Power grid control optimization method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a power grid control optimization method and device, computer equipment, a computer readable storage medium and a computer program product, and is applied to the technical field of big data, and the method comprises the steps: obtaining charging and discharging data and power grid operation data of a to-be-optimized power grid; according to the charging and discharging data and the power grid operation data, the carbon emission condition of the to-be-optimized power grid is evaluated to obtain carbon emission information, and the carbon emission information comprises carbon emission and a carbon emission object; and optimizing a power grid charging and discharging strategy of the to-be-optimized power grid according to the carbon emission, and optimizing power grid electric quantity control of the to-be-optimized power grid according to the carbon emission and the carbon emission object. By adopting the method, the environmental protection property of power grid operation can be improved.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a power grid control optimization method, device, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] As the economy continues to develop, electricity demand continues to increase, and the corresponding carbon emissions will also increase. At present, power grid control usually only considers charging and discharging efficiency and power grid energy utilization efficiency. When conducting power grid control, there may be a large amount of carbon emissions, which can easily cause a greater impact on the environment and lead to lower environmental friendliness of power grid operation. Summary of the invention

[0003] Based on this, it is necessary to provide a power grid control optimization method, device, computer equipment, computer-readable storage medium and computer program product that can improve the environmental friendliness of power grid operation in response to the above technical problems.

[0004] In a first aspect, the present application provides a power grid control optimization method, comprising:

[0005] Obtain charging and discharging data and grid operation data of the grid to be optimized;

[0006] According to the charging and discharging data and the grid operation data, the carbon emission of the grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object;

[0007] According to the carbon emissions, the grid charging and discharging strategy of the grid to be optimized is optimized; and according to the carbon emissions and the carbon emission objects, the grid power control of the grid to be optimized is optimized.

[0008] In one of the embodiments, the carbon emission of the power grid to be optimized is evaluated based on the charging and discharging data and the power grid operation data to obtain carbon emission information, including: fusing the charging and discharging data with the power grid operation data to obtain fused data, wherein the fused data includes fused sub-data obtained by fusing the charging and discharging data and the power grid operation data at each time; for each of the fused sub-data, the fused sub-data is verified to obtain a verification result, and when the verification result includes a verification failure result, the fused sub-data is updated to obtain updated sub-data; based on the updated sub-data, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated to obtain the carbon emissions at the time corresponding to the updated sub-data; based on the carbon emissions at the time corresponding to all the fused sub-data, the carbon emission sources of the power grid to be optimized are evaluated to obtain carbon emission objects.

[0009] In one embodiment, the charging and discharging data includes the charging and discharging amount at each time, and the power grid operation data includes the power grid power generation data and the power grid load data at each time; the charging and discharging data and the power grid operation data are merged to obtain the merged data, including: evaluating the power grid power consumption status of the power grid to be optimized according to the power grid power generation data and the power grid load data at each time, and obtaining the power grid power consumption evaluation data at each time; evaluating the charging and discharging status of the power grid to be optimized according to the charging and discharging amount at each time, and obtaining the charging and discharging evaluation data at each time; fusing the corresponding power grid power consumption evaluation data at each time and the charging and discharging data and the power grid operation data that match the charging and discharging evaluation data to obtain fused sub-data.

[0010] In one of the embodiments, the carbon emissions of the power grid to be optimized at the time corresponding to the update sub-data are evaluated according to the update sub-data to obtain the carbon emissions at the time corresponding to the update sub-data, including: using multiple carbon emission evaluation methods, the carbon emissions of the power grid to be optimized at the time corresponding to the update sub-data are evaluated according to the update sub-data respectively to obtain multiple pre-evaluated carbon emissions at the time corresponding to the update sub-data; if the differences between the pre-evaluated carbon emissions at the time corresponding to the multiple update sub-data are all less than the preset difference threshold, then the average value between the pre-evaluated carbon emissions at the time corresponding to the multiple update sub-data is determined as the carbon emissions at the time corresponding to the update sub-data; if the differences between the pre-evaluated carbon emissions at the time corresponding to the multiple update sub-data are not all less than the preset difference threshold, then according to the evaluation information corresponding to the multiple carbon emission evaluation methods, the pre-evaluated carbon emissions at the time corresponding to the multiple update sub-data are merged to obtain the carbon emissions at the time corresponding to the update sub-data, wherein the evaluation information corresponding to the carbon emission evaluation method is used to characterize the evaluation authority of the carbon emission evaluation method.

[0011] In one of the embodiments, the pre-assessed carbon emissions at the corresponding times of the multiple updated sub-data are merged according to the assessment information corresponding to the multiple carbon emission assessment methods to obtain the carbon emissions at the corresponding time of the updated sub-data, including: selecting a target carbon emission assessment method from the multiple carbon emission assessment methods according to the assessment information corresponding to the multiple carbon emission assessment methods; and correcting the pre-assessed carbon emissions corresponding to the target carbon emission assessment method according to the pre-assessed carbon emissions corresponding to the carbon emission assessment methods other than the target carbon emission assessment method among the multiple carbon emission assessment methods to obtain the carbon emissions at the corresponding time of the updated sub-data.

