Internet of vehicles and photovoltaic hydrogen production collaborative scheduling method and system

Abstract

The application relates to the technical field of photovoltaic power supply and distribution, and discloses a vehicle networking photovoltaic hydrogen production collaborative scheduling method and system. The method comprises the following steps: constructing a station time matrix by collecting hydrogen storage amounts and position information of hydrogen energy vehicles; calculating a preheating time length based on the alkali temperature of an electrolytic tank and determining an optimal hot start time; taking the optimal hot start time as a time anchor point, matching a photovoltaic power distribution window, and issuing a power distribution instruction; and in the case of multi-station conflict, completing photovoltaic power redistribution by combining a heat loss cost with a station urgency. The application improves the effective consumption rate of photovoltaic power and the timing coordination accuracy of regional hydrogen energy vehicle energy supplement scheduling.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power supply and distribution technology, and in particular to a method and system for coordinated scheduling of photovoltaic hydrogen production via vehicle networking. Background Technology

[0002] With the advancement of large-scale demonstration applications of hydrogen fuel cell vehicles, photovoltaic-driven water electrolysis hydrogen production technology has been widely deployed in regional hydrogen refueling networks due to its green and low-carbon hydrogen production path. Existing hydrogen production station scheduling methods typically use a single hydrogen production station as the control unit, relying on the detection of hydrogen storage levels after a vehicle arrives to trigger hydrogen production. A typical implementation involves using GPS positioning to determine if a vehicle is approaching a refueling station; when the station's hydrogen storage level is detected to be lower than the arriving vehicle's demand, the electrolyzer is controlled to start incremental hydrogen production above the baseline. In scenarios where photovoltaic power output is intermittent and fluctuating, the hydrogen production behavior of the hydrogen production station is entirely driven by the vehicle arrival event, lacking a pre-planned timing coordination mechanism between photovoltaic power output plans and vehicle refueling needs.

[0003] However, alkaline electrolyzers require a complete preheating process to reach their rated operating temperature from a cold state. During this preheating period, the electrolyzer continuously consumes heating power without producing hydrogen, creating a pure energy loss window. Existing scheduling methods treat the electrolyzer's thermal state merely as a fixed response delay parameter within the hydrogen production station, failing to couple the preheating duration with the predicted vehicle arrival time or align peak photovoltaic output with the electrolyzer's entry into efficient hydrogen production mode. This leads to two frequent contradictions in actual operation: first, photovoltaic output is at its peak while the electrolyzer is still in the preheating stage, resulting in insufficient photovoltaic power utilization and wasted solar power; second, the electrolyzer temperature is below the rated operating temperature when vehicles arrive, leading to low hydrogen production efficiency and prolonged vehicle waiting times. The root cause of these contradictions lies in the fact that existing technologies always take the supply side as the starting point for scheduling, lacking the technical means to transmit hydrogen-consuming timing information back to the power supply and distribution scheduling layer. Summary of the Invention

[0004] This application provides a vehicle-to-everything (V2X) photovoltaic hydrogen production collaborative scheduling method and system, which solves the problems in the prior art where the thermal state of the electrolyzer and the predicted arrival time of the vehicle are disconnected, resulting in the misalignment between the peak output of photovoltaic power and the efficient hydrogen production period of the electrolyzer, as well as the lack of a power allocation priority mechanism based on the joint quantification of heat loss cost and arrival urgency in multi-station scenarios. It improves the effective absorption rate of photovoltaic power and the timing coordination accuracy of regional hydrogen energy vehicle refueling scheduling.

[0005] Firstly, this application provides a vehicle-to-everything (V2X) photovoltaic-hydrogen production collaborative scheduling method, the V2X photovoltaic-hydrogen production collaborative scheduling method comprising: Step S1: Collect hydrogen storage capacity and location information of hydrogen-powered vehicles in the area, calculate the predicted arrival time of each vehicle to each hydrogen production station based on the road network travel time, and obtain the arrival time matrix. Step S2: Read the current temperature and rated operating temperature of the alkaline solution in the electrolyzer of each hydrogen production station. Divide the difference between the current temperature and the rated operating temperature of the alkaline solution and the product of the mass of the alkaline solution and the specific heat capacity by the preheating power to obtain the preheating time. Subtract the preheating time and the safety margin time from the predicted arrival time in the arrival time matrix to obtain the optimal hot start time of each hydrogen production station. Step S3: Using the optimal hot start time as the time anchor point, retrieve a continuous time period in the photovoltaic output prediction curve that is not less than the sum of the electrolyzer preheating power and the rated hydrogen production power to obtain the photovoltaic power allocation window, and issue a power allocation instruction to the corresponding hydrogen production station with the photovoltaic power allocation window as the power supply interval. Step S4: When the optimal hot start time of multiple hydrogen production stations overlaps with the same peak photovoltaic output period, the product of the heat loss power of each hydrogen production station and the delayed start time is used as the heat loss cost. The power allocation instructions of each hydrogen production station are prioritized based on the urgency of arrival, and the photovoltaic power is redistributed.

[0006] Secondly, this application provides a vehicle-to-everything (V2X) photovoltaic-hydrogen production collaborative scheduling system, the V2X photovoltaic-hydrogen production collaborative scheduling system comprising: The calculation module is used to collect the hydrogen storage capacity and location information of hydrogen-powered vehicles in the region, calculate the predicted arrival time of each vehicle to each hydrogen production station based on the road network travel time, and obtain the arrival time matrix. The analysis module is used to read the current temperature and rated operating temperature of the alkaline solution in the electrolyzer of each hydrogen production station, divide the difference between the current temperature and the rated operating temperature of the alkaline solution and the product of the mass of the alkaline solution and the specific heat capacity by the preheating power to obtain the preheating time, and subtract the preheating time and the safety margin time from the predicted arrival time corresponding to the arrival time matrix to obtain the optimal hot start time of each hydrogen production station. The allocation module is used to retrieve a continuous period in the photovoltaic output prediction curve that is not less than the sum of the electrolyzer preheating power and the rated hydrogen production power, with the optimal hot start time as the time anchor point, to obtain the photovoltaic power allocation window, and to issue a power allocation instruction to the corresponding hydrogen production station with the photovoltaic power allocation window as the power supply interval. The sorting module is used to prioritize the power allocation instructions of each hydrogen production station when the optimal hot start time of multiple hydrogen production stations overlaps with the same peak photovoltaic output period. The module uses the product of the heat loss power of each hydrogen production station and the delayed start time as the heat loss cost, and combines the urgency of arrival at the station to complete the redistribution of photovoltaic power.

