Charging and discharging scheduling method and device, storage medium, product and computer equipment

Abstract

The invention relates to a charging and discharging scheduling method and device, a storage medium, a product and computer equipment, and the method comprises the steps: obtaining the charging and discharging scheduling related data of each electric device in an electric device cluster of a charging station under the condition that a charging and discharging scheduling related state updating event is detected; and based on the charging and discharging scheduling associated data, updating a scheduling plan of the electric equipment cluster so as to perform charging and discharging scheduling of the electric equipment cluster according to the updated scheduling plan. The state updating event is responded in real time, the scheduling plan of the electric equipment cluster is updated in combination with the charging and discharging scheduling associated data, and the charging and discharging scheduling associated data relates to the charging and discharging demand of the user, so that the charging and discharging change condition can be responded in real time, the personalized charging and discharging demand of the user can be met, the real-time performance of charging and discharging scheduling is improved, and the user experience is improved. And meanwhile, personalized requirements of users are met.

Description

Technical Field

[0001] This application relates to the field of charging technologies, and in particular, to a charging and discharging scheduling method, device, storage medium, product, and computer device. Background Art

[0002] Currently, the electrification process of road traffic has driven the rapid development of the electric vehicle industry. The large-scale random charging load of electric vehicles has brought significant challenges to the stable operation of the power system. Moreover, since the time distribution of electric vehicle charging behavior is similar to the distribution law of the basic power consumption load of the power grid, it is easy to cause phenomena such as "peak on peak" of the power grid load and voltage instability.

[0003] In related technologies, through vehicle-grid interaction technologies such as orderly charging and orderly bi-directional charging and discharging, by means of peak shaving and valley filling, the charging time and power of electric vehicles are adjusted, and even the power is output in the reverse direction to transfer the peak-time charging load, which can effectively reduce the charging cost, improve the operation revenue of the charging station, and the stability of the power grid. However, in actual charging and discharging scenarios, situations where the charging and discharging process of electric vehicles undergoes unnatural changes occur frequently, such as charging pile failures, inconsistencies in the states of each vehicle and the wishes of each vehicle owner in an electric vehicle cluster, as well as leaving unexpectedly midway, changing charging requirements, etc., which exacerbate the complexity of the charging and discharging scheduling of the electric device cluster. The existing vehicle-grid interaction technologies such as orderly charging and orderly bi-directional charging and discharging are difficult to respond to charging and discharging change situations in real time and meet the personalized charging and discharging needs of users. Summary of the Invention

[0004] Embodiments of this application provide a charging and discharging scheduling method, device, storage medium, product, and computer device, which can solve the technical problems that related technologies are difficult to meet the personalized charging and discharging needs of users and the real-time responsiveness, and at least partially solve the above technical problems.

[0005] To achieve the above object, according to the first aspect of this application, a charging and discharging scheduling method is provided. The method includes:

[0006] When a charging and discharging scheduling associated state update event is detected, obtain the charging and discharging scheduling associated data of each electric device in the electric device cluster of the charging station;

[0007] Based on the charging and discharging scheduling associated data, update the scheduling plan of the electric device cluster, and perform charging and discharging scheduling of the electric device cluster according to the updated scheduling plan.

[0008] According to the second aspect of this application, a charging and discharging scheduling device is provided. The device includes:

[0009] An acquisition module, configured to acquire the charge-discharge scheduling association data of each electric device in the electric device cluster of the charging station when detecting a charge-discharge scheduling association status update event;

[0010] A scheduling module, configured to update the scheduling plan of the electric device cluster based on the charge-discharge scheduling association data, so as to perform the charge-discharge scheduling of the electric device cluster according to the updated scheduling plan.

[0011] According to the third aspect of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned charge-discharge scheduling method is implemented.

[0012] According to the fourth aspect of the present application, there is provided a computer program product, including a computer program, and when the computer program is executed by a processor, the above-mentioned charge-discharge scheduling method is implemented.

[0013] According to the fifth aspect of the present application, there is provided a computer device, including a processor and a memory, where the memory stores multiple instructions; the processor loads the instructions from the memory to execute the steps of the charge-discharge scheduling method as described in the first aspect.

[0014] In the charge-discharge scheduling method, device, storage medium, product and computer device according to the embodiments of the present application, when detecting a charge-discharge scheduling association status update event, the charge-discharge scheduling association data of each electric device in the electric device cluster of the charging station is acquired; based on the charge-discharge scheduling association data, the scheduling plan of the electric device cluster is updated, so as to perform the charge-discharge scheduling of the electric device cluster according to the updated scheduling plan. Since it responds to the status update event in real time and updates the scheduling plan of the electric device cluster in combination with the charge-discharge scheduling association data, and the charge-discharge scheduling association data involves the user's charge-discharge requirements, therefore, it can respond to the charge-discharge change situation in real time, meet the user's personalized charge-discharge requirements, improve the real-time performance of the charge-discharge scheduling, and meet the user's personalized needs at the same time.

[0015] Other features and advantages of the present application will be described in detail in the subsequent specific implementation part. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application, and those skilled in the art can obtain other drawings without creative efforts based on these drawings.

[0017] To more fully understand the present application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings, where the same reference numerals in the following description represent the same parts.

[0018] Figure 1 is a schematic flowchart of a charge and discharge scheduling method provided in some embodiments of the present application;

[0019] Figure 2 is a schematic structural diagram of a charge and discharge scheduling system provided in some embodiments of the present application;

[0020] Figure 3 is a flowchart of charge and discharge scheduling provided in some embodiments of the present application;

[0021] Figure 4 is a schematic diagram of a charge and discharge scheduling process provided in some embodiments of the present application;

[0022] Figure 5 is a schematic diagram of an updated scheduling plan when the available capacity of a charging station meets the charging demand provided in some other embodiments of the present application;

[0023] Figure 6 is a schematic diagram of an updated scheduling plan when the available capacity of a charging station does not meet the charging demand provided in some embodiments of the present application;

[0024] Figure 7 is a schematic structural diagram of a charge and discharge scheduling device provided in some embodiments of the present application;

[0025] Figure 8 is a schematic structural diagram of a computer device provided in some embodiments of the present application. Detailed Embodiments

[0026] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present application.

[0027] In the description of the present application, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more features. In the description of the present application, "a plurality" means two or more, unless otherwise specifically defined.

[0028] In the description of the present application, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described in the present application as "for example" is not necessarily to be construed as more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not elaborated in detail so as not to obscure the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed in the present application.

[0029] An embodiment of the present application provides a charging and discharging scheduling method. When a charging and discharging scheduling associated state update event is detected, charging and discharging scheduling associated data of each electric device in the electric device cluster of a charging station is acquired; based on the charging and discharging scheduling associated data, the scheduling plan of the electric device cluster is updated, so as to perform charging and discharging scheduling of the electric device cluster according to the updated scheduling plan. Since it responds to the state update event in real time and combines the charging and discharging scheduling associated data to update the scheduling plan of the electric device cluster, and the charging and discharging scheduling associated data involves the charging and discharging demands of users, therefore, it can respond to charging and discharging change situations in real time, meet the personalized charging and discharging demands of users, improve the real-time performance of charging and discharging scheduling, and meet the personalized demands of users at the same time.

[0030] Please refer to Figure 1 , a charging and discharging scheduling method is provided, and this method is applied to a computer device. Among them, the computer device may be a terminal device or a server. The method includes:

[0031] Step S101, when a charging and discharging scheduling associated state update event is detected, acquire charging and discharging scheduling associated data of each electric device in the electric device cluster of a charging station.

[0032] Among them, the electric device in this embodiment refers to a device that needs to be charged and discharged, such as an electric vehicle. The electric device cluster refers to the set of all electric devices connected to the charging piles in the charging station.

[0033] A state update event is an event that occurs when there is an unnatural change during the charging and discharging process of an electric vehicle in the charging and discharging scheduling scenario of the vehicle. For example, changes in the user's charging and discharging requirements (such as the user changing the charging and discharging mode, the expected departure time for charging and discharging, etc.), changes in the charging station (such as charging pile failures, recoveries, changes in the number of charging and discharging vehicles), the current moment reaching the preset scheduling plan change moment, changes in the distribution network, etc. The state update event can be detected according to the change situation of the input parameters of the computer device, and the change situation of the input parameters can be that the current moment reaches the preset update duration, the user demand changes, the charging mode changes from unordered charging (V0G) to ordered charging (V1G), etc.