[0012] In one of the embodiments, the carbon emission sources of the power grid to be optimized are evaluated based on the carbon emissions at the corresponding time of all the fused sub-data to obtain a carbon emission object, including: generating the carbon emissions of each stage in the product life cycle stage of the power grid to be optimized based on the carbon emissions at the corresponding time of all the fused sub-data; evaluating the carbon emission sources of the power grid to be optimized based on the carbon emissions of each stage in the product life cycle stage of the power grid to be optimized to obtain a carbon emission object.

[0013] In a second aspect, the present application also provides a power grid control optimization device, comprising:

[0014] An acquisition module, used to acquire charging and discharging data and grid operation data of the grid to be optimized;

[0015] An evaluation module, configured to evaluate the carbon emission of the power grid to be optimized according to the charging and discharging data and the power grid operation data, and obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object;

[0016] The optimization module is used to optimize the grid charging and discharging strategy of the grid to be optimized according to the carbon emissions, and to optimize the grid power control of the grid to be optimized according to the carbon emissions and the carbon emission objects.

[0017] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0018] Obtain charging and discharging data and grid operation data of the grid to be optimized;

[0019] According to the charging and discharging data and the grid operation data, the carbon emission of the grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object;

[0020] According to the carbon emissions, the grid charging and discharging strategy of the grid to be optimized is optimized; and according to the carbon emissions and the carbon emission objects, the grid power control of the grid to be optimized is optimized.

[0021] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0022] Obtain charging and discharging data and grid operation data of the grid to be optimized;

[0023] According to the charging and discharging data and the grid operation data, the carbon emission of the grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object;

[0024] According to the carbon emissions, the grid charging and discharging strategy of the grid to be optimized is optimized; and according to the carbon emissions and the carbon emission objects, the grid power control of the grid to be optimized is optimized.

[0025] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0026] Obtain charging and discharging data and grid operation data of the grid to be optimized;

[0027] According to the charging and discharging data and the grid operation data, the carbon emission of the grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object;

[0028] According to the carbon emissions, the grid charging and discharging strategy of the grid to be optimized is optimized; and according to the carbon emissions and the carbon emission objects, the grid power control of the grid to be optimized is optimized.

[0029] The above-mentioned power grid control optimization method, device, computer equipment, computer-readable storage medium and computer program product obtain the charging and discharging data and power grid operation data of the power grid to be optimized; evaluate the carbon emission of the power grid to be optimized based on the charging and discharging data and the power grid operation data to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object; optimize the power grid charging and discharging strategy of the power grid to be optimized based on the carbon emission amount, and optimize the power grid power control of the power grid to be optimized based on the carbon emission amount and the carbon emission object, so as to characterize the current charging and discharging strategy of the power grid to be optimized and the carbon emission information under the power grid power control, and optimize the current charging and discharging strategy and power grid power control of the power grid to be optimized, so that the optimized power grid can reduce carbon emissions to a certain extent, thereby improving the environmental protection of the power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 A diagram showing an application environment of a power grid control optimization method in an embodiment;

[0032] Figure 2 A schematic diagram of a flow chart of a power grid control optimization method in one embodiment;

[0033] Figure 3 A flowchart of the steps after the model weight information is iteratively optimized by a particle swarm algorithm according to the weight fusion information to obtain the target model weight information in an embodiment;

[0034] Figure 4 A schematic diagram of the structure of a target power risk assessment result in one embodiment;

[0035] Figure 5 A structural block diagram of a power grid control optimization device in one embodiment;

[0036] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0038] It should be noted that the information (including but not limited to charging and discharging data and power grid operation data, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data are in compliance with the relevant provisions of national laws and regulations. For content pushed to users (for example, power risk assessment results, etc.), users can refuse or conveniently refuse content push, etc. In the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0039] The power grid control optimization method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The server 104 obtains the charging and discharging data and the grid operation data of the power grid to be optimized; according to the charging and discharging data and the grid operation data, the carbon emission of the power grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission and carbon emission objects; according to the carbon emission, the grid charging and discharging strategy of the power grid to be optimized is optimized, and, according to the carbon emission and carbon emission objects, the grid power control of the power grid to be optimized is optimized. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The head mounted device may be a virtual reality (VR) device, an augmented reality (AR) device, smart glasses, etc. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0040] In an exemplary embodiment, Figure 2 As shown, a power grid control optimization method is provided, which is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps 202 to 206. Among them:

[0041] Step 202, acquiring charging and discharging data and grid operation data of the grid to be optimized.

[0042] Among them, the power grid to be optimized in step 202 is a power grid waiting for power grid control optimization. The power grid to be optimized can be set by the user on demand or in response to preset conditions, which is not limited here. The charging and discharging data include at least one of the charging time, the charging amount corresponding to the charging time period, the discharging time and the discharging amount corresponding to the discharging time period. The charging (discharging) time can be a charging (discharging) time point or a charging (discharging) time period. The power grid operation data includes at least one of the power grid load data, the power grid power generation data and the power information. The power grid load data includes at least one of the power grid load rate and the power grid load value. The power grid power generation data includes at least one of the power grid power generation and the power grid power generation type. The power information includes at least one of the loss in the power distribution process and the loss in the power transportation process.

