Ground-low altitude heterogeneous collaborative energy filling control method, system, device and medium

Abstract

The application discloses a ground-low-altitude heterogeneous collaborative charging control method and system, equipment and medium, and relates to the field of power grid charging. The method is applied to an energy management controller in a ground-low-altitude heterogeneous collaborative charging control system, comprising collecting the running state data of each device in a double-layer integrated charging station; determining that the DC bus voltage is in a preset voltage dead zone range according to the DC bus voltage and the preset voltage dead zone range; taking the flight safety requirement of the eVTOL as a rigid constraint, taking the target parameters as optimization variables, taking the minimization of the multi-objective optimization function as the optimization target, and determining the target scheduling instruction; the target parameters include adjustable parameters of the EV, the eVTOL and the energy storage system, the multi-objective optimization function is used for indicating the operation cost of the charging station, and the target scheduling instruction is used for indicating the optimal value of the target parameters; the target scheduling instruction is sent to the corresponding devices in the double-layer integrated charging station for execution. The application can realize the heterogeneous X2G resource collaboration of the EV and the eVTOL, and improve the economic benefits.

Description

Technical Field

[0001] This application relates to the field of power grid charging, and in particular to a ground-low-altitude heterogeneous collaborative charging control method, system, equipment and medium. Background Technology

[0002] With the development of human society, the large-scale application of electric vehicles (EVs) and electric vertical takeoff and landing (eVTOL) aircraft is also constantly developing. On the one hand, the large-scale application of EVs leads to a high degree of spatial and temporal concentration of charging loads, while their distributed power batteries also have the potential to become flexible energy storage resources. V2G (Vehicle-to-Grid) technology has become an important technical path for load-side response. On the other hand, as the core transportation equipment of the low-altitude economy, eVTOL is gradually being demonstrated and applied in scenarios such as urban air traffic, emergency rescue, and logistics distribution, creating an urgent need for high-power, high-reliability integrated air-to-ground energy supply facilities.

[0003] At the same time, the new power system faces regulation pressure due to the high proportion of renewable energy access, and urgently needs massive distributed flexible resources to participate in grid interaction. This provides demand traction for the inclusion of electric vehicles such as EVs and eVTOLs into the source-grid-load-storage coordinated dispatch system, and also promotes the evolution of traditional V2G technology towards the X2G (Everything-to-Grid) technology system with a wider coverage.

[0004] Currently, existing technologies still have significant shortcomings in air-to-ground integrated energy supply and X2G synergy, mainly in the following aspects: First, the infrastructure layout is fragmented. Existing EV charging stations and eVTOL take-off and landing charging facilities are planned and constructed independently, with separate power distribution, energy storage and energy management systems. This has failed to form a unified X2G interactive infrastructure system, resulting in redundant investment and waste of urban land resources, power distribution capacity and energy storage systems, and making it difficult to realize the synergistic benefits of heterogeneous transportation resources. Second, there is a lack of a coordinated scheduling mechanism. The existing V2G interaction of EVs and the charging management of eVTOL operate independently, failing to integrate the two into a unified multi-dimensional heterogeneous X2G resource pool, thus failing to maximize economic benefits. Summary of the Invention

[0005] The purpose of this application is to provide a ground-low-altitude heterogeneous collaborative charging control method, system, device and medium, which can realize heterogeneous X2G resource collaboration between EV and eVTOL and improve economic benefits.

[0006] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a ground-low-altitude heterogeneous collaborative charging control method, applied to an energy management controller in a ground-low-altitude heterogeneous collaborative charging control system. The ground-low-altitude heterogeneous collaborative charging control system includes a dual-layer integrated charging station and an energy management controller, with the dual-layer integrated charging station electrically connected to the energy management controller. The dual-layer integrated charging station includes a lower-layer ground-based EV charging and discharging area, an upper-layer airborne eVTOL take-off and landing and charging / discharging area, and photovoltaic equipment, as well as a shared power distribution system, energy storage system, and DC bus for the upper and lower layers and the photovoltaic equipment. The ground-low-altitude heterogeneous collaborative charging control method includes: Collect operational status data of each device within the dual-layer integrated charging station; Based on the DC bus voltage and the preset voltage dead zone range, it is determined that the DC bus voltage is within the preset voltage dead zone range; Using the flight safety requirements of eVTOL as a rigid constraint, the target parameters are used as optimization variables, and minimizing the multi-objective optimization function is the optimization objective to determine the target scheduling command. The target parameters include the adjustable parameters of EV, eVTOL and energy storage system. The multi-objective optimization function is used to indicate the operating cost of the charging station, and the target scheduling command is used to indicate the optimal value of the target parameters. The target scheduling command is issued to the corresponding equipment in the dual-layer integrated charging station for execution.

[0007] Optionally, rigid constraints include minimum flight power constraints, discharge prohibition constraints during flight mission periods, and power smoothing constraints.

[0008] Optionally, after determining that the DC bus voltage is within a preset voltage dead zone, the ground-low-altitude heterogeneous coordinated charging control method further includes: When the aggregated charge state of EVs in the station is less than the preset aggregated charge state safety threshold, the minimum flight charge constraint is updated according to the preset minimum flight charge margin value.

[0009] Optionally, after determining that the DC bus voltage is within a preset voltage dead zone, the ground-low-altitude heterogeneous coordinated charging control method further includes: The predicted voltage of the distribution network node is calculated based on power flow sensitivity. When the difference between the predicted voltage of the distribution network node and the preset safe lower limit of the node voltage is less than the preset difference threshold, and there is a target eVTOL in the dual-layer integrated charging station that is in a ground-based docking state and whose battery power meets the minimum flight power constraint, the adjustable discharge capacity of the target eVTOL is determined as the target parameter.