[0007] Thirdly, a vehicle-to-everything (V2X) photovoltaic-hydrogen production collaborative scheduling device is provided, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the V2X photovoltaic-hydrogen production collaborative scheduling device to execute the aforementioned V2X photovoltaic-hydrogen production collaborative scheduling method.

[0008] Fourthly, a computer-readable storage medium is provided, wherein instructions are stored in the computer and, when executed on a computer, cause the computer to perform the above-described vehicle-to-everything (V2X) photovoltaic-hydrogen production coordinated scheduling method.

[0009] The technical solution provided in this application transforms the physical preheating constraint of the electrolyzer into a time quantity that can participate in scheduling decisions—the preheating duration—by dividing the product of the difference between the current temperature of the alkali solution and the rated operating temperature, and the product of the alkali solution mass and specific heat capacity, by the preheating power. Then, the optimal hot start time is obtained by subtracting the preheating duration and safety margin time from the earliest predicted arrival time of each hydrogen production station in the arrival time matrix. This calculation logic binds the thermal state parameters, originally isolated within the hydrogen production station, with the vehicle timing information from the vehicle network side on the same time axis, transforming the electrolyzer preheating start-up behavior from a passive internal equipment response into an active scheduling variable driven by vehicle arrival prediction information. By using the optimal hot start time as the time anchor point, continuous time periods that satisfy the sum of preheating power and rated hydrogen production power are retrieved from the photovoltaic power output prediction curve. This makes the determination of the photovoltaic power allocation window subject to the dual constraints of the electrolyzer's thermophysical constraints and the photovoltaic power output characteristics. Thus, for the first time at the power supply and distribution scheduling level, the coordinated alignment of vehicle refueling timing, electrolyzer thermal efficiency timing, and photovoltaic power output timing has been achieved, solving the fundamental problem of the misalignment between the peak photovoltaic power output and the high-efficiency hydrogen production state of the electrolyzer in the existing technology.

[0010] In multi-station scenarios, the product of heat loss power and delayed start-up time is used as the heat loss cost. Combined with the arrival urgency coefficient, which is obtained by taking the reciprocal of the difference between the earliest predicted arrival time and the current system timestamp, a weighted sum is used to obtain the comprehensive priority score of each power conflicting station. This unifies the two heterogeneous dimensions of heat physical loss cost and traffic time urgency to the same comparable quantitative index. This algorithm design makes power allocation decisions no longer dependent on a single-dimensional ranking criterion. The introduction of heat loss cost ensures that stations with high heat dissipation loss obtain an allocation weight commensurate with their physical loss in power competition, while the introduction of arrival urgency ensures that the demand of vehicles with the strongest energy replenishment timeliness is given priority in power allocation. The weighted combination of the two ensures that the redistribution of photovoltaic power in multi-station conflict scenarios takes into account both the thermal economy on the equipment side and the energy replenishment timeliness on the user side. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of one embodiment of the vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method in this application. Figure 2 This is a schematic diagram of the arrival time matrix in the embodiments of this application. Detailed Implementation

[0013] This application provides a method and system for coordinated scheduling of vehicle-to-everything (V2X) photovoltaic hydrogen production. The terms "first," "second," "third," "fourth," etc. (if present)," in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method in this application includes: Step S1: Collect hydrogen storage capacity and location information of hydrogen-powered vehicles in the area, calculate the predicted arrival time of each vehicle to each hydrogen production station based on the road network travel time, and obtain the arrival time matrix. Specifically, the arrival time matrix is ​​a two-dimensional timetable constructed using the vehicle number to be refueled as the row index and the hydrogen production station number within the region as the column index. Each element in the matrix records the predicted arrival time of the corresponding vehicle heading to the corresponding hydrogen production station. This time is obtained by adding the travel time calculated from the vehicle's current GPS coordinates using the road network shortest path algorithm to the current system timestamp. The hydrogen refueling trigger threshold is set at 25% of the rated capacity of the hydrogen storage tank. This value is determined based on the range safety margin of fuel cell vehicles in the low hydrogen range; below this percentage, the vehicle faces the risk of driving interruption. The road network shortest path algorithm uses the average historical travel time for vehicles on fixed routes and the Dijkstra algorithm with real-time congestion coefficient weighting for freely moving vehicles. The distinction between the two types of vehicles is based on the vehicle task type label field.

[0015] Step S2: Read the current temperature and rated operating temperature of the alkaline solution in the electrolyzer of each hydrogen production station. Divide the difference between the current temperature and the rated operating temperature of the alkaline solution, the product of the mass of the alkaline solution and the specific heat capacity, by the preheating power to obtain the preheating time. Subtract the preheating time and the safety margin time from the predicted arrival time in the arrival time matrix to obtain the optimal hot start time of each hydrogen production station. Specifically, the preheating time is calculated by dividing the heat required for the alkaline solution to rise from its current temperature to its rated operating temperature by the preheating power. The mass and specific heat capacity of the alkaline solution are retrieved from the hydrogen production station's equipment log. The specific heat capacity of the alkaline solution in the alkaline electrolyzer is taken as 3.8 kJ / (kg·℃), which is the standard thermal parameter for 30% KOH solution within the engineering application temperature range. A fixed safety margin of 5 minutes is used to cover deviations in the heating rate introduced by factors such as fluctuations in alkaline solution flow and changes in ambient temperature during the preheating calculation, ensuring that the electrolyzer is fully operational at full power before the vehicle arrives, rather than in the unstable range at the end of the heating phase. The optimal hot start time is obtained by subtracting the preheating time and safety margin time from the earliest arrival time. If this calculated result is earlier than the current system timestamp, it indicates that the electrolyzer cannot complete preheating according to the ideal sequence. The hot start time is then corrected to the current timestamp and marked as a lagging hot start station for separate handling during subsequent power redistribution.