[0034] The charging and discharging scheduling related data refers to the data related to the charging and discharging scheduling and affecting the charging and discharging decision-making during the charging and discharging scheduling process of an electric device cluster, such as data representing the user's personalized charging and discharging requirements (such as the charging mode selected by the user, the expected SOC, the expected departure time, etc.), and data representing the state of the electric device (such as the SOC value of the electric device at the current moment, the battery power, the charged time, etc.).

[0035] Specifically, the computer device can detect whether a state update event is triggered through a timing detection mechanism and real-time event listening. When a state update event is detected, it obtains the charging and discharging scheduling related data of each electric device in the electric device cluster of the charging station, so as to subsequently update the charging and discharging scheduling plan of the electric device cluster in real time based on the charging and discharging scheduling related data to meet the user's personalized charging and discharging requirements. At the same time, real-time response to the state update event realizes the real-time scheduling of charging and discharging.

[0036] In some embodiments, the state update event includes at least one of reaching the scheduling plan update moment, change in the number of the electric device cluster, change in the state of the electric device, change in the state of the charging pile, response to the grid output adjustment requirement, and change in the user's charging and discharging requirement.

[0037] Among them, reaching the scheduling plan update moment means whether the current moment reaches the moment when the scheduling plan needs to be updated, and it can be judged whether the scheduling plan update moment is reached through a timing detection mechanism, such as through a timing task (such as detecting once every 5 minutes).

[0038] The change in the number of the electric device cluster can be updated by listening to events, such as listening to the electric device access or departure events.

[0039] The change in the state of the electric device can detect the charge and discharge state change event through the state of the electric device.

[0040] The change in the state of the charging pile can detect the fault event or the fault recovery event through the charging pile.

[0041] In response to the grid output adjustment requirements, it is possible to listen to the grid commands and respond to the requirements of grid peak shaving, frequency modulation, or phase modulation.

[0042] The change in the user's charging and discharging requirements can be obtained by listening to the user's operations and acquiring change events such as the change in the charging and discharging mode, the expected state of charge (SOC), and the predicted departure time.

[0043] The condition judgment of the status update event can be that any of the above situations occurs, triggering the status update event.

[0044] In some embodiments, the charging and discharging scheduling associated data includes at least one of the status data of the electric device and the corresponding user charging and discharging requirement data.

[0045] Among them, the status data can be data representing the status of the electric device (such as the SOC value, battery power, and charged time of the electric device at the current moment), and the user charging and discharging requirement data can be data representing the user's personalized charging and discharging requirements (such as the charging mode selected by the user, the expected SOC, the expected departure time, etc., the subscription mode of the charging and discharging scheduling, the charging and discharging scheduling charging mode, etc.).

[0046] Step S102: Based on the charging and discharging scheduling associated data, update the scheduling plan of the electric device cluster, and perform the charging and discharging scheduling of the electric device cluster according to the updated scheduling plan.

[0047] Among them, the scheduling plan is the original scheduling plan before the original trigger of the status update event, which can be data of a changeable and extensible type stored in the charging and discharging management platform, including the electric device ID, the vehicle charging and discharging commands at time t and subsequent times (such as vehicle scheduling commands, vehicle charging and discharging power values). The original scheduling plan can be determined through a scheduling model.

[0048] Specifically, after obtaining the charging and discharging scheduling associated data, the scheduling plan can be updated according to the charging and discharging scheduling associated data to obtain the updated scheduling plan. It can be understood that since the updated scheduling plan is determined according to the charging and discharging scheduling associated data, the updated scheduling plan has a strong correlation with the charging and discharging scheduling associated data. Scheduling the electric device cluster according to the updated scheduling plan can meet the user's personalized charging requirements and improve the user's satisfaction with charging and discharging.

[0049] In a specific embodiment, as Figure 2 shown, it is a schematic structural diagram of a charging and discharging scheduling system. The electric device is illustrated by taking an electric vehicle as an example.

[0050] The charge and discharge scheduling system includes a charging station management platform 100, a data input terminal 200, and an execution terminal device 300. The charging station management platform 100 includes, but is not limited to, an algorithm scheduling module, a data receiving module, an instruction issuing module, and a data storage module. The data input terminal 200 includes, but is not limited to, a user application terminal, a vehicle-mounted terminal, and a charging pile panel terminal, and is used to obtain charge and discharge scheduling related data. The execution terminal device 300 includes, but is not limited to, a smart meter, a communication device, and a smart charging pile, and is used for operations such as real-time monitoring, status reporting, and instruction execution, so as to realize the charge and discharge scheduling of an electric device cluster.

[0051] In another specific embodiment, as Figure 3 shown, it is a flowchart of charge and discharge scheduling by the Figure 2 charge and discharge scheduling system therein. Taking an electric vehicle as an example for the electric device, the process includes the steps:

[0052] Step S201: The charging station management platform determines whether a status update event is triggered at time t. If triggered, the subsequent steps S203 - S205 are executed; if not triggered, step S202 is executed;

[0053] Step S202: If the status update event is not triggered, directly read the original scheduling plan stored in the charging station management platform. The charging station management platform issues the vehicle charge and discharge instructions at time t in the scheduling plan, and the electric device cluster executes their respective instructions. The cycle time t = t + Δt, where the cycle time increment Δt is the vehicle scheduling accuracy and its value is a value set by the algorithm. Return to step S201;

[0054] Step S203: After the status update event is triggered, read the owner's selection (user charge and discharge demand data) and vehicle data (status data). The owner's selection is uploaded from the data input terminal 20 to the charging station management platform 10, supporting data change and real-time upload, including but not limited to the selection of charging piles, vehicle charge and discharge modes, expected departure time, expected SOC value, minimum discharge SOC value of the battery, etc., as well as the selection of vehicle charge and discharge scheduling modes such as subscription mode and charging mode; according to the vehicle charge and discharge mode selected by the owner, divide the electric device cluster into different components such as unordered charging (V0G), ordered charging (V1G), and ordered bidirectional charge and discharge (V2G), establish a charge and discharge scheduling model of the electric device cluster at the current time t, and use the scheduling algorithm of the charge and discharge scheduling model to calculate the scheduling plan of the electric device cluster in the charging station at the current time t;

[0055] Step S204: Use the scheduling plan at time t calculated in step S203 as the new vehicle scheduling plan, update and store it in the charging station management platform to replace the original scheduling plan;

[0056] Step S205: The charging station management platform issues the charging and discharging instructions for the vehicle at time t in the vehicle scheduling plan, and the electric device cluster executes its respective instructions. The cycle time t = t + Δt, and return to step S201.

[0057] It can be understood that in the above charging and discharging scheduling process, the real-time scheduling of the charging and discharging of the electric device cluster triggered by the state update event takes into account the input parameter changes such as the fixed update duration of the arrival algorithm, the change in the number of electric vehicles in the charging station, the charging pile failure, the response to the power grid peak shaving and frequency modulation requirements, and the change in the owner's selection. By continuously optimizing and updating the scheduling plan of the electric vehicle cluster, the optimal allocation of the charging and discharging power of the electric device cluster at each moment can be achieved.

[0058] In some embodiments, updating the scheduling plan of the electric device cluster based on the charging and discharging scheduling associated data includes: constructing a cluster charging and discharging scheduling model based on the state data of the electric devices and the corresponding user charging and discharging demand data; and updating the scheduling plan of the electric device cluster according to the cluster charging and discharging scheduling model.

[0059] Among them, the cluster charging and discharging scheduling model is a scheduling model for overall optimization of the charging and discharging scheduling of the electric device cluster. It can be a revenue model representing the charging and discharging revenue of the electric device cluster, a charging and discharging amount model representing the charging and discharging amount of the electric device cluster, or a combination of the revenue model and the charging and discharging amount model.

[0060] The cluster charging and discharging scheduling model can be constructed according to the state data of each electric device in the electric device cluster and the corresponding user charging and discharging demand data according to the overall optimization goal.