[0010] Optionally, after determining that the DC bus voltage is within a preset voltage dead zone, the ground-low-altitude heterogeneous coordinated charging control method further includes: When the current adjustable capacity of the EV in the station is lower than the preset adjustable capacity safety threshold, the target minimum flight power margin value is determined based on the current adjustable capacity and the preset adjustable capacity safety threshold; the minimum flight power constraint is updated based on the target minimum flight power margin value.

[0011] Alternatively, the multi-objective optimization function is as follows: in, , , , , In the formula, For the cost of purchasing electricity from the power grid, For battery cycle loss costs, For carbon emission costs, For market-based profits; , , , These are weighted by electricity purchase cost, loss cost, carbon emission cost, and market-based revenue; , , For adjustment coefficients, This is the per-unit value of the grid connection point voltage. As a flight mission urgency factor, for, For reference voltage, for, The estimated takeoff time for the jth eVTOL aircraft. As a preset positive number, As a benchmark value for carbon emission cost weighting, The carbon price sensitivity coefficient, for The carbon trading price at any given time. For carbon trading reference prices, As the benchmark value for market-based return weighting, The flexible capacity excitation coefficient, for The total capacity within the station can be flexibly adjusted to meet the needs. , For the first eVTOL adjustable discharge capacity For the adjustable charge and discharge capacity of the energy storage system, This represents the upper limit of the station's flexible adjustment capacity.

[0012] Furthermore, when determining the target scheduling command, the ground-low-altitude heterogeneous coordinated energy charging control method includes: According to the safety-first arbitration agreement, the weights of loss costs and market-based benefits are determined; the safety-first arbitration agreement includes: when If the value exceeds a preset urgency threshold, the loss cost weight is determined to be a preset positive number that is greater than the electricity purchase cost weight and the carbon emission cost weight, and differs by at least two orders of magnitude; the market-based revenue weight is 0. The weight of electricity purchase cost is determined as follows: The market-based revenue weight is 0; This is the lower limit of the node voltage safety. This is the upper limit for the safe voltage of the node.

[0013] Secondly, this application provides a ground-low-altitude heterogeneous collaborative energy charging control system, comprising: A dual-layer integrated charging station and an energy management controller, with the dual-layer integrated charging station and the energy management controller electrically connected; The dual-layer integrated charging station includes a ground-based EV charging and discharging area on the lower layer, an aerial eVTOL take-off and landing and charging and discharging area and photovoltaic equipment on the upper layer, as well as a power distribution system, energy storage system and DC bus shared by the upper and lower layers and the photovoltaic equipment; The energy management controller is used to implement the ground-low-altitude heterogeneous coordinated energy charging control method of the first aspect.

[0014] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the ground-low-altitude heterogeneous coordinated energy charging control method of the first aspect described above.

[0015] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the ground-low-altitude heterogeneous coordinated energy charging control method of the first aspect described above.

[0016] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the ground-low-altitude heterogeneous coordinated energy charging control method of the first aspect described above.

[0017] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a ground-low-altitude heterogeneous collaborative charging control method. It collects operational status data from various devices within a dual-layer integrated charging station. Based on the DC bus voltage and a preset voltage dead zone, it determines that the DC bus voltage is within the preset voltage dead zone, eliminating the need for voltage regulation during charging or discharging and avoiding voltage pressure risks in subsequent optimization. Using eVTOL flight safety requirements as a rigid constraint ensures that the optimization results will not affect eVTOL flight safety. By using target parameters (adjustable parameters of the EV, eVTOL, and energy storage system) as optimization variables and a multi-objective optimization function minimizing the operating cost of the charging station as the optimization objective, the heterogeneous X2G resources of the EV and eVTOL can be integrated for combined economic benefit optimization, resulting in a target scheduling command with the optimal value of the target parameters. This target scheduling command is then sent to the corresponding devices within the dual-layer integrated charging station for execution, maximizing the economic benefits of the dual-layer integrated charging station. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of a ground-low-altitude heterogeneous collaborative energy charging control system provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of the dual-layer integrated charging station provided in the embodiments of this application; Figure 3 A schematic flowchart of the ground-low-altitude heterogeneous collaborative energy charging control method provided in the embodiments of this application; Figure 4 The combined X2G charging and discharging power curves of EV and eVTOL; Figure 5 The SOC variation curve of the energy storage system; Figure 6 A diagram illustrating the composition of the system's 24-hour operating cost after multi-objective optimization; Figure 7 This is a diagram illustrating the overall advantages assessment. Figure 8 This is the overall framework diagram; Figure 9 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] The ground-low-altitude heterogeneous coordinated energy charging control method provided in this application embodiment can be applied to, for example... Figure 1 The ground-low-altitude heterogeneous collaborative energy charging control system shown includes: A dual-layer integrated charging station 101 and an energy management controller 102 are electrically connected; like Figure 2 As shown, the dual-layer integrated charging station includes a ground-based EV charging and discharging area on the lower layer, an aerial eVTOL take-off and landing and charging and discharging area on the upper layer (the area above which is completely clear) and photovoltaic equipment (including rooftop photovoltaics and facade photovoltaics), as well as a power distribution system, energy storage system and DC bus shared by the upper and lower layers and the photovoltaic equipment; The energy management controller is used to implement the ground-low-altitude heterogeneous coordinated energy charging control method.

