Photovoltaic hydrogen production power supply topological structure based on MPPT and control method

Abstract

The invention discloses a photovoltaic hydrogen production power supply topological structure based on MPPT and a control method, and relates to the technical field of renewable energy electrolysis hydrogen production, and the photovoltaic hydrogen production power supply topological structure mainly comprises a photovoltaic power module, a direct current bus, a water electrolysis hydrogen production unit, an energy storage unit and a control unit. The photovoltaic power modules are connected in parallel to the direct current bus through the independent DC / DC converter, and are matched with the automatic identification and scheduling functions of the control unit, the system operation strategy is automatically adjusted when the modules are newly added or faults exit, and plug-and-play, fault isolation and power reconstruction of the photovoltaic power modules can be supported; the duty ratio change step length of the DC / DC converter is limited when the current rapidly fluctuates due to the change of the photovoltaic output power, the current change rate of the electrolytic cell stack is effectively controlled, the service life protection of the electrolytic cell can be considered, the high modular access capability is achieved, multi-source collaborative scheduling is supported, and bus voltage stabilization and system current sharing optimization can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of renewable energy electrolysis hydrogen production, and in particular to a photovoltaic hydrogen production power supply topology structure and a control method based on MPPT. Background Art

[0002] Photovoltaic power generation directly converts solar energy into electricity, providing a renewable energy source for clean hydrogen production. Photovoltaic-driven green hydrogen production technology is becoming an important path for the intensive utilization of renewable energy. However, existing photovoltaic hydrogen production systems have exposed several key technical bottlenecks in long-term operation.

[0003] First, traditional maximum power point tracking (MPPT) control algorithms generally aim to maximize power output at the photovoltaic end, lacking consideration for dynamic adaptation to the operating characteristics of the downstream electrolyzer. In actual operation, frequent and dramatic current fluctuations can accelerate the aging of the electrolyzer electrode materials, significantly shortening the equipment lifespan and making long-term operational reliability difficult to ensure. Second, existing photovoltaic hydrogen production power supply architectures mostly employ a centralized topology, lacking flexible modular expansion capabilities. In the event of system expansion or localized failures, plug-and-play power modules, scheduling isolation, and load balancing cannot be achieved, severely restricting the system's maintainability and scalability. Third, in applications where multiple renewable DC power sources (such as photovoltaics, wind power, and energy storage) are connected in parallel for power supply, traditional energy management solutions generally employ static strategies that fail to fully coordinate the dynamic response capabilities and operating costs of each power source, resulting in low power distribution efficiency, large bus voltage fluctuations, and uneven load distribution across power equipment.

[0004] In addition, in the distributed photovoltaic module grid-connected hydrogen production system, the bus cable layout is complex, and voltage unevenness and circulating current interference are prone to occur. If there is a lack of an effective current equalization regulation mechanism, the system stability risk will be further aggravated.

[0005] Therefore, how to construct a photovoltaic hydrogen production power supply topology and control method that can not only take into account the life protection of the electrolyzer, but also has highly modular access capabilities, supports multi-source coordinated scheduling, and can achieve bus voltage stability and system current optimization has become a key technical issue that urgently needs to be broken through in this field. Summary of the Invention

[0006] The purpose of the present invention is to solve the problems of large power fluctuations, limited electrolyzer life, difficult module expansion and weak multi-source energy supply coordination capabilities in existing photovoltaic hydrogen production systems. A photovoltaic hydrogen production power supply topology structure and control method based on MPPT is proposed, which can not only take into account the life protection of the electrolyzer, but also has highly modular access capabilities, supports multi-source coordinated scheduling, and can achieve bus voltage stability and system current sharing optimization.

