of the set of data deviation values ​​is a is 0.55, and the mean of the set of data deviation values ​​is -0.0345. For load resource object 2, the set of data deviation values ​​based on multiple data deviation values ​​is {-0.1548, -0.0441, -0.0530, -0.0445, -0.0284, -0.0256, -0.0056, -0.0032, -0.0170, 0.0148, 0.0252, 0.0362, -0.0052, 0.0101, 0.0206, 0.0129, 0.0078, 0.0185, 0.0172, 0.0158, 0.0029, -0.0008, -0.0003, -0.0217}, and the variance of the set of data deviation values ​​is σ a is 0.0389, and the mean of the set of data deviation values ​​is -0.0093. For load resource object 3, the set of data deviation values ​​based on multiple data deviation values ​​is {-0.1863, -0.0145, -0.0375, -0.0360, -0.0318, -0.0181, -0.0149, 0.0017, 0.0157, 0.0291, 0.0523, 0.0543, 0.0238, 0.0159, 0.0107, 0.0276, 0.0375, 0.0202, 0.0179, 0.0182, 0.0200, 0.0069, -0.0078, -0.0220}, and the variance of the set of data deviation values ​​is σ a is 0.471, and the mean of the set of data deviation values ​​is 0.

[0085] For example, the variance σ of the set of data deviation values ​​of the load resource object 1 is A is 0.55, the mean of the set of data deviation values ​​is -0.0345, and the variance σ of the set of data deviation values ​​of load resource object 2 is a is 0.0389, the mean of the set of data deviation values ​​is -0.0093, and the variance of the set of data deviation values ​​of load resource object 3 is σ aTaking the case where the mean of the set of data deviation values ​​is 0 as an example, the quality factor evaluation results of each load resource object in the auxiliary service scenario can be obtained based on the above formulas (2) and (3).

[0086] S202. Determine the timeliness evaluation result of each load resource object in the auxiliary service scenario according to the data deviation value and the timeliness factor evaluation model.

[0087] Optionally, the timeliness factor evaluation model is represented by a fourth formula, which is shown in the following formula (4):

[0088]

[0089] in, represents the timeliness assessment result, t rec Indicates the receiving time. represents the scene correlation coefficient, Indicates the maximum allowable deviation of the load resource object.

[0090] For example, for different auxiliary service scenarios, the scenario correlation coefficient For example, when the auxiliary service scenario is a frequency modulation scenario, the scenario correlation coefficient It can be set to 0.9. When the auxiliary service scenario is a primary backup scenario, the scenario correlation coefficient It can be set to 0.7. When the auxiliary service scenario is a secondary backup scenario, the scenario correlation coefficient Can be set to 0.8.

[0091] For example, Indicates the timeliness evaluation result, reflecting the time after a certain reception time t rec The resulting data quality degradation, and in different auxiliary service scenarios, the same amount of data quality degradation has different effects on the intrinsic properties of the data. On this basis, once the maximum allowable deviation of the load resource object is determined Combined with the scene correlation coefficient under the corresponding auxiliary service scene and receiving time t rec , the above formula (4) can be used to determine the timeliness evaluation result of each load resource object in the auxiliary service scenario.

[0092] S203. Determine the intrinsic attribute evaluation result of each load resource object in the auxiliary service scenario according to the quality factor evaluation result, the timeliness evaluation result and the intrinsic attribute evaluation model.

[0093] Optionally, the intrinsic attribute evaluation model is represented by a fifth formula, which is shown in the following formula (5):

[0094]

[0095] Among them, VoI a,w represents the intrinsic attribute evaluation result, represents the quality factor evaluation result, Indicates the timeliness assessment results, represents the coefficient corresponding to the quality factor evaluation result, Represents the coefficient corresponding to the timeliness assessment result.

[0096] For example, the coefficient corresponding to the quality factor evaluation result is Coefficients corresponding to timeliness assessment results The specific value setting of can be determined according to the importance of the quality factor evaluation results and the timeliness evaluation results on the intrinsic attributes of the data. For example, the coefficient corresponding to the quality factor evaluation result Can be set to 0.8, the coefficient corresponding to the timeliness evaluation result It can be set to 0.2. On this basis, once the quality factor evaluation results and timeliness evaluation results are determined, the above formula (5) can be used to determine the intrinsic attribute evaluation results of each load resource object in the auxiliary service scenario.

[0097] S204. Determine the value assessment result of each load resource object in the auxiliary service scenario based on the value-related data and the value assessment model.