[0061] Specifically, a cluster charging and discharging scheduling model can be constructed based on the state data of the electric devices and the corresponding user charging and discharging demand data, and the scheduling plan corresponding to the cluster charging and discharging scheduling model can be solved, that is, the charging and discharging power at each moment. The solved scheduling plan is used as the updated scheduling plan to realize the update of the scheduling plan. It can be understood that in this embodiment, by obtaining the state data of the electric devices and the user charging and discharging demand data in real time, the constructed cluster charging and discharging scheduling model can quickly respond to changes and generate an optimized charging and discharging scheduling plan. And constructing the cluster charging and discharging scheduling model according to the user charging and discharging demand data can ensure that the updated scheduling plan can meet the user's personalized charging and discharging needs.

[0062] In some embodiments, the cluster charge and discharge scheduling model includes a first scheduling model; constructing the cluster charge and discharge scheduling model based on the status data of the electric devices and the corresponding user charge and discharge demand data includes: determining a first objective expression according to the charge and discharge costs and battery discharge loss costs of each electric device in the electric device cluster within a preset scheduling period; determining a first constraint condition based on the status data of the electric devices and the corresponding user charge and discharge demand data, and the first scheduling model includes the first objective expression and the first constraint condition.

[0063] Among them, the first objective expression is the objective function corresponding to the first scheduling model, which can be determined according to the charge and discharge costs and battery discharge loss costs of each electric device in the electric device cluster within a preset scheduling period, and is used to characterize the charge and discharge benefits of the electric device cluster. In some embodiments, the first objective expression can be the sum of the electric device charge and discharge costs and the battery discharge loss costs. That is, the first objective expression is as shown in Equation (1):

[0064] f1 = Minimize (E ch + cost disch ); (1)

[0065] In Equation (1), f1 is the first objective expression, Minmize() represents minimization, and E ch is the charge and discharge cost of all electric devices in the electric device cluster within a preset scheduling period (such as T), and cost disch is the battery discharge loss cost of all electric devices in the electric device cluster within a preset scheduling period.

[0066] The first constraint condition is the constraint condition corresponding to the first scheduling model, which can be determined according to the status data of the electric devices and the corresponding user charge and discharge demand data.

[0067] Specifically, determine the first objective expression according to the charge and discharge costs and battery discharge loss costs of each electric device in the electric device cluster within a preset scheduling period. Determine the first constraint condition based on the status data of the electric devices and the corresponding user charge and discharge demand data, thereby constructing the first scheduling model as the cluster charge and discharge scheduling model. It can be understood that in this embodiment, by incorporating the charge and discharge costs and battery loss costs into the objective expression, the first scheduling model can comprehensively consider economic factors, optimize the scheduling plan to reduce the charge and discharge costs. At the same time, by considering the user charge and discharge demand data, the first scheduling model can ensure that the user's charge and discharge demands are met while reducing the user's charge and discharge costs.

[0068] In some embodiments, the charging and discharging cost is determined according to the charging power, the charging cost per unit of charge, the discharging power, and the discharging revenue per unit of discharge of each electric device in the electric device cluster at each moment within a preset scheduling period; the battery discharging loss cost is determined according to the battery capacity, the number of charge and discharge cycles, and the initial investment cost of the battery of each electric device in the electric device cluster at each moment within a preset scheduling period.

[0069] Specifically, the charging and discharging cost E ch can be determined according to the charging power, the charging cost per unit of charge, the discharging power, and the discharging revenue per unit of discharge of each electric device in the electric device cluster at each moment within a preset scheduling period, and can be determined by the following formula (2):

[0070]

[0071] In formula (2), N is the number of electric devices in the current electric device cluster in the charging station, T is the duration of the preset scheduling period, x ch (n, t) is the charging power of the nth electric device at moment t, x disch (n, t) is the discharging power of the nth electric device at moment t, e ch (t) is the charging cost of the electric device per unit of charge (such as per kWh) at moment t, e disch (t) is the discharging revenue of the electric device per unit of charge (per kWh) at moment t.

[0072] The battery discharging loss cost cost disch can be determined according to the battery capacity, the number of charge and discharge cycles, and the initial investment cost of the battery of each electric device in the electric device cluster at each moment within a preset scheduling period, and can be determined by the following formula (3):

[0073]

[0074] In formula (3), P(n) is the battery capacity of the nth electric device, T life (n) is the number of charge and discharge cycles of the nth electric device, C cap (n) is the initial investment cost of the battery of the nth electric device.

[0075] In some embodiments, determining the first constraint condition based on the status data of the electric device and the corresponding user charging and discharging demand data includes: determining the user charging demand constraint condition according to the updated duration of the scheduling plan, the charging power, the discharging power, the expected end SOC value in the user charging and discharging demand data, the start charging time in the status data, and the battery capacity; determining the vehicle charging and discharging constraint condition according to the charging power, the discharging power, the expected end charging time in the user charging and discharging demand data, the maximum charging power and the maximum discharging power in the status data; determining the SOC constraint condition according to the updated duration of the scheduling plan, the charging power, the discharging power, the minimum SOC value and the maximum SOC value in the user charging and discharging demand data, and the SOC value in the status data; determining the distribution network constraint condition according to the basic load of the charging station, the available capacity of the distribution network, the charging power and the discharging power, and the first constraint condition includes the user charging demand constraint condition, the vehicle charging and discharging constraint condition, the SOC constraint condition and the distribution network constraint condition.

[0076] Among them, the user charging demand constraint condition is determined according to the updated duration of the scheduling plan, the charging power, the discharging power, the expected end SOC value in the user charging and discharging demand data, the start charging time in the status data, and the battery capacity, and is represented by the following formula (4):

[0077]

[0078] In formula (4), SOC end (n) is the expected end SOC value of the nth electric device, and SOC start (n) is the start charging SOC value of the nth electric device; Δt is the updated duration of the scheduling plan.

[0079] The vehicle charging and discharging constraint condition can be determined according to the charging power, the discharging power, the expected end charging time in the user charging and discharging demand data, the maximum charging power and the maximum discharging power in the status data, and is represented by the following formula (5):

[0080]

[0081] In formula (5), T start (n) is the start charging time of the nth electric device, and T end (n) is the expected end charging time of the nth electric device, is the maximum charging power of the nth electric device; is the maximum discharging power of the nth electric device.

[0082] The SOC constraint conditions can be determined according to the minimum SOC value, maximum SOC value in the charging and discharging power, user charging and discharging demand data, and the SOC value in the status data during the update duration of the scheduling plan, and are expressed by the following formula (6):

[0083]

[0084] In formula (6), SOC(n,t) is the SOC value of the nth electric device at time t, SOC(n,t + Δt) is the SOC value of the nth electric device at time t + Δt, SOC Min (n) is the minimum SOC value set by the user of the nth electric device, SOC Max (n) is the maximum SOC value set by the user of the nth electric device, and the maximum SOC value is usually 1.

[0085] The distribution network constraint conditions can be determined according to the basic load of the charging station, the available capacity of the distribution network, the charging power and the discharging power, and are expressed by the following formula (7):

[0086]

[0087] In formula (7), p load (t) is the basic load of the charging station at time t, is the available capacity of the distribution network.

[0088] It should be noted that in the actual scenario of charging and discharging scheduling, when there is a limit condition that the surplus power cannot be fed into the grid, the corresponding distribution network constraint conditions also include a surplus power constraint condition, which is expressed by the following formula (8):

[0089]

[0090] Formula (8) means that if the total charging and discharging amount of the electric device cluster covers the basic load of the charging station, that is, there is surplus power, this surplus power cannot be used for feeding into the grid.

[0091] In some embodiments, updating the scheduling plan of the electric device cluster according to the cluster charging and discharging scheduling model includes: under the first constraint condition, with the minimum of the first scheduling model as the target, determining the first target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period; and updating the scheduling plan of the electric device cluster based on the first target charging and discharging power.

[0092] Among them, the first target charging and discharging power is the scheduling plan output by the first scheduling model. Based on the first target charging and discharging power, the scheduling plan of the electric device cluster can be updated, which can be taking the first target charging and discharging power at each moment within a preset scheduling period as the updated scheduling plan.