[0007] The present invention achieves the above-mentioned purpose through the following technical solutions: A photovoltaic hydrogen production power supply topology based on MPPT includes several photovoltaic component strings, a DC / DC converter, a DC bus, a water electrolysis hydrogen production unit, an energy storage unit, and a control unit; The photovoltaic component string and the corresponding independent DC / DC converter constitute a photovoltaic power module, and a plurality of the photovoltaic power modules are connected in parallel to the DC bus; The water electrolysis hydrogen production unit includes an electrolyzer stack, both ends of which are connected to the DC bus for receiving DC power to produce hydrogen by water electrolysis; The energy storage unit is connected in parallel to the DC bus via a bidirectional DC / DC converter for energy buffering and power regulation; The control unit comprises: An MPPT control subunit is used to control the multiple DC / DC converters respectively so that the DC / DC converters operate at their respective maximum power points according to the operating status of the corresponding photovoltaic component strings; an electrolyzer protection control subunit, configured to limit a duty cycle change step of the DC / DC converter when a change in photovoltaic output power causes the input current change rate of the electrolyzer stack to exceed a current change rate threshold, so as to control the current change rate of the electrolyzer stack not to exceed the current change rate threshold; An energy management subunit, configured to coordinate the charge and discharge status of the energy storage unit and / or dispatch the output of other DC power supplies according to the power difference between the photovoltaic output power and the power demand of the electrolyzer stack, when the energy storage unit and / or other DC power supplies are connected in parallel to the DC bus, so as to achieve dynamic balancing of the bus voltage; The control unit is further configured to automatically identify the access status of the photovoltaic power modules. If a new photovoltaic power module is connected, it will be automatically included in the control scheduling. When any photovoltaic power module fails and exits operation, the remaining photovoltaic power modules automatically adjust their output to share the load and maintain stable operation of the system.

[0008] A further improvement of the present invention is that: the DC bus adopts a voltage-current dual-sensing segmented current-sharing coordination structure, including segmented bus cables, with voltage sampling nodes and current sampling nodes respectively provided at both ends of each segment of the bus cable; The control unit includes a plurality of distributed current-sharing regulating controllers, each of which collects the voltage and current values ​​of the corresponding bus segment and controls the working state of the DC / DC converter connected to the bus segment; The control unit adjusts the output parameters of the corresponding current sharing controller through a closed-loop control algorithm according to the voltage difference and current imbalance between any two adjacent bus sections, thereby achieving balanced regulation of the output current of each photovoltaic power module or energy storage unit; Each current sharing controller has a communication function, which is used to exchange parameters with the control unit and update the regulation strategy when the photovoltaic power module or energy storage unit is connected or disconnected.

[0009] A further improvement of the present invention is that the electrolyzer protection control subunit estimates the operating health factor of the electrolyzer stack based on the voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack through an artificial neural network algorithm ANN, and dynamically adjusts the current change rate threshold according to the operating health factor.

[0010] A further improvement of the present invention is that: the electrolytic cell protection control subunit constructs a loss function according to the difference between the electrolytic cell stack input current of the current cycle and the previous cycle in each control cycle, and adopts an online gradient descent algorithm to iteratively update the duty cycle change step of the DC / DC converter; When the input current change rate of the electrolytic cell stack exceeds the dynamically adjusted current change rate threshold, the duty cycle change step of the DC / DC converter is automatically shrunk.

[0011] A further improvement of the present invention is that: the energy management subunit is configured with a resource scheduling evaluation model constructed based on the unit power output cost, response time parameters and current available power of each DC power source; Based on the resource scheduling evaluation model, an objective function for optimized scheduling is constructed, with meeting the power demand of the electrolyzer stack as a constraint condition. Within each control cycle, the output power of various DC power sources including photovoltaic component strings, wind power generation, fuel cells, and supercapacitors is dynamically allocated according to the objective function, and an output power quota constraint is set during the allocation process to avoid long-term overload operation of any DC power source.

[0012] A further improvement of the present invention is that the energy management subunit adopts a model predictive control strategy to predict the output power disturbance trend of the photovoltaic module string and the power demand of the electrolyzer stack in the next several time steps in each control cycle, and solves the optimized control variable based on the prediction results to adjust the charge and discharge power of the energy storage unit so that the DC bus voltage approaches the rated operating voltage of the electrolyzer stack; The objective function of the model predictive control strategy is as follows: ; Where, 、 Respectively Time, Energy storage charging and discharging power at each moment; To predict the time domain length, it is dynamically adjusted according to power fluctuations; 、 To adjust the weight factor; For the The predicted bus voltage at each moment; is the set electrolyzer stack operating voltage; For the Predicted PV power changes at all times.

