Charging load complementation potential evaluation method, medium and control device

Abstract

The invention relates to the technical field of charging, particularly provides a charging load complementation potential evaluation method, a medium and a control device, and aims to solve the problem of low utilization rate of existing charging resources. The charging and swapping load complementary potential evaluation method is suitable for a plurality of charging and swapping loads connected to the same power distribution network, the charging and swapping loads are at least one of a charging pile and a swapping station, and the evaluation method comprises the following steps: selecting two charging and swapping loads from the plurality of charging and swapping loads; respectively determining the adjustable capability of the two charging loads in at least one time period in the future; calculating complementation degree scores of the two charging loads based on the adjustable capabilities of the two charging loads; calculating a distance score based on the distance between the two charging loads; and based on the complementation degree score and the distance score, calculating a complementation scheduling potential comprehensive score between the two charging loads. According to the method, the complementary potential between the charging and battery replacing loads can be reflected more comprehensively and accurately, and efficient scheduling of the charging and battery replacing resources is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of charging and battery swapping, and specifically provides a charging and battery swapping load complementary potential evaluation method, a medium and a control device. BACKGROUND

[0002] With the popularization of electric vehicles, the construction and operation of charging and battery swapping facilities have become an important research topic. The charging and battery swapping load characteristics in different scenarios differ significantly, such as high night charging demand in community scenarios, high daytime charging demand in commercial district scenarios, and high holiday charging demand in highway service area scenarios, and the demand characteristics are significantly different due to different locations of battery swapping stations (such as being placed in urban areas, intercity areas, and highways).

[0003] In the prior art, the evaluation of charging and battery swapping load mostly uses a single index, such as only considering the difference in load value, without fully considering the characteristics of different scenarios, resulting in inaccurate evaluation results and failing to provide effective basis for resource allocation, thereby leading to low resource utilization.

[0004] Correspondingly, there is a need in the art for a new technical solution to solve the above problems. SUMMARY

[0005] The present application aims to solve at least one of the above technical problems, i.e., to solve the problem of low utilization of existing charging and battery swapping resources.

[0006] In a first aspect, the present application provides a charging and battery swapping load complementary potential evaluation method, which is suitable for multiple charging and battery swapping loads connected to the same power distribution network, the charging and battery swapping load being at least one of charging piles and battery swapping stations, and the evaluation method comprising: selecting two charging and battery swapping loads from the multiple charging and battery swapping loads; determining the adjustable capacity of the two charging and battery swapping loads in at least one future time period, respectively; calculating the complementary degree score of the two charging and battery swapping loads based on their adjustable capacities; determining the distance score based on the distance between the two charging and battery swapping loads; and calculating the comprehensive complementary scheduling potential score between the two charging and battery swapping loads based on the complementary degree score and the distance score.

[0007] The present application constructs a systematic evaluation method of complementary potential between charging and battery swapping loads, calculates the complementary degree score between the charging and battery swapping loads and determines the distance score, and then calculates the comprehensive complementary scheduling potential score between the two, which, compared with single index evaluation, fully considers the spatiotemporal complementary characteristics between the charging and battery swapping loads, can more comprehensively and accurately reflect the complementary potential between the charging and battery swapping loads, provides effective basis for the allocation of charging and battery swapping resources, realizes efficient scheduling of charging and battery swapping resources, optimizes resource allocation, and reduces operating costs. At the same time, it contributes to the stability and safety of the power grid, especially the power distribution network.

[0008] In the preferred technical solution of the above-mentioned method for evaluating complementary potential of charging and swapping loads, the step of "selecting two charging and swapping loads from the plurality of charging and swapping loads" further comprises: selecting two charging and swapping loads with different load types from the plurality of charging and swapping loads under the same scene type; wherein the scene type and the load type of the charging and swapping loads are determined in advance based on user characteristics and load characteristics of the charging and swapping loads.

[0009] By determining the scene type and the load type of the charging and swapping loads in advance and selecting charging and swapping loads with different composite types under the same scene type, the application can also evaluate the complementary potential from the dimension of energy supply scenes, achieving efficient and rapid evaluation of the complementary potential of charging and swapping loads.

[0010] In the preferred technical solution of the above-mentioned method for evaluating complementary potential of charging and swapping loads, the scene type includes residential areas, commercial areas, and high-speed service areas; and / or the load type includes household charging piles, public charging piles, and swapping stations.

[0011] In the preferred technical solution of the above-mentioned method for evaluating complementary potential of charging and swapping loads, the step of "determining the adjustable capacity of each of the two charging and swapping loads in at least one future time period" further comprises: if the charging and swapping load is a charging pile, predicting the maximum adjustable power and the minimum adjustable power in the future multiple time periods based on a load prediction model, and generating a charging adjustable capacity curve; if the charging and swapping load is a swapping station, predicting the maximum adjustable power and the minimum adjustable power in the future multiple time periods based on an order prediction model, and generating a swapping adjustable capacity curve.

[0012] In the preferred technical solution of the above-mentioned method for evaluating complementary potential of charging and swapping loads, the step of "predicting the maximum adjustable power and the minimum adjustable power in at least one future time period based on a load prediction model, and generating a charging adjustable capacity curve" further comprises: predicting the charging power in the future multiple time periods based on a load prediction model; determining the maximum adjustable power of each time period as the charging power corresponding to the time period and the minimum adjustable power as 0; and generating a charging adjustable capacity curve based on the difference between the maximum adjustable power and the minimum adjustable power of each time period.