[0093] Specifically, under the first constraint condition, with the goal of minimizing the first scheduling model, determine the first target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period. Based on the first target charging and discharging power, update the scheduling plan of the electric device cluster, which can be taking the first target scheduling plan at each moment as the updated scheduling plan. It can be understood that in this embodiment, by minimizing the goal of the first scheduling model under the first constraint condition, the overall charging and discharging cost of the electric device cluster can be effectively reduced, and while ensuring the maximum benefit, it can ensure that the updated scheduling plan can respond to changes in input conditions in real time, improving the user's charging satisfaction.

[0094] In some embodiments, the step of determining the first target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period under the first constraint condition with the goal of minimizing the first scheduling model includes: under the first constraint condition, with the goal of minimizing the first target expression in the first scheduling model, solve the charging power and discharging power at each moment in the first target expression, and output the first target charging and discharging power of each electric device in the electric device cluster at each moment.

[0095] Specifically, it is possible to judge whether the available capacity of the charging station can meet the charging demand of the electric device cluster according to the power of the charging station and the charging and discharging power of the electric device cluster. When the available capacity of the charging station meets the charging demand of the electric device cluster, update the scheduling plan according to the first scheduling model, which can be under the first constraint condition, with the goal of minimizing the first target expression in the first scheduling model, solve the charging power and discharging power at each moment in the first target expression, and output the first target charging and discharging power of each electric device in the electric device cluster at each moment. That is, taking the above formulas (4)-(8) as constraint conditions, substituting formulas (2) and (3) into formula (1), and taking the minimum of f1 in formula (1) as the goal, using the sequential quadratic programming algorithm or an optimization solver to solve for x ch (n,t) and x disch (n,t) values, and output the first target charging and discharging power of each electric device in the electric device cluster at each moment (t moment). It can be understood that in this embodiment, not only cost minimization is considered, but also target optimization is carried out in combination with constraint conditions, further optimizing the charging and discharging scheduling plan.

[0096] In some embodiments, the cluster charging and discharging scheduling model further includes a second scheduling model; updating the scheduling plan of the electric device cluster based on the first target charging and discharging power includes: when the available capacity of the charging station does not meet the charging demand of the electric device cluster, based on the second scheduling model and the first target charging and discharging power, determining the second target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period; and updating the scheduling plan of the electric device cluster based on the second target charging and discharging power.

[0097] Wherein, the second target charging and discharging power is the result output by the second scheduling model in combination with the first scheduling model, and the output scheduling plan. Updating the scheduling plan of the electric device cluster based on the second target charging and discharging power may be taking the second target charging and discharging power at each moment within a preset scheduling period as the updated scheduling plan.

[0098] Wherein, when the available capacity of the charging station does not meet the charging demand of the electric device cluster, the cluster charging and discharging scheduling model further includes a second scheduling model, that is, adding a second scheduling model on the basis of the first scheduling model, that is, the cluster charging and discharging scheduling model includes the first scheduling model and the second scheduling model. The second scheduling model can reallocate the charging and discharging power of electric devices under resource constraints to preferentially meet the charging and discharging demands of key devices or users. This optimization not only improves the resource utilization efficiency but also reduces the waiting time of users due to insufficient resources.

[0099] Specifically, based on the second scheduling model and the first target charging and discharging power, determining the second target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period; and updating the scheduling plan of the electric device cluster based on the second target charging and discharging power. Since the second target charging and discharging power combines the first target charging and discharging power, it can ensure that the second target charging and discharging power can meet the cost minimization while also meeting the optimization goal of the second scheduling model, improving the accuracy and rationality of the allocation of the second target charging and discharging power.

[0100] In some embodiments, the second target expression corresponding to the second scheduling model includes the charging and discharging priority weights of each electric device in the electric device cluster, and the charging and discharging priority weights are determined according to the status data.

[0101] Wherein, the charging and discharging priority weight of an electric device represents the priority degree of charging or discharging of the corresponding electric device, including the charging priority weight and the discharging priority weight respectively. The corresponding charging and discharging priority weights can be determined according to their respective status data.

[0102] Specifically, the objective function corresponding to the second scheduling model is represented by a second objective expression, which at least includes the charging and discharging priority weights of each electric device in the electric device cluster. By assigning charging and discharging priority weights to the electric devices, the second scheduling model can perform personalized scheduling according to the current states of the electric devices (such as battery capacity, remaining power, charging demand, etc.). For example, for a device with low power and urgent charging needs, a higher charging priority can be assigned to ensure that it obtains charging resources first. At the same time, the charging and discharging priority weights are dynamically adjusted based on the state data, enabling the second scheduling model to respond in real time to changes in the states of the electric devices.

[0103] In some embodiments, the second objective expression is the sum of the products of the optimized charging power, optimized discharging power, and the corresponding charging and discharging priority weights of each electric device in the electric device cluster at each moment within a preset scheduling period.

[0104] Among them, the optimized charging power is the charging power of each electric device in the second scheduling model at each moment within a preset scheduling period, and the optimized discharging power is the discharging power of each electric device in the second scheduling model at each moment within a preset scheduling period. The second objective expression is represented by the following formula (9):

[0105]

[0106] In formula (9), f2 is the second objective expression, Maxmize() represents maximization, x' ch (n,t) is the optimized charging power of the nth electric device at time t, x′ disch (n, t) is the optimized discharging power of the nth electric device at time t, w' priority (n,t) is the charging priority weight of the nth electric device at time t, w″ priority (n,t) is the discharging priority weight of the nth electric device at time t. It can be understood that the second scheduling model includes charging and discharging priority weights, and the second objective expression of the second scheduling model is the maximization of the sum of the products of the charging and discharging priority weights and the charging and discharging powers, so as to obtain the result that "the higher the charging priority of an electric device, the greater its charging power; the higher the discharging priority of an electric device, the greater its discharging power". By maximizing the "sum of the products of the charging and discharging priority weights and the charging and discharging powers", it can achieve that "an electric device with a higher charging priority weight obtains a larger charging power instead of a smaller charging power", and can realize the charging of the electric device cluster in order and according to demand when the available capacity of the charging station is insufficient. And it can achieve the optimal distribution of charging and discharging powers at each moment, meeting the charging and discharging priority situations of the electric devices.

[0107] In some embodiments, the status data includes at least one of the battery power parameter, the SOC parameter, and the charging time parameter of the electric device; the step of determining the charge-discharge priority weight includes: determining the power priority index data according to the battery power parameter; and / or, determining the SOC priority index data according to the SOC parameter, and / or, determining the time priority index data according to the charging time parameter; determining the charge-discharge priority weight according to at least one of the power priority index data, the SOC priority index data, and the time priority index data.

[0108] Among them, the power priority index data includes the power charging priority index and the power discharging priority index respectively; similarly, the SOC priority index data includes the SOC charging priority index and the SOC discharging priority index respectively; the time priority index data includes the time charging priority index and the time discharging priority index respectively. The corresponding charging priority index and the corresponding discharging priority index are conflicting indicators, that is, the lower the priority corresponding to the charging priority index, the higher its discharging priority.

[0109] Specifically, taking the battery power parameter as the priority evaluation basis, the corresponding power priority index data includes the charged amount or the remaining amount to be charged. Based on the charged amount, the more the charged amount, the lower the power charging priority, and the higher its discharging priority, that is, the lower the corresponding charging priority weight and the higher the discharging priority weight. The charged amount in the power priority index data is represented by the following formula (11):

[0110]

[0111] In formula (11), P charging (n,t) is the charged amount of the nth electric device at time t.

[0112] Based on the remaining amount to be charged, the more the remaining amount to be charged, the higher the power charging priority, and the lower its discharging priority, that is, the higher the corresponding charging priority weight and the lower the discharging priority weight. The remaining amount to be charged in the power priority index data is represented by the following formula (12):

[0113] P need (n, t) = (SOC end (n) - SOC(n, t)).P(n); (12)

[0114] In formula (12), P need (n,t) is the remaining amount to be charged of the nth electric device at time t.