[0023] For example, the dual-layer integrated charging station, as the core physical carrier of the entire system, adopts a vertically layered three-dimensional structure design: The lower level is the ground-level electric vehicle charging and discharging area, which adopts an open parking layout. Each parking space is equipped with a high-power DC bidirectional fast charging pile (rated power not less than 120kW), supporting fast charging and X2G bidirectional discharge functions. The upper level is the eVTOL takeoff and landing and charging / discharging area, and its design must strictly adhere to relevant civil aviation and low-altitude aircraft safety operation regulations. The landing pad is paved with high-strength, high-temperature resistant, and anti-static special materials, and is equipped with a visual navigation lighting system, high-precision meteorological monitoring devices, and anti-collision protective fences. The charging interface uses a dedicated high-power fast charging / discharging interface (single interface rated power not less than 300kW), and has communication protocols and safety interlock functions compatible with eVTOL models. The upper and lower floors share the same power distribution system, energy storage unit, DC bus, and security monitoring backend. The power distribution system adopts a redundant configuration of "one transformer with two buses" or "two transformers with segmented buses" to improve power supply reliability. The energy storage system is connected to the DC bus through a bidirectional DC / DC converter, providing a unified energy buffer service for both the upper and lower floors. In this three-dimensional integrated structure, the eVTOL take-off and landing and charging / discharging area occupies a specific take-off and landing functional area on the roof, with an unobstructed clear space above it. The edge area that does not obstruct the eVTOL take-off and landing is equipped with roof photovoltaics. The facade photovoltaics are integrated into the building facade, the photovoltaic sunshade is integrated into the upper take-off and landing area fence, and the photovoltaic canopy is integrated into the lower entrance, achieving zero physical space conflict between low-altitude transportation functions and renewable energy production.

[0024] This three-dimensional integrated structure deeply integrates diverse transportation and energy facilities such as ground, low-altitude, and water, and for the first time constructs an integrated air-ground X2G interactive infrastructure at the physical level. Compared with the traditional independent construction model, it can save urban land resources and reduce redundant investment in power distribution capacity application and energy storage system.

[0025] For example, the energy management controller 102 can be a computer device, such as a terminal (e.g., a desktop computer, a laptop computer, etc.) or a server (e.g., a standalone server or a server cluster consisting of multiple servers, or a cloud server), for executing the ground-low-altitude heterogeneous collaborative energy charging control method.

[0026] Other specific implementation methods and beneficial effects of this system embodiment can be found in the following method embodiments, which will not be repeated here.

[0027] In one exemplary embodiment, such as Figure 3 As shown, a ground-low-altitude heterogeneous collaborative energy charging control method is provided. In this embodiment, the method is applied to... Figure 1 The energy management controller 102 in the example is described below, including the following S301 to S304.

[0028] S301. Collect the operating status data of each device in the dual-layer integrated charging station.

[0029] For example, runtime status data may include: Grid side: measured voltage at grid connection point, time-of-use electricity price, real-time carbon price, predicted voltage at distribution network nodes, etc. Photovoltaic equipment side: distributed photovoltaic ultra-short-term output forecast curve, confidence interval width, etc.; On the vehicle side: the SOC (State of Charge), rated capacity, user-set minimum SOC, X2G interaction permissions, etc. of each EV in the station; the SOC, rated capacity, estimated takeoff time, next flight route, real-time weather data (wind speed, temperature, etc.) of each eVTOL. Energy storage side: Current SOC, rated power, rated capacity, etc. of energy storage units; In addition, the equipment hardware parameters include the rated power of the charging and discharging interface, the rated voltage of the DC bus, and the upper limit of the transformer capacity.

[0030] S302. Determine that the DC bus voltage is within the preset voltage dead zone range based on the DC bus voltage and the preset voltage dead zone range.

[0031] For example, an energy self-organizing link mechanism can be set up, using the DC bus voltage signal as the physical link for energy linking, and a voltage dead zone range can be designed. , , The definition is as follows: In the formula, This is the rated voltage of the DC bus. , This is the voltage offset coefficient (obtained by setting the overvoltage tolerance standard and undervoltage protection threshold of grid-connected equipment, respectively). The upper limit threshold; The lower limit threshold; It is understandable that the voltage dead zone range This refers to the voltage range between the lower and upper threshold values.

[0032] For example, when the DC bus voltage When the system enters the energy collection and absorption mode, the injected power on the DC bus continuously exceeds the load consumption power (e.g., large-scale photovoltaic power generation within the station, low EV charging load, or excessive reverse power from the grid), the DC bus voltage will passively rise. Therefore, it is necessary to quickly absorb the excess power on the DC bus, pull the bus voltage back to the dead zone range, and prevent damage to DC-side equipment due to overvoltage. At the same time, it is necessary to realize the on-site storage and utilization of surplus energy. At this time, the energy storage system switches to the priority charging mode, absorbing the excess power of the bus at the maximum power allowed by the system to charge the energy storage battery; automatically locking the X2G discharge permission of all eVTOLs, prohibiting the eVTOL power battery from discharging to the bus, and preventing further rise in the bus voltage; the EV bidirectional fast charging pile automatically relaxes the upper limit of charging power, prioritizing the use of excess power to charge ground-based electric vehicles. when When the load power consumption on the DC bus continuously exceeds the injected power (e.g., multiple EVs / eVTOLs simultaneously charging at high power, a sudden drop in photovoltaic output, or insufficient grid power supply), the DC bus voltage will drop rapidly. Therefore, it is necessary to replenish the power gap on the DC bus to raise the bus voltage back to the dead zone range, ensuring continuous and reliable power supply to the charging load and preventing equipment shutdown due to undervoltage. At this time, the energy storage system automatically switches to priority discharge mode, releasing energy to the bus at the maximum power allowed by the system to directly support the bus voltage; it can unlock the V2G discharge permission of eligible EVs to call on the power batteries of ground vehicles to replenish the bus; if the voltage continues to drop and the gap further widens, it can unlock the discharge permission of docked eVTOLs that meet flight safety constraints, using their power batteries as emergency backup power to discharge to the bus for support.