[0013] In the preferred technical solutions of the above charging and battery swapping load complementary potential evaluation method, the step of "predicting the maximum adjustable power and the minimum adjustable power of at least one future period based on the order prediction model, and generating a charging adjustable capacity curve" further comprises: predicting the order quantity of multiple periods in the future based on the order prediction model; calculating the power required for battery charging corresponding to the completed order quantity as the minimum adjustable power of the period based on the order quantity of each period; calculating the power required for charging all batteries as the maximum adjustable power of the period; and generating a battery swapping adjustable capacity curve based on the difference between the maximum adjustable power and the minimum adjustable power of each period.

[0014] In the preferred technical solutions of the above charging and battery swapping load complementary potential evaluation method, the step of "calculating the complementary degree score of the two based on the adjustable capacity of the two charging and battery swapping loads" further comprises: superimposing the charging adjustable capacity curve and the battery swapping adjustable capacity curve; calculating the horizontal complementary degree and the vertical complementary degree based on the superimposed curve; and calculating the complementary degree score based on the horizontal complementary degree and the vertical complementary degree.

[0015] By superimposing the curves respectively to calculate the horizontal complementary degree and the vertical complementary degree, and then calculating the complementary degree score, the complementary degree between the charging and battery swapping loads can be evaluated from different dimensions, and the accuracy of the complementary degree calculation is improved.

[0016] In the preferred technical solutions of the above charging and battery swapping load complementary potential evaluation method, the step of "calculating the horizontal complementary degree based on the superimposed curve" further comprises: calculating the horizontal complementary degree by the following formula: ; wherein C A is the horizontal complementary degree; T is the number of periods; n is the number of loads participating in superposition; P tx is the adjustable capacity of the charging and battery swapping load x in period t.

[0017] In the preferred technical solutions of the above charging and battery swapping load complementary potential evaluation method, the step of "calculating the vertical complementary degree based on the superimposed curve" further comprises: calculating the vertical complementary degree by the following formula: ; wherein C F is the vertical complementary degree; n is the number of loads participating in superposition; P tx is the adjustable capacity of the charging and battery swapping load x in period t.

[0018] In the preferred technical solutions of the above charging and battery swapping load complementary potential evaluation method, the step of "determining the distance score based on the distance between the two charging and battery swapping loads" further comprises: calculating the Euclidean distance between the two charging and battery swapping loads and normalizing to obtain the distance score.

[0019] In the preferred technical solution of the above charging and battery swapping load complementary potential evaluation method, the step of "calculating a comprehensive complementary scheduling potential score between the two charging and battery swapping loads based on the complementary degree score and the distance score" further comprises: calculating the comprehensive complementary scheduling potential score by the following formula: ; wherein S is the comprehensive complementary scheduling potential score; C com is the complementary degree score; D com is the distance score; a is the adjustable capacity matching degree weight; β is the load coverage duration weight, and a+β=1.

[0020] In a second aspect, the present application also provides a computer-readable storage medium storing a plurality of program codes, which are adapted to be loaded and run by a processor to perform the charging and battery swapping load complementary potential evaluation method of any one of the above technical solutions.

[0021] In a third aspect, the present application also provides a control device comprising: a processor; a memory adapted to store a plurality of program codes, which are adapted to be loaded and run by the processor to perform the charging and battery swapping load complementary potential evaluation method of any one of the above technical solutions.

[0022] Scheme 1. A charging and battery swapping load complementary potential evaluation method, characterized in that it is suitable for a plurality of charging and battery swapping loads connected to the same power distribution network, the charging and battery swapping load being at least one of a charging pile and a battery swapping station, and the evaluation method comprising: selecting two charging and battery swapping loads from the plurality of charging and battery swapping loads; determining the adjustable capacity of the two charging and battery swapping loads in at least one future period respectively; calculating the complementary degree score of the two charging and battery swapping loads based on their adjustable capacity; determining the distance score based on the distance between the two charging and battery swapping loads; and calculating the comprehensive complementary scheduling potential score between the two charging and battery swapping loads based on the complementary degree score and the distance score.

[0023] Scheme 2. The charging and battery swapping load complementary potential evaluation method according to scheme 1, characterized in that the step of "selecting two charging and battery swapping loads from the plurality of charging and battery swapping loads" further comprises: selecting two charging and battery swapping loads of different load types from the plurality of charging and battery swapping loads located in the same scene type; wherein the scene type and the load type of the charging and battery swapping load are determined in advance based on the user characteristics and load characteristics of the charging and battery swapping load.

[0024] Scheme 3. The charging and battery swapping load complementary potential evaluation method according to scheme 2, characterized in that the scene type comprises residential area, commercial area and high-speed service area; and / or the load type comprises household charging pile, public charging pile and battery swapping station.

[0025] Scheme 4. The complementary potential evaluation method of charging and swapping loads according to scheme 1, characterized in that the step of "determining the adjustable capacity of the two charging and swapping loads respectively in at least one future period" further comprises: if the charging and swapping load is a charging pile, predicting the maximum adjustable power and the minimum adjustable power in multiple future periods based on the load prediction model, and generating a charging adjustable capacity curve; if the charging and swapping load is a battery swapping station, predicting the maximum adjustable power and the minimum adjustable power in multiple future periods based on the order prediction model, and generating a battery swapping adjustable capacity curve.