[0043] Optionally, the preset condition may be detecting that the usage time of the power grid is greater than a preset time threshold, wherein the preset time threshold may be set by the user as needed, may be an empirical value, or may be determined according to the greening degree of the environment in which the power grid is located. Specifically, the higher the greening degree, the longer the preset time threshold. In this way, when the power grid is in use for a long time, the cumulative carbon emissions of the power grid to the environment are high, and the power grid needs to be environmentally optimized and controlled. Therefore, the power grid is determined as the power grid to be optimized.

[0044] Optionally, the preset condition may be detecting that the greening degree of the environment where the power grid is located is lower than a preset greening degree threshold, wherein the preset greening degree threshold may be set by the user as needed, or may be an empirical value. In this way, when the greening degree of the environment where the power grid is located is low, that is, when the environment where the power grid is located cannot timely mitigate the carbon dioxide emissions from the power grid, the operation of the power grid will have a greater impact on the environment, and therefore, the power grid is determined to be a power grid to be optimized.

[0045] Exemplarily, before step 202, the method further includes: selecting a power grid to be optimized from at least one power grid according to preset conditions.

[0046] As an embodiment, step 202 includes: obtaining an operation log of the power grid to be optimized, and querying charging and discharging data and power grid operation data from the operation log.

[0047] As another embodiment, step 202 includes: obtaining a preset charging and discharging strategy and a preset grid power control strategy corresponding to the grid to be optimized, wherein the preset charging and discharging strategy is the charging and discharging strategy to be implemented by the grid to be optimized, and the preset grid power control strategy is the grid power control strategy to be implemented by the grid to be optimized; predicting the charging and discharging data of the grid to be optimized when the preset grid power control strategy is adopted; and, based on the preset grid power control strategy, predicting the grid operation data when the grid to be optimized adopts the preset grid power control strategy, wherein the prediction process can be completed by an artificial intelligence model.

[0048] Step 204 , based on the charging and discharging data and the grid operation data, the carbon emission situation of the grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes the carbon emission amount and the carbon emission object.

[0049] Exemplarily, step 204 includes: evaluating the carbon emissions of the power grid to be optimized based on the charging and discharging data and the power grid operation data to obtain the carbon emissions; and evaluating the carbon emission objects of the power grid to be optimized based on the carbon emissions to obtain the carbon emission objects.

[0050] Step 206, optimizing the grid charging and discharging strategy of the grid to be optimized according to the carbon emissions, and optimizing the grid power control of the grid to be optimized according to the carbon emissions and the carbon emission objects.

[0051] As one embodiment, the grid charging and discharging strategy of the grid to be optimized is optimized according to the carbon emissions, including: when the carbon emissions are greater than a preset carbon emissions threshold, the grid charging and discharging strategy of the grid to be optimized is optimized according to the battery health loss information corresponding to the grid charging and discharging strategy, wherein the charging and discharging speed corresponding to the optimized grid charging and discharging strategy is smaller than that of the grid charging and discharging strategy before optimization.

[0052] It is understandable that the charging and discharging strategy of the power grid is usually set to increase the charging and discharging speed in order to improve the charging and discharging efficiency, which is likely to lead to a higher degree of battery health loss, that is, the higher the degree of battery life loss, the higher the frequency of battery recycling, and the process of battery recycling will cause carbon emissions, so it will lead to more carbon emissions. Through the above operation, part of the performance of the power grid charging and discharging speed is sacrificed, thereby reducing the degree of battery life loss, and then reducing the frequency of battery recycling, which can also reduce carbon emissions to a certain extent, so the environmental protection of the power grid operation is improved.

[0053] As one embodiment, the grid power control of the power grid to be optimized is optimized according to the carbon emissions and the carbon emission objects, including: if the carbon emission object belongs to an object in the power generation stage, the grid power generation type corresponding to the power grid to be optimized is switched from a non-clean energy power generation type to a clean energy power generation type, wherein the non-clean energy power generation type includes but is not limited to coal energy power generation type, natural gas energy power generation type, oil energy power generation type and nuclear energy power generation type, etc., and the clean energy power generation type includes but is not limited to solar energy power generation type, wind energy power generation type, air energy power generation type, tidal energy power generation type and wave energy power generation type, etc.

[0054] In this way, the power generation type is switched to ensure the environmental friendliness of power generation in the power grid, thereby improving the environmental friendliness of power grid operation.

[0055] As another embodiment, the grid power control of the power grid to be optimized is optimized according to the carbon emissions and the carbon emission objects, including: when the carbon emissions are greater than a preset carbon emission threshold, selecting a target load device that matches the carbon emission object from the grid load devices corresponding to the power grid to be optimized, and reducing the grid load value of the grid load device corresponding to the power grid to be optimized.