[0013] A further improvement of the present invention is that each photovoltaic power module integrates unique module identification information and a status broadcast mechanism, calculates the power capability parameters of the current maximum power point in real time, and periodically broadcasts module status data frames containing module identification information, operating status, and power capability parameters to the control unit via a communication bus; The control unit automatically identifies newly added photovoltaic power modules and dynamically maintains a module status mapping table by monitoring module status data frames on the communication bus; The control unit further adopts a hash mapping algorithm or a distributed scheduling optimization mechanism to allocate corresponding MPPT scheduling resources according to the operating status and power capability parameters in the module status data frame, and constructs an MPPT control task queue according to the adaptive scheduling priority to achieve real-time optimization of multi-module power output; The control unit also includes a redundancy identification and fault tolerance mechanism. If the module status data frame of any photovoltaic power module is not continuously received within a preset time window, it is marked as a temporary offline state and the historical scheduling parameters of the photovoltaic power module are retained; when the photovoltaic power module resends the module status data frame, the control unit automatically identifies the reconnection state and restores the corresponding original scheduling resource allocation.

[0014] A control method for a photovoltaic hydrogen production power supply topology structure based on MPPT, the method comprising: Collect the output voltage, current and operating status of the photovoltaic module string, and control each DC / DC converter separately through the MPPT control subunit to make each photovoltaic power module operate at its respective maximum power point; The energy management subunit uses a model predictive control strategy to coordinate the charge and discharge status of the energy storage unit. Alternatively, it builds a resource scheduling evaluation model based on the difference between the photovoltaic output power and the electrolyzer stack power demand to schedule the output power of other DC power sources connected in parallel to the DC bus to achieve dynamic balance of bus power. Collecting the voltage, current, internal resistance, temperature, and hydrogen yield of the electrolyzer stack, estimating the operational health factor of the electrolyzer stack using an artificial neural network algorithm (ANN), and dynamically setting a current change rate threshold based on the operational health factor; The electrolyzer protection control subunit constructs a loss function based on the difference in electrolyzer stack input current between adjacent cycles within each control cycle, and uses an online gradient descent algorithm to iteratively update the duty cycle change step size of the DC / DC converter. The duty cycle change step size is automatically reduced when the rate of change of the electrolyzer stack input current exceeds a set current change rate threshold. The photovoltaic power module calculates the power capability parameters of the current maximum power point in real time and periodically broadcasts module status data frames through the communication bus, including module identification information, operating status and power capability parameters. The control unit receives the module status data frames, automatically identifies the access or exit status of the photovoltaic power module, updates the scheduling resource allocation, and restores the scheduling status of the faulty module through the redundancy identification mechanism.

[0015] A further improvement of the present invention is that the energy management subunit constructs a resource scheduling evaluation model based on the unit power output cost, response time parameters and current available power of each DC power source, and dynamically allocates the output power of multiple DC power sources including photovoltaic component strings, wind power generation, fuel cells, and supercapacitors; The objective function of the resource scheduling evaluation model is expressed as: ; Where, Indicates the assignment to The output power of a DC power supply; is the total number of DC power sources participating in the dispatch; is the adjustment coefficient related to the output cost weight, For the The output power of a DC power supply is Unit power output cost function when ; is the adjustment coefficient related to the response time weight, For the The dynamic response time of a DC power supply in seconds; is the total load power currently required by the electrolyzer stack.