[0026] Scheme 5. The complementary potential evaluation method of charging and swapping loads according to scheme 4, characterized in that the step of "predicting the maximum adjustable power and the minimum adjustable power in at least one future period based on the load prediction model, and generating a charging adjustable capacity curve" further comprises: predicting the charging power in multiple future periods based on the load prediction model; determining the maximum adjustable power of each period as the charging power corresponding to the period, and the minimum adjustable power as 0; generating a charging adjustable capacity curve based on the difference between the maximum adjustable power and the minimum adjustable power of each period.

[0027] Scheme 6. The complementary potential evaluation method of charging and swapping loads according to scheme 4, characterized in that the step of "predicting the maximum adjustable power and the minimum adjustable power in at least one future period based on the order prediction model, and generating a charging adjustable capacity curve" further comprises: predicting the number of orders in multiple future periods based on the order prediction model; calculating the power required to charge the batteries corresponding to the number of completed orders as the minimum adjustable power of the period based on the number of orders of each period; calculating the power required to charge all batteries as the maximum adjustable power of the period; generating a battery swapping adjustable capacity curve based on the difference between the maximum adjustable power and the minimum adjustable power of each period.

[0028] Scheme 7. The complementary potential evaluation method of charging and swapping loads according to scheme 4, characterized in that the step of "calculating the complementary degree score of the two charging and swapping loads based on their adjustable capacity" further comprises: superimposing the charging adjustable capacity curve and the battery swapping adjustable capacity curve; calculating the horizontal complementarity and the vertical complementarity based on the superimposed curve; calculating the complementary degree score based on the horizontal complementarity and the vertical complementarity.

[0029] Scheme 8. The complementary potential evaluation method of charging and swapping loads according to scheme 7, characterized in that the step of "calculating the horizontal complementarity based on the superimposed curve" further comprises: calculating the horizontal complementarity by the following formula: ; wherein, C A is the horizontal complementarity; T is the number of periods; n is the number of loads participating in superposition; P txAdjustable capacity of the charging and swapping load x in the t period.

[0030] Scheme 9. The charging and swapping load complementary potential evaluation method according to scheme 7, characterized in that the step of "calculating the vertical complementary degree based on the superimposed curve" further comprises: calculating the vertical complementary degree by the following formula: ; wherein, C F is the vertical complementary degree; n is the number of loads participating in superposition; P tx is the adjustable capacity of the charging and swapping load x in the t period.

[0031] Scheme 10. The charging and swapping load complementary potential evaluation method according to scheme 1, characterized in that the step of "calculating the distance score based on the distance between the two charging and swapping loads" further comprises: calculating the Euclidean distance between the two charging and swapping loads and normalizing to obtain the distance score.

[0032] Scheme 11. The charging and swapping load complementary potential evaluation method according to scheme 1, characterized in that the step of "calculating the complementary scheduling potential comprehensive score between the two charging and swapping loads based on the complementary degree score and the distance score" further comprises: calculating the complementary scheduling potential comprehensive score by the following formula: ; wherein, S is the complementary scheduling potential comprehensive score; C com is the complementary degree score; D com is the distance score; a is the adjustable capacity matching degree weight; b is the load coverage time length weight, and a+b=1.

[0033] Scheme 12. A computer readable storage medium storing a plurality of program codes, characterized in that the program codes are adapted to be loaded and run by a processor to execute the charging and swapping load complementary potential evaluation method according to any one of schemes 1 to 11.

[0034] Scheme 13. A control device, characterized in that it comprises: a processor; a memory adapted to store a plurality of program codes, the program codes being adapted to be loaded and run by the processor to execute the charging and swapping load complementary potential evaluation method according to any one of schemes 1 to 11. BRIEF DESCRIPTION OF DRAWINGS

[0035] The preferred embodiments of the present application will be described below with reference to the accompanying drawings.

[0036] Figure 1 is a schematic diagram of the application scenario of the charging and swapping load complementary potential evaluation method of the present application.

[0037] Figure 2 is a flowchart of the charging and swapping load complementary potential evaluation method of the present application. DETAILED DESCRIPTION

[0038] Preferred embodiments of this application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of this application and are not intended to limit the scope of protection of this application. It should be noted that although the detailed steps of the method of this application are described in detail below, those skilled in the art can combine, split, and rearrange the following steps without departing from the basic principles of this application. Such modifications do not change the basic concept of this application and therefore also fall within the scope of protection of this application.

[0039] First refer to Figure 1 This paper briefly introduces the applicable scenarios for the charging / swapping load complementarity potential assessment method of this application. For example... Figure 1 As shown, in one possible application scenario, multiple charging and swapping loads are connected to the same power distribution network. These charging and swapping loads are all connected to the cloud IoT platform, which in turn is connected to the virtual power plant. Figure 1 In the diagram, solid arrows represent top-down instruction distribution, such as issuing scheduling strategy instructions; dashed arrows represent the aggregation and feedback of various data from the charging and swapping loads by the cloud-based IoT platform, such as load data, location information, and adjustability of the charging and swapping loads. In this application, the charging and swapping load can be a charging pile or a swapping station.