[0056] In the above-mentioned power grid control optimization method, the charging and discharging data and power grid operation data of the power grid to be optimized are obtained; based on the charging and discharging data and the power grid operation data, the carbon emission situation of the power grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object; based on the carbon emission amount, the power grid charging and discharging strategy of the power grid to be optimized is optimized; and, based on the carbon emission amount and the carbon emission object, the power grid electricity control of the power grid to be optimized is optimized, so as to characterize the current charging and discharging strategy of the power grid to be optimized and the carbon emission information under the power grid electricity control, the current charging and discharging strategy and power grid electricity control of the power grid to be optimized are optimized, so that the optimized power grid can reduce carbon emissions to a certain extent, thereby improving the environmental protection of the power grid operation.

[0057] It is understandable that when querying the charging and discharging data and grid operation data from the operation logs collected and recorded by sensors, there may be a sensor failure resulting in inaccurate charging and discharging data or grid operation data collected, or, when predicting the charging and discharging data and grid operation data according to the preset charging and discharging strategy and the preset grid power control strategy, there may be inaccurate predictions, that is, the charging and discharging data and grid operation data are inaccurate. When the charging and discharging data and grid operation data are inaccurate, the carbon emission information obtained by carbon emission assessment based on the charging and discharging data and grid operation data will also be inaccurate. Therefore, there is an urgent need for a way to accurately assess carbon emission information.

[0058] In an exemplary embodiment, Figure 3 As shown, a method for accurately evaluating carbon emission information is provided, and the carbon emission of the power grid to be optimized is evaluated according to the charging and discharging data and the power grid operation data, and the carbon emission information is obtained, including steps 302 to 308. Among them:

[0059] Step 302: fuse the charge-discharge data and the grid operation data to obtain fused data, wherein the fused data includes fused sub-data obtained by fusing the charge-discharge data and the grid operation data at each time.

[0060] Exemplarily, step 302 includes: fusing the charging and discharging data and the grid operation data corresponding to each time period to obtain fused sub-data at each time period.

[0061] As an embodiment, step 302 includes: the charging and discharging data includes the charging and discharging amount at each time, and the power grid operation data includes the power grid power generation data and the power grid load data at each time; based on the power grid power generation data and the power grid load data at each time, the power grid power consumption status of the power grid to be optimized is evaluated to obtain the power grid power consumption evaluation data at each time; based on the charging and discharging amount at each time, the charging and discharging status of the power grid to be optimized is evaluated to obtain the charging and discharging evaluation data at each time; the charging and discharging data and the power grid operation data that match the corresponding power grid power consumption evaluation data and the charging and discharging evaluation data at each time are fused to obtain fused sub-data.

[0062] Furthermore, based on the power generation data and the power load data of the power grid at each time, the power consumption status of the power grid to be optimized is evaluated to obtain the power grid power consumption evaluation data at each time, including: the power generation data includes the power generation of the power grid, the power load data includes the power load value of the power grid load equipment, the power grid power consumption evaluation data includes the power grid power consumption, and based on the power generation of the power grid and the power load value of the power grid load equipment at each time, the power consumption status of each power grid load equipment in the power grid to be optimized is evaluated to obtain the power grid power consumption of each power grid load equipment at each time; the power grid power consumption of each power grid load equipment at each time is integrated to obtain the power grid power consumption at each time.

[0063] Step 304: for each fused sub-data, verify the fused sub-data to obtain a verification result, and when the verification result includes a verification failure result, update the fused sub-data to obtain updated sub-data.

[0064] Exemplarily, step 304 includes: for each fused sub-data, obtaining the first grid power at the current time represented by the charging and discharging data in the fused sub-data, and obtaining the second grid power at the current time represented by the grid operation data in the fused sub-data; if the difference between the first grid power and the second grid power is greater than a preset difference threshold, determining that the verification result includes a verification failure result, and updating the fused sub-data to obtain updated sub-data; if the difference between the first grid power and the second grid power is not greater than the preset difference threshold, determining the current fused sub-data as the updated sub-data.

[0065] Further, the fused sub-data is updated to obtain updated sub-data, including: according to the difference between the first power grid quantity and the second power grid quantity, at least one of the charging and discharging data and the power grid operation data of the fused sub-data is updated to obtain updated sub-data.

[0066] Step 306 , based on the updated sub-data, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated to obtain the carbon emissions at the time corresponding to the updated sub-data.

[0067] Exemplarily, step 306 includes: for each updated sub-data, evaluating the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data according to the updated sub-data through a carbon emissions evaluation method to obtain the carbon emissions at the time corresponding to the updated sub-data.

[0068] Furthermore, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated according to the updated sub-data through a carbon emission assessment method to obtain the carbon emissions at the time corresponding to the updated sub-data, including: evaluating the carbon emissions per unit of electricity of the power grid to be optimized at the time corresponding to the updated sub-data through a carbon emission assessment method according to the updated sub-data to obtain the carbon emissions per unit of electricity at the time corresponding to the updated sub-data; determining the ratio between the charge and discharge amount at the time corresponding to the updated sub-data and the carbon emissions per unit of electricity as the carbon emissions at the time corresponding to the updated sub-data.