[0033] when When the DC bus voltage is within the preset voltage dead zone, the system does not need to perform voltage regulation and can be optimized economically.

[0034] Understandably, this mechanism also ensures that the system can maintain power balance and equipment safety under abnormal operating conditions such as communication interruption.

[0035] S303. Using the flight safety requirements of eVTOL as rigid constraints, the target parameters are used as optimization variables, and the goal is to minimize the multi-objective optimization function to determine the target scheduling instructions.

[0036] The target parameters include EV, eVTOL and adjustable parameters of the energy storage system. The multi-objective optimization function is used to indicate the operating cost of the charging station, and the target scheduling instruction is used to indicate the optimal value of the target parameters.

[0037] In some possible implementations, rigid constraints include minimum flight power constraints, discharge prohibition constraints during flight mission periods, and power smoothing constraints.

[0038] For example, the minimum flight power constraint can be: In the formula, This represents the state of charge of the j-th eVTOL at time t. Let be the minimum state-of-charge threshold of the j-th eVTOL at time t.

[0039] For example, It can be dynamically calculated based on the expected flight distance of the next flight, backup power requirements, and weather conditions. The calculation expression is as follows: In the formula, For the energy needed for the next flight, there is ,in For the estimated range (km), Energy consumption per unit distance (kWh / km); This is the minimum backup energy required by aviation regulations (usually 30% to 50% of the range energy). To be based on wind speed and temperature Additional meteorological energy margin, ,in This is the wind speed correction factor (kW·h / m). Let t be the predicted wind speed (m / s). This is the temperature correction factor (kW·h / ℃). Let t be the predicted ambient temperature (°C) at time t. The optimal operating temperature (°C) for the eVTOL power battery; This is the rated capacity of the jth eVTOL.

[0040] Understandably, the minimum flight power constraint ensures that the eVTOL has the energy reserves to complete subsequent flight missions at any time.

[0041] For example, the restriction on discharging during flight missions can be: during the time when the eVTOL is performing a flight mission (including takeoff, cruise, and landing phases), external discharge is strictly prohibited, and the power battery is only used for the propulsion system.

[0042] It is understandable that prohibiting discharge during flight missions can ensure the safety of flight power supply, avoid bidirectional power surges during flight missions, and protect the airborne electrical system and battery body.

[0043] For example, the power smoothing constraint can be: In the formula, This represents the charging power of the j-th eVTOL at time t. This represents the charging power of the j-th eVTOL at time t-1. This represents the discharge power of the j-th eVTOL at time t. This represents the discharge power of the j-th eVTOL at time t-1. This represents the maximum permissible power change per step.

[0044] Understandably, power smoothing constraints can prevent drastic fluctuations in charging and discharging power from impacting battery life and the aircraft's electrical system.

[0045] For example, the constraints of multi-objective optimization also include DC bus power balance constraints, the expression of which is: In the formula, This represents the exchange power (kW) between the charging station and the power distribution network; a positive value indicates purchased electricity. Photovoltaic power output (kW). This refers to the non-charging base load (kW) within the station. The discharge power (kW) of the energy storage system. Charging power (kW) for the energy storage system. For the first The discharge power (kW) of the eVTOL. For the first The charging power (kW) of the eVTOL. For the first The charging power (kW) of an EV.

[0046] It is understandable that the DC bus power balance constraint ensures that the power commands of each device obtained by the optimization solution are physically feasible. At any given time, the injected power on the DC bus (grid power supply, photovoltaic power generation, energy storage discharge, eVTOL discharge) must be equal to the consumed power (base load, energy storage charging, eVTOL charging, EV charging).

[0047] For example, the multi-objective optimization function is shown in the following equation: in, , , , , In the formula, For the cost of purchasing electricity from the power grid, For battery cycle loss costs, For carbon emission costs, For market-based profits; , , , These are weighted by electricity purchase cost, loss cost, carbon emission cost, and market-based revenue; , , For adjustment coefficients, This is the per-unit value of the grid connection point voltage. As a flight mission urgency factor, This is the preset lower limit for the weighting of electricity purchase costs. This serves as the benchmark value for weighting battery degradation costs. For reference voltage, The estimated takeoff time for the jth eVTOL aircraft. Preset a positive number (a very small positive number, used to avoid the denominator being zero). As a benchmark value for carbon emission cost weighting, The carbon price sensitivity coefficient, for Carbon trading price at any given time (yuan·tCO2) -1 ), Reference price for carbon trading (yuan·tCO2) -1 ), As the benchmark value for market-based return weighting, The flexible capacity excitation coefficient, for The total available capacity (kWh) within the station can be flexibly adjusted to meet the needs. , For the first eVTOL adjustable discharge capacity For the adjustable charge and discharge capacity of the energy storage system, This is the upper limit of the station's flexible regulation capacity (kWh).

[0048] It is understandable that the weight coefficients in the multi-objective optimization function are not preset constants, but time-varying functions dynamically calculated based on the real-time sensing distribution network voltage deviation index and the flight mission urgency factor. This allows the optimization model to favor different optimization directions in different scenarios, and ultimately output the optimal values ​​of the target parameters for the corresponding scenario.