[0115] Taking the SOC parameter as the priority evaluation basis, the corresponding SOC priority index data includes the charged SOC or the remaining SOC to be charged. Based on the charged SOC, the more charged the SOC is, the lower the SOC charging priority, and the higher the discharge priority, that is, the lower the corresponding charging priority weight and the higher the discharge priority weight. The charged amount in the power priority index data is represented by the following formula (13):

[0116]

[0117] In formula (13), SOC charging (n,t) is the charged SOC value of the nth electric device at time t.

[0118] Based on the remaining SOC to be charged, the more remaining SOC to be charged, the higher the charging priority, and the lower the discharge priority, that is, the higher the corresponding charging priority weight and the lower the discharge priority weight. The remaining SOC to be charged in the SOC priority index data is represented by the following formula (14):

[0119] SOC need (n,t) = (SOC end (n) - SOC(n,t)); (14)

[0120] In formula (14), SOC need (n,t) is the remaining SOC to be charged of the nth electric device at time t.

[0121] Taking the charging time parameter as the priority evaluation basis, the corresponding time priority index data includes the remaining charging time or the charging stay time. Based on the remaining charging time, the longer the remaining charging time, the lower the charging priority, and the higher the discharge priority, that is, the lower the corresponding charging priority weight and the higher the discharge priority weight. The remaining charging time in the time priority index data is represented by the following formula (15):

[0122] T left (n,t) = (T end (n) - t); (15)

[0123] In formula (15), T left (n,t) is the remaining charging time of the nth electric device at time t.

[0124] Based on the charging stay time, the longer the charging stay time, the higher the charging priority and the lower the discharge priority. That is, the higher the corresponding charging priority weight and the lower the discharge priority weight. The charging stay time in the time priority index data is represented by the following formula (16):

[0125] T stay(n,t) = (t - T start )(n))

[0126] In formula (16), T stay (n,t) is the charging residence time of the nth electric device at time t.

[0127] In some embodiments, determining the charge-discharge priority weight according to at least one of the power priority index data, the SOC priority index data, and the time priority index data includes: determining the charge-discharge priority weight of the electric device according to the maximum value, the minimum value, and the power priority index data of the electric device corresponding to the power priority index data of the electric device cluster, and / or determining the charge-discharge priority weight of the electric device according to the maximum value, the minimum value, and the SOC priority index data of the electric device corresponding to the SOC priority index data of the electric device cluster, and / or determining the charge-discharge priority weight of the electric device according to the maximum value, the minimum value, and the time priority index data of the electric device corresponding to the time priority index data of the electric device cluster.

[0128] Specifically, for at least one of the power priority index data, the SOC priority index data, or the time priority index data, the corresponding charge-discharge priority weight can be determined according to the maximum value and the minimum value of the corresponding power priority index data and the power priority index data of the electric device cluster. The corresponding charge-discharge priority weight can be determined according to the maximum value and the minimum value of the corresponding SOC priority index data and the SOC priority index data of the electric device cluster. The corresponding charge-discharge priority weight can be determined according to the maximum value and the minimum value of the corresponding time priority index data and the time priority index data of the electric device cluster.

[0129] As can be seen from the above embodiments, the remaining charge required in the power priority index data, the remaining SOC to be charged in the SOC priority index data, and the remaining charging time in the time priority index data are positively correlated with the charging priority weight. The charged amount in the power priority index data, the charged SOC in the SOC priority index data, and the charging residence time in the time priority index data are positively correlated with the discharging priority weight. They can be determined using the formulas corresponding to the positive correlation parameters in the following formula (17). The remaining charge required in the power priority index data, the remaining SOC to be charged in the SOC priority index data, and the remaining charging time in the time priority index data are negatively correlated with the discharging priority weight. The charged amount in the power priority index data, the charged SOC in the SOC priority index data, and the charging residence time in the time priority index data are negatively correlated with the charging priority weight. They can be determined using the formulas corresponding to the negative correlation parameters in the following formula (17).

[0130]

[0131] Among them, formula (17) is the formula for dimensionless processing of data. Based on the charged amount in the battery power parameters, the charging and discharging priority weights are expressed by the following formula (18):

[0132]

[0133] In formula (18), w' capicity (n,t) is the charging priority weight of the nth electric device at time t, and w″ capicity (n,t) is the discharging priority weight value of the nth electric device at time t. is the maximum charged amount in the electric device cluster at time t, that is, the maximum value, is the minimum charged amount in the electric device cluster at time t, that is, the minimum value.

[0134] The electric device cluster can use any one or more of the above parameters as the basis for priority evaluation. When the electric device cluster is based on the three parameters of battery power parameters, SOC parameters, and charging time parameters, the charging and discharging priority weights can be expressed by the following formula (19):

[0135] w' priority (n,t) = w' capicity (n,t) + w' SOC (n,t) + w' time (n,t)

[0136] w″ priority (n,t) = w″ capicity (n,t) + w″ SOC(n,t) + w t ” ime (n,t); (19)

[0137] In formula (19), w' priority (n,t) is the charging priority weight of the nth electric device at time t determined based on battery parameters, w″ priority (n,t) is the discharging priority weight of the nth electric device at time t determined based on battery parameters, w' SOC (n,t) is the charging priority weight of the nth electric device at time t determined based on SOC parameters, w″ SOC (n,t) is the discharging priority weight of the nth electric device at time t determined based on SOC parameters, w' time (n,t) is the charging priority weight of the nth electric device at time t determined based on charging time parameters, w″ time (n,t) is the discharging priority weight of the nth electric device at time t determined based on charging time parameters.

[0138] In some embodiments, determining the second target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period based on the second scheduling model and the first target charging and discharging power includes: determining additional constraint conditions corresponding to the second scheduling model according to the first target charging and discharging power; and determining the second target charging and discharging power of each electric device in the electric device cluster at each moment within the preset scheduling period with the maximum of the second scheduling model as the target according to the additional constraint conditions.

[0139] Specifically, determining the additional constraint conditions corresponding to the second scheduling model according to the first target charging and discharging power means that the constraint conditions of the second scheduling model inherit the first target charging and discharging power output by the first scheduling model and use this as a constraint condition for the second scheduling model. According to the additional constraint conditions, with the maximum of the second scheduling model as the target, the second target charging and discharging power of each electric device in the electric device cluster at each moment within the preset scheduling period is determined. It can be understood that the constraint conditions of the second scheduling model inherit the output results of the first scheduling model, ensuring cost minimization under the premise of the charging requirements of the electric device cluster, and achieving the optimal allocation of charging and discharging power at each moment based on the charging and discharging priority weights, thus realizing the second target charging and discharging power, that is, ensuring that the second target charging and discharging power is the optimal charging and discharging power.

[0140] In some embodiments, determining the additional constraint conditions corresponding to the second scheduling model according to the first target charging and discharging power includes: determining the charging and discharging amounts at each corresponding moment according to the first target charging and discharging power; and determining the additional constraint conditions according to the charging and discharging amounts.

[0141] Specifically, the charge and discharge amounts at corresponding moments can be determined according to the first target charge and discharge power. It can be to calculate the cumulative sum of the charging power and the discharging power in the first target charge and discharge power at each moment to obtain the charge and discharge amounts, and the charge and discharge amounts determine the additional constraint conditions.

[0142] In a specific embodiment, the additional constraint conditions are represented by the following formula (20):

[0143]

[0144] It can be understood that the accessory constraint conditions in this embodiment inherit the first target charge and discharge power output by the first scheduling model, so as to ensure the distribution of the second target charge and discharge power on the premise of minimizing costs, and realize the optimization of the second target charge and discharge power distribution.

[0145] In some embodiments, the second constraint conditions corresponding to the second scheduling model include the user charging demand constraint conditions and the vehicle charge and discharge constraint conditions.

[0146] Specifically, the second constraint conditions corresponding to the second scheduling model further include the user charging demand constraint conditions and the vehicle charge and discharge constraint conditions, that is, the above formulas (4) and (5).

[0147] In some embodiments, according to the additional constraint conditions, with the maximum of the second scheduling model as the goal, determining the second target charge and discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period includes: under the additional constraint conditions and the second constraint conditions, with the maximum of the second scheduling model as the goal, solving the charging power and discharging power at each moment in the second target expression in the second scheduling model, and outputting the second target charge and discharge power of each electric device in the electric device cluster at each moment.