[0040] For multiple charging and swapping loads connected under the same distribution network, in one specific scenario, they could be charging and swapping loads from different operators located at the same substation and connected to the same transformer, such as charging piles and swapping stations from different operators connected to the same transformer. In another specific scenario, they could be charging and swapping loads located at the same substation and connected to the same distribution line but under different transformers, such as multiple sub-transformers connected to a main transformer, each sub-transformer connecting to a charging and swapping load from one operator. Yet another specific scenario could be multiple charging and swapping loads located at different substations connected to the same distribution line, such as two main transformers connected to a distribution bus, each main transformer corresponding to one substation, where a single substation can be any of the two scenarios described above. In summary, as long as multiple charging and swapping loads are connected to the same distribution network, regardless of whether they are located at the same substation, the method described in this application can be implemented. In one practical application scenario, charging and swapping loads with spatiotemporal complementary characteristics from different substations can be connected to the same distribution network. For example, if public charging piles and battery swapping stations in commercial areas, home charging piles in residential areas, and public charging piles and battery swapping stations in highway service areas are connected to the same power distribution network, the demand for charging in residential areas is high at night, the demand for charging and battery swapping in commercial areas is high during the day, and the demand for charging and battery swapping in highway service areas is high on holidays. Therefore, the above-mentioned types of charging and battery swapping loads are complementary in terms of electricity consumption habits in terms of time and space.

[0041] In one possible implementation, all charging and swapping loads in this application have self-prediction and communication capabilities. The charging and swapping loads can predict their adjustability for a certain period of time in the future (such as the next 5 minutes, 15 minutes, 30 minutes, etc.) or multiple periods of time (such as the next 1 hour, 12 hours, 24 hours, etc., with 5 minutes as a period). The adjustability is then uniformly reported to the cloud IoT platform. The cloud IoT platform interacts with the virtual power plant and uniformly sends the adjustability to the virtual power plant. The controller set in the virtual power plant evaluates the complementary potential of the charging and swapping loads based on the adjustability and schedules the charging and swapping loads based on the evaluation results.

[0042] Of course, the above-described method of assessing the complementary potential of charging and swapping loads by setting up a controller in a virtual power plant is merely illustrative. Those skilled in the art will understand that the operation of the following assessment method is not limited to a virtual power plant; it can also be implemented on a cloud-based IoT platform, which sends the estimation results to the virtual power plant to provide a scheduling strategy. Furthermore, although the prediction of adjustable capacity in this application is described in conjunction with the self-prediction of charging and swapping loads, the execution location of this prediction is not limited to the charging and swapping loads. In other embodiments, the prediction can also be implemented in a cloud-based IoT platform or a virtual power plant, as long as the cloud-based IoT platform or virtual power plant can set up models or algorithms related to the prediction. In addition, the communication link between the virtual power plant and the cloud-based IoT platform is also merely illustrative. In other embodiments, the connection method can be changed according to the different access requirements of the charging and swapping loads. For example, the virtual power plant can directly connect to the charging and swapping loads. Furthermore, although the type of distribution network is not described above, those skilled in the art will understand that both AC and DC distribution networks are applicable to this application.

[0043] Next, refer to Figure 2 This paper briefly introduces the method for assessing the complementary potential of charging and swapping loads in this application. Figure 2 As shown, in order to solve the problem of low utilization rate of existing charging and swapping resources, this application provides a method for evaluating the complementary potential of charging and swapping loads, which includes steps S101 to S109.

[0044] S101, select two charging and swapping loads from the plurality of charging and swapping loads. For example, when evaluating the complementary potential of the charging and swapping loads, the potential between all charging and swapping loads needs to be evaluated, so two charging and swapping loads are selected from all charging and swapping loads for evaluation each time until all charging and swapping loads to be evaluated are evaluated. The selection of charging and swapping loads can be randomly selected and then iteratively evaluated, or can be selectively selected to improve evaluation efficiency and accuracy. The latter selection method will be described in detail below.

[0045] S103, respectively determine the adjustable capacity of the two charging and swapping loads in at least one future period. The adjustable capacity specifically refers to the ability of the charging and swapping load to adjust its load according to the demand of the power grid, more specifically, the power adjustable range in any period. The adjustable capacity can be predicted by the charging and swapping load itself, or by uploading relevant data to the cloud platform or virtual power plant.

[0046] S105, based on the adjustable capacity of the two charging and swapping loads, calculate the complementary degree score of the two. For example, the complementary degree in this application refers to the ability of other charging and swapping loads to provide dispatchable capacity when the capacity demand of one charging and swapping load is large. It can be considered that the higher the similarity of the adjustable capacity of the two charging and swapping loads, the lower the complementary degree, and vice versa. For example, for home charging piles and public charging piles with time and space characteristics, the charging demand of home charging piles is low during the day, i.e. the adjustable capacity is high; while the charging demand of public charging piles is high, so the adjustable capacity is low, at this time the complementary degree between home charging piles and public charging piles is high, when the demand for electricity of public charging piles is large, the electricity of home charging piles can be dispatched to balance the load of the power grid, to reduce the peak-valley difference and improve the utilization efficiency of charging and swapping loads. For example, for a battery swapping station, when the number of battery swapping orders is low, the battery charging is not urgent, most of the batteries can be charged at low power or not charged, at this time the adjustable capacity is high, and the complementary degree with the charging pile or the battery swapping station with low adjustable capacity is high. When the number of battery swapping orders is large, the battery charging is urgent, most of the batteries need to complete the charging target when the order is executed, at this time the adjustable capacity is low, and the complementary degree between the charging pile or the battery swapping station with high adjustable capacity is high. Therefore, the complementary degree score between the two can be calculated based on the adjustable capacity of the two charging and swapping loads, the lower the similarity of the adjustable capacity, the higher the complementary degree score.

