Master-slave cooperative regulation method, device and system for networked charging pile

Abstract

The application provides a network-constructing charging pile master-slave cooperative regulation method, device and system, and relates to the technical field of network-constructing charging piles. The method comprises the following steps: acquiring network-constructing load demand information, operating state information of a master pile and multiple slave piles, and vehicle information of multiple discharging vehicles; determining the target discharging vehicle quantity required to meet the network-constructing load demand information and the target discharging power of each discharging vehicle based on the network-constructing load demand information and the vehicle information of the multiple discharging vehicles by using a greedy algorithm; and determining a matching strategy between the master pile and the multiple slave piles and the multiple discharging vehicles of the target discharging vehicle quantity based on the target discharging vehicle quantity, the target discharging power of each discharging vehicle and the operating state information. The application solves the problems that the existing network-constructing charging pile is difficult to meet the micro-grid demand of high power and multiple vehicles participating in the operation when the single pile independently operates, and the scheduling efficiency is low.

Description

Technical Field

[0001] This invention relates to the field of grid-type charging pile technology, specifically to a master-slave collaborative control method, a master-slave collaborative control device, a master-slave collaborative control system, a machine-readable storage medium, and a computer program product for grid-type charging piles. Background Technology

[0002] Traditional charging stations only support unidirectional charging. With the development of new power systems, Vehicle-to-Grid (V2G) technology has emerged. V2G technology utilizes the energy storage potential of electric vehicle batteries as a buffer between the power grid and new energy sources, thereby enabling bidirectional charging and discharging of electric vehicles and the power grid. Grid-based charging stations possess the ability to actively construct, stabilize, and support bidirectional charging and discharging of the power grid. They charge and discharge when the grid is normal, and when the grid is weak or offline, they function like traditional generators, establishing stable voltage and frequency to form an independent and stable "microgrid," providing power security for emergency loads.

[0003] When existing grid-type charging piles operate independently, they are unable to meet the demands of microgrids with high power and multiple vehicles, and their dispatching efficiency is low. Summary of the Invention

[0004] The purpose of this invention is to provide a master-slave collaborative control method, device, and system for grid-type charging piles, in order to solve the problems that existing grid-type charging piles, when operating independently, cannot meet the needs of microgrids with high power and multiple vehicles, and have low scheduling efficiency.

[0005] To achieve the above objectives, embodiments of the present invention provide a master-slave collaborative control method for a grid-type charging pile, comprising: Obtain information on grid load demand, operating status of main piles and multiple slave piles, and vehicle information of multiple discharge vehicles; Using a greedy algorithm, based on the network load demand information and the vehicle information of the multiple discharge vehicles, the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle are determined. Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information, a matching strategy is determined between the main pile and multiple slave piles and the multiple discharge vehicles of the target number of discharge vehicles.

[0006] On the other hand, embodiments of the present invention also provide a master-slave collaborative control device for a grid-type charging pile, comprising: The acquisition module is used to acquire information on the load demand of the network, the operating status of the main pile and multiple slave piles, and the vehicle information of multiple discharge vehicles. The determination module is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles using a greedy algorithm. The matching module is used to determine the matching strategy between the main pile and multiple slave piles and multiple discharge vehicles of the target discharge vehicle number based on the target discharge vehicle number, the target discharge power of each discharge vehicle and the operating status information.

[0007] On the other hand, embodiments of the present invention also provide a network-type charging pile master-slave collaborative control system, including: a master pile and a plurality of slave piles communicatively connected to the master pile; The main pile is used to acquire network load demand information, operating status information of the main pile and multiple slave piles, and vehicle information of multiple discharge vehicles. Using a greedy algorithm, based on the network load demand information and the vehicle information of the multiple discharge vehicles, the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle are determined. Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information, a matching strategy is determined between the main pile and the multiple slave piles and the target number of discharge vehicles to perform matching between the main pile and the discharge vehicles. The matching strategy is then sent to the multiple slave piles. The slave pile is used to receive the matching strategy to perform matching between the slave pile and the discharge vehicle.

[0008] On the other hand, the present invention also provides a machine-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described master-slave collaborative control method for grid-type charging piles.

[0009] On the other hand, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described master-slave collaborative control method for grid-type charging piles.

[0010] Through the above technical solution, this invention collects and analyzes the operating status information of the main piles and slave piles, as well as the information of the discharging vehicles. When network construction is required, a greedy algorithm can quickly calculate the required number of target vehicles and the target discharge power of each vehicle. Then, based on the number of target vehicles, the target discharge power of each vehicle, and the operating status information, intelligent optimization is performed to achieve a matching strategy between the main piles and multiple slave piles and the target number of discharging vehicles. This invention unifies the scheduling of main piles, multiple slave piles, and vehicle resources to achieve clustered and systematic microgrid construction, meeting the needs of high-power, multi-vehicle microgrids and solving the problem of low scheduling efficiency in existing technologies under high-power, multi-vehicle scenarios.

[0011] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0012] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating the master-slave collaborative control method for grid-type charging piles provided by the present invention. Figure 2 This is one of the structural schematic diagrams of the master-slave collaborative control system for grid-type charging piles provided by the present invention; Figure 3 This is a flowchart illustrating the greedy algorithm provided by the present invention; Figure 4 This is a schematic diagram of the structure of the master-slave collaborative control device for the grid-type charging pile provided by the present invention; Figure 5 This is the second schematic diagram of the master-slave collaborative control system for the grid-type charging pile provided by the present invention. Detailed Implementation

[0013] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0014] Although grid-connected charging piles have the ability to actively establish voltage and frequency and support microgrids, existing technologies still have many limitations: (1) Existing grid-connected charging piles cannot provide independent power when the power grid is interrupted and do not have emergency power supply capabilities; (2) Existing grid-type charging piles are mostly single-pile independent operations, lacking an effective coordination mechanism, making it difficult to meet the needs of high-power microgrids with multiple vehicles participating, and the dispatch efficiency is low; (3) Lack of a unified collaborative control architecture: In the existing technology, each charging pile or vehicle makes independent decisions and lacks a global optimization "brain" to coordinate and plan, resulting in low resource utilization and poor system stability; (4) Imperfect vehicle selection and power allocation algorithms: Existing solutions often simply sort by capacity or power, failing to comprehensively consider multiple factors such as vehicle SOC, battery health (SOH), user demand, and grid load forecast, resulting in insufficient intelligence and precision of the control strategy.

[0015] Therefore, the purpose of this invention is to provide a master-slave collaborative control method, device, and system for grid-type charging piles, at least to solve the problems that existing grid-type charging piles mostly operate independently, making it difficult to meet the needs of microgrids with high power and multiple vehicles, and resulting in low scheduling efficiency.

[0016] Method Implementation Examples Please refer to Figure 1 This invention provides a master-slave collaborative control method for a grid-type charging pile, comprising: Step 100: Obtain network load demand information, operating status information of main piles and multiple slave piles, and vehicle information of multiple discharge vehicles.

[0017] The master-slave collaborative control method for grid-type charging piles of the present invention is implemented based on the master pile in the master-slave collaborative control system of the grid-type charging piles. Please refer to... Figure 2 A network-type charging pile master-slave collaborative control system consists of one master pile and multiple slave piles. The communication and collaboration parameters between the master and slave piles are crucial for ensuring synchronous operation of multiple piles. The master and slave piles can communicate via CAN bus, RS485, or Ethernet. In one embodiment, the site addresses and roles of the master and slave piles are defined as follows: Master pile: Set Device ID (e.g., 01), Role = Master. Slave pile: Set Device ID (e.g., 02, 03...), Role = Slave. This establishes a command chain and prevents "multi-master" conflicts. Afterwards, the master and slave piles can coordinate their communication baud rate and protocol type. The master pile contains a master pile controller, which serves as the core management unit of the entire charging pile cluster. It is responsible for real-time collection, analysis, and configuration of three types of information: microgrid operation information, master and slave pile operating status information, and vehicle information.