[0069] Step 308, based on the carbon emissions of all fused sub-data at corresponding times, the carbon emission sources of the power grid to be optimized are evaluated to obtain carbon emission objects.

[0070] As an embodiment, step 308 includes: generating the carbon emissions of each stage in the product life cycle of the power grid to be optimized based on the carbon emissions of all fused sub-data at corresponding times; evaluating the carbon emission sources of the power grid to be optimized based on the carbon emissions of each stage in the product life cycle of the power grid to be optimized to obtain a carbon emission object.

[0071] Furthermore, based on the carbon emissions at the corresponding time of all the fused sub-data, the carbon emissions at each stage in the product life cycle of the power grid to be optimized are generated, including: based on the time and carbon emissions corresponding to all the fused sub-data, the carbon emissions corresponding to all the fused sub-data are associated with each stage in the product life cycle of the power grid to be optimized to obtain the carbon emissions at each stage in the product life cycle of the power grid to be optimized.

[0072] Furthermore, based on the carbon emissions at each stage in the product life cycle of the power grid to be optimized, the carbon emission sources of the power grid to be optimized are evaluated to obtain carbon emission objects, including: selecting a target stage in the product life cycle of the power grid to be optimized based on the carbon emissions at each stage in the product life cycle of the power grid to be optimized; and determining the product production objects corresponding to the target stage as carbon emission objects.

[0073] In this embodiment, the charging and discharging data and the power grid operation data are integrated to obtain integrated data, wherein the integrated data includes integrated sub-data obtained by integrating the charging and discharging data and the power grid operation data at each time; for each integrated sub-data, the integrated sub-data is verified to obtain a verification result, and when the verification result includes a verification failure result, the integrated sub-data is updated to obtain updated sub-data; based on the updated sub-data, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated to obtain the carbon emissions at the time corresponding to the updated sub-data; based on the carbon emissions at the time corresponding to all the integrated sub-data, the carbon emission sources of the power grid to be optimized are evaluated to obtain the carbon emission objects, and by verifying the integrated sub-data, when the charging and discharging data and the power grid operation data are inaccurate, the integrated sub-data can be updated in time to obtain the updated sub-data, thereby ensuring the accuracy of the carbon emission information obtained by the carbon emission assessment based on the updated sub-data, thereby improving the assessment accuracy of the carbon emission information.

[0074] It is understandable that there are currently many ways to assess carbon emissions. It is possible that a certain carbon emissions assessment method is only suitable for the calculation of power grid carbon emissions in a certain scenario. Therefore, the calculated carbon emissions may be inaccurate. Therefore, there is an urgent need for a method to accurately calculate carbon emissions.

[0075] In an exemplary embodiment, Figure 4 As shown, in order to provide a method for accurately calculating carbon emissions, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated according to the updated sub-data, and the carbon emissions at the time corresponding to the updated sub-data are obtained, including steps 402 to 406. Among them:

[0076] Step 402 , using multiple carbon emission assessment methods, respectively assess the carbon emission of the power grid to be optimized at the time corresponding to the updated sub-data according to the updated sub-data, to obtain multiple pre-assessed carbon emissions at the time corresponding to the updated sub-data.

[0077] The multiple carbon emission assessment methods in step 402 include but are not limited to LCA (Life Cycle Assessment), IPCC (based on the energy used), Emissions calculation) method, IO (input-output method) and Kaya carbon emission identity.

[0078] As an embodiment, step 402 includes: for each carbon emission assessment method, mapping the updated sub-data to the carbon emission of the power grid to be optimized at the time corresponding to the updated sub-data through the assessment formula corresponding to the carbon emission assessment method.

[0079] Step 404: if the differences between the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data are less than the preset difference threshold, the average value of the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data is determined as the carbon emissions at the time corresponding to the updated sub-data.

[0080] Step 406, if the differences between the pre-assessed carbon emissions at the corresponding time of multiple updated sub-data are not all less than the preset difference threshold, then according to the assessment information corresponding to the multiple carbon emission assessment methods, the pre-assessed carbon emissions at the corresponding time of the multiple updated sub-data are merged to obtain the carbon emissions at the corresponding time of the updated sub-data, wherein the assessment information corresponding to the carbon emission assessment method is used to characterize the assessment authority of the carbon emission assessment method.

[0081] As an embodiment, based on the assessment information corresponding to multiple carbon emission assessment methods, the pre-assessed carbon emissions at the corresponding times of multiple updated sub-data are merged to obtain the carbon emissions at the corresponding time of the updated sub-data, including: selecting a target carbon emission assessment method from multiple carbon emission assessment methods based on the assessment information corresponding to the multiple carbon emission assessment methods; correcting the pre-assessed carbon emissions corresponding to the target carbon emission assessment method based on the pre-assessed carbon emissions corresponding to the carbon emission assessment method other than the target carbon emission assessment method among the multiple carbon emission assessment methods to obtain the carbon emissions at the corresponding time of the updated sub-data.