[0016] Step S3: Using the optimal hot start time as the time anchor point, search for a continuous period in the photovoltaic output prediction curve that is not less than the sum of the electrolyzer preheating power and the rated hydrogen production power to obtain the photovoltaic power allocation window, and issue a power allocation instruction to the corresponding hydrogen production station with the photovoltaic power allocation window as the power supply interval. Specifically, the photovoltaic output prediction curve is discretized into an output prediction sequence with a time granularity of 15 minutes. Starting from the optimal hot start time, the sequence is traversed backwards. Within a continuous time period, the predicted photovoltaic output value for each granularity is no less than the sum of the electrolyzer preheating power and the rated hydrogen production power. This continuous time period constitutes the photovoltaic power allocation window. The unit hydrogen production energy consumption is taken as the measured value of the alkaline electrolyzer at its rated operating temperature, typically ranging from 4.5 to 5.5 kWh / kg. Specific values ​​are provided by the equipment ledgers of each hydrogen production station. The expected hydrogen production within the window is obtained by dividing the net hydrogen production power of each granularity within the window by the unit hydrogen production energy consumption, multiplying by the time granularity conversion factor, and summing the results. This hydrogen production is compared with the total hydrogen replenishment demand of vehicles heading to the corresponding station. If the difference is negative, the station is marked as a power conflict station.

[0017] Step S4: When the optimal hot start-up time of multiple hydrogen production stations overlaps with the same peak photovoltaic output period, the product of the heat loss power of each hydrogen production station and the delayed start-up time is used as the heat loss cost. The power allocation instructions for each hydrogen production station are prioritized based on the urgency of arrival, thus completing the redistribution of photovoltaic power. Specifically, the heat loss cost is defined as the product of the heat dissipation power of the electrolyzer in the current thermal state of the hydrogen production station and the delay time corresponding to postponing the optimal hot start time to the start of the second-optimal photovoltaic window. The heat dissipation power is obtained from the measured data of the thermal instruments at the station, and the delay time is calculated from the difference between the start time of the second-optimal window and the optimal hot start time. The arrival urgency coefficient is the reciprocal of the difference between the earliest predicted arrival time of all vehicles waiting to refuel at the station and the current system timestamp; the smaller the difference, the larger the urgency coefficient. The comprehensive priority score is obtained by multiplying the arrival urgency coefficient by a weighting coefficient of 0.6 and the standardized value obtained by dividing the heat loss cost by the rated hydrogen production power by a weighting coefficient of 0.4. The sum of the two weights is 1. The allocation of 0.6 and 0.4 is based on the engineering experience that the timeliness of vehicle refueling takes precedence over the control of equipment heat loss in actual operation. Power conflict stations are sorted from high to low according to this score and then allocated available photovoltaic power windows in turn.

[0018] In one specific embodiment, step S1 includes: Based on the ratio of the current pressure to the rated pressure of the hydrogen storage tank of each hydrogen fuel cell vehicle, the rated capacity of the hydrogen storage tank is proportionally converted to obtain the current hydrogen storage capacity of each hydrogen fuel cell vehicle. The current hydrogen storage capacity is compared with the preset hydrogen replenishment trigger threshold, and hydrogen fuel cell vehicles whose current hydrogen storage capacity is lower than the hydrogen replenishment trigger threshold are selected to obtain a set of vehicles to be replenished with hydrogen. Based on the real-time location of each vehicle in the set of vehicles waiting for hydrogen replenishment, the travel time of each vehicle to each hydrogen production station in the region is calculated using the road network shortest path algorithm, and the travel time sequence of each vehicle to each hydrogen production station is obtained. The current system timestamp is added to the corresponding travel time in the travel time series to obtain the predicted arrival time of each vehicle in the set of vehicles to be replenished with hydrogen to each hydrogen production station. The predicted arrival times are then arranged by indexing the correspondence between vehicles and hydrogen production stations to obtain the arrival time matrix.

[0019] Specifically, the hydrogen in the hydrogen storage tank approximately exhibits isothermal compression characteristics within the engineering application pressure range, and the hydrogen storage capacity is linearly proportional to the tank pressure. Therefore, the current hydrogen storage capacity of each hydrogen fuel cell vehicle is obtained by multiplying the ratio of the current pressure of the storage tank to the rated pressure by the rated capacity of the storage tank, in kilograms. The hydrogen replenishment trigger threshold is set at 25% of the rated capacity of the storage tank. This value is determined based on the range safety margin of fuel cell vehicles in the low hydrogen storage range. When the hydrogen storage capacity is lower than this percentage, the vehicle faces the risk of running out of hydrogen on the way to the hydrogen production station. The 25% threshold retains a reasonable safety margin while covering the hydrogen consumption required to reach the nearest hydrogen production station. Vehicles with a current hydrogen storage capacity lower than the hydrogen replenishment trigger threshold are included in the hydrogen replenishment waiting vehicle set. This set is indexed by the vehicle's unique identifier and records the real-time GPS coordinates and hydrogen replenishment demand of each vehicle. The hydrogen replenishment demand is obtained by subtracting the current hydrogen storage capacity from the rated capacity of the storage tank.

[0020] For each vehicle in the set of vehicles awaiting hydrogen replenishment, the travel time is calculated using the road network shortest path algorithm, starting from its real-time GPS coordinates and ending at the geographical coordinates of each hydrogen production station within the region. For vehicles on fixed routes, the travel time is the average of historical travel times for the same route at the same time. For vehicles traveling freely, the travel time is calculated using Dijkstra's algorithm with real-time congestion coefficient weighting. The distinction between the two types of vehicles is based on the task type tag field in the vehicle registration information. The travel time of each vehicle to all hydrogen production stations within the region constitutes its travel time sequence. The current system timestamp is added to the corresponding travel time for each hydrogen production station in the travel time sequence to obtain the predicted arrival time of the vehicle to each hydrogen production station. Using all vehicles in the set of vehicles awaiting hydrogen replenishment as rows and all hydrogen production stations within the region as columns, the predicted arrival times of each vehicle to each hydrogen production station are filled into the corresponding positions to form an arrival time matrix. Any element in the matrix represents the estimated time node for the corresponding vehicle to reach the corresponding hydrogen production station under the current road conditions.