[0049] For example, optimization variables may include the exchange power between the charging station and the distribution network. ;No. The charging power of the eVTOL power battery Discharge power Charging power of the on-site energy storage system Discharge power ; and parameters characterizing the flexible regulation capability over long time scales, specifically the first eVTOL adjustable discharge capacity Adjustable charge / discharge capacity of energy storage systems .

[0050] Electricity purchase cost The calculation formula can be: In the formula, for Time-of-use electricity price (yuan·kWh) -1 ), The power purchased (kW, i.e., the power exchanged between the charging station and the power distribution network). To optimize the time step (h).

[0051] It's understandable that battery cycle loss costs... It consists of two parts: the first part is the charge-discharge cycle loss of the eVTOL power battery, and the second part is the charge-discharge cycle loss of the energy storage system battery. Battery cycle loss cost. The calculation formula can be: In the formula, For the first Replacement cost of the eVTOL power battery (in yuan). This is the equivalent full cycle life (times). The rated capacity (kWh) of the j-th eVTOL power battery in the station. The cost of replacing batteries in the energy storage system (in yuan). The equivalent full cycle life (cycles) of the energy storage system battery. Rated capacity (kWh) of the energy storage system.

[0052] Carbon emission costs The calculation formula can be: In the formula, Carbon trading price (yuan·tCO2) -1 ), For the carbon emission factor of the power grid (tCO2·kWh) -1 ).

[0053] Market-based returns The calculation formula can be: In the formula, Demand response compensation electricity price (yuan·kWh) -1 ), For flexible regulation power (kW) participating in demand response. Peak shaving service price (yuan·kWh) -1 ), Peak shaving power (kWh).

[0054] in, The adjustable discharge capacity of the eVTOL within the station and the adjustable charge / discharge capacity of the energy storage system are jointly determined, and the following requirements should be met. Peak-shaving power Defined as .

[0055] Understandable, the first Adjustable discharge capacity of eVTOL Larger, adjustable charge and discharge capacity of energy storage system The larger the value, the greater the flexible regulation power and peak-shaving power that can participate in demand response, and the greater the market benefits. The higher.

[0056] Furthermore, when determining the target scheduling command, the ground-low-altitude heterogeneous coordinated energy charging control method includes: According to the safety-first arbitration agreement, the weights of loss costs and market-based benefits are determined. A security-first arbitration agreement includes: when If the weight of loss cost exceeds a preset urgency threshold, the weight is determined to be a preset positive number (a very large positive number, used to greatly increase battery safety priority) that is greater than the weight of electricity purchase cost and carbon emission cost and differs by at least two orders of magnitude; the weight of market revenue is 0. The weight of electricity purchase cost is determined as follows: The market-based revenue weight is 0; This is the lower limit of the node voltage safety (pu). The safe upper limit for node voltage (pu).

[0057] It is understandable that through the safety-first arbitration agreement, the weights can be forcibly adjusted when the flight mission is urgent or the grid voltage exceeds the limit, so that the system can automatically and smoothly switch between the three modes of maximizing green energy consumption, maximizing market benefits, and maximizing safety margin.

[0058] For example, the multi-objective optimization function can be solved using existing solvers (such as commercial MILP solvers like CPLEX and Gurobi, interior-point solvers like Ipopt) to obtain the optimal values ​​of the objective parameters, which in turn yields the objective scheduling instruction.

[0059] S304. Send the target scheduling command to the corresponding equipment in the dual-layer integrated charging station for execution.

[0060] For example, the corresponding equipment in the dual-layer integrated charging station can update the value of the target parameter to the optimal value of the target parameter in the target scheduling instruction, thereby maximizing the economic benefits of the dual-layer integrated charging station.

[0061] This application embodiment collects the operating status data of each device in the dual-layer integrated charging station; based on the DC bus voltage and the preset voltage dead zone range, it determines that the DC bus voltage is within the preset voltage dead zone range. At this time, there is no need to perform voltage regulation for charging or discharging, avoiding voltage pressure risks in subsequent optimization; using the flight safety requirements of eVTOL as a rigid constraint, it can be ensured that the optimization results will not affect the flight safety of eVTOL. The target parameters (adjustable parameters of EV, eVTOL and energy storage system) are used as optimization variables. With the multi-objective optimization function that minimizes the operating cost of the charging station as the optimization objective, the heterogeneous X2G resources of EV and eVTOL can be integrated and optimized together to maximize economic benefits, thereby obtaining the target scheduling instruction with the optimal value of the target parameters; the target scheduling instruction is issued to the corresponding device in the dual-layer integrated charging station for execution, thereby maximizing the economic benefits of the dual-layer integrated charging station.

[0062] In some possible embodiments, after determining that the DC bus voltage is within a preset voltage dead zone range, the ground-low-altitude heterogeneous coordinated charging control method further includes: When the aggregated charge state of EVs in the station is less than the preset aggregated charge state safety threshold, the minimum flight charge constraint is updated according to the preset minimum flight charge margin value.

[0063] For example, the preset aggregated state of charge safety threshold can be determined by the following formula: in, This indicates the preset safe threshold for the aggregated state of charge. The minimum permissible state of charge set for the i-th EV; Let i be the rated capacity of the i-th EV; An additional safety margin is added (which can be determined based on historical travel patterns and grid demand response capacity requirements, with a typical value range of [0.05, 0.15]).