[0082] Further, according to the pre-assessed carbon emissions corresponding to the carbon emission assessment methods other than the target carbon emission assessment method among the multiple carbon emission assessment methods, the pre-assessed carbon emissions corresponding to the target carbon emission assessment method are corrected to obtain the carbon emissions at the corresponding time of the updated sub-data, including: for each other carbon emission assessment method other than the target carbon emission assessment method among the multiple carbon emission assessment methods, according to the difference between the pre-assessed carbon emissions corresponding to the other carbon emission assessment methods and the pre-assessed carbon emissions corresponding to the target carbon emission assessment method, generating a correction coefficient for the other carbon emission assessment method; according to all other The correction coefficient of the carbon emission assessment method corrects the pre-assessed carbon emissions corresponding to the target carbon emission assessment method to obtain the carbon emissions at the time corresponding to the updated sub-data, wherein the correction method includes a summation method or a product method. When the correction method is the summation method, the correction coefficient includes a correction direction and a correction value. For example, when the correction coefficient is a positive value, it represents an increase correction by the correction coefficient, and when the correction coefficient is a negative value, it represents a decrease correction by the correction coefficient; when the correction method is the product method, when the correction coefficient is greater than 1, it represents an increase correction by the correction coefficient, and when the correction coefficient is less than 1, it represents a decrease correction by the correction coefficient.

[0083] As one embodiment, the assessment information corresponding to the carbon emission assessment method includes the usage frequency and verification accuracy corresponding to the carbon emission assessment method. The assessment authority of the carbon emission assessment method is generated based on the usage frequency and verification accuracy corresponding to the carbon emission assessment method, wherein the higher the usage frequency, the higher the assessment authority, and the higher the verification accuracy, the higher the assessment authority.

[0084] In this embodiment, through multiple carbon emission assessment methods, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated according to the updated sub-data respectively, and the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data are obtained; if the differences between the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data are less than the preset difference threshold, then the average value between the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data is determined as the carbon emissions at the time corresponding to the updated sub-data; if the differences between the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data are not less than the preset difference threshold, then according to the assessment information corresponding to the multiple carbon emission assessment methods, the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data are merged to obtain the carbon emissions at the time corresponding to the updated sub-data, wherein the assessment information corresponding to the carbon emission assessment method is used to characterize the assessment authority of the carbon emission assessment method, and the pre-assessed carbon emissions of the multiple carbon emission assessment methods are merged based on the assessment authority, to ensure that each carbon emission assessment method can participate in the decision-making in the carbon emission assessment process, thereby improving the accuracy of the assessed carbon emissions.

[0085] As a detailed embodiment, the charging and discharging data and the grid operation data of the power grid to be optimized are obtained; the power grid power consumption status of the power grid to be optimized is evaluated according to the power grid generation data and the power grid load data at each time, and the power grid power consumption evaluation data at each time is obtained; the charging and discharging status of the power grid to be optimized is evaluated according to the charge and discharge amount at each time, and the charge and discharge evaluation data at each time is obtained; the corresponding power grid power consumption evaluation data at each time and the charging and discharging data and the grid operation data that match the charge and discharge evaluation data are fused to obtain fused sub-data; for each fused sub-data, the fused sub-data is verified to obtain a verification result, and when the verification result includes a verification failure result, the fused sub-data is updated to obtain updated sub-data; through multiple carbon emission evaluation methods, the updated sub-data are respectively evaluated according to the updated sub-data corresponding to the power grid to be optimized The carbon emissions at the time are evaluated to obtain the pre-assessed carbon emissions at the corresponding times of multiple updated sub-data; if the differences between the pre-assessed carbon emissions at the corresponding times of multiple updated sub-data are all less than the preset difference threshold, the average value of the pre-assessed carbon emissions at the corresponding times of multiple updated sub-data is determined as the carbon emissions at the corresponding time of the updated sub-data; if the differences between the pre-assessed carbon emissions at the corresponding times of multiple updated sub-data are not all less than the preset difference threshold, then according to the assessment information corresponding to the multiple carbon emission assessment methods, a target carbon emission assessment method is selected from the multiple carbon emission assessment methods; according to the pre-assessed carbon emissions corresponding to the carbon emission assessment methods other than the target carbon emission assessment method among the multiple carbon emission assessment methods, the pre-assessed carbon emissions corresponding to the target carbon emission assessment method are corrected to obtain the carbon emissions at the corresponding time of the updated sub-data.

[0086] Furthermore, based on the carbon emissions at the corresponding time of all fused sub-data, the carbon emissions of each stage in the product life cycle of the power grid to be optimized are generated; based on the carbon emissions of each stage in the product life cycle of the power grid to be optimized, the carbon emission sources of the power grid to be optimized are evaluated to obtain the carbon emission objects; based on the carbon emissions, the power grid charging and discharging strategy of the power grid to be optimized is optimized; and, based on the carbon emissions and the carbon emission objects, the power grid power control of the power grid to be optimized is optimized.