[0021] Figure 2 This is a schematic diagram of the arrival time matrix in the embodiments of this application. Figure 2In the matrix, each row corresponds to one of the five vehicles waiting to be refueled with hydrogen, and each column corresponds to one of the four hydrogen production stations. The value of each cell is the predicted arrival time of the corresponding vehicle calculated using the shortest path algorithm based on the current GPS coordinates, in minutes. The color intensity reflects the length of the arrival time, with darker colors indicating later arrival times. The cell with the smallest value in each column is marked with a black box, representing the vehicle with the earliest predicted arrival time among all vehicles heading to the corresponding hydrogen production station. This minimum value is the earliest arrival time of the corresponding hydrogen production station and serves as the time reference input for subsequent calculations of the optimal hot start time.

[0022] In one specific embodiment, step S2 reads the current temperature and rated operating temperature of the alkaline solution in each hydrogen production station's electrolyzer, including: The current temperature of the alkaline solution in the electrolyzers of each hydrogen production station is read at a fixed acquisition cycle. The current temperature of the alkaline solution is compared with the rated operating temperature to obtain the thermal state category of each electrolyzer. The thermal state category is divided into four levels: cold state, warm-up state, hot standby state, and operating state. The corresponding current temperature ranges of the alkaline solution are below 40℃, 40℃ to 65℃, 65℃ to the rated operating temperature, and not lower than the rated operating temperature, respectively.

[0023] Specifically, the current temperature of the alkaline solution is reported to the vehicle-to-everything (V2X) cloud control platform by a temperature sensor installed on the alkaline solution circulation pipeline of the electrolyzer at a fixed acquisition cycle of 60 seconds. The acquisition cycle of 60 seconds is based on the fact that the natural rate of change of the alkaline solution temperature in the alkaline electrolyzer is usually less than 0.5℃ / minute without external heating intervention. A 60-second cycle is sufficient to capture the phased changes in temperature without generating redundant data. The rated operating temperature is the target temperature that the alkaline solution should maintain under full-power hydrogen production conditions in the alkaline electrolyzer. In engineering, a typical value is 80℃. This value is read from the design parameter field in the electrolyzer equipment ledger. The rated operating temperature varies for different models of equipment, and the actual value in the ledger shall prevail. The four-level classification of thermal states is determined based on the electrochemical characteristics of the alkaline electrolyzer: below 40°C, the electrolyzer is in a cold state, with extremely low electrolysis efficiency and a risk of alkaline crystallization during startup; 40°C to 65°C is the warm-up state, where the fluidity of the alkaline solution gradually recovers, but the ion conductivity has not yet reached the high-efficiency hydrogen production range; 65°C to the rated operating temperature is the hot standby state, where the electrolyzer has the capacity for low-power hydrogen production; and above the rated operating temperature is the operating state, where the electrolyzer is in the high-efficiency hydrogen production range.

[0024] Thermal status categories are stored in the platform's scheduling database using a unique identifier for each hydrogen production station. These categories, along with the current alkaline solution temperature and rated operating temperature, constitute the thermal status profile of each hydrogen production station's electrolyzer. This profile is updated synchronously after each 60-second data collection cycle. Based on the updated thermal status category, the platform determines the temperature difference between the current electrolyzer and its rated operating temperature. The magnitude of this temperature difference directly determines the numerator value in the preheating time calculation. For hydrogen production stations in operation, the temperature difference is zero, and the preheating time is recorded as zero, eliminating the need to trigger a hot start command. The introduction of thermal status categories discretizes continuous alkaline solution temperature values ​​into four clearly defined engineering status levels. This allows the platform to directly use the thermal status level, rather than the original temperature value, as the scheduling basis when making multi-station power allocation decisions, avoiding frequent switching of scheduling commands due to minor temperature fluctuations.

[0025] In one specific embodiment, step S2 divides the product of the difference between the current temperature of the alkali solution and the rated operating temperature, and the product of the alkali solution mass and specific heat capacity, by the preheating power to obtain the preheating time, including: Based on the thermal state category, the product of the difference between the rated operating temperature and the current temperature of the alkali solution and the mass and specific heat capacity of the alkali solution is used as the numerator, and the product of the preheating power and the time conversion factor is used as the denominator. The numerator and denominator are divided to obtain the preheating time required for each hydrogen production station's electrolyzer to rise from the thermal state category to the operating state. Among them, the preheating time of the hydrogen production station in the operating state category is recorded as zero.

[0026] Specifically, the alkali solution mass is read from the alkali solution filling quantity field of the electrolyzer in the equipment ledger of each hydrogen production station, in kilograms. Specific heat capacity is taken as the standard thermal parameter of 30% KOH solution in alkaline electrolyzers within the temperature range of 40℃ to 80℃, taken as 3.8 kJ / (kg·℃). This value is a common parameter in industry-standard thermal manuals and does not require on-site measurement. Preheating power is read from the rated power field of the electrolyzer heater in the equipment ledger of each hydrogen production station, in kilowatts. Heating power varies between different specifications of hydrogen production stations; the actual value in the ledger should be used. The time conversion factor is taken as 60. Its dimensional meaning is to convert the time unit (seconds) obtained by dividing the specific heat capacity unit (kJ / (kg·℃)) in the numerator by the heating power unit (kW, i.e., kJ / s) in the denominator into minutes, ensuring that the preheating time calculation result is output in minutes, consistent with the time accuracy unit of the predicted arrival time in the arrival time matrix.

[0027] The calculation of preheating time essentially involves dividing the total heat required to raise the alkaline solution in the electrolyzer from its current temperature to its rated operating temperature by the thermal power that the heater can provide per unit time. The numerator is the difference between the rated operating temperature and the current alkaline solution temperature multiplied by the mass of the alkaline solution and then by its specific heat capacity, resulting in the total heat required for the heating process, expressed in kilojoules (kJ). The denominator is the preheating power multiplied by a time conversion factor of 60, converting the power unit from kilojoules per second to kilojoules per minute. Dividing the two yields the preheating time, which is then rounded up to the nearest whole minute. This rounding is based on the fact that the actual heating rate of the alkaline solution is affected by factors such as environmental heat dissipation and fluctuations in the alkaline solution circulation flow rate, resulting in a measured heating rate that is generally lower than the theoretical value. Rounding up can cover these deviations without requiring additional complex compensation models. For hydrogen production stations in the operational state, the current alkaline solution temperature is not lower than the rated operating temperature, the temperature difference is zero, the numerator is zero, and the preheating time is directly recorded as zero. This type of hydrogen production station does not require triggering a preheating heater start-up command.