[0047] S107, determine the distance score based on the distance between two charging / swapping loads. For example, the distance between different charging / swapping loads has a certain impact on the scheduling of charging / swapping resources. The closer the charging / swapping resources are, the more favorable the scheduling of charging / swapping resources is. Therefore, a distance score can be given based on the distance between the charging / swapping loads; for example, the closer the distance, the higher the score. Of course, scores can also be manually assigned based on the distance.

[0048] S109. Based on the complementarity score and distance score, calculate the comprehensive score of complementary dispatch potential between two charging and swapping loads. For example, after calculating the complementarity score and confirming the distance score, assign different weight coefficients to the two and sum them to calculate the final comprehensive score of complementary dispatch potential. This score can reflect the complementary potential between the two charging and swapping loads from the perspectives of complementarity degree and distance.

[0049] This application constructs a systematic evaluation method for the complementary potential between charging and swapping loads. By calculating the complementarity score and confirming the distance score between the charging and swapping loads, a comprehensive score for their complementary scheduling potential is calculated. Compared with single-index evaluation, this method fully considers the spatiotemporal complementarity characteristics between charging and swapping loads, and can more comprehensively and accurately reflect their complementary potential. This provides an effective basis for the allocation of charging and swapping resources, enabling efficient scheduling of these resources, optimizing resource allocation, and reducing operating costs. Simultaneously, it contributes to the stability and security of the power grid, especially the distribution network.

[0050] The following section provides a detailed description of the evaluation method for the complementary potential of charging and swapping loads in this application.

[0051] In one possible implementation, the step of "selecting two charging and swapping loads from multiple charging and swapping loads" further includes: selecting two charging and swapping loads with different load types from multiple charging and swapping loads located in the same scenario type; wherein the scenario type and load type of the charging and swapping load are predetermined based on the user characteristics and load characteristics of the charging and swapping load.

[0052] Specifically, before implementation, the evaluation method of this application first classifies the charging and swapping loads into three categories and three charging and swapping scenarios based on user behavior characteristics and load fluctuation patterns. The three categories of charging and swapping loads are: home charging piles, public charging piles, and battery swapping stations. The three categories of charging and swapping scenarios are: residential areas, commercial areas, and highway service areas. The load type can be determined based on the geographical location and load characteristics of the charging and swapping load, such as by determining whether it is a home charging pile or a public charging pile based on charging time, number of charging sessions, and number of users. A specific example of the criteria for determining the scenario type is described below.

[0053] Residential areas: The core users are residents, and the typical load characteristics are "high at night and low during the day". The peak period is from 18:00 to 8:00 the next day, and the off-peak period is from 8:00 to 18:00. The equipment is mainly slow charging piles (accounting for ≥70%), and the average charging time for users is more than 4 hours.

[0054] Commercial area: The core users are commercial pedestrians (shopping and office workers). The typical load characteristics are "high during the day and low at night". The peak period is 10:00-20:00 and the off-peak period is 20:00-10:00 the next day. The equipment is mainly fast charging piles (accounting for ≥90%) or battery swapping stations. The average charging time for users is 0.5-1.5 hours.

[0055] Highway service areas: The core users are long-distance drivers. The typical load characteristics are "high on holidays and low on non-holidays". The peak period is from 9:00 to 18:00 on statutory holidays, and the off-peak period is all day on non-holidays. The equipment is mainly ultra-fast charging piles (accounting for 100%) or battery swapping stations. The average charging time for users is 0.3-1 hour.

[0056] After classifying all charging and swapping loads by load type and scenario type, each charging and swapping load can be tagged by its load type and scenario type. Then, when selecting charging and swapping loads, two charging and swapping loads of different load types can be selected from the same scenario type. For example, two loads tagged as residential home charging piles, public charging piles, and swapping stations can be selected, or public charging piles and swapping stations tagged as commercial areas, or public charging piles and swapping stations in highway service areas can be selected.

[0057] Since charging and swapping loads located in the same scenario type are relatively close to each other, and different load types are more likely to have high complementarity scores due to their different spatiotemporal characteristics, by pre-determining the scenario type and load type of the charging and swapping loads, and selectively choosing different composite types of charging and swapping loads from the same scenario type, the complementarity potential can be evaluated from the perspective of the energy replenishment scenario. This allows for faster identification of charging and swapping loads with high complementarity potential, avoids traversing the search process and affecting the evaluation efficiency of the method, and achieves efficient and rapid evaluation of the complementarity potential of charging and swapping loads.

[0058] In one possible implementation, the step of "determining the adjustable capacity of the two charging and swapping loads for at least one time period in the future" further includes: if the charging and swapping load is a charging pile, then based on the load prediction model, predicting the maximum and minimum adjustable power for multiple time periods in the future, and generating a charging adjustable capacity curve; if the charging and swapping load is a swapping station, then based on the order prediction model, predicting the maximum and minimum adjustable power for multiple time periods in the future, and generating a swapping adjustable capacity curve.

[0059] Specifically, if it is necessary to predict the load of charging piles or the orders of battery swapping stations, it is necessary to train the prediction model using historical data. In this application, the following historical data for the past three months can be collected in advance for the three types of charging and swapping loads and the three types of charging and swapping scenarios.

[0060] Charging and battery swapping load data: The charging power and charging amount of the charging piles are collected every 15 minutes, and a time-series load curve is generated. The battery swapping amount and number of swaps are collected for each battery swapping session.