[0098] Optionally, value-related data include: transaction parameters, scheduling cycle, and collection interval within the scheduling cycle. Among them, the transaction parameters are, for example, the unit electricity transaction price of the load resource object participating in the auxiliary service scenario, and the scheduling cycle is the scheduling cycle of the auxiliary service scenario, such as the time period of power system scheduling, which can be the peak period or valley period of the day. Since the fluctuation of power demand in different time periods will affect the timeliness and importance of the data, different scheduling cycles will also affect the value of the data. The collection interval within the scheduling cycle is the time interval for data collection within a given scheduling cycle. The shorter the collection interval, the higher the freshness of the data. In addition, the frequency of data collection can also be determined by the scheduling cycle and the collection interval within the scheduling cycle.

[0099] Optionally, the value assessment model is represented by a sixth formula, which is as described in the following formula (6):

[0100]

[0101] Among them, VoE a,w Indicates the value assessment result, p a,w represents the transaction parameters, τ w represents the scheduling period, f wrepresents the collection interval within the scheduling period, and χ represents the unit conversion factor.

[0102] For example, the value evaluation result VoE a,w For example, it can be the economic value assessment result of the power load data of the load resource object, the transaction parameter p a,w The unit power transaction price of the load resource object participating in the auxiliary service scenario can be used, and the unit conversion factor χ is used to unify the unit of the power transaction price, for example, converting the price unit from $ / MW (US dollar per megawatt) to $ / GB (US dollar per gigabyte). The scheduling period τ w It can be 5 minutes, and the collection interval within the scheduling period is f w It can be 1min, and accordingly, the data collection frequency τ w / f w That is 5. On this basis, the value assessment result of each load resource object in the auxiliary service scenario can be determined based on the above formula (6).

[0103] S205. Determine data value assessment information based on intrinsic attribute assessment results, value assessment results and comprehensive assessment model.

[0104] Optionally, the comprehensive evaluation model is represented by a seventh formula, which is shown in the following formula (7):

[0105] VOD a,w =VoI a,w V0E a,w (7)

[0106] Among them, VoD a,w Indicates data value assessment information, VoI a,w Indicates the intrinsic attribute evaluation result, VoE a,w Indicates the value assessment result.

[0107] For example, the intrinsic attribute evaluation result VoI a,w and value evaluation results VoE a,w The expression form is a specific value. Based on the above formula (7), once the intrinsic attribute evaluation result VoI is obtained, a,w and value evaluation results VoE a,w , multiplying the two together can obtain the data value assessment information, which is also expressed as a specific numerical value, and the size of the numerical value can reflect the data value of the power load data of the corresponding load resource object.

[0108] For example, in the auxiliary service scenario of frequency modulation, based on the above formula (7), the data value of the power load data of load resource object 1 is 0.8, the data value of the power load data of load resource object 2 is 0.7, and the data value of the power load data of load resource object 3 is 0.6. Then, the data value of the power load data of each load resource object is determined from high to low as follows: load resource object 1, load resource object 2, load resource object 3.

[0109] Optionally, Figure 3 The data value distribution diagram of different load resource objects in the same auxiliary service scenario provided by the embodiment of the present application is shown. Figure 3 As shown in the figure, in the process of demand-side load resource regulation, considering the different data generation-collection-application processes, different load resource objects have differentiated intrinsic properties, which are manifested in different data quality and data timeliness. In addition, due to the participation in the same ancillary service, the power transaction prices of different load resources are unified, so different load resource objects have the same data value.

[0110] Based on this, by determining the data value distribution of different load resource objects in the same ancillary service scenario, not only the efficiency of data management and system operation is improved, but also the power system can be ensured to operate more intelligently and efficiently.

[0111] As a possible implementation, the above step S104 determines the transmission order of the power load data of each load resource object according to the data value of the power load data of each load resource object, including:

[0112] According to the data value of the power load data of each load resource object, the priority of the power load data of each load resource object is determined; according to the priority of the power load data of each load resource object, the transmission order of the power load data of each load resource object is determined.

[0113] Exemplarily, taking the data value of the power load data of the above-mentioned load resource object 1 as 0.8, the data value of the power load data of the load resource object 2 as 0.7, and the data value of the power load data of the load resource object 3 as 0.6, since the data values ​​of the power load data of each load resource object are from high to low: load resource object 1, load resource object 2, load resource object 3, based on the principle that the higher the data value, the priority of the data is transmitted, the priority of the power load data of each load resource object is determined as: load resource object 1>load resource object 2>load resource object 3, accordingly, the power load data of load resource object 1 is given priority during network transmission.