[0028] In one specific embodiment, step S2 subtracts the preheating time and safety margin time from the predicted arrival time in the arrival time matrix to obtain the optimal hot start time for each hydrogen production station, including: Based on the arrival time matrix, the minimum predicted arrival time of all vehicles heading to the same hydrogen production station is extracted to obtain the earliest arrival time of each hydrogen production station. The optimal hot start time for each hydrogen production station is obtained by subtracting the preheating time and the fixed safety margin time from the earliest arrival time. The safety margin time is a fixed value of 5 minutes. When the optimal hot start time is earlier than the current system timestamp, the optimal hot start time is corrected to the current system timestamp, and the corresponding hydrogen production station is marked as a hot start lagging station.

[0029] Specifically, the arrival time matrix uses vehicles awaiting hydrogen replenishment as rows and hydrogen production stations as columns. The minimum value of all elements in the same column is taken to obtain the earliest predicted arrival time among all vehicles heading to that hydrogen production station. This is the earliest arrival time of that station. The rationale for taking the minimum value is that the electrolyzer at the hydrogen production station must be preheated and operational before the earliest arriving vehicle. If the hot-start time is calculated based on the arrival time of later arriving vehicles, the electrolyzer will not have reached its rated operating temperature when the earliest arriving vehicle arrives, thus failing to meet the vehicle's immediate hydrogen replenishment needs. A fixed safety margin of 5 minutes is used. This value covers the time deviation introduced by engineering factors such as ambient temperature fluctuations and changes in alkaline solution circulation flow rate, which are lower than the theoretical calculation value. The 5-minute value is determined based on the typical temperature stabilization time of the alkaline electrolyzer during the final heating stage at rated heating power. Below this value, although the electrolyzer has reached its rated temperature, the internal temperature distribution is not yet uniform, and the hydrogen production efficiency has not yet reached full power.

[0030] The optimal hot start time is obtained by subtracting the sum of the preheating time and the safety margin time from the earliest arrival time. This time is the target time node for the platform to issue a preheating start command to the corresponding hydrogen production station. When the calculated optimal hot start time is earlier than the current system timestamp, it indicates that the preheating process is insufficient from the current time, and the electrolyzer cannot reach the operating state when the vehicle arrives. In this case, the optimal hot start time is corrected to the current system timestamp, meaning that the platform immediately issues a hot start command to minimize the time difference before the electrolyzer reaches the required temperature. The corresponding hydrogen production station is marked as a hot start lagging station. This mark is used as one of the input parameters in the subsequent priority ranking of power allocation among multiple stations. Because the electrolyzer reaches the required temperature later than the vehicle's arrival time, the hot start lagging station has a different priority in power competition than a normal hot start station. The platform decides whether to issue a waiting notification or a relocation guidance command to the corresponding vehicle based on this mark.

[0031] In one specific embodiment, step S3 includes: The photovoltaic power output prediction curve for the future prediction period is obtained with a fixed time granularity, and the photovoltaic power output prediction curve is discretized into a photovoltaic power output prediction sequence with a fixed time granularity. Starting from the optimal hot start time of each hydrogen production station, the photovoltaic power output prediction sequence is traversed backward to select continuous time periods in each time granularity where the predicted photovoltaic power output is not lower than the sum of the preheating power of the electrolyzer and the rated hydrogen production power of the corresponding hydrogen production station, thus obtaining the photovoltaic power allocation window of each hydrogen production station. Subtract the preheating power of the corresponding hydrogen production station from the photovoltaic output prediction value at each time granularity within the photovoltaic power allocation window, divide by the unit hydrogen production energy consumption, and accumulate the quotients at each time granularity within the photovoltaic power allocation window to obtain the expected hydrogen production of each hydrogen production station within the window. The expected hydrogen production within the window is compared with the total hydrogen replenishment demand of all vehicles heading to the corresponding hydrogen production station. For hydrogen production stations whose expected hydrogen production within the window is not less than the total hydrogen replenishment demand, a power allocation instruction is issued with the photovoltaic power allocation window as the power supply range. Hydrogen production stations whose expected hydrogen production within the window is less than the total hydrogen replenishment demand are marked as power conflict stations.

[0032] Specifically, the photovoltaic (PV) output forecast curve is provided by a meteorological forecasting interface. The forecast period covers the next 6 hours, with a fixed time granularity of 15 minutes. This means the next 6 hours are divided into 24 consecutive time granularities, each corresponding to a PV output forecast value in kilowatts. The 15-minute time granularity is chosen because the variation in PV output within this time scale typically does not exceed 5% of the installed capacity. This 15-minute granularity ensures forecast accuracy while maintaining consistency with the intraday rolling dispatch time granularity commonly used in the power dispatching field, facilitating integration with the grid-side dispatching system. Starting from the optimal hot start time of each hydrogen production station, the photovoltaic output prediction sequence is traversed granularly to determine whether the predicted photovoltaic output value of each granularity is not lower than the sum of the preheating power of the electrolyzer and the rated hydrogen production power of the corresponding hydrogen production station. This sum of power is the minimum total electrical power required for the electrolyzer to maintain the operation of the heater and start low-power hydrogen production during the preheating stage. Only when all granularities in a continuous period meet this condition is the continuous period confirmed as a photovoltaic power allocation window. If the output of any granularity is lower than the threshold, the continuity is interrupted and the search must be restarted from the interruption point.