[0148] Specifically, when the available capacity of the charging station does not meet the charging demand of the electric device cluster, it can be under the additional constraint conditions and the second constraint conditions, with the maximum of the second target expression in the second scheduling model as the goal, using the sequential quadratic programming algorithm or an optimization solver to solve the charging power and discharging power at each moment in the second target expression, and outputting the second target charge and discharge power of each electric device in the electric device cluster at each moment. That is, using the above formulas (4)-(5) and (20) as the constraint conditions of the second scheduling model, with the maximum of f2 in formula (9) as the goal, using the sequential quadratic programming algorithm or an optimization solver to solve x' ch (n,t) and x′ disch(n, t) values are output, and the second target charging and discharging power of each electric device in the electric device cluster at each moment (t moment) is obtained. It can be understood that in this embodiment, not only cost minimization is considered, but also the charging and discharging power at each moment is optimally allocated based on the charging and discharging priority weights, that is, it is ensured that the second target charging and discharging power is the optimal charging and discharging power, and then the available capacity of the charging station is reasonably allocated to meet the charging needs of the electric vehicle cluster when the available capacity of the charging station is insufficient, effectively avoiding the situation that some electric devices have long charging times and low battery power, and improving the user's charging and discharging satisfaction.

[0149] In a specific embodiment, as Figure 4 shown, the schematic diagram of the charging and discharging scheduling process is as follows:

[0150] First, read input data such as the owner's selection, vehicle data, distribution network information, and electricity price information, determine the charging and discharging priority weights of the electric device cluster, and construct a cluster charging and discharging scheduling model for the electric device cluster;

[0151] Then, use mature algorithms or optimization solvers such as the sequential quadratic programming algorithm to solve the first scheduling model in the charging and discharging scheduling model of the electric device cluster to obtain the best total charging amount at each moment of the electric device cluster;

[0152] Finally, use the output result of the first scheduling model as the constraint condition of the second scheduling model, and use mature algorithms or optimization solvers such as the sequential quadratic programming algorithm to perform optimization solving of the second scheduling model. The output result includes the optimal charging and discharging power of each vehicle at each moment, which can reasonably allocate the available capacity of the charging station and improve the owner's charging satisfaction.

[0153] In a specific embodiment, assume that 10 electric vehicles arrive at the charging station successively according to their respective times for charging and discharging. The owner's selection (user's charging and discharging demand data) and vehicle data (status data) are shown in Table 1, and the electricity price information is shown in Table 2:

[0154] Table 1, the owner's selection and vehicle data are as follows:

[0155]

[0156]

[0157] Table 2, electricity price information

[0158]

[0159] Assume that the charging and discharging conditions of the above 10 electric vehicles do not exceed the available capacity of the charging station, and the scheduling plan of each electric vehicle is as Figure 5 shown, Figure 5Schematic diagram of the updated scheduling plan when the available capacity of the charging station meets the charging demand.

[0160] Assume that the charging and discharging conditions of the above 10 electric vehicles will exceed the available capacity of the charging station at some moments. At the moments of over-limit, some vehicles with lower charging and discharging priority will reduce the charging power or suspend charging. The specific scheduling plan of the charging station at each moment is as Figure 6 shown. Figure 6 Schematic diagram of the updated scheduling plan when the available capacity of the charging station does not meet the charging demand.

[0161] In the above charging and discharging scheduling method, when a state update event associated with the charging and discharging scheduling is detected, the charging and discharging scheduling associated data of each electric device in the electric device cluster of the charging station is obtained; based on the charging and discharging scheduling associated data, the scheduling plan of the electric device cluster is updated to perform the charging and discharging scheduling of the electric device cluster according to the updated scheduling plan. Since it responds to the state update event in real time and updates the scheduling plan of the electric device cluster in combination with the charging and discharging scheduling associated data, and the charging and discharging scheduling associated data involves the charging and discharging demands of users, it can respond to the changes in charging and discharging in real time, meet the personalized charging and discharging demands of users, improve the real-time performance of the charging and discharging scheduling, and meet the personalized demands of users at the same time.

[0162] It should be understood that although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the arrows, these steps do not necessarily need to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order restriction, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily need to be executed at the same moment, but can be executed at different moments. The execution order of these steps or stages does not necessarily need to be sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0163] Based on the same inventive concept, the present application also provides a charging and discharging scheduling device for implementing the charging and discharging scheduling method involved in the above embodiments with a computer device as the execution subject. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the charging and discharging scheduling device provided below can refer to the limitations of the charging and discharging scheduling method involved in the embodiments with a computer device as the execution subject in the above text, and will not be repeated here.

[0164] In some embodiments, such as Figure 7As shown, a charge and discharge scheduling device is provided. The charge and discharge scheduling device can be integrated in a computer device and includes:

[0165] An acquisition module 701 and a scheduling module 702, where:

[0166] The acquisition module 701 is configured to obtain the charge and discharge scheduling associated data of each electric device in the electric device cluster of the charging station when detecting a charge and discharge scheduling associated status update event;

[0167] The scheduling module 702 is configured to update the scheduling plan of the electric device cluster based on the charge and discharge scheduling associated data, so as to perform charge and discharge scheduling on the electric device cluster according to the updated scheduling plan.

[0168] In some embodiments, the scheduling module 702 is specifically configured to construct a cluster charge and discharge scheduling model based on the status data of the electric device and the corresponding user charge and discharge demand data;

[0169] Update the scheduling plan of the electric device cluster according to the cluster charge and discharge scheduling model.

[0170] In some embodiments, the cluster charge and discharge scheduling model includes a first scheduling model; the scheduling module 702 is specifically further configured to determine a first objective expression according to the charge and discharge costs and battery discharge loss costs of each electric device in the electric device cluster within a preset scheduling period;

[0171] Determine a first constraint condition based on the status data of the electric device and the corresponding user charge and discharge demand data, and the first scheduling model includes the first objective expression and the first constraint condition.

[0172] In some embodiments, the scheduling module 702 is specifically further configured to determine user charging demand constraint conditions according to the scheduling plan update duration, the charging power, the discharging power, the expected end SOC value in the user charge and discharge demand data, the start charging time in the status data, and the battery capacity;

[0173] Determine vehicle charge and discharge constraint conditions according to the charging power, the discharging power, the expected end charging time in the user charge and discharge demand data, the maximum charging power and maximum discharging power in the status data;

[0174] Determine SOC constraint conditions according to the scheduling plan update duration, the charging power, the discharging power, the minimum SOC value and maximum SOC value in the user charge and discharge demand data, and the SOC value in the status data;

[0175] Determine the distribution network constraint conditions based on the basic load of the charging station, the available capacity of the distribution network, the charging power, and the discharging power. The first constraint conditions include the user charging demand constraint conditions, the vehicle charging and discharging constraint conditions, the SOC constraint conditions, and the distribution network constraint conditions.

[0176] In some embodiments, the scheduling module 702 is further specifically configured to, under the first constraint conditions, with the minimum of the first scheduling model as the objective, determine the first target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period.

[0177] Update the scheduling plan of the electric device cluster based on the first target charging and discharging power.

[0178] In some embodiments, the scheduling module 702 is further specifically configured to, when the available capacity of the charging station does not meet the charging demand of the electric device cluster, based on the second scheduling model and the first target charging and discharging power, determine the second target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period.

[0179] Update the scheduling plan of the electric device cluster based on the second target charging and discharging power.

[0180] In some embodiments, the scheduling module 702 is further specifically configured to determine the charging and discharging priority weights of the electric devices according to the maximum value, the minimum value, and the power priority index data of the electric devices in the power priority index data corresponding to the electric device cluster, and / or

[0181] Determine the charging and discharging priority weights of the electric devices according to the maximum value, the minimum value, and the SOC priority index data of the electric devices in the SOC priority index data corresponding to the electric device cluster, and / or

[0182] Determine the charging and discharging priority weights of the electric devices according to the maximum value, the minimum value, and the time priority index data of the electric devices in the time priority index data corresponding to the electric device cluster.

[0183] In some embodiments, the scheduling module 702 is further specifically configured to determine the additional constraint conditions corresponding to the second scheduling model according to the first target charging and discharging power.