[0087] In this way, by acquiring the charging and discharging data and the grid operation data of the power grid to be optimized; evaluating the carbon emission situation of the power grid to be optimized based on the charging and discharging data and the grid operation data, and obtaining the carbon emission information, wherein the carbon emission information includes the carbon emission amount and the carbon emission object; optimizing the grid charging and discharging strategy of the power grid to be optimized based on the carbon emission amount, and optimizing the grid power control of the power grid to be optimized based on the carbon emission information under the current charging and discharging strategy and grid power control of the power grid to be optimized, so that the optimized power grid can reduce carbon emissions to a certain extent, thereby improving the environmental protection of the power grid operation.

[0088] Furthermore, by verifying the fused sub-data, the fused sub-data can be updated in time to obtain updated sub-data when the charging and discharging data and the grid operation data are inaccurate, thereby ensuring the accuracy of the carbon emission information obtained by carbon emission assessment based on the updated sub-data, thereby improving the accuracy of the carbon emission information assessment; and, based on the authority of the assessment, the pre-assessed carbon emissions of multiple carbon emission assessment methods are merged to ensure that each carbon emission assessment method can participate in the decision-making in the carbon emission assessment process, thereby improving the accuracy of the assessed carbon emissions.

[0089] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0090] Based on the same inventive concept, the embodiment of the present application also provides a power grid control optimization device for implementing the power grid control optimization method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more power grid control optimization device embodiments provided below can refer to the limitations of the power grid control optimization method above, and will not be repeated here.

[0091] In an exemplary embodiment, Figure 5As shown, a power grid control optimization device 500 is provided, comprising: an acquisition module 502, an evaluation module 504 and an optimization module 506, wherein:

[0092] An acquisition module 502 is used to acquire charging and discharging data and grid operation data of the grid to be optimized;

[0093] An evaluation module 504 is used to evaluate the carbon emission of the power grid to be optimized based on the charging and discharging data and the power grid operation data, and obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object;

[0094] The optimization module 506 is used to optimize the grid charging and discharging strategy of the grid to be optimized according to the carbon emissions, and to optimize the grid power control of the grid to be optimized according to the carbon emissions and the carbon emission objects.

[0095] In one of the embodiments, the evaluation module 504 is also used to fuse the charging and discharging data with the power grid operation data to obtain fused data, wherein the fused data includes fused sub-data obtained by fusing the charging and discharging data with the power grid operation data at each time; for each fused sub-data, the fused sub-data is verified to obtain a verification result, and when the verification result includes a verification failure result, the fused sub-data is updated to obtain updated sub-data; based on the updated sub-data, the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data are evaluated to obtain the carbon emissions at the time corresponding to the updated sub-data; based on the carbon emissions at the time corresponding to all fused sub-data, the carbon emission sources of the power grid to be optimized are evaluated to obtain carbon emission objects.

[0096] In one embodiment, the charging and discharging data include the charging and discharging amount at each time, and the power grid operation data include the power grid generation data and the power grid load data at each time; the evaluation module 504 is also used to evaluate the power grid power consumption status of the power grid to be optimized according to the power grid generation data and the power grid load data at each time, and obtain the power grid power consumption evaluation data at each time; evaluate the charging and discharging status of the power grid to be optimized according to the charging and discharging amount at each time, and obtain the charging and discharging evaluation data at each time; fuse the corresponding power grid power consumption evaluation data and the charging and discharging evaluation data at each time with the power grid operation data, and obtain the fused sub-data.

[0097] In one of the embodiments, the evaluation module 504 is also used to evaluate the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data according to the updated sub-data through multiple carbon emission evaluation methods, and obtain multiple pre-evaluated carbon emissions at the time corresponding to the updated sub-data; if the differences between the pre-evaluated carbon emissions at the time corresponding to the multiple updated sub-data are all less than the preset difference threshold, then the average value of the pre-evaluated carbon emissions at the time corresponding to the multiple updated sub-data is determined as the carbon emissions at the time corresponding to the updated sub-data; if the differences between the pre-evaluated carbon emissions at the time corresponding to the multiple updated sub-data are not all less than the preset difference threshold, then according to the evaluation information corresponding to the multiple carbon emission evaluation methods, the pre-evaluated carbon emissions at the time corresponding to the multiple updated sub-data are merged to obtain the carbon emissions at the time corresponding to the updated sub-data, wherein the evaluation information corresponding to the carbon emission evaluation method is used to characterize the evaluation authority of the carbon emission evaluation method.

[0098] In one of the embodiments, the evaluation module 504 is also used to select a target carbon emission assessment method from multiple carbon emission assessment methods based on the evaluation information corresponding to the multiple carbon emission assessment methods; and to correct the pre-assessed carbon emissions corresponding to the target carbon emission assessment method based on the pre-assessed carbon emissions corresponding to the carbon emission assessment methods other than the target carbon emission assessment method among the multiple carbon emission assessment methods to obtain the carbon emissions at the corresponding time of the updated sub-data.

[0099] In one of the embodiments, the evaluation module 504 is also used to generate the carbon emissions of each stage in the product life cycle of the power grid to be optimized based on the carbon emissions of all fused sub-data at corresponding times; based on the carbon emissions of each stage in the product life cycle of the power grid to be optimized, the carbon emission sources of the power grid to be optimized are evaluated to obtain carbon emission objects.