[0033] The calculation of the expected hydrogen production within the window is based on the net available hydrogen production power for each particle size. The net available hydrogen production power is the difference between the predicted photovoltaic output and the preheating power for that particle size, expressed in kilowatts (kW). Dividing the net available hydrogen production power by the unit hydrogen production energy consumption yields the hydrogen production rate for that particle size, expressed in kilograms per hour. The unit hydrogen production energy consumption is obtained from the measured energy consumption field of the electrolyzer at rated operating temperature in the equipment ledger of each hydrogen production station. The typical value range for alkaline electrolyzers is 4.5 to 5.5 kWh per kilogram. Multiplying the hydrogen production rate by 0.25, the number of hours corresponding to the time particle size, yields the hydrogen production amount within that particle size. The hydrogen production amounts for all particles within the photovoltaic power allocation window are summed to obtain the expected hydrogen production within the window, expressed in kilograms. The total hydrogen replenishment demand is obtained by summing the hydrogen replenishment demands of all vehicles heading to the corresponding hydrogen production station. The hydrogen replenishment demand of each vehicle has been calculated and stored during the arrival time matrix construction phase. Hydrogen production stations whose expected hydrogen production is lower than the total hydrogen replenishment demand within the window are marked as power conflict stations, which triggers a multi-station power priority sorting process.

[0034] In one specific embodiment, step S4 includes: For power conflict stations, the heat loss power of each power conflict station is multiplied by the delay start-up time of postponing the optimal hot start time to the start of the suboptimal photovoltaic power allocation window to obtain the heat loss cost of each power conflict station. Based on the arrival time matrix, the minimum predicted arrival time of all vehicles waiting to refuel at each power conflict station is extracted. The reciprocal of the difference between the current system timestamp and the minimum value is taken to obtain the arrival urgency coefficient of each power conflict station. The product of the urgency coefficient and the first weighting coefficient is added to the product of the quotient obtained by dividing the heat loss cost by the corresponding power conflict station's rated hydrogen power and the second weighting coefficient to obtain the comprehensive priority score of each power conflict station; where the first weighting coefficient is 0.6 and the second weighting coefficient is 0.4. Power conflict stations are sorted from highest to lowest based on their comprehensive priority score. Photovoltaic power allocation windows that satisfy the sum of preheating power and rated hydrogen production power are allocated to each power conflict station from the current remaining available photovoltaic output sequence. For power conflict stations that still cannot obtain a photovoltaic power allocation window that meets their needs after sorting, their power allocation instructions are updated to the power supply section corresponding to the second-best photovoltaic power allocation window, and vehicles heading to that station for hydrogen replenishment are marked as vehicles to be guided.

[0035] Specifically, heat loss power is the heat power loss corresponding to the temperature drop of the alkaline solution in the electrolyzer due to natural heat dissipation when the external heater is not connected. It is measured by the station-end thermal instruments when the electrolyzer is shut down, and the unit is kilowatts. This value reflects the minimum amount of heat required to maintain the temperature of the electrolyzer under the current thermal state. The suboptimal photovoltaic power allocation window is defined as the next consecutive time period in the current photovoltaic output prediction sequence that meets the condition of the sum of preheating power and rated hydrogen production power, following the optimal photovoltaic power allocation window. Its starting time is obtained by the platform continuing to traverse the photovoltaic output prediction sequence after completing the optimal window search. The delayed start-up time is the difference between the starting time of the suboptimal photovoltaic power allocation window and the original optimal hot start-up time, and the unit is minutes. The heat loss cost is obtained by multiplying the heat dissipation power by the delayed start-up time, with the dimension kilowatt-minutes. It is standardized by dividing by the corresponding power-conflicting station's rated hydrogen production power to eliminate the incomparability of heat loss costs due to differences in rated power between hydrogen production stations of different specifications. The standardized heat loss cost and the arrival urgency coefficient have the same dimensions and can then be included in the weighted summation. The arrival urgency coefficient is the reciprocal of the difference between the earliest predicted arrival time of all vehicles heading to the power-conflicting station and the current system timestamp, with the difference in minutes. The smaller the difference, the larger the reciprocal, and the higher the urgency coefficient.

[0036] The comprehensive priority score is obtained by multiplying the arrival urgency coefficient by a first weighting coefficient of 0.6 and the standardized heat loss cost by a second weighting coefficient of 0.4, with the sum of the two weights being 1. The first weighting coefficient of 0.6 is based on the fact that the timeliness of vehicle refueling has a greater impact on the overall scheduling target than equipment heat loss control in actual operation, and the weight of timeliness is higher than that of heat loss. The second weighting coefficient of 0.4 ensures that the heat loss cost still has a substantial impact in power competition, preventing the neglect of the physical losses of sites with high heat loss costs when timeliness is used as the sole ranking criterion. After power conflicting sites are arranged from high to low according to their comprehensive priority scores, photovoltaic power allocation windows are greedily allocated from the remaining available photovoltaic output sequence. The remaining available photovoltaic output sequence is the output sequence remaining after deducting the power already allocated to non-conflicting sites from the complete photovoltaic output prediction sequence. When a power conflict station ranked lower cannot find a continuous time period that meets the conditions in the remaining sequence, its power allocation instruction is updated to the power supply interval corresponding to the suboptimal photovoltaic power allocation window. Vehicles waiting to refuel hydrogen heading to the station are marked as vehicles to be guided, and the platform pushes delayed entry time or relocation guidance instructions to the corresponding vehicles based on the mark.

[0037] The above describes the vehicle-to-everything (V2X) photovoltaic-hydrogen production collaborative scheduling method in the embodiments of this application. The following describes the V2X photovoltaic-hydrogen production collaborative scheduling system in the embodiments of this application. One embodiment of the V2X photovoltaic-hydrogen production collaborative scheduling system in the embodiments of this application includes: The calculation module is used to collect the hydrogen storage capacity and location information of hydrogen-powered vehicles in the region, calculate the predicted arrival time of each vehicle to each hydrogen production station based on the road network travel time, and obtain the arrival time matrix. The analysis module is used to read the current temperature and rated operating temperature of the alkaline solution in the electrolyzer of each hydrogen production station, divide the difference between the current temperature and the rated operating temperature of the alkaline solution and the product of the mass of the alkaline solution and the specific heat capacity by the preheating power to obtain the preheating time, and subtract the preheating time and the safety margin time from the predicted arrival time corresponding to the arrival time matrix to obtain the optimal hot start time of each hydrogen production station. The allocation module is used to retrieve a continuous period in the photovoltaic output prediction curve that is not less than the sum of the electrolyzer preheating power and the rated hydrogen production power, with the optimal hot start time as the time anchor point, to obtain the photovoltaic power allocation window, and to issue a power allocation instruction to the corresponding hydrogen production station with the photovoltaic power allocation window as the power supply interval. The sorting module is used to prioritize the power allocation instructions of each hydrogen production station when the optimal hot start time of multiple hydrogen production stations overlaps with the same peak photovoltaic output period. The module uses the product of the heat loss power of each hydrogen production station and the delayed start time as the heat loss cost, and combines the urgency of arrival at the station to complete the redistribution of photovoltaic power.