[0184] According to the additional constraint conditions, with the maximum of the second scheduling model as the objective, determine the second target charging and discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period.

[0185] In some embodiments, the scheduling module 702 is further specifically configured to determine the charge and discharge amounts at corresponding moments according to the first target charge and discharge power;

[0186] Determine the additional constraint conditions according to the charge and discharge amounts.

[0187] In some embodiments, the scheduling module 702 is further specifically configured to, under the additional constraint conditions and the second constraint conditions, with the maximization of the second scheduling model as the target, solve the charge power and discharge power at each moment in the second target expression in the second scheduling model, and output the second target charge and discharge power of each electric device in the electric device cluster at each moment.

[0188] Each module in the above-mentioned devices can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor in the control device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0189] In some embodiments, a computer device is provided, and its internal structure diagram can be as Figure 7 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, 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. Among them, 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 for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a charge and discharge scheduling method.

[0190] Optionally, the computer device further includes a display unit. The display unit of the computer device is used to form a visually visible picture, and 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. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or can also be an external keyboard, a touchpad, or a mouse, etc.

[0191] Those skilled in the art can understand,Figure 8 The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the control device to which the solution of this application is applied. The specific control device may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0192] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. 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 methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0193] Correspondingly, the embodiments of this application also provide a computer device, which can be a terminal device or a server.

[0194] As Figure 8 shown, Figure 8The structural schematic diagram of the computer device provided by the embodiment of the present application. The computer device 1000 includes a processor 1001 having one or more processing cores, a memory 1002 having one or more computer-readable storage media, and a computer program stored in the memory 1002 and executable on the processor. Among them, the processor 1001 is electrically connected to the memory 1002. Those skilled in the art can understand that the structure of the computer device shown in the figure does not constitute a limitation on the computer device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0195] The processor 1001 is the control center of the computer device 1000, connecting various parts of the entire computer device 1000 through various interfaces and lines. By running or loading software programs and / or units stored in the memory 1002, and calling the data stored in the memory 1002, it executes various functions of the computer device 1000 and processes data, thereby monitoring the computer device 1000 as a whole. The processor 1001 can be a central processing unit (CPU), a graphics processing unit (GPU), a network processor (NP), etc., and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application.

[0196] In the embodiment of the present application, the processor 1001 in the computer device 1000 will load the instructions corresponding to the processes of one or more application programs into the memory 1002 according to the following steps, and the processor 1001 will run the application programs stored in the memory 1002 to implement various functions. For example: in the case of detecting a charging and discharging scheduling association status update event, obtaining the charging and discharging scheduling association data of each electric device in the electric device cluster of the charging station; based on the charging and discharging scheduling association data, updating the scheduling plan of the electric device cluster to perform the charging and discharging scheduling of the electric device cluster according to the updated scheduling plan. The specific implementation of each of the above operations can be seen in the previous embodiments and will not be repeated here.

[0197] Optionally, as Figure 8 shown, the computer device 1000 further includes: a touch display screen 1003, a radio frequency circuit 1004, an audio circuit 1005, an input unit 1006, and a power supply 1007. Among them, the processor 1001 is electrically connected to the touch display screen 1003, the radio frequency circuit 1004, the audio circuit 1005, the input unit 1006, and the power supply 1007 respectively. Those skilled in the art can understand that Figure 8 the structure of the computer device shown in does not constitute a limitation on the computer device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0198] The touch display screen 1003 can be used to display a graphical user interface and receive operation instructions generated by a user's interaction with the graphical user interface. The touch display screen 1003 may include a display panel and a touch panel. Among them, the display panel can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the computer device. These graphical user interfaces can be composed of graphics, text, icons, videos, and any combination thereof. Optionally, the display panel can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), etc. The touch panel can be used to collect touch operations of the user on or near it (such as operations of the user using any suitable object or accessory, such as a finger or a stylus, on or near the touch panel), and generate corresponding operation instructions, and the operation instructions execute the corresponding program. Optionally, the touch panel can include two parts: a touch detection device and a touch computer device. Among them, the touch detection device detects the touch position of the user and detects the signal brought by the touch operation, and transmits the signal to the touch computer device; the touch computer device receives the touch information from the touch detection device, converts it into contact coordinates, and then sends it to the processor 1001, and can receive and execute commands sent by the processor 1001. The touch panel can cover the display panel. When the touch panel detects a touch operation on or near it, it transmits it to the processor 1001 to determine the type of touch event. Subsequently, the processor 1001 provides a corresponding visual output on the display panel according to the type of touch event. In the embodiments of the present application, the touch panel and the display panel can be integrated into the touch display screen 1003 to implement input and output functions. However, in some embodiments, the touch panel and the touch panel can be implemented as two independent components to implement input and output functions. That is, the touch display screen 1003 can also be used as part of the input unit 1006 to implement the input function.

[0199] The radio frequency circuit 1004 can be used to transmit and receive radio frequency signals to establish wireless communication with a network device or other computer devices through wireless communication, and transmit and receive signals with the network device or other computer devices.

[0200] The audio circuit 1005 can be used to provide an audio interface between the user and the computer device through a speaker and a microphone. The audio circuit 1005 can transmit the electrical signal converted from the received audio data to the speaker, and the speaker converts it into a sound signal for output; on the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit 1005 and then converted into audio data. After the audio data is output to the processor 1001 for processing, it is sent through the radio frequency circuit 1004 to, for example, another computer device, or the audio data is output to the memory 1002 for further processing. The audio circuit 1005 may also include an earphone jack to provide communication between the peripheral earphone and the computer device.

[0201] The input unit 1006 can be used to receive input digital, character information or user characteristic information (such as fingerprint, iris, face information, etc.), and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.

[0202] The power supply 1007 is used to supply power to each component of the computer device 1000. Optionally, the power supply 1007 can be logically connected to the processor 1001 through a power management system, so as to realize functions such as management of charging, discharging, and power consumption management through the power management system. The power supply 1007 may also include any components such as one or more DC or AC power supplies, a recharge system, a power failure detection circuit, a power converter or inverter, and a power status indicator.

[0203] Although Figure 8 not shown in the figure, the computer device 1000 may also include a camera, a sensor, a Wi-Fi module, a Bluetooth module, etc., which will not be elaborated here.

[0204] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0205] Those of ordinary skill in the art can understand that all or part of the steps in the above various methods can be completed by instructions or by controlling relevant hardware through instructions. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0206] To this end, an embodiment of the present application provides a computer-readable storage medium, which stores multiple computer programs that can be loaded by a processor to execute any of the charge and discharge scheduling methods provided by the embodiments of the present application. The computer program can execute the following steps of the charge and discharge scheduling method: when a charge and discharge scheduling associated state update event is detected, obtain the charge and discharge scheduling associated data of each electric device in the electric device cluster of the charging station; based on the charge and discharge scheduling associated data, update the scheduling plan of the electric device cluster to perform charge and discharge scheduling of the electric device cluster according to the updated scheduling plan. For the specific implementation of each of the above operations, reference can be made to the previous embodiments, which will not be elaborated here.

[0207] Among them, the computer-readable storage medium may include: Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disc, etc.

[0208] Since the computer program stored in the computer-readable storage medium can execute any of the charge and discharge scheduling methods provided by the embodiments of the present application, the beneficial effects that can be achieved by any of the charge and discharge scheduling methods provided by the embodiments of the present application can be realized. For details, reference can be made to the previous embodiments, which will not be elaborated here.

[0209] According to an aspect of the present application, a computer program product or a computer program is further provided. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in various alternative implementations in the above embodiments.

[0210] In the above embodiments of the charge and discharge scheduling device, computer-readable storage medium, computer device, and computer program product, the descriptions of each embodiment have their own emphases. For parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments. Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes and the beneficial effects that can be brought by the above-described charge and discharge scheduling device, computer-readable storage medium, computer program product, computer device, and their corresponding units can refer to the description of the charge and discharge scheduling method in the above embodiments, which will not be elaborated here specifically.

[0211] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered as the scope recorded in this specification.

[0212] The above are only the preferred embodiments of the present application and do not impose any formal restrictions on the present application. Although in the embodiments of the present application, the descriptions of the various embodiments have their own focuses, for the parts not detailed in a certain embodiment, reference can be made to the relevant embodiments of other embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present application without departing from the content of the technical solution of the present application still fall within the scope of the technical solution of the present application.