[0016] A further improvement of the present invention is that the electrolyzer protection control subunit inputs the voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack into a pre-trained artificial neural network model. The artificial neural network model is a three-layer feedforward structure, the input layer contains the above five parameters, and the output layer is a normalized operation health factor. , used to characterize the operational aging status of the current electrolyzer stack; Based on the operational health factor Dynamically calculate the maximum allowable current change rate threshold , the formula is: ; Where, The maximum current change rate initially set for the system; 、 is the adjustable weight coefficient; 、 They are The operating health factor and current change rate threshold at each moment; In each control cycle, calculate the difference in the electrolytic cell stack input current , and construct the loss function ,in, , , 、 Input current to the electrolyzer stack of adjacent cycles; An online gradient descent algorithm is used to iteratively update the duty cycle change step size of the DC / DC converter , the update rule is: ; when When , the forced contraction duty cycle change step is: ; Where, is the learning rate; is the contraction factor, which is dynamically adjusted according to the excess amplitude; The MPPT control subunit adopts a maximum power point tracking strategy that includes feedback of the operating health factor. The objective function is as follows: ; Where, is the optimized maximum power point target voltage; Indicates voltage Find the voltage point in the space that maximizes the expression in the brackets; is the photovoltaic module efficiency function; is the life protection weight factor; The MPPT control subunit outputs a target voltage according to the target function Real-time adjustment of the operating voltage of the photovoltaic module string, balancing the photovoltaic output efficiency and the electrolyzer stack life protection requirements, and real-time calculation of the power capability parameters of the current maximum power point , the formula is: ,in is the output current at the current voltage.

[0017] The beneficial effects of the present invention are as follows: each photovoltaic power module is connected to the DC bus in parallel through an independent DC / DC converter, and in conjunction with the automatic identification and scheduling function of the control unit, it can support plug-and-play, fault isolation and power reconstruction of the photovoltaic power module, and has good flexibility and maintenance convenience; when a module is added or a fault is exited, the system operation strategy is automatically adjusted to maintain the overall energy supply continuity, and the system availability and redundancy fault tolerance are improved; when the photovoltaic output power changes and the current fluctuates rapidly, the duty cycle change step of the DC / DC converter is limited, and the current change rate of the electrolyzer stack is effectively controlled to avoid overheating of the electrolyzer due to frequent current shocks , polarization aggravation and other phenomena, thereby extending its service life and improving the stability of system operation; through the MPPT control sub-unit, the DC / DC converters corresponding to multiple photovoltaic component strings are controlled separately, so that each photovoltaic power module always operates at its maximum power point, improving the conversion efficiency of photovoltaic energy and enhancing the power generation capacity of the system under different lighting conditions; when the energy storage unit and / or other DC power sources are connected to the bus, it can dynamically adjust the energy storage charging and discharging status or dispatch other power outputs according to the real-time difference between the photovoltaic output and the power demand of the electrolyzer, realize the stable control of the DC bus voltage, and enhance the system's adaptability to load fluctuations and the uncertainty of renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort. Among them: Figure 1 Schematic diagram of the topological structure in an embodiment of the present invention; Figure 2 is a flow chart of a method in an embodiment of the present invention; Figure 3 This is a flow chart of the combined method of MPPT control and electrolytic cell protection coupling control in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0020] like Figure 1As shown, an embodiment of the present invention provides an MPPT-based photovoltaic hydrogen production power supply topology structure, including several photovoltaic component strings, DC / DC converters, DC buses, water electrolysis hydrogen production units, energy storage units, control units, etc.

[0021] Photovoltaic power module: A photovoltaic power module consists of a string of photovoltaic modules and a corresponding independent DC / DC converter. Each string of photovoltaic modules is connected to the DC bus through its own DC / DC converter. Each photovoltaic power module is equipped with independent MPPT control, which adjusts the DC / DC converter duty cycle in real time to track the maximum power point of the module. The use of multiple low-power DC / DCs instead of a single high-power converter realizes a modular design on the photovoltaic side. This modular topology enables independent output and protection of each photovoltaic string: when the power of a photovoltaic string drops due to shading or fault, the remaining photovoltaic strings are not affected and can still operate at their respective maximum power points. In addition, the system capacity can be elastically expanded by adding or removing photovoltaic power modules, which has plug-and-play characteristics.