[0038] This invention also provides a vehicle-to-everything (V2X) photovoltaic-hydrogen production collaborative scheduling device, which can be a server. The V2X photovoltaic-hydrogen production collaborative scheduling device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor, designed as a computer, provides computing and control capabilities. The memory of the V2X photovoltaic-hydrogen production collaborative scheduling device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the V2X photovoltaic-hydrogen production collaborative scheduling device stores the corresponding data in this embodiment. The network interface of the V2X photovoltaic-hydrogen production collaborative scheduling device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0039] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method.

[0040] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0041] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a vehicle-to-everything (V2X) photovoltaic hydrogen production collaborative scheduling device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0042] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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. Such 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 method for coordinated scheduling of photovoltaic hydrogen production via vehicle-to-everything (V2X) networks, characterized in that, The method includes: Step S1: Collect hydrogen storage capacity and location information of hydrogen-powered vehicles in the area, calculate the predicted arrival time of each vehicle to each hydrogen production station based on the road network travel time, and obtain the arrival time matrix. Step S2: Read the current temperature and rated operating temperature of the alkaline solution in the electrolyzer of each hydrogen production station. Divide the difference between the current temperature and the rated operating temperature of the alkaline solution and the product of the mass of the alkaline solution and the specific heat capacity by the preheating power to obtain the preheating time. Subtract the preheating time and the safety margin time from the predicted arrival time in the arrival time matrix to obtain the optimal hot start time of each hydrogen production station. Step S3: Using the optimal hot start time as the time anchor point, retrieve a continuous time period in the photovoltaic output prediction curve that is not less than the sum of the electrolyzer preheating power and the rated hydrogen production power to obtain the photovoltaic power allocation window, and issue a power allocation instruction to the corresponding hydrogen production station with the photovoltaic power allocation window as the power supply interval; wherein, the expected hydrogen production in the window is compared with the total hydrogen replenishment demand of all vehicles heading to the corresponding hydrogen production station, and a power allocation instruction with the photovoltaic power allocation window as the power supply interval is issued to the hydrogen production station with the expected hydrogen production in the window not less than the total hydrogen replenishment demand, and the hydrogen production station with the expected hydrogen production in the window less than the total hydrogen replenishment demand is marked as a power conflict station; Step S4: When the optimal hot start time of multiple hydrogen production stations overlaps with the same peak photovoltaic output period, the product of the heat loss power of each hydrogen production station and the delayed start time is used as the heat loss cost. The power allocation instructions of each hydrogen production station are prioritized based on the arrival urgency to complete the redistribution of photovoltaic power. This includes: for the power conflict stations, multiplying the heat loss power of each power conflict station by the delayed start time that postpones the optimal hot start time to the start of the suboptimal photovoltaic power allocation window to obtain the heat loss cost of each power conflict station; based on the arrival time matrix, extracting the minimum predicted arrival time among all vehicles heading to each power conflict station, and taking the reciprocal of the difference between the current system timestamp and the minimum value to obtain the arrival urgency coefficient of each power conflict station; and then... The product of the arrival urgency coefficient and the first weighting coefficient is added to the product of the quotient obtained by dividing the heat loss cost by the corresponding power conflict station's rated hydrogen power and the second weighting coefficient to obtain the comprehensive priority score of each power conflict station; wherein, the first weighting coefficient is 0.6 and the second weighting coefficient is 0.4; the power conflict stations are sorted from high to low according to the comprehensive priority score, and photovoltaic power allocation windows that satisfy the sum of the preheating power and the rated hydrogen power are allocated to each power conflict station from the current remaining available photovoltaic power output sequence. For power conflict stations that still cannot obtain a photovoltaic power allocation window that meets the requirements after sorting, their power allocation instruction is updated to the power supply section corresponding to the suboptimal photovoltaic power allocation window, and vehicles heading to that station for hydrogen replenishment are marked as vehicles to be guided.

2. The vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method according to claim 1, characterized in that, Step S1 includes: Based on the ratio of the current pressure to the rated pressure of the hydrogen storage tank of each hydrogen fuel cell vehicle, the rated capacity of the hydrogen storage tank is proportionally converted to obtain the current hydrogen storage capacity of each hydrogen fuel cell vehicle. The current hydrogen storage capacity is compared with a preset hydrogen replenishment trigger threshold, and hydrogen fuel cell vehicles whose current hydrogen storage capacity is lower than the hydrogen replenishment trigger threshold are selected to obtain a set of vehicles to be replenished with hydrogen. Based on the real-time location of each vehicle in the set of vehicles to be replenished with hydrogen, the travel time of each vehicle to each hydrogen production station in the region is calculated using the road network shortest path algorithm, and the travel time sequence of each vehicle to each hydrogen production station is obtained. The current system timestamp is added to the corresponding travel time in the travel time sequence to obtain the predicted arrival time of each vehicle in the set of vehicles to be replenished with hydrogen to each hydrogen production station. The predicted arrival times are arranged by indexing the correspondence between vehicles and hydrogen production stations to obtain the arrival time matrix.

3. The vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method according to claim 1, characterized in that, Step S2, which involves reading the current temperature and rated operating temperature of the alkaline solution in the electrolyzers of each hydrogen production station, includes: The current temperature of the alkaline solution in the electrolyzers of each hydrogen production station is read at a fixed acquisition cycle. The current temperature of the alkaline solution is compared with the rated operating temperature to obtain the thermal state category of each electrolyzer. The thermal state category is divided into four levels: cold state, warm-up state, hot standby state, and operating state. The corresponding current temperature ranges of the alkaline solution are below 40℃, 40℃ to 65℃, 65℃ to the rated operating temperature, and not lower than the rated operating temperature, respectively.