[0061] User behavior data: user charging time preferences, charging duration, charging frequency, battery swapping needs, and battery swapping frequency (obtained through charging / swapping apps or charging / swapping devices).

[0062] Grid-related data: electricity consumption type, rated power of charging and swapping equipment, idle capacity, rated capacity of the distribution network to which the scenario belongs, output data of supporting photovoltaic power generation, and charging and discharging data of energy storage.

[0063] For charging piles, a load forecasting model can be used to predict the charging power for multiple future time periods. The maximum adjustable power for each time period is defined as the corresponding charging power, and the minimum adjustable power is defined as 0. Based on the difference between the maximum and minimum adjustable power for each time period, a charging adjustability curve is generated. For example, after obtaining the above data, a CRNN model is trained using the charging pile-related data to form a load forecasting model. Then, based on this load forecasting model, the charging power for multiple future time periods can be predicted. If the predicted charging power for a certain time period is P, then the maximum adjustable power P for that time period is determined. max =P, minimum adjustable power P min =0. Then, based on the difference between the maximum and minimum adjustable power in each time period (P... max -P min This generates the adjustable capability curve of the charging station.

[0064] For battery swapping stations, an order prediction model can be used to predict the number of orders in multiple future time periods. Based on the number of orders in each time period, the power required to charge the batteries corresponding to the number of orders is calculated as the minimum adjustable power for that time period. The power required to charge all batteries is calculated as the maximum adjustable power for that time period. Based on the difference between the maximum and minimum adjustable power for each time period, a battery swapping adjustability curve is generated. For example, after obtaining the above data, a CRNN model is trained using the data related to battery swapping stations to form an order prediction model. Then, based on this order prediction model, the number of orders in multiple future time periods can be predicted. If the number of orders in a certain time period is predicted to be 'a', then the electricity required to complete these orders can be calculated based on this number of orders 'a', for example, using a formula... To calculate the minimum charging capacity, and then use the formula Calculate the minimum adjustable power. Where E chg1 This is the minimum charging capacity, where SOC i Let C be the state of charge of the i-th battery in the battery array, sorted from highest to lowest remaining charge, from the first to the a-th battery. 额定 Let η be the battery's rated capacity, η be the charging efficiency, and t be the current time period. The maximum adjustable power corresponds to the power required to fully charge all batteries, for example, using the formula... Calculate the maximum charging capacity, then use the formula Calculate the maximum adjustable power, where E chg1 The minimum charging capacity is given by 'b', where 'b' represents the total number of batteries currently at the battery swapping station. Other letters have the same meaning as above. After calculating the maximum and minimum adjustable power for each time period, the difference between the maximum and minimum adjustable power for each time period (P) is used as the basis for the calculation. max -P min This generates the adjustable capacity curve for the battery swapping station.

[0065] Of course, the above method for calculating the maximum and minimum adjustable power of charging piles and battery swapping stations is merely an example, and those skilled in the art can make adjustments as long as the adjustability of the charging piles and battery swapping stations can be effectively calculated. For example, those skilled in the art can choose any other commonly used algorithm model in the field to predict load and orders. Furthermore, the minimum adjustable power of the charging pile can also be set with a lower limit based on user experience. Also, the batteries in the battery swapping stations are described using a fully charged battery as an example, merely for the purpose of illustrating the principle of this solution; the actual situation is not limited to this, and those skilled in the art can set the target SOC of the batteries requiring charging based on actual conditions.

[0066] In one possible implementation, the step of "calculating the complementarity score of the two charging and swapping loads based on their adjustable capabilities" further includes: superimposing the charging adjustable capability curve and the swapping adjustable capability curve; calculating the horizontal complementarity and vertical complementarity based on the superimposed curve; and calculating the complementarity score based on the horizontal complementarity and vertical complementarity.

[0067] Specifically, the step of "calculating the horizontal complementarity based on the superimposed curves" further includes: calculating the horizontal complementarity using the following formula: Among them, C A Horizontal complementarity; T is the number of time periods; n is the number of loads participating in the overlay; P txLet t be the adjustable capacity of the charging / swapping load x during time period t. In this application, horizontal complementarity refers to the ratio of the average sum of the adjustable capacities of different devices at each time to the maximum value of the adjustable capacities of different devices at each time. It reflects the smoothness of the overall new adjustable capacity curve after superimposing the adjustable capacity curves of different loads. In other words, the smoother the overall adjustable capacity curve after superposition, the more complementary the two charging / swapping loads are. For example, in an ideal case, the high adjustable capacity of the adjustable capacity curve of the first load corresponds to the low adjustable capacity of the adjustable capacity curve of the second load. This proves that the excess capacity of the first load can be dispatched to the second load.

[0068] The step of "calculating the vertical complementarity based on the superimposed curves" further includes: calculating the vertical complementarity using the following formula: Among them, C F The vertical complementarity is represented by n; the number of loads participating in the superposition is represented by P. tx Let t represent the adjustable capacity of the charging / swapping load x during time period t. In this application, to represent the extreme value difference of the new adjustable capacity curve after superimposing the adjustable capacity curves of different charging / swapping loads, the concept of vertical complementarity is introduced. Vertical complementarity refers to the ratio of the minimum value of the sum of the adjustable capacities of different charging / swapping loads at each time to the maximum value of the sum of the adjustable capacities of different charging / swapping loads at each time. It reflects the magnitude of the peak-to-valley difference of the new load curve after superimposing the adjustable capacity curves of different charging / swapping loads. In other words, the smaller the peak-to-valley difference of the new load curve after superposition, the more complementary the two charging / swapping loads are. For example, in an ideal situation, the smaller the peak-to-valley difference after superimposing the adjustable capacity curves of two charging / swapping loads, the more capacity one charging / swapping load supplements for the other.