[0022] Water electrolysis hydrogen production unit: includes an electrolyzer stack, which is composed of a number of water electrolysis cells connected in series. The positive and negative poles of the electrolyzer stack are connected to the output terminals of each DC / DC converter through a DC bus, and receive power from the DC bus to perform water electrolysis reaction to produce hydrogen. In order to protect the electrolyzer, the topology of the present invention is designed to ensure that the voltage at both ends of the electrolyzer stack is always maintained within a safe operating range, and the ripple of the bus current / voltage is reduced through a control strategy. If necessary, RC filtering can be connected in parallel at both ends of the electrolyzer or a DC / DC with isolation can be used to further improve the output quality. However, in the topology of this embodiment, due to multi-source coordinated control, the electrolyzer can already obtain a DC power supply with extremely low ripple.

[0023] Energy storage unit (or other DC power source): Preferably, it includes an energy storage battery and its bidirectional DC / DC converter. The energy storage unit is connected to the DC bus and stores energy during periods of excess photovoltaic power and releases it during periods of insufficient photovoltaic power, thereby smoothing out photovoltaic power fluctuations and ensuring continuous and stable power supply to the electrolyzer. The bidirectional DC / DC converter controls the battery charge and discharge currents to support and regulate the DC bus voltage. Furthermore, it coordinates with the PV-side MPPT through a higher-level control system to provide instantaneous power compensation or discharge to the electrolyzer during dynamic processes. In addition to batteries, the DC bus of the present invention can also be connected in parallel to other DC power sources, such as wind turbine rectifier output, supercapacitors, and DC distribution networks, to form a DC microgrid architecture. Multiple energy sources are connected to the common bus through their respective power conversion interfaces and are centrally coordinated by the energy management system to collaboratively power the electrolyzer. When photovoltaic power is temporarily in excess, excess energy can be stored in the battery or supplied to other loads. Conversely, when sunlight is insufficient, energy storage or other power sources can supplement the power shortfall, significantly improving the power supply stability and availability of the hydrogen production system.

[0024] The DC bus, consisting of a conductor busbar, connects the DC / DC outputs of the above units in parallel. The bus voltage is determined by the instantaneous operating voltage of the electrolyzer stack (or by a reference set by, for example, the battery converter). In the embodiments of the present invention, it is typically maintained at a level close to the rated voltage of the electrolyzer. To account for long-distance transmission and minimize losses, the bus voltage can be designed to be higher (e.g., hundreds of volts DC). Each DC / DC converter adjusts its output based on the bus voltage, injecting or drawing current into or from the bus. The bus structure creates a star-parallel topology for the entire system. The photovoltaic side, energy storage side, and load (electrolyzer) are each connected to the bus via electronic converters. Electrical isolation and decoupling between modules are achieved by controlling their respective converters. If necessary, a DC / DC converter with a high-frequency isolation transformer can be used to ensure electrical isolation between the photovoltaic and electrolyzer systems, improving safety and noise immunity.

[0025] Control unit: includes an MPPT control subunit, an electrolyzer protection control subunit, and an energy management subunit. The MPPT control subunit controls multiple DC / DC converters, enabling them to operate at their respective maximum power points based on the operating status of the corresponding PV module string. When the PV output power changes, causing the input current change rate of the electrolyzer stack to exceed the current change rate threshold, the electrolyzer protection control subunit limits the duty cycle change step of the DC / DC converter to control the current change rate of the electrolyzer stack to not exceed the current change rate threshold. When an energy storage unit and / or other DC power supply are connected in parallel to the DC bus, the energy management subunit coordinates the charge and discharge status of the energy storage unit and / or dispatches the output of other DC power supplies based on the power difference between the PV output power and the power demand of the electrolyzer stack, thereby achieving dynamic balancing of the bus voltage.

[0026] The control unit is further configured to automatically identify the access status of the photovoltaic power modules. If a new photovoltaic power module is connected, it will be automatically included in the control scheduling. If any photovoltaic power module fails and exits operation, the remaining photovoltaic power modules automatically adjust their output to share the load and maintain stable operation of the system.