[0018] Microgrid operation information refers to the operation information of microgrids requiring emergency power supply. In some embodiments, microgrid operation information includes microgrid node voltage and frequency; active power, reactive power, power factor, load status, grid fault information, etc. The operation status information of the master pile and multiple slave piles can include the master pile's operating mode, input / output power, operating status, fault alarms, communication status, module temperature, switch status, etc.; and the slave piles' operating mode, input / output power, operating status, fault alarms, communication status, module temperature, switch status, etc. Vehicle information can be collected through communication with the master pile or slave piles. In some embodiments, vehicle information can include basic vehicle battery information, charging requirements and protocol information, and transaction and identity information. Basic vehicle battery information includes BMS (Battery Management System) data. BMS data includes the battery's current SOC (current remaining charge), SOH (State of Health), battery temperature, maximum allowable charging / discharging power, battery type and capacity, etc. Battery type and capacity information includes rated capacity (kWh) and battery chemistry (e.g., ternary lithium, lithium iron phosphate, affecting charge / discharge strategies). Charging requirements and protocol information includes user settings, charging mode, and protocol version information. User settings include target SOC (target remaining charge after discharge) and scheduled departure time. Charging modes include normal charging, fast charging, or V2G discharge (whether authorized to feed power back to the grid). Protocol version information includes supported communication protocols. Transaction and identity information includes user ID / account information, charging start and end times and charge volume, and electricity price sensitivity. User ID / account information is used for billing and authorization verification. Charging start and end times and charge volume are used for settlement and load curve analysis. Electricity price sensitivity indicates whether the user participates in time-of-use pricing or demand-side response.

[0019] In some embodiments, the main pile controller analyzes microgrid information periodically (e.g., once every half hour), and obtains and stores the total load demand data (active power and reactive power of all loads) required by the microgrid for each time period based on the grid configuration information, such as the emergency level.

[0020] Step 200: Using a greedy algorithm, determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles.

[0021] In one embodiment, the main pile controller can use a greedy algorithm to determine the target number of discharge vehicles and the target discharge power of each discharge vehicle required to meet the network load demand information based on the active power and reactive power of all loads and the rated discharge power of the multiple discharge vehicles. For example, using a greedy algorithm to determine the target number of discharge vehicles and the target discharge power of each discharge vehicle required to meet the network load demand information based on the active power and reactive power of all loads and the rated discharge power of the multiple discharge vehicles includes: constructing a first set and a second set; the first set includes the apparent power of all loads; the apparent power is determined based on the active power and reactive power of the loads; the second set includes the rated discharge power of multiple discharge vehicles sorted from largest to smallest; determining the sum of the apparent power of all loads in the first set; repeating the following steps until a set stopping condition is reached: determining the second set The sum of the rated discharge power of the n discharge vehicles with the highest numerical values ​​in the set is used; n is a non-negative integer; the sum of the rated discharge power is compared with the total load demand power; the total load demand power is determined based on the ratio of the apparent power sum to a set power efficiency; wherein, the set stopping condition is that the sum of the rated discharge power is greater than the total load demand power; if the sum of the rated discharge power is less than or equal to the total load demand power, n is incremented by one; the value of n at the end of the iteration is taken as the target number of discharge vehicles; the rated discharge power of the discharge vehicles in the second set at the end of the iteration that are ranked the same as the target number of discharge vehicles is taken as the target discharge power.

[0022] Please refer to Figure 3 Specifically, when the main pile controller receives the network construction request, it reads the active power and reactive power of all loads, as well as the rated discharge power of multiple nearby discharge vehicles, forming set 1 (first set) and set 2 (second set). Set 1 is the active power P of all loads representing the expected total load demand. load and reactive power Q load The sum of squares (i.e., the apparent power of all loads) In set 1, n represents the load index. Set 2 represents the rated discharge power of multiple discharge vehicles. In this set, n represents the serial number of the discharge vehicle. First, the elements of set 1 are sorted in ascending order (from smallest to largest), and the elements of set 2 are sorted in descending order (from largest to smallest). The number of elements in set 1 is determined based on network requirements, and then summed. For example, in one embodiment, the main pile controller determines the apparent power sum SUM1 of all loads in the first set. Next, the rated discharge power sum of the n (n is a non-negative integer) discharge vehicles with higher numerical rankings in the second set is determined; the relationship between the rated discharge power sum (or rated capacity sum) and the total load demand power is compared. For example, selection can start from the first element of set 2 (the highest-ranked element), and the calculation continues until the rated discharge power sum of the n discharge vehicles in set 2 is greater than the apparent power sum SUM1 divided by the power coefficient. The total load demand power is determined based on the ratio of the apparent power sum (or load power sum) to the set power efficiency; if the rated discharge power sum is less than or equal to the total load demand power, n is incremented by one. The power coefficient can be set according to the application scenario, such as 0.6.

[0023] The value of n at the end of the iteration is taken as the target number of discharge vehicles; the rated discharge power of the discharge vehicles in the second set at the end of the iteration, which are sorted with the same number of target discharge vehicles, is taken as the target discharge power. For example, if the value of n at the end of the iteration is 3, then the target number of discharge vehicles required to meet the network load demand information is 3 vehicles. The rated discharge power of the discharge vehicle corresponding to the third element in the second set, sorted from largest to smallest, is the target discharge power of each discharge vehicle.

[0024] Step 300: Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information, determine the matching strategy between the main pile and multiple slave piles and the multiple discharge vehicles of the target number of discharge vehicles.

[0025] The main charging pile controller determines the matching strategy between the main charging pile and multiple slave charging piles and the multiple charging vehicles based on the target number of charging vehicles, the target discharge power of each charging vehicle, and the operating status information. For example, if the target number of charging vehicles is 3, and the rated discharge power of each charging vehicle is 40W, the main charging pile controller will use this parameter (3 target charging vehicles, 40W rated discharge power per vehicle) to search for similar vehicles on the dispatching main station and the APP. After finding a vehicle that meets the rated discharge power requirement (rated discharge power greater than or equal to 40W), the controller will find a main charging pile or slave charging pile with a maximum input power greater than or equal to 40W based on the power matching of the charging pile, thus achieving a good match between the vehicle and the charging pile. For example, there may be 4 charging piles with a maximum input power greater than or equal to 40W. The four charging piles are: Main pile 1 (maximum input power 80W), Slave pile 1 (maximum input power 70W), Slave pile 2 (maximum input power 50W), and Slave pile 3 (maximum input power 40W). The main pile controller selects the three charging piles with the highest maximum input power (Main pile 1, Slave pile 1, and Slave pile 2) as target charging piles and matches them with the three discharging vehicles. Upon receiving the network construction request, this embodiment of the invention first uses a greedy algorithm to quickly estimate the required number of target vehicles and the target discharge power of each vehicle; then, it combines the operating status information of the main and slave piles for precise matching, ultimately determining the optimal number of participating vehicles and the power allocation scheme between each vehicle and the charging pile.

[0026] This invention collects and analyzes the operating status information of master piles and slave piles, as well as the information of discharging vehicles. When network construction is required, a greedy algorithm is used to quickly calculate the required number of target vehicles and the target discharge power of each vehicle. Then, based on the number of target vehicles, the target discharge power, and the operating status information, intelligent optimization is performed to achieve a matching strategy between the master piles and multiple slave piles and the target number of discharging vehicles. This invention unifies the scheduling of master piles, multiple slave piles, and vehicle resources to achieve clustered and systematic microgrid construction, meeting the needs of high-power, multi-vehicle microgrids and solving the problem of low scheduling efficiency in existing technologies under high-power, multi-vehicle scenarios.

[0027] In other aspects of the embodiments of the present invention, the vehicle information includes the rated discharge power of the discharge vehicle; the step of using a greedy algorithm to determine the target number of discharge vehicles required to satisfy the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the plurality of discharge vehicles includes: under capacity circle constraints and droop characteristic constraints, using a greedy algorithm to determine the target number of discharge vehicles required to satisfy the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the plurality of discharge vehicles.