[0064] For example, the aggregated state of charge (AUC) of EVs within the station can be fed back to the energy management controller in real time via a data bus. When the AUC of EVs within the station is lower than a preset AUC safety threshold, the constraint threshold in the minimum flight power constraint of the eVTOL (which can be the threshold in the aforementioned embodiment) is adjusted. Increase the preset minimum flight battery margin value (which is about to be increased) (Added to the preset minimum flight battery margin value) to complete the update of the minimum flight battery constraint.

[0065] This ensures the safety of eVTOL flight missions even when the EV group's adjustment capabilities are insufficient.

[0066] In some possible embodiments, after determining that the DC bus voltage is within a preset voltage dead zone range, the ground-low-altitude heterogeneous coordinated charging control method further includes: Calculate the predicted voltage values ​​of distribution network nodes based on power flow sensitivity; When the difference between the predicted voltage of a distribution network node and the preset safe lower limit of the node voltage is less than the preset difference threshold, and there is a target eVTOL in the dual-layer integrated charging station that is in a ground-based docking state and whose battery power meets the minimum flight power constraint, the adjustable discharge capacity of the target eVTOL is determined as the target parameter.

[0067] For example, the predicted voltage value of a distribution network node can be determined by the following formula: in, For node k in Predicted voltage values ​​at distribution network nodes at any given time. This is the measured voltage value at the current node k. This is the sensitivity coefficient of node voltage to injected power (which can be calculated offline from the distribution network admittance matrix). This is a predicted value for ultra-short-term power changes. The sensitivity coefficient of node k voltage to load power changes (pu / kW, which can be calculated offline from the distribution network admittance matrix) is given. For nodes The predicted value of load power change (kW).

[0068] It is understandable that when the difference between the predicted voltage value of a distribution network node and the preset safe lower limit of the node voltage is less than the preset difference threshold, it is essentially due to excessive regional load, excessive active power transmission from the grid, and excessive line voltage drop. If the target eVTOL discharge permission is unlocked at this node, and its power battery is used as an emergency backup power source for the distribution network, and participates in subsequent optimization through adjustable discharge capacity, the active current transmitted from the upper-level grid to this area will be directly reduced, the line voltage drop will decrease simultaneously, and the node voltage will quickly rise back to the safe range, thus achieving a safe and deep coupling between air traffic resources and ground grid resources.

[0069] In some possible embodiments, after determining that the DC bus voltage is within a preset voltage dead zone range, the ground-low-altitude heterogeneous coordinated charging control method further includes: When the current adjustable capacity of the EV in the station is lower than the preset adjustable capacity safety threshold, the target minimum flight power margin value is determined based on the current adjustable capacity and the preset adjustable capacity safety threshold. Update the minimum flight power constraint based on the target minimum flight power margin value.

[0070] For example, the target minimum flight power margin can be determined by the following formula: In the formula, The target minimum flight power margin value, To adjust the coefficient, The current available capacity for EVs within the station can be reduced. To preset an adjustable capacity safety threshold, This is the base margin value.

[0071] For example, when the current adjustable capacity of the EV in the station is lower than a preset adjustable capacity safety threshold, the constraint threshold in the minimum flight power constraint of the eVTOL (which can be the threshold in the aforementioned embodiment) can be adjusted. The minimum flight power margin is added to the target minimum flight power margin value to update the minimum flight power constraint.

[0072] It's understandable that when the current adjustable capacity of EVs within the station falls below the preset adjustable capacity safety threshold, it indicates the depletion of the ground-based flexible regulation resource pool (e.g., a large number of EVs leaving the site, and generally low vehicle SOC). The original ability of EVs to handle grid voltage regulation, smooth solar power fluctuations, and peak shaving and valley filling is significantly reduced. Under normal operating conditions, EV discharge is prioritized to cover grid power shortages and voltage drops. After an EV fails, the system can only rely on energy storage or even temporarily unlocking eVTOL discharge to support the grid, continuously consuming the aircraft's reserve power and directly threatening flight safety. Therefore, raising the minimum flight power constraint at this time essentially provides a larger power safety buffer for eVTOL in advance.

[0073] For example, while updating the minimum flight power constraints, the reserved capacity for grid power purchases can also be increased simultaneously.

[0074] For example, the increase in the reserve capacity for power grid purchases can be determined by the following formula: In the formula, This represents the increase in the reserved capacity for power grid purchases. This refers to the change in the minimum flight power margin (pu) for the aforementioned target. This represents the sum of the rated capacities (kWh) of all eVTOL power batteries within the station. This indicates the reserved capacity response time step (h).

[0075] It is understandable that increasing the reserve capacity for purchasing electricity from the power grid is to lock in a certain amount of power that can be used at any time from the distribution network in advance. When the energy storage in the station discharges to the lower limit and the eVTOL is limited to discharge due to the increase of the minimum SOC, the system can immediately increase the purchase of electricity from the power grid to make up for the power shortage in the station and avoid the DC bus voltage drop and the low voltage over-limit of the distribution network node.

[0076] In some possible embodiments, after determining that the DC bus voltage is within a preset voltage dead zone range, the ground-low-altitude heterogeneous coordinated charging control method further includes: When the confidence interval width of the photovoltaic ultra-short-term prediction is greater than the preset confidence interval width threshold, the upper limit of the state of charge of the energy storage system and the lower limit of the state of charge of the energy storage system are updated according to the confidence interval width of the photovoltaic ultra-short-term prediction and the preset confidence interval width threshold.

[0077] For example, the upper limit of the state of charge (SBC) and the lower limit of the SBC of the energy storage system can be updated using the following formula: In the formula, This indicates the updated state of charge limit of the energy storage system. This indicates the updated upper limit of the state of charge of the energy storage system. This indicates the state of charge limit of the energy storage system before the update. This indicates the upper limit of the state of charge of the energy storage system before the update. This is the energy storage margin adjustment coefficient. The width of the confidence interval for ultra-short-term photovoltaic forecasts. To set a threshold for the width of the preset information interval.