[0027] The above topology fully embodies the design philosophy of modularity and multi-source collaboration. By operating multiple power conversion modules in parallel, "N+1" redundant configuration is achieved. Even if a single module fails, the others can still operate normally, significantly improving system reliability and maintainability. Furthermore, while ensuring electrical isolation and independent control of each module, plug-and-play operation of the photovoltaic power generation units is achieved. Once a new module is connected to the busbar, it is automatically recognized and put into operation by the control unit, eliminating the need for major modifications to the existing system. This architecture facilitates future expansion of the photovoltaic system or the integration of new DC power sources (such as wind power).

[0028] In one embodiment, the DC bus adopts a voltage-current dual-sensing segmented current-sharing coordination structure to solve the problems of uneven bus current distribution and increased circulating current risk caused by physical wiring asymmetry, load concentration, etc. when photovoltaic power modules and energy storage units operate in parallel.

[0029] The DC bus is divided into several independent bus cables. A voltage sampling node and a current sampling node are set at both ends of each bus cable. The two ends of each bus cable correspond to the output ports of two photovoltaic power modules or energy storage units.

[0030] Each bus section is equipped with a distributed current sharing controller, whose functions include: Sampling: used to collect the voltage values ​​at both ends of the bus cable in real time 、 and the current flowing through the cable ; Control: Embedded microcontroller with local closed-loop regulation algorithm; Execution: Control the working state of the DC / DC converter between the bus section and the connected photovoltaic power module, and adjust its output power; Communication: Maintains periodic communication with the control unit to synchronize module status, power quota, and current sharing instructions.

[0031] The control unit calculates the voltage difference between any two adjacent bus sections ( ) and the degree of current imbalance ( ), calculate the regulation target, and adjust the output parameters of the corresponding current sharing regulation controller through a closed-loop control algorithm (such as proportional-integral PI control). The control algorithm target is: ;in, is the number of busbar sections, 、 To adjust the weight factor, it is used to adjust the relative priority of voltage consistency and current balance.

[0032] When a photovoltaic power module or energy storage unit is added or removed, the corresponding module broadcasts the status change information on the communication bus. Each current sharing controller obtains this information through the communication interface and reports the access status to the control unit. The control unit automatically updates the regulation strategy based on the current system topology, including: Reset the target voltage difference range of each bus section; Assign new current sharing control priority; Send boundary conditions to each current sharing controller.

[0033] Each current sharing regulation controller can independently perform voltage closed-loop and current sharing control tasks locally based on the issued targets and the voltage and current sampling results of this section, thereby achieving distributed current sharing regulation and adaptive coordination between bus sections without the need for centralized real-time control, effectively preventing voltage drops, current overshoots or circulating currents caused by local load changes.

[0034] This implementation is suitable for large-scale parallel power supply scenarios containing multiple photovoltaic power modules and energy storage modules, and has good scalability and dynamic stability.

[0035] In one embodiment, the electrolyzer protection control subunit estimates the operating health factor of the electrolyzer stack through an artificial neural network algorithm ANN based on the voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack. , and dynamically adjust the current change rate threshold according to the operating health factor , the formula is: ; Where, The maximum current change rate initially set for the system; 、 is the adjustable weight coefficient; 、 They are The operating health factor and current change rate threshold at each moment; The electrolytic cell protection control subunit controls the electrolytic cell stack input current difference between the current and the previous cycle in each control cycle. Constructing the loss function , using the online gradient descent algorithm to iteratively update the duty cycle change step of the DC / DC converter When the input current change rate of the electrolyzer stack exceeds the dynamically adjusted current change rate threshold, the duty cycle change step of the DC / DC converter is automatically reduced. The MPPT control subunit solves the optimized maximum power point target voltage based on the feedback of the operating health factor. , according to the target voltage Real-time adjustment of the operating voltage of the photovoltaic module string to balance the photovoltaic output efficiency and the electrolyzer stack life protection requirements.