[0114] Based on this, the transmission priority and order are determined by evaluating the data value of the power load data of each load resource object, which not only optimizes the data transmission process and improves data utilization efficiency, but also ensures the timely delivery of key data, thereby improving the overall performance and service quality of the power system.

[0115] Figure 4 FIG. 2 is a flow chart of another method for processing power load data provided by an embodiment of the present application. Figure 4 As shown, the method specifically comprises the following steps:

[0116] S401. Obtain power load data of a target load resource object in multiple auxiliary service scenarios, and determine a data deviation value of the power load data in each auxiliary service scenario. The target load resource object is any one of the multiple load resource objects.

[0117] Optionally, the auxiliary service scenarios include but are not limited to: frequency modulation scenarios, primary backup scenarios, and secondary backup scenarios. The target load resource object may be any one of the load resource objects 1, 2, and 3. Taking the target load resource object as load resource object 1 as an example, the power load data of load resource object 1 in the frequency modulation scenario, the primary backup scenario, and the secondary backup scenario are obtained respectively, and the data deviation values ​​of the power load data of load resource object 1 in the frequency modulation scenario, the primary backup scenario, and the secondary backup scenario are determined respectively.

[0118] S402. Determine the data value assessment information of the power load data of the target load resource object in each auxiliary service scenario based on the data deviation value and value-related data of the power load data in each auxiliary service scenario, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model.

[0119] Optionally, value-related data include: transaction parameters, scheduling cycle, and collection interval within the scheduling cycle. Data value assessment information mainly includes assessment information on the intrinsic attributes and value of the data. The data value of different load resource objects is determined by comprehensively considering multiple factors, thereby providing a basis for data priority sorting and transmission. The process of determining the data value assessment information of the power load data of the target load resource object in each auxiliary service scenario according to the above-mentioned multiple assessment models is similar to the above-mentioned process of determining the data value assessment information of each load resource object in the auxiliary service scenario, which will not be repeated here.

[0120] S403. Perform value evaluation on the power load data in each auxiliary service scenario according to the data value evaluation information of the power load data of the target load resource object in each auxiliary service scenario to obtain the data value of the power load data in each auxiliary service scenario.

[0121] Optionally, a comprehensive evaluation is performed on the power load data of the target load resource object in each auxiliary service scenario through multiple evaluation models to obtain preliminary data value evaluation information. On this basis, the power load data of the target load resource object in each auxiliary service scenario is further value-evaluated and processed, and the various indicators in the data value evaluation information are used to obtain the specific data value of the power load data of the target load resource object in each auxiliary service scenario. The specific data value can reflect the data value of the power load data, and can also further reflect the importance and priority of the target load resource object in multiple auxiliary service scenarios.

[0122] S404. Determine the transmission order of the power load data in each auxiliary service scenario according to the data value of the power load data in each auxiliary service scenario, and transmit the power load data in each auxiliary service scenario in sequence according to the transmission order of the power load data in each auxiliary service scenario.

[0123] Optionally, in order to optimize data transmission and ensure that key data can be delivered first when facing a large number of concurrent data transmission requirements, the embodiment of the present application adopts a transmission strategy based on data value. Specifically, power load data with higher data value will be transmitted first, while power load data with lower value will be transmitted later, thus ensuring that important data can be processed as soon as possible, thereby improving data utilization efficiency.

[0124] Optionally, the transmission order of the power load data is determined according to the data value of the power load data of the target load resource object in each auxiliary service scenario. In this process, the data value is evaluated based on data quality, timeliness and other value-related indicator parameters, so that the data value is obtained through comprehensive evaluation, and a priority is assigned to the power load data according to the data value. Data with high priority will be arranged for transmission first, while data with lower priority will be arranged at the back.

[0125] Optionally, Figure 5 The data value distribution diagram of the same load resource object in different auxiliary service scenarios provided by the embodiment of the present application is shown. Figure 5As shown in the figure, the data quality of the same load resource object remains unchanged in different auxiliary service scenarios, but the data quality attenuation coefficients are different in different auxiliary service scenarios. Therefore, the data timeliness factors of the same load resource object in the three auxiliary scenarios of frequency regulation, primary backup and secondary backup are different. In addition, due to the differences in the transaction prices of power resources for frequency regulation, primary backup and secondary backup, the same load resource object has different data values ​​in different auxiliary service scenarios.