[0078] In this way, the interference of random photovoltaic power output fluctuations on eVTOL charging can be isolated, avoiding insufficient power supply to the aircraft due to sudden changes in sunlight, and reducing the transmission of short-term drastic fluctuations in photovoltaic power within the station to the distribution network, thereby alleviating the pressure on distribution network voltage regulation.

[0079] To further illustrate the effects of this application, simulation was conducted to obtain... Figures 4 to 7 The simulation results.

[0080] Figure 4 The combined X2G charging and discharging power curves of EV and eVTOL allow for a direct observation of how eVTOL's short-term high-power discharge support during evening peak hours complements the EV's long-term flexible adjustment.

[0081] Figure 5 The SOC variation curve of the energy storage system reflects the dynamic adjustment process of energy storage in the face of photovoltaic power output fluctuations and grid support events.

[0082] Figure 6 This diagram illustrates the composition of the 24-hour operating cost of the system after multi-objective optimization. It clearly shows the structural proportions of grid purchase costs, battery loss costs, carbon emission costs, and market revenue, making the green electricity self-sufficiency rate and cost optimization effect readily apparent.

[0083] Figure 7 This diagram illustrates the comprehensive advantages of the proposed solution. It compares the effectiveness of the proposed solution with that of the traditional independent dispatching solution from multiple dimensions, including grid support capacity, flight safety assurance, green energy consumption level, operational economy, and heterogeneous collaboration level.

[0084] For example, to quantitatively evaluate the technical effects of this application, the following comprehensive advantage evaluation indicators are defined. Each indicator is based on a simulation period. (24h, step size) The system calculates operational data within the system, and except for flight safety indicators, all other indicators are compared with the traditional independent scheduling scheme (i.e., the scheme in which EV charging stations and eVTOL charging facilities operate independently and optimized).

[0085] Power grid support capacity indicators Measured by the improvement rate of grid connection point voltage deviation, its calculation expression is: In the formula, Under the present invention The per-unit value of the grid connection point voltage at a given time. This represents the per-unit value of the grid connection point voltage at the same moment under the traditional scheme. This is the reference voltage (usually 1.0 pu). The larger the value, the more significant the improvement effect of the present invention on the voltage quality of the distribution network.

[0086] Flight safety assurance indicators Measured by the minimum SOC safety margin across the entire fleet and all time periods, its calculation formula is as follows: In the formula, For the first eVTOL in State of charge at time t, The corresponding minimum state of charge threshold (dynamically calculated according to the aforementioned minimum flight charge constraint formula). This is the eVTOL collection within the site. Take the worst-case scenario for the entire fleet over the entire lifecycle. The larger the value, the greater the safety margin for flight.

[0087] Green electricity consumption level indicators Measured by the local photovoltaic power consumption rate, its calculation formula is as follows: In the formula, for The photovoltaic power output of the station at all times for Total charging power within the station at any given time. ,in, For the first The charging power (kW) of an EV. The larger the value, the higher the proportion of photovoltaic power generation that is consumed locally within the station, and the less power is fed back to the distribution network.

[0088] Operating economic indicators Measured by the overall operating cost reduction rate, its calculation formula is as follows: In the formula, This refers to the cumulative value of the multi-objective optimization function of the present invention during the simulation period (i.e., the aforementioned). (cumulative value within the period) This represents the sum of the cumulative values ​​of the objective functions of each traditional independent scheduling scheme under the same operating conditions after optimization. The larger the value, the more significant the reduction in overall operating costs.

[0089] Heterogeneous synergy level index The combined EV and eVTOL response coverage is measured and calculated using the following formula: In the formula, This refers to the set of time periods during which the distribution network voltage exceeds the limit. This is the per-unit value of the grid connection point voltage. , These are the lower and upper safety limits for node voltage, respectively. The set of time periods during which EV and eVTOL simultaneously participate in the discharge response within the voltage over-limit period is given. ,in, for The total discharge power of all EVs within the station at any given time; for The total discharge power of all ground-based eVTOLs within the time station is That's understandable. The selection focuses on the voltage over-limit period because the system does not require additional coordinated discharge support when the voltage is normal. The advantage of heterogeneous coordination is precisely reflected in the joint response capability when dealing with extreme conditions such as voltage over-limit. The larger the value, the more fully the heterogeneous synergy and complementarity between the EV's long-term flexible adjustment capability and the eVTOL's short-term high-power support capability.

[0090] It is understandable that the above five indicators quantify the technical effects of this invention from the perspectives of the power grid, aircraft, new energy, economy, and synergy, respectively. to Converting to percentage indicators of 0%–100% can be done on a radar chart (such as...). Figure 7 The advantages of the present invention and traditional solutions in various dimensions are presented uniformly and intuitively compared in the same way.

[0091] Figure 8 This is a general framework diagram of the present application, which illustrates the overall framework of the present application.

[0092] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 9 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When the computer program is executed by the processor, it implements the aforementioned ground-low-altitude heterogeneous collaborative charging control method.