[0028] In other embodiments, a greedy algorithm, capacity circle constraints, and droop constraint can be combined to determine the target number of discharge vehicles required to meet the grid load demand information and the target discharge power of each discharge vehicle. The capacity circle constraint characterizes the active power and reactive power constraints shared by each discharge vehicle. That is, the capacity circle constraint ensures that the discharge power of a single discharge vehicle does not exceed the limit. The droop constraint characterizes the microgrid frequency deviation constraint. That is, the droop constraint ensures frequency / voltage stability and avoids excessive frequency deviation.

[0029] In one embodiment, determining the target number of discharge vehicles and the target discharge power of each discharge vehicle required to meet the grid load demand information using a greedy algorithm based on the grid load demand information and the rated discharge power of the multiple discharge vehicles, under the constraints of capacity circle and droop characteristics, includes: determining the initial number of discharge vehicles and the initial discharge power of each discharge vehicle required to meet the grid load demand information using a greedy algorithm based on the active power and reactive power of all loads and the rated discharge power of the multiple discharge vehicles; determining the minimum integer value that satisfies the capacity circle constraint and the droop characteristic constraint based on the active power and reactive power of all loads, the initial discharge power, and the safety margin; determining the maximum value between the initial number of vehicles and the minimum integer value as the candidate number of discharge vehicles; determining the frequency deviation of the bus based on the candidate number of discharge vehicles, the rated frequency of the microgrid, the rated capacity of a single charging pile, and the droop coefficient; and determining the candidate number of discharge vehicles as the target number of discharge vehicles and the initial discharge power as the target discharge power if the frequency deviation is less than or equal to a set threshold.

[0030] The specific steps for determining the initial number of discharge vehicles and the initial discharge power of each discharge vehicle based on the active and reactive power of all loads and the rated discharge power of the multiple discharge vehicles using a greedy algorithm can be found in step 200 above, which describes using a greedy algorithm based on the network load demand information and the vehicle information of the multiple discharge vehicles to determine the target number of discharge vehicles and the target discharge power of each discharge vehicle to meet the network load demand information. These details will not be elaborated upon here. The capacity circle constraint in this embodiment is that N identical network-type discharge vehicles operate in parallel, and the corresponding rated capacity is set as the target discharge power calculated by the greedy algorithm. The active power of discharge shared by each discharge vehicle and discharge reactive power The following constraints must be met: In one embodiment, a safety margin is considered. Then the formula for the capacity circle constraint becomes: The droop characteristic constraint in this embodiment of the invention is a limitation of the control strategy. The main pile controller outputs power by adjusting the voltage amplitude V and frequency f, wherein the active power-frequency droop formula is: The reactive power-voltage droop formula is: .in, The active power-frequency droop factor is... Reactive power-voltage droop coefficient. This is the measured angular frequency. This is the rated voltage amplitude. This represents the measured voltage amplitude. During steady-state operation, ω and V are the same for all parallel discharging vehicles. Therefore, if the droop coefficients Dp and Dq are set identically for all discharging vehicles, the power will be automatically distributed evenly. That is: , ; in, The sum of the active power of all loads, Let N be the sum of reactive power for all loads. Therefore, we need to find the smallest integer value N that satisfies the two constraints mentioned above. min .

[0031] P unit and Q unit Substituting into the capacity circle formula, we get

[0032] but: The smallest integer value N that satisfies both the capacity circle constraint and the droop characteristic constraint can be obtained. min =P load P load This represents the apparent power of all loads. If the target number of discharge vehicles N is too small, the discharge power borne by a single discharge vehicle will be too large, causing the bus frequency / voltage to deviate significantly from the rated value. This results in a situation where power can be supplied physically, but the power quality is substandard. If the calculated number of target discharge vehicles N causes the frequency deviation Δf to be too large (e.g., >0.5Hz), the number of target discharge vehicles N is increased until the frequency deviation is within the allowable range. The formula for the frequency deviation is as follows: ; ; Where, k p f is the droop slope. n The rated frequency of the microgrid, such as 50Hz; P rated The rated capacity (kVA) of a single charging pile is given; the adjustment coefficient R is set to 0.02 (2%). The main pile controller uses the target number of discharging vehicles N and N' obtained by a greedy algorithm. min The larger value (number of candidate discharge vehicles) is used to check the load P.load / N(P) load The optimal solution is determined by checking if the discharge power of a single discharge vehicle is within its effective droop control range. If it is, then the optimal solution is found. If not, the target number of discharge vehicles N = N + 1, meaning the target number of discharge vehicles N is incremented by one. The target number of discharge vehicles N should be less than the number of auxiliary piles. The greedy algorithm is then re-executed, and this process is repeated until the optimal solution is found.

[0033] This invention introduces a dual verification mechanism of "capacity circle constraint" and "droop characteristic constraint." This ensures that when calculating the required number of vehicles, not only the total capacity is considered, but also the output power of a single vehicle is strictly limited. This prevents the bus frequency / voltage from deviating significantly from the rated value due to single-pile overload, thereby guaranteeing the power quality and operational stability of the microgrid. The vehicle quantity and power allocation method based on greedy algorithm and constraint optimization in this invention, upon receiving the network construction request, firstly uses a greedy algorithm to quickly estimate the required number of target discharge vehicles; then, combining the capacity circle constraint (ensuring that the power of a single vehicle does not exceed the limit) and the droop characteristic constraint (ensuring frequency / voltage stability and avoiding excessive deviation), precise calculations are performed to finally determine the optimal number of vehicles participating in the target discharge and the power allocation scheme for each discharge vehicle.

[0034] In other aspects of the embodiments of the present invention, the vehicle information further includes multi-dimensional status information of the discharging vehicle; the step of determining the matching strategy between the main pile and multiple slave piles and the multiple discharging vehicles of the target number of discharging vehicles based on the target number of discharging vehicles, the target discharge power of each discharging vehicle, and the operating status information includes: determining the matching strategy between the main pile and multiple slave piles and the multiple discharging vehicles of the target number of discharging vehicles based on the target number of discharging vehicles, the target discharge power of each discharging vehicle, the operating status information, and the multi-dimensional status information; the multi-dimensional status information includes at least two of the following: the vehicle's current remaining power, battery health, battery temperature, scheduled departure time, and target remaining power after discharge.

[0035] This invention utilizes a vehicle search algorithm to search for vehicles based on at least two of the following: the vehicle's current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge. This yields candidate discharge vehicles that match the target number of discharge vehicles. Then, a matching strategy is determined between the candidate discharge vehicle's main charging station and multiple slave charging stations and the candidate discharge vehicles. For example, the vehicle search algorithm in this invention incorporates multi-dimensional dynamic information such as the vehicle's current remaining battery power, battery health, battery temperature, user needs (scheduled departure time, target remaining battery power after discharge), and grid load forecasts as admission constraints, weighted scoring factors, power allocation restrictions, and safety verification conditions into the calculation process, achieving global optimization of vehicle combination and power allocation.

[0036] In some embodiments, the operating status includes the maximum input power of the main charging pile and the slave charging piles; the step of determining the matching strategy between the main charging pile and the multiple slave charging piles and the multiple discharge vehicles of the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information includes: using at least one of the remaining power threshold, the dischargeable capacity threshold, and the discharge duration threshold to filter out multiple candidate discharge vehicles that match the target number of discharge vehicles from all discharge vehicles; calculating the priority score of each candidate discharge vehicle based on the current remaining power, battery health, battery temperature, scheduled departure time, and target remaining power after discharge; determining the discharge priority of all candidate discharge vehicles based on the priority scores of all candidate discharge vehicles; and performing power matching for each candidate discharge vehicle based on the maximum input power of the main charging pile, the maximum input power of all slave charging piles, and the target discharge power of each vehicle to determine the target charging pile corresponding to each candidate discharge vehicle; the target charging pile includes the main charging pile and / or the slave charging piles.