4. The vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method according to claim 3, characterized in that, Step S2 involves dividing the product of the difference between the current temperature and the rated operating temperature of the alkali solution, and the product of the alkali solution mass and specific heat capacity, by the preheating power to obtain the preheating time, including: Based on the thermal state category, the product of the difference between the rated operating temperature and the current temperature of the alkali solution and the mass and specific heat capacity of the alkali solution is used as the numerator, and the product of the preheating power and the time conversion factor is used as the denominator. The numerator and the denominator are divided to obtain the preheating time required for each hydrogen production station's electrolyzer to rise from the thermal state category to the operating state; wherein, for hydrogen production stations whose thermal state category is the operating state, the preheating time is recorded as zero.

5. The vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method according to claim 4, characterized in that, Step S2 involves subtracting the preheating time and safety margin time from the predicted arrival time in the arrival time matrix to obtain the optimal hot start time for each hydrogen production station, including: Based on the arrival time matrix, the minimum predicted arrival time of all vehicles heading to the same hydrogen production station is extracted to obtain the earliest arrival time of each hydrogen production station. The optimal hot start time for each hydrogen production station is obtained by subtracting the preheating time and the fixed safety margin time from the earliest arrival time. The safety margin time is a fixed value of 5 minutes. When the optimal hot start time is earlier than the current system timestamp, the optimal hot start time is corrected to the current system timestamp, and the corresponding hydrogen production station is marked as a hot start lagging station.

6. The vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method according to claim 1, characterized in that, Step S3 includes: A photovoltaic power output prediction curve for a future prediction period is obtained at a fixed time granularity, and the photovoltaic power output prediction curve is discretized into a photovoltaic power output prediction sequence according to the fixed time granularity. Taking the optimal hot start time of each hydrogen production station as the starting point, the photovoltaic output prediction sequence is traversed backward to select continuous time periods in each time granularity where the predicted photovoltaic output value is not lower than the sum of the preheating power of the electrolyzer and the rated hydrogen production power of the corresponding hydrogen production station, thus obtaining the photovoltaic power allocation window of each hydrogen production station. Subtract the preheating power of the corresponding hydrogen production station from the photovoltaic output prediction value at each time granularity within the photovoltaic power allocation window, divide by the unit hydrogen production energy consumption, and accumulate the quotients at each time granularity within the photovoltaic power allocation window to obtain the expected hydrogen production amount of each hydrogen production station within the window.

7. A vehicle-to-everything (V2X) photovoltaic hydrogen production collaborative scheduling system, characterized in that, For implementing the vehicle-to-everything (V2X) photovoltaic-hydrogen production collaborative scheduling method as described in any one of claims 1-6, the V2X photovoltaic-hydrogen production collaborative scheduling system comprises: The calculation module is used to collect the hydrogen storage capacity and location information of hydrogen-powered vehicles in the region, calculate the predicted arrival time of each vehicle to each hydrogen production station based on the road network travel time, and obtain the arrival time matrix. The analysis module is used to read the current temperature and rated operating temperature of the alkaline solution in the electrolyzer of each hydrogen production station, divide the difference between the current temperature and the rated operating temperature of the alkaline solution and the product of the mass of the alkaline solution and the specific heat capacity by the preheating power to obtain the preheating time, and subtract the preheating time and the safety margin time from the predicted arrival time corresponding to the arrival time matrix to obtain the optimal hot start time of each hydrogen production station. The allocation module is used to retrieve a continuous time period in the photovoltaic output prediction curve that is not less than the sum of the electrolyzer preheating power and the rated hydrogen production power, using the optimal hot start time as the time anchor point, to obtain a photovoltaic power allocation window, and to issue a power allocation instruction to the corresponding hydrogen production station with the photovoltaic power allocation window as the power supply interval; wherein, the expected hydrogen production in the window is compared with the total hydrogen replenishment demand of all vehicles waiting to replenish hydrogen heading to the corresponding hydrogen production station, and a power allocation instruction with the photovoltaic power allocation window as the power supply interval is issued to the hydrogen production station with the expected hydrogen production in the window not less than the total hydrogen replenishment demand, and the hydrogen production station with the expected hydrogen production in the window less than the total hydrogen replenishment demand is marked as a power conflict station; The sorting module is used to prioritize the power allocation instructions of each hydrogen production station when the optimal hot start time of multiple hydrogen production stations overlaps with the same peak photovoltaic output period. This is achieved by using the product of the heat loss power of each hydrogen production station and the delayed start time as the heat loss cost, and combining this with the arrival urgency to complete the redistribution of photovoltaic power. The module includes: for the power conflict stations, multiplying the heat loss power of each power conflict station with the delayed start time that postpones the optimal hot start time to the start of the second-best photovoltaic power allocation window to obtain the heat loss cost of each power conflict station; and based on the arrival time matrix, extracting the minimum predicted arrival time among all vehicles heading to each power conflict station, and taking the reciprocal of the difference between the current system timestamp and the minimum value to obtain the arrival urgency coefficient of each power conflict station. The product of the arrival urgency coefficient and the first weighting coefficient is added to the product of the quotient obtained by dividing the heat loss cost by the corresponding power conflict station's rated hydrogen power and the second weighting coefficient to obtain the comprehensive priority score of each power conflict station; wherein, the first weighting coefficient is 0.6 and the second weighting coefficient is 0.4; the power conflict stations are sorted from high to low according to the comprehensive priority score, and photovoltaic power allocation windows that satisfy the sum of the preheating power and the rated hydrogen power are allocated to each power conflict station from the current remaining available photovoltaic power output sequence. For power conflict stations that still cannot obtain a photovoltaic power allocation window that meets the requirements after sorting, their power allocation instruction is updated to the power supply section corresponding to the suboptimal photovoltaic power allocation window, and vehicles heading to that station for hydrogen replenishment are marked as vehicles to be guided.

8. A vehicle-to-everything (V2X) photovoltaic hydrogen production collaborative scheduling device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the vehicle-to-everything (V2X) photovoltaic hydrogen production coordinated scheduling method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it causes the processor to execute the vehicle-to-everything (V2X) photovoltaic hydrogen production collaborative scheduling method as described in any one of claims 1 to 6.

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