[0069] After calculating the horizontal and vertical complementarity, a complementarity score is calculated based on these scores. Specifically, this can be achieved using the formula... To calculate the complementarity score, where C com The complementarity score is calculated. Alternatively, horizontal and vertical complementarity can be added together, but the difference in results is less pronounced than with the method described above.

[0070] By superimposing the curves to calculate the horizontal and vertical complementarity, and then calculating the complementarity score, the complementarity between charging and swapping loads can be evaluated from different dimensions, thus improving the accuracy of complementarity calculation.

[0071] In one possible implementation, the step of "calculating a distance score based on the distance between two charging / swapping loads" further includes: calculating the Euclidean distance between the two charging / swapping loads and normalizing it to obtain the distance score. Specifically, before applying this evaluation method, the geographical location information of each charging / swapping load is collected and recorded in advance. Then, by calculating the Euclidean distance between the two selected charging / swapping loads and normalizing it, the distance score can be obtained. For example, the Euclidean distance d between the two charging / swapping loads can be calculated and normalized to the range [0,1] to obtain d. norm Then calculate the distance score as D. com =1-d norm , where D com This is used to obtain the distance score. Alternatively, one can calculate the Euclidean distance *d* between the two charging / swapping loads, take the reciprocal of the Euclidean distance (1 / d), and then normalize this value to obtain the distance score *D*. com Of course, since the location of the charging and swapping loads is unlikely to change, the distance scores between each charging and swapping load can be calculated in advance and stored for later use.

[0072] In one possible implementation, the step of "calculating the comprehensive score of complementary scheduling potential between two charging / swapping loads based on complementarity score and distance score" further includes: calculating the comprehensive score of complementary scheduling potential using the following formula: Where S is the comprehensive score of complementary scheduling potential; C com The complementarity score; D com The distance score is represented by α; the adjustability matching weight is represented by β; and the load coverage duration weight is represented by α+β=1. Specifically, after calculating the complementarity score and the distance score, different weights are assigned to them based on operational needs, and a comprehensive score for complementary scheduling potential that takes into account both complementarity and distance dimensions can be calculated.

[0073] After calculating the comprehensive score of complementary scheduling potential among different charging and swapping loads under the three scenario types using the method described above, this comprehensive score can be used to guide capacity scheduling among charging and swapping loads. For example, when a charging or swapping load has a response demand, resources with high complementarity, i.e., high comprehensive score of complementary potential, are prioritized. If the capacity of that resource is insufficient, the next resource is then called according to the same standard. Furthermore, when a charging or swapping load fails, other charging or swapping loads with high complementarity can provide timely power support, effectively reducing the risk of power outages, improving the aggregation efficiency of charging and swapping loads, and enhancing the resilience of the entire system.

[0074] In summary, the charging and swapping load complementarity potential assessment method of this application, based on fully considering the spatiotemporal complementarity characteristics of charging and swapping loads, assesses the adjustability of charging and swapping loads, constructs a complementarity assessment matrix using adjustability and site physical distance, and calculates a comprehensive score of complementary scheduling potential based on the complementarity assessment matrix. This can guide the platform to aggregate and schedule charging and swapping loads, achieving the following effects.

[0075] 1. Improve the utilization rate of charging and battery swapping resources to solve the problem of "coexistence of idle and scarce resources". By classifying scenarios (residential areas / commercial areas / highway service areas) and matching peak and valley differences, guide the allocation of idle charging resources during off-peak hours in communities to peak hours during the daytime in commercial areas, thereby improving the overall utilization rate of charging and battery swapping equipment in the region.

[0076] 2. Guide the optimization of energy resources to avoid "peak-hour power rush and off-peak waste" in a single scenario. Transfer idle electricity in highway service areas during non-holiday periods to community nighttime charging peaks to reduce redundant power supply in the power grid and reduce the energy waste rate of charging and swapping in the region.

[0077] 3. Optimize charging and battery swapping operation strategies, reduce operating costs, and evaluate the priority of output solutions in a tiered manner (sorted by score). This can directly guide operators to "first allocate high-adaptability scenarios and then handle low-adaptability scenarios", avoiding blind scheduling and improving scheduling efficiency.

[0078] This application also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to this application, the computer-readable storage medium can be configured to store a program that performs the charging / swapping load complementarity potential assessment method of the above-described method embodiments. This program can be loaded and run by a processor to implement the above-described charging / swapping load complementarity potential assessment method. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The computer-readable storage medium can be a storage device device comprising various electronic devices. Optionally, in the embodiments of the present invention, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0079] This application also provides a control device. In one embodiment of the control device according to this application, the control device includes a processor and a memory. The memory can be configured to store a program for executing the charging / swapping load complementarity potential assessment method of the above-described method embodiments. The processor can be configured to execute the program in the memory, which includes, but is not limited to, a program for executing the charging / swapping load complementarity potential assessment method of the above-described method embodiments. For ease of explanation, only the parts related to the embodiments of the present invention are shown. For specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The control device can be a device comprising various electronic devices.