[0126] Based on this, the embodiment of the present application provides a method for evaluating the value of load resource regulation data on the demand side of a power grid taking into account multiple auxiliary service scenarios. The method aims to conduct a comprehensive evaluation from two aspects: the intrinsic attributes of the data and the value of the data. In terms of the intrinsic attributes of the data, the present application considers the consistency and time decay characteristics of the data in the entire process from data generation to application, and constructs a data quality factor evaluation model, a timeliness factor evaluation model, and an intrinsic attribute evaluation model. In terms of data value, the value of the power resources of the load resource objects participating in multiple auxiliary services is considered, and a value evaluation model considering the data application scenario is constructed. The present application innovatively proposes a method for evaluating the value of load resource regulation data on the demand side, which provides an innovative solution to the communication congestion problem caused by the massive data transmission generated by the load resources on the power demand side. By orderly transmitting data of different values, the efficiency of the joint regulation of load resources and communication resources on the power demand side is improved. It has broad application potential and will make a positive contribution to the green and low-carbon operation of the power system.

[0127] Based on the same inventive concept, an embodiment of the present application also provides an electric power load data processing device corresponding to the electric power load data processing method. Since the principle of solving the problem by the electric power load data processing device in the embodiment of the present application is similar to the above-mentioned electric power load data processing method in the embodiment of the present application, the implementation of the electric power load data processing device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0128] Reference Figure 6 FIG. 6 is a schematic diagram of the structure of a power load data processing device provided in an embodiment of the present application. The power load data processing device 600 includes: an acquisition module 601, a determination module 602, a value assessment module 603 and a transmission module 604, wherein:

[0129] An acquisition module 601 is used to acquire power load data of multiple load resource objects in the same auxiliary service scenario, and determine a data deviation value of the power load data of each load resource object, where the data deviation value is a deviation value between initial power load data generated by the load resource object and target power load data obtained by collecting the initial power load data;

[0130] The determination module 602 is used to determine the data value evaluation information of each load resource object in the auxiliary service scenario according to the data deviation value and value-related data of the power load data of each load resource object, the data quality factor evaluation model, the timeliness factor evaluation model, the intrinsic attribute evaluation model, the value evaluation model and the comprehensive evaluation model, wherein the value-related data includes: transaction parameters, the scheduling cycle and the collection interval within the scheduling cycle;

[0131] The value evaluation module 603 is used to perform value evaluation processing on the power load data of each load resource object according to the data value evaluation information of each load resource object in the auxiliary service scenario, so as to obtain the data value of the power load data of each load resource object;

[0132] The transmission module 604 is used to determine the transmission order of the power load data of each load resource object according to the data value of the power load data of each load resource object, and transmit the power load data of each load resource object in sequence according to the transmission order of the power load data of each load resource object.

[0133] Based on this, according to the power load data processing device of the embodiment of the present application, by conducting a value assessment on the power load data and determining the data transmission order according to the value assessment result, it is ensured that the critical data is transmitted first and the transmission delay of the critical data is reduced. And the priority of network transmission is determined according to the value of the data, and communication resources are reasonably allocated to avoid network congestion caused by all power load data competing for bandwidth at the same time. Therefore, the present application can effectively alleviate the transmission pressure caused by a large number of concurrent data communication demands in the communication network, and prevent the occurrence of communication congestion, thereby improving the transmission efficiency and utilization value of power load data in auxiliary service scenarios.

[0134] In a possible implementation manner, the determination module 602 is specifically configured to:

[0135] Determine the quality factor evaluation result of each load resource object in the auxiliary service scenario according to the data deviation value and the data quality factor evaluation model;

[0136] Determine the timeliness evaluation results of each load resource object in the auxiliary service scenario based on the data deviation value and the timeliness factor evaluation model;

[0137] Determine the intrinsic attribute evaluation results of each load resource object in the auxiliary service scenario based on the quality factor evaluation results, timeliness evaluation results and intrinsic attribute evaluation model;

[0138] Determine the value assessment results of each load resource object in the auxiliary service scenario based on value-related data and value assessment models;

[0139] Determine data value assessment information based on intrinsic attribute assessment results, value assessment results and comprehensive assessment model.