[0037] This invention aims to meet the total active / reactive power demand of the power grid (active and reactive power of all loads). First, it filters discharge vehicles based on multi-dimensional state information to obtain candidate discharge vehicles. Then, a weighted scoring model determines the participation priority of these candidate vehicles. Following this, power allocation is performed based on priority and constraints. Finally, multiple checks are conducted on battery safety, user rights, and power quality to form a complete decision-making closed loop. The multi-dimensional state information includes the following: 1) SOC (Current Remaining Battery): As the core constraint for the admission of vehicles for discharge, it sets the minimum allowable remaining battery threshold, and vehicles below the remaining battery threshold are directly excluded; it is also used to calculate the maximum discharge capacity of vehicles for discharge and determine the upper limit of power allocation.

[0038] 2) SOH (Battery Health): As a key factor in weighted scoring, the higher the SOH, the higher the priority of the vehicle participating in the discharge, while limiting the maximum discharge power of unhealthy batteries and extending battery life.

[0039] 3) Battery temperature: As a safety constraint, when the temperature exceeds the safe range, the output power is limited or participation in grid construction is prohibited to avoid safety risks caused by overheating / overcooling of the battery.

[0040] 4) User's scheduled departure time: As a rigid constraint, ensure that the vehicle's discharge time does not exceed the remaining stay time to avoid affecting the user's normal travel.

[0041] 5) User's target SOC (target remaining charge after discharge): As a bottom line constraint for discharge, the remaining charge of the vehicle after discharge shall not be lower than the target remaining charge after discharge, so as to ensure the user's basic power needs.

[0042] 6) Power grid load forecasting: As a basis for power allocation, the total demand power and duration are determined according to the forecast load curve, which guides the number of vehicles and the power configuration of each vehicle.

[0043] Below, taking a microgrid emergency grid construction scenario as an example, the system needs to provide a total active power of 120kW and continuous power supply for 1 hour. The main pile controller collects information on 4 vehicles to be selected for discharge. The execution flow of this embodiment is as follows: Admission Filtering: Set the remaining battery power threshold to 60%, the discharge capacity threshold to 20%, and the discharge duration threshold to 1 hour. Iterating through vehicle information, vehicle D currently has 50% remaining battery power (less than the 60% threshold), a scheduled departure time of 0.5 hours (less than the 1-hour discharge duration threshold), and a target remaining battery power of 40% after discharge (dischargeable capacity of 10%, less than the 20% threshold). Therefore, vehicle D's remaining battery power, dischargeable capacity, and discharge time all fail to meet the requirements and are directly excluded. Vehicle B departs after 1 hour (meets the 1-hour discharge duration threshold), has a remaining battery power threshold of 60%, and a target remaining battery power of 40% after discharge. Vehicle B's dischargeable capacity just meets the requirements, but its dischargeable capacity is limited, so it is marked as a low-priority candidate. Vehicle C's battery temperature is 35℃, close to the safety limit, limiting its maximum discharge power to 80% of the rated value. All other parameters are met, so it is marked as a medium-priority candidate. Vehicle A meets all requirements and is included as a high-priority candidate. Therefore, this embodiment of the invention utilizes threshold conditions of remaining power threshold, dischargeable capacity threshold, and discharge duration threshold to filter out multiple candidate discharge vehicles matching the target number of discharge vehicles from all discharge vehicles. In other embodiments, one or two of the remaining power threshold, dischargeable capacity threshold, and discharge duration threshold can also be used to filter out multiple candidate discharge vehicles matching the target number of discharge vehicles from all discharge vehicles. For example, this embodiment of the invention can also use the remaining power threshold and discharge duration threshold to filter out multiple candidate discharge vehicles matching the target number of discharge vehicles from all discharge vehicles.

[0044] The main pile controller can calculate the priority score of each candidate discharge vehicle based on its multi-dimensional state information. For example, in one embodiment, the priority score is calculated based on the current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge for each candidate discharge vehicle. For instance, calculating the priority score based on the current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge for each candidate discharge vehicle includes: calculating the priority score based on the current remaining battery power, a first weighting coefficient corresponding to the current remaining battery power, the battery health, a second weighting coefficient corresponding to the battery health, the battery temperature, a third weighting coefficient corresponding to the battery temperature, the scheduled departure time, a fourth weighting coefficient corresponding to the scheduled departure time, the difference between the current remaining battery power and the target remaining battery power after discharge, and a fifth weighting coefficient corresponding to the difference. Specifically, the priority score uses a multi-factor weighted scoring model, and the calculation formula is as follows: Score=W1×SOC+W2×SOH+W3×(1 / Temp)+W4×LeaveTime+W5×(SOC TargetSOC); Wherein, W1~W5 are normalized weighting coefficients, namely the first weighting coefficient, the second weighting coefficient, the third weighting coefficient, the fourth weighting coefficient, and the fifth weighting coefficient, respectively. SOC is the current remaining power, SOH is the battery health status, Temp is the battery temperature, LeaveTime is the scheduled departure time, and TargetSOC is the target remaining power after discharge.

[0045] It should be noted that, in other embodiments, the priority score can also be determined by selecting some factors from the current remaining power, battery health, battery temperature, scheduled departure time, and target remaining power after discharge, along with their corresponding weighting coefficients. For example, in other embodiments, the priority score Score can also be calculated as: Score = W1 × SOC + W2 × SOH + W3 × (1 / Temp) + W4 × LeaveTime.

[0046] Then, based on the priority scores of the candidate discharge vehicles, the discharge priority of all candidate discharge vehicles is determined. For example, if three candidate discharge vehicles A, B, and C are calculated and ranked by priority scores, the order is: A > C > B; therefore, the priority of the candidate discharge vehicles is: A > C > B. Next, power allocation calculation is performed: power is allocated according to the total demand of 120kW and the priority scores. Vehicle A outputs 40kW at full power, vehicle C outputs 40kW according to temperature constraints (maximum discharge power is 80% of the rated value), and the remaining 40kW is handled by vehicle B. The total output power meets the grid load demand.

[0047] Next, multiple constraint checks are performed to verify that the remaining battery power of each candidate vehicle after discharge is not lower than the target SOC (target remaining battery power after discharge), the battery temperature and discharge power are within safe ranges, and the discharge duration matches the scheduled departure time. All constraints are met. The final algorithm outputs the optimal combination of three vehicles, A, B, and C, with a power allocation of 40kW for vehicle A, 40kW for vehicle B, and 40kW for vehicle C. This satisfies the high-power grid construction requirements of the microgrid while taking into account battery safety, user rights, and system stability. Finally, based on the maximum input power of the main charging pile, the maximum input power of all slave charging piles, and the target discharge power of each vehicle, power matching is performed for each candidate vehicle. The steps for determining the target charging pile corresponding to each candidate vehicle are the same as those in step 300, and are described in detail in step 300. After determining the candidate vehicles and the target charging piles matched to each candidate vehicle, the target charging piles are controlled to communicate and be set up with the candidate vehicles according to the GB / T 27930 vehicle-charging pile protocol to start the microgrid. During the load operation, real-time calculations and updates are performed based on the acquired data, and the configuration parameters are readjusted.

[0048] Existing technologies often select vehicles based solely on battery capacity or power. This invention innovatively incorporates multi-dimensional dynamic information into the algorithm model, including the vehicle's current remaining charge, battery health, battery temperature, user needs (e.g., scheduled departure time, target remaining charge after discharge), and grid load forecasts. This enables a more scientific and precise vehicle combination and power allocation, balancing grid stability and user experience while improving resource utilization efficiency.

[0049] In other aspects of the embodiments of the present invention, the method further includes: setting parameters for the main pile, including at least one of the following: main pile operating mode, reference value, sag coefficient, soft start parameter, and protection threshold; sending parameter setting instructions to all the slave piles so that all the slave piles complete the parameter setting; the parameter setting instructions include setting instructions for at least one of the following: slave pile operating mode, power distribution parameter, and phase-locked loop parameter.