[0080] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the server or client according to the embodiments of this application. This application can also be implemented as a device or apparatus program (e.g., a PC program and PC program products) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a PC-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0081] Although the steps in the above embodiments are described in the above sequence, those skilled in the art will understand that, in order to achieve the effect of this embodiment, different steps do not necessarily need to be executed in this order. They can be executed simultaneously (in parallel) or in reverse order, and these simple variations are all within the scope of protection of this application. For example, if the adjustable capacity is determined by the charging and swapping load itself, steps S101 and S103 can be swapped. That is, each charging and swapping load uploads its determined adjustable capacity to the virtual power plant, and then the virtual power plant selects two charging and swapping loads to calculate the complementarity score. Similarly, steps S105 and S107 can also be swapped or executed in parallel. That is, the logic for calculating the complementarity score of two charging and swapping loads and the logic for calculating the distance score between two charging and swapping loads are not strictly combined into a single order.

[0082] Those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, any of the claimed embodiments in the claims of this application can be used in any combination.

[0083] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.

Claims

1. A method for evaluating the complementary potential of charging and swapping loads, characterized in that, This method is applicable to multiple charging and swapping loads connected under the same power distribution network, wherein the charging and swapping loads are at least one of charging piles and battery swapping stations. The evaluation method includes: Select two charging / swapping loads from a pool of charging / swapping loads; Determine the adjustability of each of the two charging / swapping loads for at least one time period in the future; Based on the adjustability of the two charging and swapping loads, the complementarity score between them is calculated. A distance score is determined based on the distance between the two charging / swapping loads; Based on the complementarity score and the distance score, a comprehensive score of complementary scheduling potential between the two charging and swapping loads is calculated.

2. The method for assessing the complementary potential of charging and swapping loads according to claim 1, characterized in that, The step of "selecting two charging / swapping loads from multiple charging / swapping loads" further includes: From multiple charging and swapping loads located in the same scenario type, select two charging and swapping loads with different load types; Among them, the scenario type and load type of charging and swapping load are predetermined based on the user characteristics and load characteristics of the charging and swapping load.

3. The method for evaluating the complementary potential of charging and swapping loads according to claim 2, characterized in that, The scenario types include residential areas, commercial areas, and highway service areas; and / or the load types include home charging piles, public charging piles, and battery swapping stations.

4. The method for assessing the complementary potential of charging and swapping loads according to claim 1, characterized in that, The step of "determining the adjustability of the two charging / swapping loads for at least one time period in the future" further includes: If the charging and swapping load is a charging pile, then based on the load prediction model, the maximum and minimum adjustable power for multiple future time periods are predicted, and a charging adjustable capacity curve is generated. If the charging and swapping load is a battery swapping station, then based on the order prediction model, the maximum and minimum adjustable power for multiple future time periods are predicted, and a battery swapping adjustable capacity curve is generated.

5. The method for evaluating the complementary potential of charging and swapping loads according to claim 4, characterized in that, The step of "predicting the maximum and minimum adjustable power for at least one future time period based on a load forecasting model and generating a charging adjustability curve" further includes: Based on the load forecasting model, the charging power is predicted for multiple future time periods; The maximum adjustable power for each time period is defined as the charging power corresponding to that time period, and the minimum adjustable power is defined as 0. A charging adjustability curve is generated based on the difference between the maximum and minimum adjustable power for each time period.

6. The method for evaluating the complementary potential of charging and swapping loads according to claim 4, characterized in that, The step of "predicting the maximum and minimum adjustable power for at least one future time period based on an order forecasting model and generating a charging adjustability curve" further includes: Based on the order forecasting model, the number of orders in multiple future time periods is predicted; Based on the number of orders in each time period, the power required to charge the battery corresponding to the number of orders completed is calculated as the minimum adjustable power for that time period. The power required to complete charging of all batteries is calculated as the maximum adjustable power for that period. Based on the difference between the maximum and minimum adjustable power in each time period, a battery swapping adjustable capability curve is generated.

7. The method for evaluating the complementary potential of charging and swapping loads according to claim 4, characterized in that, The step of "calculating the complementarity score between the two charging and swapping loads based on their adjustability" further includes: Superimpose the adjustable charging capability curve and the adjustable battery swapping capability curve; Based on the superimposed curves, the horizontal complementarity and vertical complementarity are calculated. Complementarity scores are calculated based on horizontal and vertical complementarity.

8. The method for evaluating the complementary potential of charging and swapping loads according to claim 7, characterized in that, The step of "calculating the horizontal complementarity based on the superimposed curves" further includes: Horizontal complementarity is calculated using the following formula: Among them, C A Horizontal complementarity; T is the number of time periods; n is the number of loads participating in the overlay; P tx The adjustable capacity of the charging and swapping load x during time period t.

9. The method for assessing the complementary potential of charging and swapping loads according to claim 7, characterized in that, The step of "calculating the vertical complementarity based on the superimposed curves" further includes: Vertical complementarity is calculated using the following formula: Among them, C F The vertical complementarity is represented by n; the number of loads participating in the superposition is represented by P. tx The adjustable capacity of the charging and swapping load x during time period t.

10. The method for assessing the complementary potential of charging and swapping loads according to claim 1, characterized in that, The step of "calculating the distance score based on the distance between two charging / swapping loads" further includes: Calculate the Euclidean distance between the two charging / swapping loads and normalize it to obtain the distance score.

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