[0036] In one embodiment, the energy management subunit is configured with a resource scheduling evaluation model constructed based on the unit power output cost, response time parameters and current available power of each DC power source; an objective function for optimized scheduling is constructed based on the resource scheduling evaluation model, with meeting the power demand of the electrolyzer stack as a constraint condition. Within each control cycle, the output power of various DC power sources including photovoltaic component strings, wind power generation, fuel cells, and supercapacitors is dynamically allocated according to the objective function, and an output power quota constraint is set during the allocation process to avoid long-term overload operation of any DC power source.

[0037] Optionally, in another embodiment, the energy management subunit may further adopt a model predictive control strategy to predict the output power disturbance trend of the photovoltaic module string and the power demand of the electrolyzer stack in the next several time steps in each control cycle, and solve the optimized control variable based on the prediction results to adjust the charge and discharge power of the energy storage unit so that the DC bus voltage approaches the rated operating voltage of the electrolyzer stack; The objective function of the model predictive control strategy is as follows: ; Where, 、 Respectively Time, Energy storage charging and discharging power at each moment; To predict the time domain length, it is dynamically adjusted according to power fluctuations; 、 To adjust the weight factor; For the The predicted bus voltage at each moment; is the set electrolyzer stack operating voltage; For the Predicted PV power changes at all times.

[0038] Specifically, as one implementation of the present invention, each photovoltaic power module integrates unique module identification information and a status broadcast mechanism, calculates the power capability parameters of the current maximum power point in real time, and periodically broadcasts a module status data frame containing module identification information, operating status, and power capability parameters to a control unit via a communication bus; The control unit automatically identifies newly added photovoltaic power modules and dynamically maintains the module status mapping table by monitoring the module status data frames on the communication bus; The control unit further uses a hash mapping algorithm or a distributed scheduling optimization mechanism to allocate corresponding MPPT scheduling resources according to the operating status and power capability parameters in the module status data frame, and builds an MPPT control task queue according to the adaptive scheduling priority to achieve real-time optimization of multi-module power output; The control unit also includes a redundancy identification and fault-tolerance mechanism. If the module status data frame of any photovoltaic power module is not continuously received within a preset time window, it is marked as a temporary offline state and the historical scheduling parameters of the photovoltaic power module are retained; when the photovoltaic power module resends the module status data frame, the control unit automatically identifies the reconnection state and restores the corresponding original scheduling resource allocation.