[0050] In some embodiments, the master pile controller needs to set three types of parameters for the master pile: master pile PCS (Power Convert System) parameters, slave pile PCS following parameters, and master-slave communication and cooperative control parameters. The master pile PCS parameters include setting at least one of the following: master pile operating mode, reference value, droop coefficient, soft-start parameters, and protection threshold. In one embodiment, to achieve accurate establishment, stable operation, and safe protection of the microgrid, the master pile controller performs parameter settings for the master pile operating mode, reference value, droop coefficient, soft-start parameters, and protection threshold. The master pile operating mode includes parameter items and setting values. Parameter items include control mode and work mode. Setting values ​​include V / f Control (voltage / frequency control mode) corresponding to control mode and Grid Forming (grid formation mode) corresponding to work mode. Grid formation mode is used to instruct the master pile PCS to no longer lock phase to the external power grid, but instead generate sinusoidal voltage and frequency itself. Reference values ​​include parameter items and setting values. The parameters include the reference voltage (Uref) and the reference frequency (Fref). The reference voltage and frequency settings can be determined by selecting the load according to the microgrid's network level. For example, if the original load operates at 220V and 50Hz, the reference voltage and frequency will be 220V and 50Hz respectively during network construction. The droop factor parameters include the active-frequency droop factor and the reactive-voltage droop factor. The formula for the active-frequency droop factor is... The formula for the reactive power-voltage droop coefficient is: The soft-start parameters include Ramp Rate, Start Voltage, and Pre-charge Time. Setting these parameters prevents a surge in power-on load and ensures a smooth voltage build-up. The protection threshold parameters include Virtual Impedance Threshold and Current Limiting Threshold. These thresholds limit the maximum output current to protect equipment during microgrid islanding operation, while also ensuring the system can withstand the starting shock from building motors.

[0051] The master pile controller also sends parameter setting instructions to all slave piles to enable all slave piles to complete parameter settings. These parameter setting instructions include instructions for setting at least one of the following parameters: slave pile operating mode, power distribution parameters, and phase-locked loop (PLL) parameters. Similarly, in one embodiment, to achieve accurate establishment, stable operation, and safe protection of the microgrid, the parameter setting instructions include instructions for setting slave pile operating mode, power distribution parameters, and PLL parameters. Slave pile operating modes include power control mode, current source mode, and grid-following mode. It should be noted that in this embodiment, setting slave piles to V / f mode (voltage / frequency control mode) is strictly prohibited; otherwise, the slave piles will conflict with the master piles, leading to a grid failure. Power distribution parameters include Target Power or Power Ratio. The target power can be set to a specific kW / kVar output value through a fixed power mode. The power ratio can be set through a current sharing / proportional mode to determine the weight of the slave pile in the master-slave system. PLL parameters ensure that the slave piles can quickly and accurately lock the voltage phase established by the master pile, achieving impact-free grid connection (parallel connection).

[0052] This invention enables fine-grained settings of the main pile PCS parameters. The main pile controller settings include a complete set of parameters, including operating mode (V / f control), reference voltage / frequency, droop coefficient, soft-start parameters, and protection thresholds (virtual impedance threshold, current limiting threshold), to achieve precise establishment, stable operation, and safe protection of the microgrid. The slave pile PCS parameter following mode configuration explicitly requires the slave pile to be set to PQ control mode (constant power control mode) or current source mode, and strictly prohibits setting it to V / f mode to prevent conflict with the main pile. Simultaneously, the target power or power ratio is set, and the phase-locked loop parameters are configured to ensure that it can quickly and accurately lock the voltage phase established by the main pile, achieving impact-free parallel connection.

[0053] In addition to defining the roles (Master / Slave), communication protocols (CAN, RS485, Ethernet), and site addresses between the master and slave piles, this invention also sets up a heartbeat and timeout protection mechanism (hereinafter referred to as the heartbeat mechanism) and current sharing / circulation suppression parameters between the master and slave piles. The heartbeat mechanism parameters include the heartbeat interval (e.g., the master pile and all slave piles send a specific heartbeat frame to the communication bus between the master and slave piles every second or every few seconds) and the timeout protection time (e.g., a timeout of 200ms). For example, if a slave pile loses a heartbeat frame from the master pile, the slave pile should immediately stop or switch to standby mode to prevent loss of control; if the master pile detects that a slave pile has gone offline, it needs to recalculate the load distribution.

[0054] In addition to defining the roles (Master / Slave), communication protocols (CAN, RS485, Ethernet), and site addresses between master and slave piles, this embodiment of the invention also sets up a heartbeat mechanism and current sharing / circulation suppression parameters to ensure reliable communication and stable coordination among multi-pile systems. Therefore, this embodiment of the invention defines in detail the complete parameter setting scheme for the master pile PCS and slave pile PCS, including operating modes, reference values, droop coefficients, soft-start parameters, protection thresholds, etc., and establishes a master-slave communication protocol and heartbeat mechanism, forming a complete control closed loop from perception and decision-making to execution.

[0055] In other aspects of the embodiments of the present invention, the method further includes: when the number of inductive loads connected to the main pile exceeds a set threshold, setting the main pile to activate a short-term overload support mode, and sending a reactive power support command from the slave piles to all the slave piles, so that the main pile has short-term overload capability and all the slave piles have reactive power support capability.

[0056] This invention also includes specific settings for microgrid scenarios. Specifically, for buildings with a large number of inductive loads (the number of air conditioning compressors, elevators, and fans exceeding a set threshold), the main pile controller is configured to activate a short-term overload support mode. That is, the main pile controller sets the overload capacity of the main pile to support short-term (e.g., 150% overload within 10 seconds) overloads to handle motor starting current. The main pile controller also sends reactive power support commands to all slave piles, enabling the main piles to have short-term overload capacity and all slave piles to have reactive power support capacity. In other words, the reactive power support capacity of the slave piles is activated to assist the main piles in maintaining building voltage stability.

[0057] This invention, tailored to specific load scenarios (such as buildings with numerous inductive loads like air conditioners and elevators), specifically incorporates overload capacity for the main piles and reactive power support capacity for the slave piles to cope with motor starting current surges and ensure stable microgrid operation. In other words, this invention provides customized optimization for specific scenarios. Addressing the significant starting impact of numerous inductive loads (such as air conditioners and elevators) in buildings, this invention specifically incorporates short-term overload capacity for the main piles and reactive power support capacity for the slave piles, effectively mitigating motor starting current surges and ensuring stable microgrid operation under complex loads.

[0058] In other embodiments, the present invention can also set a black start sequence, that is, the main pile controller can be configured to power on in the following order: main pile pre-charges -> main pile establishes V / f -> delay (e.g., 2 seconds) -> slave piles close grid connection after detecting normal voltage -> gradual loading. By constructing a black start sequence, the present invention achieves safe and orderly reconstruction of system power supply, avoiding current surges, voltage oscillations, or communication competition caused by the simultaneous startup of multiple modules, and ensuring that the system composed of the main pile and multiple slave piles enters the working state stably and reliably.

[0059] In other embodiments, the present invention can also set grid-connected / off-grid switching logic. For a photovoltaic-storage-charging microgrid, the linkage parameters of the STS (Static Transfer Switch) need to be set. For example, the present invention can set the following parameters: synchronous detection conditions when mains power is restored (voltage difference < 5%, frequency difference < 0.2 Hz, phase difference < 5 degrees). After the conditions are met, the main pile controller smoothly switches the main pile from V / f mode to PQ control mode (or shuts down), and it is powered by mains power.