[0100] Each module in the above-mentioned power grid control optimization device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0101] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a power grid control optimization method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

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

[0103] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0104] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0105] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0106] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in 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. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0107] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0108] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A power grid control optimization method, characterized in that: The method comprises: Obtain charging and discharging data and grid operation data of the grid to be optimized; According to the charging and discharging data and the grid operation data, the carbon emission of the grid to be optimized is evaluated to obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object; According to the carbon emissions, the grid charging and discharging strategy of the grid to be optimized is optimized; and according to the carbon emissions and the carbon emission objects, the grid power control of the grid to be optimized is optimized.

2. The method according to claim 1, characterized in that: The step of evaluating the carbon emission of the power grid to be optimized according to the charging and discharging data and the power grid operation data to obtain carbon emission information includes: The charging and discharging data and the power grid operation data are fused to obtain fused data, wherein the fused data includes fused sub-data obtained by fusion of the charging and discharging data and the power grid operation data at each time; For each of the fused sub-data, verify the fused sub-data to obtain a verification result, and if the verification result includes a verification failure result, update the fused sub-data to obtain updated sub-data; According to the update sub-data, the carbon emissions of the power grid to be optimized at the time corresponding to the update sub-data are evaluated to obtain the carbon emissions at the time corresponding to the update sub-data; According to the carbon emissions at the corresponding time of all the fused sub-data, the carbon emission sources of the power grid to be optimized are evaluated to obtain a carbon emission object.

3. The method according to claim 2, characterized in that The charging and discharging data includes the charging and discharging amount at each time, and the power grid operation data includes the power grid generation data and the power grid load data at each time; the charging and discharging data and the power grid operation data are fused to obtain fused data, including: According to the power grid generation data and the power grid load data at each time, the power grid power consumption status of the power grid to be optimized is evaluated to obtain the power grid power consumption evaluation data at each time; According to the charge and discharge amount at each time, the charge and discharge status of the power grid to be optimized is evaluated to obtain the charge and discharge evaluation data at each time; The charging and discharging data and the grid operation data that match the grid power consumption evaluation data and the charging and discharging evaluation data corresponding to each time are fused to obtain fused sub-data.

4. The method according to claim 2, characterized in that: The step of evaluating the carbon emissions of the power grid to be optimized at the time corresponding to the updated sub-data according to the updated sub-data to obtain the carbon emissions at the time corresponding to the updated sub-data includes: Through multiple carbon emission assessment methods, the carbon emission of the power grid to be optimized at the time corresponding to the updated sub-data is assessed according to the updated sub-data respectively, so as to obtain the pre-assessed carbon emission at the time corresponding to the multiple updated sub-data; If the differences between the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data are all less than the preset difference threshold, the average value of the pre-assessed carbon emissions at the time corresponding to the multiple updated sub-data is determined as the carbon emissions at the time corresponding to the updated sub-data; If the differences between the pre-assessed carbon emissions at the corresponding times of the multiple updated sub-data are not all less than the preset difference threshold, the pre-assessed carbon emissions at the corresponding times of the multiple updated sub-data are merged according to the assessment information corresponding to the multiple carbon emission assessment methods to obtain the carbon emissions at the corresponding time of the updated sub-data, wherein the assessment information corresponding to the carbon emission assessment method is used to characterize the assessment authority of the carbon emission assessment method.

5. The method according to claim 4, characterized in that The step of fusing the pre-assessed carbon emissions at the corresponding times of the multiple updated sub-data according to the assessment information corresponding to the multiple carbon emissions assessment methods to obtain the carbon emissions at the corresponding times of the updated sub-data includes: Selecting a target carbon emission assessment method from the multiple carbon emission assessment methods according to the assessment information corresponding to the multiple carbon emission assessment methods; According to the pre-assessed carbon emissions corresponding to the carbon emission assessment methods other than the target carbon emission assessment method among the multiple carbon emission assessment methods, the pre-assessed carbon emissions corresponding to the target carbon emission assessment method are corrected to obtain the carbon emissions at the time corresponding to the updated sub-data.

6. The method according to claim 2, characterized in that The step of evaluating the carbon emission sources of the power grid to be optimized according to the carbon emissions at the corresponding time of all the fused sub-data to obtain the carbon emission objects includes: Generate the carbon emissions of each stage in the product life cycle of the power grid to be optimized according to the carbon emissions at the corresponding time of all the fused sub-data; According to the carbon emissions at each stage in the product life cycle of the power grid to be optimized, the carbon emission sources of the power grid to be optimized are evaluated to obtain carbon emission objects.

7. A power grid control optimization device, characterized in that: The device comprises: An acquisition module, used to acquire charging and discharging data and grid operation data of the grid to be optimized; An evaluation module, configured to evaluate the carbon emission of the power grid to be optimized according to the charging and discharging data and the power grid operation data, and obtain carbon emission information, wherein the carbon emission information includes carbon emission amount and carbon emission object; The optimization module is used to optimize the grid charging and discharging strategy of the grid to be optimized according to the carbon emissions, and to optimize the grid power control of the grid to be optimized according to the carbon emissions and the carbon emission objects.

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

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

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

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