[0140] In a possible implementation, the data quality factor evaluation model is represented by a first formula, a second formula, and a third formula;

[0141] The first formula is: Among them, q a,w Indicates the data deviation value, Represents the initial power load data generated by the load resource object. represents the target power load data obtained by collecting the initial power load data;

[0142] The second formula is: in, represents the quality factor evaluation result, Indicates the maximum allowable deviation of the load resource object;

[0143] The third formula is: in, Indicates the maximum allowable deviation of the load resource object, q a,w Represents the data deviation value, σ a Represents the variance of the set of data deviation values, μ a The mean of the set of deviation values ​​representing the data.

[0144] In a possible implementation, the timeliness factor evaluation model is represented by the fourth formula;

[0145] The fourth formula is: in, represents the timeliness assessment result, t rec Indicates the receiving time. represents the scene correlation coefficient, Indicates the maximum allowable deviation of the load resource object.

[0146] In one possible implementation, the intrinsic attribute evaluation model is represented by the fifth formula;

[0147] The fifth formula is: Among them, VoI a,w represents the intrinsic attribute evaluation result, represents the quality factor evaluation result, Indicates the timeliness assessment results, represents the coefficient corresponding to the quality factor evaluation result, Represents the coefficient corresponding to the timeliness assessment result.

[0148] In a possible implementation, the value assessment model is represented by the sixth formula;

[0149] The sixth formula is: Among them, VoE a,w Indicates the value assessment result, p a,w represents the transaction parameters, τ w represents the scheduling period, f w represents the collection interval within the scheduling period, and χ represents the unit conversion factor.

[0150] In a possible implementation, the comprehensive evaluation model is represented by the seventh formula;

[0151] The seventh formula is: VoD a,w =VoI a,w V0E a,w , where VoD a,w Indicates data value assessment information, VoI a,w Indicates the intrinsic attribute evaluation result, VoE a,w Indicates the value assessment result.

[0152] In a possible implementation manner, the transmission module 604 is specifically configured to:

[0153] Determine the priority of the power load data of each load resource object according to the data value of the power load data of each load resource object;

[0154] The transmission order of the power load data of each load resource object is determined according to the priority of the power load data of each load resource object.

[0155] In a possible implementation manner, the power load data processing device 600 is further used for:

[0156] Acquire power load data of a target load resource object in multiple auxiliary service scenarios, and determine a data deviation value of the power load data in each auxiliary service scenario, wherein the target load resource object is any one of the multiple load resource objects;

[0157] Determine the data value assessment information of the power load data of the target load resource object in each auxiliary service scenario based on the data deviation value and value-related data of the power load data in each auxiliary service scenario, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model;

[0158] According to the data value evaluation information of the power load data of the target load resource object in each auxiliary service scenario, the power load data in each auxiliary service scenario is value evaluated to obtain the data value of the power load data in each auxiliary service scenario;

[0159] According to the data value of the power load data in each auxiliary service scenario, the transmission order of the power load data in each auxiliary service scenario is determined, and the power load data in each auxiliary service scenario is transmitted sequentially according to the transmission order of the power load data in each auxiliary service scenario.

[0160] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference may be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0161] The present application embodiment also provides an electronic device 700, such as Figure 7 As shown, it is a schematic diagram of the structure of an electronic device 700 provided in an embodiment of the present application, including: a processor 701, a memory 702, and optionally, a bus 703. The memory 702 stores machine-readable instructions executable by the processor 701. When the electronic device 700 is running, the processor 701 communicates with the memory 702 through the bus 703. When the machine-readable instructions are executed by the processor 701, the steps in the power load data processing method described in any one of the above items are executed.

[0162] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the power load data processing method as described in any one of the above items are executed.

[0163] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the method embodiment, and will not be repeated in this application. In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0164] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or part of the technical solution that contributes to the prior art or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Mem ory), disk or optical disk and other media that can store program code.

[0165] The above are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A method for processing power load data, characterized in that: include: Obtaining power load data of multiple load resource objects in the same auxiliary service scenario, and determining a data deviation value of the power load data of each of the load resource objects, wherein the data deviation value is a deviation value between initial power load data generated by the load resource object and target power load data obtained by collecting the initial power load data; Determine the data value assessment information of each load resource object in the auxiliary service scenario according to the data deviation value and value-related data of the power load data of each load resource object, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model, wherein the value-related data includes: transaction parameters, the scheduling cycle and the collection interval within the scheduling cycle; According to the data value evaluation information of each load resource object in the auxiliary service scenario, the power load data of each load resource object is value evaluated to obtain the data value of the power load data of each load resource object; According to the data value of the power load data of each load resource object, the transmission order of the power load data of each load resource object is determined, and the power load data of each load resource object is transmitted in sequence according to the transmission order of the power load data of each load resource object.