[0093] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0094] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0095] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0096] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0097] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0098] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0099] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0100] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0101] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A ground-low-altitude heterogeneous collaborative energy charging control method, characterized in that, An energy management controller is applied in a ground-low-altitude heterogeneous collaborative charging control system. The ground-low-altitude heterogeneous collaborative charging control system includes a dual-layer integrated charging station and an energy management controller, with the dual-layer integrated charging station electrically connected to the energy management controller. The dual-layer integrated charging station includes a lower-layer ground-based EV charging / discharging area, an upper-layer airborne eVTOL takeoff and landing / charging / discharging area and photovoltaic equipment, as well as a shared power distribution system, energy storage system, and DC bus for the upper and lower layers and the photovoltaic equipment. The ground-low-altitude heterogeneous collaborative charging control method includes: Collect operational status data of each device within the dual-layer integrated charging station; Based on the DC bus voltage and the preset voltage dead zone range, it is determined that the DC bus voltage is within the preset voltage dead zone range; Using the flight safety requirements of eVTOL as a rigid constraint, the target parameters are used as optimization variables, and minimizing the multi-objective optimization function is the optimization objective to determine the target scheduling instruction. The target parameters include the adjustable parameters of EV, eVTOL, and energy storage system. The multi-objective optimization function is used to indicate the operating cost of the charging station, and the target scheduling instruction is used to indicate the optimal value of the target parameters. The target scheduling command is sent to the corresponding equipment in the dual-layer integrated charging station for execution.

2. The ground-low-altitude heterogeneous coordinated energy charging control method according to claim 1, characterized in that, The rigid constraints include minimum flight power constraints, discharge prohibition constraints during flight mission periods, and power smoothing constraints.

3. The ground-low-altitude heterogeneous coordinated energy charging control method according to claim 2, characterized in that, After determining that the DC bus voltage is within the preset voltage dead zone range, the ground-low-altitude heterogeneous collaborative charging control method further includes: When the aggregated charge state of EVs in the station is less than the preset aggregated charge state safety threshold, the minimum flight charge constraint is updated according to the preset minimum flight charge margin value.

4. The ground-low-altitude heterogeneous coordinated energy charging control method according to claim 2, characterized in that, After determining that the DC bus voltage is within the preset voltage dead zone range, the ground-low-altitude heterogeneous collaborative charging control method further includes: Calculate the predicted voltage values ​​of distribution network nodes based on power flow sensitivity; When the difference between the predicted value of the distribution network node voltage and the preset node voltage safety lower limit is less than the preset difference threshold, and there is a target eVTOL in the dual-layer integrated charging station that is in a ground-based docking state and whose battery power meets the minimum flight power constraint, the adjustable discharge capacity of the target eVTOL is determined as the target parameter.

5. The ground-low-altitude heterogeneous coordinated energy charging control method according to claim 2, characterized in that, After determining that the DC bus voltage is within the preset voltage dead zone range, the ground-low-altitude heterogeneous collaborative charging control method further includes: When the current adjustable capacity of the EV in the station is lower than the preset adjustable capacity safety threshold, the target minimum flight power margin value is determined based on the current adjustable capacity and the preset adjustable capacity safety threshold. The minimum flight power constraint is updated based on the target minimum flight power margin value.

6. The ground-low-altitude heterogeneous coordinated energy charging control method according to claim 1, characterized in that, The multi-objective optimization function is shown in the following equation: in, , ， ， ， In the formula, For the cost of purchasing electricity from the power grid, For battery cycle loss costs, For carbon emission costs, For market-based profits; , , , These are weighted by electricity purchase cost, loss cost, carbon emission cost, and market-based revenue; , , For adjustment coefficients, This is the per-unit value of the grid connection point voltage. As a flight mission urgency factor, This is the preset lower limit for the weighting of electricity purchase costs. This serves as the benchmark value for weighting battery degradation costs. For reference voltage, The estimated takeoff time for the jth eVTOL aircraft. As a preset positive number, As a benchmark value for carbon emission cost weighting, The carbon price sensitivity coefficient, for The carbon trading price at any given time. For carbon trading reference prices, As the benchmark value for market-based return weighting, The flexible capacity excitation coefficient, for The total capacity within the station can be flexibly adjusted to meet the needs. , For the first eVTOL adjustable discharge capacity For the adjustable charge and discharge capacity of the energy storage system, This represents the upper limit of the station's flexible adjustment capacity.

7. The ground-low-altitude heterogeneous coordinated energy charging control method according to claim 6, characterized in that, When determining the target scheduling command, the ground-low-altitude heterogeneous collaborative energy charging control method includes: According to the safety-first arbitration agreement, the weights of loss costs and market-based benefits are determined. The security-first arbitration agreement includes: when If the value exceeds a preset urgency threshold, the loss cost weight is determined to be a preset positive number that is greater than the electricity purchase cost weight and the carbon emission cost weight, and differs by at least two orders of magnitude; the market-based revenue weight is 0. The weight of electricity purchase cost is determined as follows: The market-based revenue weight is 0; This is the lower limit of the node voltage safety. This is the upper limit for the safe voltage of the node.

8. A ground-low-altitude heterogeneous collaborative energy charging control system, characterized in that, The ground-low-altitude heterogeneous collaborative energy charging control system includes: A dual-layer integrated charging station and an energy management controller, wherein the dual-layer integrated charging station is electrically connected to the energy management controller; The dual-layer integrated charging station includes a ground-based EV charging and discharging area in the lower layer, an aerial eVTOL take-off and landing and charging and discharging area and photovoltaic equipment in the upper layer, as well as a power distribution system, energy storage system and DC bus shared by the upper and lower layers and the photovoltaic equipment; The energy management controller is used to execute the ground-low-altitude heterogeneous collaborative energy charging control method according to any one of claims 1-7.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the ground-low-altitude heterogeneous coordinated energy charging control method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the ground-low-altitude heterogeneous coordinated energy charging control method according to any one of claims 1-7.

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