[0060] In summary, this invention proposes a master-slave pile collaborative master pile controller. Through the master pile controller's monitoring algorithm, it monitors the information of master piles, slave piles, and vehicles in real time. When network construction is required, it can quickly calculate the required number of vehicles and the power parameters of master and slave piles, and adjust the settings accordingly to meet the needs of rapid and high-power network construction. This invention proposes a "master-slave collaborative" control architecture consisting of one master pile and multiple slave piles. The master pile acts as the core controller, responsible for global decision-making, status monitoring, and command issuance; the slave piles act as execution units, working under the unified scheduling of the master pile to jointly build a stable microgrid, solving the pain points of independent operation and lack of coordination in existing technologies. This master-slave collaborative control architecture differs from the existing independent network construction or simple parallel connection modes. By using a smart master pile as the "brain," it uniformly schedules multiple slave piles and vehicle resources, realizing clustered and systematic microgrid construction, and solving the problems of low scheduling efficiency and poor coordination in high-power, multi-vehicle scenarios in existing technologies. This invention aims to address the problems of existing charging piles being unable to supply power during grid outages, lack of coordination in grid-connected charging piles, low scheduling efficiency, and unintelligent vehicle allocation. It proposes a master-slave collaborative control method for grid-connected charging piles based on a master-slave architecture. By real-time collecting and analyzing the operating status and multi-dimensional information (microgrid operating information, slave pile operating status information, and vehicle information) of the master pile, slave piles, and vehicles through the master pile controller, a comprehensive data foundation for subsequent intelligent decision-making can be provided. When grid connection is required, the method can quickly calculate the number of participating vehicles and the target discharge power of each vehicle. Intelligent optimization is then performed by combining factors such as current remaining battery power, battery health, and user needs to achieve precise matching of vehicle combinations and power allocation. Finally, the master and slave piles are collaboratively controlled to quickly construct a stable, efficient, and reliable microgrid.

[0061] Device Examples Please refer to Figure 4 On the other hand, embodiments of the present invention also provide a master-slave collaborative control device for a grid-type charging pile, comprising: The acquisition module 401 is used to acquire network load demand information, operating status information of main piles and multiple slave piles, and vehicle information of multiple discharge vehicles. The determination module 402 is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles using a greedy algorithm. The matching module 403 is used to determine the matching strategy between the main pile and multiple slave piles and multiple discharge vehicles of the target discharge vehicle number based on the target discharge vehicle number, the target discharge power of each discharge vehicle and the operating status information.

[0062] This invention collects and analyzes the operating status information of master piles and slave piles, as well as the information of discharging vehicles. When network construction is required, a greedy algorithm is used to quickly calculate the required number of target vehicles and the target discharge power of each vehicle. Then, based on the number of target vehicles, the target discharge power, and the operating status information, intelligent optimization is performed to achieve a matching strategy between the master piles and multiple slave piles and the target number of discharging vehicles. This invention unifies the scheduling of master piles, multiple slave piles, and vehicle resources to achieve clustered and systematic microgrid construction, meeting the needs of high-power, multi-vehicle microgrids and solving the problem of low scheduling efficiency in existing technologies under high-power, multi-vehicle scenarios.

[0063] Optionally, the vehicle information includes the rated discharge power of the discharge vehicle; the step of using a greedy algorithm to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles includes: Under the constraints of capacity circle and droop characteristic, a greedy algorithm is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the multiple discharge vehicles. The capacity circle constraint condition characterizes the active power constraint and reactive power constraint shared by each discharge vehicle; the droop characteristic constraint condition characterizes the frequency deviation constraint of the microgrid.

[0064] Optionally, under the constraints of capacity circle and droop characteristic, the step of using a greedy algorithm to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the multiple discharge vehicles includes: Using a greedy algorithm, based on the active and reactive power of all loads and the rated discharge power of the multiple discharge vehicles, the initial number of discharge vehicles required for the grid load demand information and the initial discharge power of each discharge vehicle are determined. Based on the active power, reactive power, initial discharge power, and safety margin of all loads, determine the minimum integer value that satisfies the capacity circle constraint and the droop characteristic constraint. The maximum value between the initial number of vehicles and the minimum integer value is determined as the candidate number of discharge vehicles; The frequency deviation of the bus is determined based on the number of candidate discharge vehicles, the rated frequency of the microgrid, the rated capacity of a single charging pile, and the droop coefficient. If the frequency deviation is less than or equal to a set threshold, the number of candidate discharge vehicles is determined as the target number of discharge vehicles, and the initial discharge power is determined as the target discharge power.

[0065] Optionally, the step of using a greedy algorithm to determine the initial number of discharge vehicles and the initial discharge power of each discharge vehicle required for the grid load demand information based on the active power and reactive power of all loads and the rated discharge power of the multiple discharge vehicles includes: Construct a first set and a second set; the first set includes the apparent power of all loads; the apparent power is determined based on the active power and reactive power of the loads; the second set includes the rated discharge power of multiple discharge vehicles sorted from largest to smallest. Determine the apparent power of all loads in the first set; Repeat the following steps until the set stopping condition is met: Determine the sum of the rated discharge power of the n discharge vehicles with the highest numerical values ​​in the second set; n is a non-negative integer; Compare the rated discharge power with the total load demand power; the total load demand power is determined based on the apparent power and the ratio to the set power efficiency. Wherein, the set stopping condition is that the rated discharge power is greater than the total load demand power; when the rated discharge power is less than or equal to the total load demand power, n is incremented by one; the value of n at the end of the iteration is taken as the initial number of discharge vehicles; the rated discharge power of the discharge vehicles in the second set at the end of the iteration, which are sorted with the same number of initial discharge vehicles, is taken as the initial discharge power.

[0066] Optionally, the vehicle information further includes multi-dimensional status information of the discharging vehicles; the matching strategy for determining the main pile and multiple slave piles with the target number of discharging vehicles based on the target number of discharging vehicles, the target discharge power of each discharging vehicle, and the operating status information includes: Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information, a matching strategy is determined between the main pile and multiple slave piles and multiple discharge vehicles of the target number of discharge vehicles. The multidimensional status information includes at least two of the following: the vehicle's current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge.

[0067] Optionally, the operating status includes the maximum input power of the main pile and the slave piles; the matching strategy for determining the main piles and multiple slave piles with the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information includes: Using at least one of the following threshold conditions—remaining power threshold, dischargeable capacity threshold, and discharge duration threshold—multiple candidate discharge vehicles matching the target number of discharge vehicles are selected from all discharge vehicles. Based on the current remaining power, battery health, battery temperature, scheduled departure time, and target remaining power after discharge for each candidate discharge vehicle, a priority score is calculated for each candidate discharge vehicle. Based on the priority scores of all candidate discharge vehicles, the discharge priority of all candidate discharge vehicles is determined. Based on the maximum input power of the main charging pile, the maximum input power of all slave charging piles, and the target discharge power of each vehicle, power matching is performed on each candidate discharge vehicle to determine the target charging pile corresponding to each candidate discharge vehicle; the target charging pile includes the main charging pile and / or the slave charging pile.

[0068] Optionally, the priority score for each candidate discharge vehicle is calculated based on its current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge, including: Based on the current remaining power, the first weighting coefficient corresponding to the current remaining power, the battery health, the second weighting coefficient corresponding to the battery health, the battery temperature, the third weighting coefficient corresponding to the battery temperature, the scheduled departure time, the fourth weighting coefficient corresponding to the scheduled departure time, the difference between the current remaining power and the target remaining power after discharge, and the fifth weighting coefficient corresponding to the difference, the priority score of each candidate discharge vehicle is calculated.

[0069] Optionally, the device further includes: The first setting module is used to set parameters for the main pile, including at least one of the following: main pile operating mode, reference value, sag coefficient, soft start parameter, and protection threshold; and to send parameter setting instructions to all the slave piles so that all the slave piles complete the parameter setting; the parameter setting instructions include setting instructions for at least one of the following: slave pile operating mode, power distribution parameter, and phase-locked loop parameter.