2. The method according to claim 1, characterized in that Determining the data value assessment information of each load resource object in the auxiliary service scenario according to the data deviation value of the power load data of each load resource object, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model includes: Determining a quality factor evaluation result of each of the load resource objects in the auxiliary service scenario according to the data deviation value and the data quality factor evaluation model; Determine a timeliness evaluation result of each of the load resource objects in the auxiliary service scenario according to the data deviation value and the timeliness factor evaluation model; Determine an intrinsic attribute evaluation result of each of the load resource objects in the auxiliary service scenario according to the quality factor evaluation result, the timeliness evaluation result and the intrinsic attribute evaluation model; Determine, according to the value-related data and the value assessment model, a value assessment result of each of the load resource objects in the auxiliary service scenario; The data value assessment information is determined based on the intrinsic attribute assessment result, the value assessment result and the comprehensive assessment model.

3. The method according to claim 2, characterized in that The data quality factor evaluation model is represented by a first formula, a second formula and a third formula; The first formula is: Among them, q a,w represents the data deviation value, represents the initial power load data generated by the load resource object, represents the target power load data obtained by collecting the initial power load data; The second formula is: in, represents the quality factor evaluation result, represents the maximum allowable deviation of the load resource object; The third formula is: in, represents the maximum allowable deviation of the load resource object, q a,w represents the data deviation value, σ a represents the variance of the set of data deviation values, μ a Represents the mean of the set of data deviation values.

4. The method according to claim 2, characterized in that: The timeliness factor evaluation model is represented by the fourth formula; The fourth formula is: in, represents the timeliness assessment result, t rec Indicates the receiving time. represents the scene correlation coefficient, Indicates the maximum allowable deviation of the load resource object.

5. The method according to claim 2, characterized in that: The intrinsic attribute evaluation model is represented by the fifth formula; The fifth formula is: Among them, VoI a,w represents the intrinsic property evaluation result, represents the quality factor evaluation result, represents the timeliness assessment result, represents the coefficient corresponding to the quality factor evaluation result, Represents the coefficient corresponding to the timeliness evaluation result.

6. The method according to claim 2, characterized in that The value assessment model is represented by the sixth formula; The sixth formula is: Among them, VoE a,w Represents the value assessment result, p a,w represents the transaction parameters, τ w represents the scheduling period, f w It represents the collection interval within the scheduling period, and X represents the unit conversion factor.

7. The method according to claim 2, characterized in that The comprehensive evaluation model is represented by the seventh formula; The seventh formula is: VoD a,w =VoI a,w V0E a,w , where VoD a,w Indicates the data value assessment information, VoI a,w Indicates the intrinsic attribute evaluation result, VoE a,w Indicates the value assessment result.

8. The method according to claim 1, characterized in that The step of determining the transmission order of the power load data of each load resource object according to the data value of the power load data of each load resource object comprises: Determining the priority of the power load data of each of the load resource objects according to the data value of the power load data of each of the load resource objects; The transmission order of the power load data of each load resource object is determined according to the priority of the power load data of each load resource object.

9. The method according to claim 1, characterized in that: Also includes: Acquire power load data of a target load resource object in a plurality of auxiliary service scenarios, and determine a data deviation value of the power load data in each of the auxiliary service scenarios, wherein the target load resource object is any one of the plurality of load resource objects; Determine the data value assessment information of the power load data of the target load resource object in each of the auxiliary service scenarios according to the data deviation value and value-related data of the power load data in each of the auxiliary service scenarios, the data quality factor assessment model, the timeliness factor assessment model, the intrinsic attribute assessment model, the value assessment model and the comprehensive assessment model; According to the data value evaluation information of the power load data of the target load resource object in each of the auxiliary service scenarios, value evaluation processing is performed on the power load data in each of the auxiliary service scenarios to obtain the data value of the power load data in each of the auxiliary service scenarios; According to the data value of the power load data in each of the auxiliary service scenarios, the transmission order of the power load data in each of the auxiliary service scenarios is determined, and the power load data in each of the auxiliary service scenarios is transmitted sequentially according to the transmission order of the power load data in each of the auxiliary service scenarios.

10. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor executes the machine-readable instructions to perform the steps of the power load data processing method as described in any one of claims 1 to 9.

Images