Claims

1. A charge and discharge scheduling method, characterized in that, The method includes: When a charging and discharging scheduling associated status update event is detected, obtaining the charging and discharging scheduling associated data of each electric device in the electric device cluster of the charging station; Based on the charging and discharging scheduling associated data, updating the scheduling plan of the electric device cluster to perform the charging and discharging scheduling of the electric device cluster according to the updated scheduling plan.

2. The method according to claim 1, wherein The charging and discharging scheduling associated data includes at least one of the status data of the electric device and the corresponding user charging and discharging demand data.

3. The method according to claim 2, wherein The updating the scheduling plan of the electric device cluster based on the charging and discharging scheduling associated data includes: Based on the status data of the electric device and the corresponding user charging and discharging demand data, constructing a cluster charging and discharging scheduling model; According to the cluster charging and discharging scheduling model, updating the scheduling plan of the electric device cluster.

4. The method according to claim 3, wherein The cluster charging and discharging scheduling model includes a first scheduling model; the constructing the cluster charging and discharging scheduling model based on the status data of the electric device and the corresponding user charging and discharging demand data includes: Determining a first objective expression according to the charging and discharging costs and the battery discharge loss costs of each electric device in the electric device cluster within a preset scheduling period; Determining a first constraint condition based on the status data of the electric device and the corresponding user charging and discharging demand data, and the first scheduling model includes the first objective expression and the first constraint condition.

5. The method according to claim 4, wherein The first objective expression is the sum of the charging and discharging costs and the battery discharge loss costs.

6. The method according to claim 5, wherein The charging and discharging costs are determined according to the charging power of each electric device in the electric device cluster at each moment within a preset scheduling period, the charging cost per unit of charge, the discharging power, and the discharging income per unit of discharge; The battery discharge loss costs are determined according to the battery capacity, the number of charge and discharge cycles, and the initial investment cost of the battery of each electric device in the electric device cluster at each moment within a preset scheduling period.

7. The method according to claim 6, characterized in that, The determining the first constraint condition based on the status data of the electric device and the corresponding user charging and discharging demand data includes: Determining a user charging demand constraint condition according to the scheduling plan update duration, the charging power, the discharging power, the expected end SOC value in the user charging and discharging demand data, the start charging time in the status data, and the battery capacity; Determining a vehicle charging and discharging constraint condition according to the charging power, the discharging power, the expected end charging time in the user charging and discharging demand data, the maximum charging power and the maximum discharging power in the status data; Determining an SOC constraint condition according to the scheduling plan update duration, the charging power, the discharging power, the minimum SOC value, the maximum SOC value in the user charging and discharging demand data, and the SOC value in the status data; Determining a distribution network constraint condition according to the basic load of the charging station, the available capacity of the distribution network, the charging power, and the discharging power, and the first constraint condition includes the user charging demand constraint condition, the vehicle charging and discharging constraint condition, the SOC constraint condition, and the distribution network constraint condition.

8. The method according to claim 4, characterized in that, Updating the scheduling plan of the electric device cluster according to the cluster charge and discharge scheduling model includes: Under the first constraint condition, with the minimum of the first scheduling model as the goal, determining the first target charge and discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period; Updating the scheduling plan of the electric device cluster based on the first target charge and discharge power.

9. The method according to claim 8, wherein The determining the first target charge and discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period under the first constraint condition with the minimum of the first scheduling model as the goal includes: Under the first constraint condition, with the minimum of the first target expression in the first scheduling model as the goal, solving the charging power and discharging power at each moment in the first target expression, and outputting the first target charge and discharge power of each electric device in the electric device cluster at each moment.

10. The method according to claim 8, wherein The cluster charge and discharge scheduling model further includes a second scheduling model; the updating the scheduling plan of the electric device cluster based on the first target charge and discharge power includes: In the case where the available capacity of the charging station does not meet the charging requirements of the electric device cluster, based on the second scheduling model and the first target charge and discharge power, determining the second target charge and discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period; Updating the scheduling plan of the electric device cluster based on the second target charge and discharge power.

11. The method according to claim 10, characterized in that, The second target expression corresponding to the second scheduling model includes the charge and discharge priority weights of each electric device in the electric device cluster, and the charge and discharge priority weights are determined according to the status data.

12. The method according to claim 11, characterized in that, The second target expression is the sum of the products of the optimized charging power, optimized discharging power of each electric device in the electric device cluster at each moment within a preset scheduling period and the corresponding charge and discharge priority weights.

13. The method according to claim 11, wherein The status data includes at least one of the battery power parameter, SOC parameter, and charging time parameter of the electric device; The determining step of the charge and discharge priority weight includes: Determining the power priority index data according to the battery power parameter; and / or, Determining the SOC priority index data according to the SOC parameter, and / or, Determining the time priority index data according to the charging time parameter; Determining the charge and discharge priority weight according to at least one of the power priority index data, the SOC priority index data, and the time priority index data.

14. The method according to claim 13, characterized in that, The power priority index data includes the charged amount or the remaining amount to be charged; and / or, The SOC priority index data includes the charged SOC value or the remaining SOC value to be charged; and / or, The time priority index data includes the remaining charging time or the charging stay time.

15. The method according to claim 13, wherein The determining the charge and discharge priority weight according to at least one of the power priority index data, the SOC priority index data, and the time priority index data includes: Determine the charge-discharge priority weights of the electric devices based on the maximum value, minimum value in the power priority index data corresponding to the electric device cluster and the power priority index data of the electric devices, and / or, Determine the charge-discharge priority weights of the electric devices based on the maximum value, minimum value in the SOC priority index data corresponding to the electric device cluster and the SOC priority index data of the electric devices, and / or, Determine the charge-discharge priority weights of the electric devices based on the maximum value, minimum value in the time priority index data corresponding to the electric device cluster and the time priority index data of the electric devices.

16. The method according to claim 12, characterized in that, Based on the second scheduling model and the first target charge-discharge power, determining the second target charge-discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period includes: Determine the additional constraint conditions corresponding to the second scheduling model according to the first target charge-discharge power; Based on the additional constraint conditions, with the maximum of the second scheduling model as the target, determine the second target charge-discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period.

17. The method according to claim 16, wherein The determining the additional constraint conditions corresponding to the second scheduling model according to the first target charge-discharge power includes: Determine the charge-discharge amount at each corresponding moment according to the first target charge-discharge power; Determine the additional constraint conditions according to the charge-discharge amount.

18. The method according to claim 10, wherein The second constraint conditions corresponding to the second scheduling model include the user charging demand constraint conditions and the vehicle charge-discharge constraint conditions.

19. The method according to claim 16, wherein Based on the additional constraint conditions, with the maximum of the second scheduling model as the target, determining the second target charge-discharge power of each electric device in the electric device cluster at each moment within a preset scheduling period includes: Under the additional constraint conditions and the second constraint conditions, with the maximum of the second scheduling model as the target, solve the charging power and discharging power at each moment in the second target expression in the second scheduling model, and output the second target charge-discharge power of each electric device in the electric device cluster at each moment.

20. The method according to any one of claims 1-19, characterized in that, The state update event includes at least one of reaching the scheduling plan update moment, change in the number of electric device clusters, change in the state of electric devices, change in the state of charging piles, response to grid output adjustment requirements, and change in user charge-discharge demands.

21. A charge and discharge scheduling device, characterized in that, The device includes: An acquisition module, configured to acquire the charge-discharge scheduling associated data of each electric device in the electric device cluster of the charging station when detecting a state update event associated with charge-discharge scheduling; A scheduling module, configured to update the scheduling plan of the electric device cluster based on the charge-discharge scheduling associated data, so as to perform charge-discharge scheduling of the electric device cluster according to the updated scheduling plan.

22. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the charge-discharge scheduling method according to any one of claims 1 to 20.

23. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the charge-discharge scheduling method according to any one of claims 1 to 20.

24. A computer device, characterized in that, Including: A memory, on which a computer program is stored; A processor for executing the computer program in the memory to implement the charge and discharge scheduling method according to any one of claims 1 to 20.

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