[0070] Optionally, the device further includes: The second setting module is used to set the main pile to activate the short-term overload support mode and send a reactive power support command from the slave piles to all the slave piles when the number of inductive loads connected to the main pile exceeds a set threshold, so that the main pile has short-term overload capability and all the slave piles have reactive power support capability.

[0071] The network-type charging pile master-slave collaborative control device includes a processor and a memory. The aforementioned acquisition module 401, determination module 402, and matching module 403 are all stored as program units in the memory. The processor executes these program units stored in the memory to achieve the corresponding functions. The processor contains a kernel, which retrieves the corresponding program units from the memory. One or more kernels may be provided. The memory may include non-permanent memory in computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory includes at least one memory chip.

[0072] Please refer to Figure 5 On the other hand, the present invention also provides a network-type charging pile master-slave collaborative control system, including: a master pile 510 and a plurality of slave piles 520 that are communicatively connected to the master pile 510.

[0073] The main pile 510 is used to acquire network load demand information, operating status information of the main pile 510 and multiple slave piles 520, and vehicle information of multiple discharge vehicles. Using a greedy algorithm, based on the network load demand information and the vehicle information of the multiple discharge vehicles, it determines the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle. Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information, it determines a matching strategy between the main pile 510 and the multiple slave piles 520 and the target number of discharge vehicles to perform matching between the main pile 510 and the discharge vehicles. The matching strategy is sent to the multiple slave piles 520. The slave piles 520 are used to receive the matching strategy to perform matching between themselves and the discharge vehicles.

[0074] The network-type charging pile master-slave collaborative control system is used to execute the network-type charging pile master-slave collaborative control method in the above method embodiment.

[0075] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a machine-readable storage medium. When the computer program is executed by a processor, the computer can execute a master-slave collaborative control method for a network-type charging pile. The method includes: acquiring network load demand information, operating status information of the master pile and multiple slave piles, and vehicle information of multiple discharge vehicles; using a greedy algorithm based on the network load demand information and the vehicle information of the multiple discharge vehicles, determining the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle; and determining a matching strategy between the master pile and multiple slave piles and the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information.

[0076] In another aspect, the present invention also provides a machine-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a master-slave collaborative control method for a network-type charging pile. The method includes: acquiring network load demand information, operating status information of the master pile and multiple slave piles, and vehicle information of multiple discharge vehicles; using a greedy algorithm based on the network load demand information and the vehicle information of the multiple discharge vehicles, determining the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle; and determining a matching strategy between the master pile and multiple slave piles and the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information.

[0077] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A master-slave collaborative control method for a grid-type charging pile, characterized in that, include: Obtain information on grid load demand, operating status of main piles and multiple slave piles, and vehicle information of multiple discharge vehicles; Using a greedy algorithm, based on the network load demand information and the vehicle information of the multiple discharge vehicles, the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle are determined. Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information, a matching strategy is determined between the main pile and multiple slave piles and the multiple discharge vehicles of the target number of discharge vehicles.

2. The master-slave collaborative control method for grid-type charging piles according to claim 1, characterized in that, The vehicle information includes the rated discharge power of the discharge vehicles; the step of using a greedy algorithm to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles includes: Under the constraints of capacity circle and droop characteristic, a greedy algorithm is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the multiple discharge vehicles. The capacity circle constraint condition characterizes the active power constraint and reactive power constraint shared by each discharge vehicle; the droop characteristic constraint condition characterizes the frequency deviation constraint of the microgrid.

3. The master-slave collaborative control method for grid-type charging piles according to claim 2, characterized in that, Under the constraints of capacity circle and droop characteristic, a greedy algorithm is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the multiple discharge vehicles. This includes: Using a greedy algorithm, based on the active and reactive power of all loads and the rated discharge power of the multiple discharge vehicles, the initial number of discharge vehicles required for the grid load demand information and the initial discharge power of each discharge vehicle are determined. Based on the active power, reactive power, initial discharge power, and safety margin of all loads, determine the minimum integer value that satisfies the capacity circle constraint and the droop characteristic constraint. The maximum value between the initial number of vehicles and the minimum integer value is determined as the candidate number of discharge vehicles; The frequency deviation of the bus is determined based on the number of candidate discharge vehicles, the rated frequency of the microgrid, the rated capacity of a single charging pile, and the droop coefficient. If the frequency deviation is less than or equal to a set threshold, the number of candidate discharge vehicles is determined as the target number of discharge vehicles, and the initial discharge power is determined as the target discharge power.

4. The master-slave collaborative control method for grid-type charging piles according to claim 3, characterized in that, The step of using a greedy algorithm to determine the initial number of discharge vehicles and the initial discharge power of each discharge vehicle required for grid load demand information, based on the active and reactive power of all loads and the rated discharge power of the multiple discharge vehicles, includes: Construct a first set and a second set; the first set includes the apparent power of all loads; the apparent power is determined based on the active power and reactive power of the loads; the second set includes the rated discharge power of multiple discharge vehicles sorted from largest to smallest. Determine the apparent power of all loads in the first set; Repeat the following steps until the set stopping condition is met: Determine the sum of the rated discharge power of the n discharge vehicles with the highest numerical values ​​in the second set; n is a non-negative integer; Compare the rated discharge power with the total load demand power; the total load demand power is determined based on the apparent power and the ratio to the set power efficiency. Wherein, the set stopping condition is that the rated discharge power is greater than the total load demand power; when the rated discharge power is less than or equal to the total load demand power, n is incremented by one; the value of n at the end of the iteration is taken as the initial number of discharge vehicles; the rated discharge power of the discharge vehicles in the second set at the end of the iteration, which are sorted with the same number of initial discharge vehicles, is taken as the initial discharge power.

5. The master-slave collaborative control method for grid-type charging piles according to claim 1, characterized in that, The vehicle information also includes multi-dimensional status information of the discharge vehicles; the matching strategy for determining the main pile and multiple slave piles with the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information includes: Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information, a matching strategy is determined between the main pile and multiple slave piles and multiple discharge vehicles of the target number of discharge vehicles. The multidimensional status information includes at least two of the following: the vehicle's current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge.

6. The master-slave collaborative control method for grid-type charging piles according to claim 5, characterized in that, The operating status includes the maximum input power of the main pile and the slave piles; the matching strategy for determining the main piles and multiple slave piles with the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information includes: Using at least one of the following threshold conditions—remaining power threshold, dischargeable capacity threshold, and discharge duration threshold—multiple candidate discharge vehicles matching the target number of discharge vehicles are selected from all discharge vehicles. Based on the current remaining power, battery health, battery temperature, scheduled departure time, and target remaining power after discharge for each candidate discharge vehicle, a priority score is calculated for each candidate discharge vehicle. Based on the priority scores of all candidate discharge vehicles, the discharge priority of all candidate discharge vehicles is determined. Based on the maximum input power of the main charging pile, the maximum input power of all slave charging piles, and the target discharge power of each vehicle, power matching is performed on each candidate discharge vehicle to determine the target charging pile corresponding to each candidate discharge vehicle; the target charging pile includes the main charging pile and / or the slave charging pile.

7. The master-slave collaborative control method for grid-type charging piles according to claim 6, characterized in that, The priority score for each candidate discharge vehicle is calculated based on its current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge. This includes: Based on the current remaining power, the first weighting coefficient corresponding to the current remaining power, the battery health, the second weighting coefficient corresponding to the battery health, the battery temperature, the third weighting coefficient corresponding to the battery temperature, the scheduled departure time, the fourth weighting coefficient corresponding to the scheduled departure time, the difference between the current remaining power and the target remaining power after discharge, and the fifth weighting coefficient corresponding to the difference, the priority score of each candidate discharge vehicle is calculated.

8. The master-slave collaborative control method for grid-type charging piles according to claim 1, characterized in that, The method further includes: The parameter settings for the main pile include at least one of the following: main pile operation mode, reference value, sag coefficient, soft start parameter, and protection threshold. Send parameter setting instructions to all slave piles so that all slave piles complete parameter settings; the parameter setting instructions include setting instructions for at least one of the slave pile operating mode, power distribution parameters, and phase-locked loop parameters.

9. The master-slave collaborative control method for grid-type charging piles according to claim 1, characterized in that, The method further includes: If the number of inductive loads connected to the main pile exceeds a set threshold, the main pile is set to activate a short-term overload support mode, and a reactive power support command is sent to all the slave piles, so that the main pile has short-term overload capability and all the slave piles have reactive power support capability.

10. A master-slave collaborative control device for a grid-type charging pile, characterized in that, include: The acquisition module is used to acquire information on the load demand of the network, the operating status of the main pile and multiple slave piles, and the vehicle information of multiple discharge vehicles. The determination module is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles using a greedy algorithm. The matching module is used to determine the matching strategy between the main pile and multiple slave piles and multiple discharge vehicles of the target discharge vehicle number based on the target discharge vehicle number, the target discharge power of each discharge vehicle and the operating status information.

11. The master-slave collaborative control device for a grid-type charging pile according to claim 10, characterized in that, The vehicle information includes the rated discharge power of the discharge vehicles; the step of using a greedy algorithm to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the vehicle information of the multiple discharge vehicles includes: Under the constraints of capacity circle and droop characteristic, a greedy algorithm is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the multiple discharge vehicles. The capacity circle constraint condition characterizes the active power constraint and reactive power constraint shared by each discharge vehicle; the droop characteristic constraint condition characterizes the frequency deviation constraint of the microgrid.

12. The master-slave collaborative control device for a grid-type charging pile according to claim 11, characterized in that, Under the constraints of capacity circle and droop characteristic, a greedy algorithm is used to determine the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle based on the network load demand information and the rated discharge power of the multiple discharge vehicles. This includes: Using a greedy algorithm, based on the active and reactive power of all loads and the rated discharge power of the multiple discharge vehicles, the initial number of discharge vehicles required for the grid load demand information and the initial discharge power of each discharge vehicle are determined. Based on the active power, reactive power, initial discharge power, and safety margin of all loads, determine the minimum integer value that satisfies the capacity circle constraint and the droop characteristic constraint. The maximum value between the initial number of vehicles and the minimum integer value is determined as the candidate number of discharge vehicles; The frequency deviation of the bus is determined based on the number of candidate discharge vehicles, the rated frequency of the microgrid, the rated capacity of a single charging pile, and the droop coefficient. If the frequency deviation is less than or equal to a set threshold, the number of candidate discharge vehicles is determined as the target number of discharge vehicles, and the initial discharge power is determined as the target discharge power.

13. The master-slave collaborative control device for a grid-type charging pile according to claim 12, characterized in that, The step of using a greedy algorithm to determine the initial number of discharge vehicles and the initial discharge power of each discharge vehicle required for grid load demand information, based on the active and reactive power of all loads and the rated discharge power of the multiple discharge vehicles, includes: Construct a first set and a second set; the first set includes the apparent power of all loads; the apparent power is determined based on the active power and reactive power of the loads; the second set includes the rated discharge power of multiple discharge vehicles sorted from largest to smallest. Determine the apparent power of all loads in the first set; Repeat the following steps until the set stopping condition is met: Determine the sum of the rated discharge power of the n discharge vehicles with the highest numerical values ​​in the second set; n is a non-negative integer; Compare the rated discharge power with the total load demand power; the total load demand power is determined based on the apparent power and the ratio to the set power efficiency. Wherein, the set stopping condition is that the rated discharge power is greater than the total load demand power; when the rated discharge power is less than or equal to the total load demand power, n is incremented by one; the value of n at the end of the iteration is taken as the initial number of discharge vehicles; the rated discharge power of the discharge vehicles in the second set at the end of the iteration, which are sorted with the same number of initial discharge vehicles, is taken as the initial discharge power.

14. The master-slave collaborative control device for a grid-type charging pile according to claim 10, characterized in that, The vehicle information also includes multi-dimensional status information of the discharge vehicles; the matching strategy for determining the main pile and multiple slave piles with the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information includes: Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information, a matching strategy is determined between the main pile and multiple slave piles and multiple discharge vehicles of the target number of discharge vehicles. The multidimensional status information includes at least two of the following: the vehicle's current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge.

15. The master-slave collaborative control device for a grid-type charging pile according to claim 14, characterized in that, The operating status includes the maximum input power of the main pile and the slave piles; the matching strategy for determining the main piles and multiple slave piles with the target number of discharge vehicles based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, the operating status information, and the multi-dimensional status information includes: Using at least one of the following threshold conditions—remaining power threshold, dischargeable capacity threshold, and discharge duration threshold—multiple candidate discharge vehicles matching the target number of discharge vehicles are selected from all discharge vehicles. Based on the current remaining power, battery health, battery temperature, scheduled departure time, and target remaining power after discharge for each candidate discharge vehicle, a priority score is calculated for each candidate discharge vehicle. Based on the priority scores of all candidate discharge vehicles, the discharge priority of all candidate discharge vehicles is determined. Based on the maximum input power of the main charging pile, the maximum input power of all slave charging piles, and the target discharge power of each vehicle, power matching is performed on each candidate discharge vehicle to determine the target charging pile corresponding to each candidate discharge vehicle; the target charging pile includes the main charging pile and / or the slave charging pile.

16. The master-slave collaborative control device for a grid-type charging pile according to claim 15, characterized in that, The priority score for each candidate discharge vehicle is calculated based on its current remaining battery power, battery health, battery temperature, scheduled departure time, and target remaining battery power after discharge. This includes: Based on the current remaining power, the first weighting coefficient corresponding to the current remaining power, the battery health, the second weighting coefficient corresponding to the battery health, the battery temperature, the third weighting coefficient corresponding to the battery temperature, the scheduled departure time, the fourth weighting coefficient corresponding to the scheduled departure time, the difference between the current remaining power and the target remaining power after discharge, and the fifth weighting coefficient corresponding to the difference, the priority score of each candidate discharge vehicle is calculated.

17. The master-slave collaborative control device for a grid-type charging pile according to claim 10, characterized in that, The device further includes: The first setting module is used to set parameters for the main pile, including at least one of the following: main pile operating mode, reference value, sag coefficient, soft start parameter, and protection threshold; and to send parameter setting instructions to all the slave piles so that all the slave piles complete the parameter setting; the parameter setting instructions include setting instructions for at least one of the following: slave pile operating mode, power distribution parameter, and phase-locked loop parameter.

18. The master-slave collaborative control device for a grid-type charging pile according to claim 10, characterized in that, The device further includes: The second setting module is used to set the main pile to activate the short-term overload support mode and send a reactive power support command from the slave piles to all the slave piles when the number of inductive loads connected to the main pile exceeds a set threshold, so that the main pile has short-term overload capability and all the slave piles have reactive power support capability.

19. A master-slave collaborative control system for a grid-type charging pile, characterized in that, include: A main pile and multiple slave piles that are communicatively connected to the main pile; The main pile is used to obtain information on the load demand of the power grid, the operating status information of the main pile and multiple slave piles, and the vehicle information of multiple discharge vehicles. Using a greedy algorithm based on the network load demand information and the vehicle information of the multiple discharge vehicles, the target number of discharge vehicles required to meet the network load demand information and the target discharge power of each discharge vehicle are determined. Based on the target number of discharge vehicles, the target discharge power of each discharge vehicle, and the operating status information, a matching strategy is determined between the main pile and multiple slave piles and the multiple discharge vehicles of the target number of discharge vehicles to perform matching between the main pile and the discharge vehicles. Send the matching strategy to the plurality of slave stubs; The slave pile is used to receive the matching strategy to perform matching between the slave pile and the discharge vehicle.

20. A machine-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the master-slave collaborative control method for grid-type charging piles as described in any one of claims 1 to 9.

21. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the master-slave collaborative control method for grid-type charging piles as described in any one of claims 1 to 9.

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