[0039] like Figure 2 、 Figure 3 FIG. 1 is an embodiment of the present invention, which provides a control method for a photovoltaic hydrogen production power supply topology structure based on MPPT, including: Collect the output voltage, current and operating status of the photovoltaic module string, and control each DC / DC converter separately through the MPPT control subunit to make each photovoltaic power module operate at its respective maximum power point; The energy management subunit uses a model predictive control strategy to coordinate the charging and discharging status of the energy storage unit. Alternatively, it constructs a resource scheduling evaluation model based on the difference between the photovoltaic output power and the electrolyzer stack power demand to schedule the output power of other DC power sources connected in parallel to the DC bus to achieve dynamic balance of bus power. Specifically, the energy management subunit constructs a resource scheduling evaluation model based on the unit power output cost, response time parameters, and current available power of each DC power source to dynamically allocate the output power of multiple DC power sources including photovoltaic module strings, wind power generation, fuel cells, and supercapacitors. The objective function of the resource scheduling evaluation model is expressed as: ; Where, Indicates the assignment to The output power of a DC power supply; is the total number of DC power sources participating in the dispatch; is the adjustment coefficient related to the output cost weight, For the The output power of a DC power supply is Unit power output cost function when ; is the adjustment coefficient related to the response time weight, For the The dynamic response time of a DC power supply in seconds; is the total load power currently required by the electrolyzer stack; The voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack are collected, and the artificial neural network algorithm ANN is used to estimate the operation health factor of the electrolyzer stack. Specifically, the electrolyzer protection control subunit inputs the voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack into the pre-trained artificial neural network model. The artificial neural network model is a three-layer feedforward structure. The input layer contains the above five parameters, and the output layer is the normalized operation health factor. , used to characterize the operational aging status of the current electrolyzer stack; Based on operational health factors Dynamically adjust the maximum allowable current change rate threshold , the formula is: ; Where, The maximum current change rate initially set for the system; 、 is the adjustable weight coefficient; 、 They are The operating health factor and current change rate threshold at each moment; In each control cycle, calculate the difference in the electrolytic cell stack input current , and construct the loss function ,in, , , 、 Input current to the electrolyzer stack of adjacent cycles; An online gradient descent algorithm is used to iteratively update the duty cycle change step size of the DC / DC converter , the update rule is: ; when When , the forced contraction duty cycle change step is: ; Where, is the learning rate; is the contraction factor, which is dynamically adjusted according to the excess amplitude; The photovoltaic power module calculates the power capability parameters of the current maximum power point in real time. Specifically, it adopts a maximum power point tracking strategy that includes feedback of the operating health factor. The objective function is as follows: ; Where, is the optimized maximum power point target voltage; Indicates voltage Find the voltage point in the space that maximizes the expression in the brackets; is the photovoltaic module efficiency function; is the life protection weight factor; The MPPT control subunit outputs the target voltage according to the objective function Real-time adjustment of the operating voltage of the photovoltaic module string, balancing the photovoltaic output efficiency and the electrolyzer stack life protection requirements, and real-time calculation of the power capability parameters of the current maximum power point , the formula is: ,in is the output current under the current voltage; Each photovoltaic power module is written with module identification information (unique ID, such as MAC, SN or UUID) during manufacturing or initialization, and is configured with an embedded MCU (such as STM32, ESP32) to periodically broadcast module status data frames, including module identification information, operating status (operating, standby, fault), power capability parameters (except The control unit receives the module status data frame, automatically identifies the access or exit status of the photovoltaic power module, updates the scheduling resource allocation, and restores the scheduling status of the faulty module through the redundancy identification mechanism.

[0040] In summary, the present invention starts from the two aspects of system structure and control strategy, by constructing a modular, scalable, multi-source collaborative photovoltaic hydrogen production power supply topology, and integrating control mechanisms such as electrolyzer life protection, dynamic MPPT scheduling, energy storage coordination control and busbar current sharing management, etc., to achieve the overall efficient utilization of photovoltaic energy, life optimization of the water electrolysis system, flexible scheduling of power modules, dynamic balance of multi-source power supply and safe and reliable system operation, which significantly improves the comprehensive performance, stability and engineering applicability of the photovoltaic hydrogen production system.

[0041] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various modifications or substitutions within the technical scope disclosed in this application, and such modifications or substitutions should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A photovoltaic hydrogen production power topology based on MPPT, including several photovoltaic module strings, a DC / DC converter, a DC bus, a water electrolysis hydrogen production unit, an energy storage unit, and a control unit, characterized by: The photovoltaic component string and the corresponding independent DC / DC converter constitute a photovoltaic power module, and a plurality of the photovoltaic power modules are connected in parallel to the DC bus; The water electrolysis hydrogen production unit includes an electrolyzer stack, both ends of which are connected to the DC bus for receiving DC power to produce hydrogen by water electrolysis; The energy storage unit is connected in parallel to the DC bus via a bidirectional DC / DC converter for energy buffering and power regulation; The control unit comprises: An MPPT control subunit is used to control the multiple DC / DC converters respectively so that the DC / DC converters operate at their respective maximum power points according to the operating status of the corresponding photovoltaic component strings; an electrolyzer protection control subunit, configured to limit a duty cycle change step of the DC / DC converter when a change in photovoltaic output power causes the input current change rate of the electrolyzer stack to exceed a current change rate threshold, so as to control the current change rate of the electrolyzer stack not to exceed the current change rate threshold; An energy management subunit, configured to coordinate the charge and discharge status of the energy storage unit and / or dispatch the output of other DC power supplies according to the power difference between the photovoltaic output power and the power demand of the electrolyzer stack, when the energy storage unit and / or other DC power supplies are connected in parallel to the DC bus, so as to achieve dynamic balancing of the bus voltage; The control unit is further configured to automatically identify the access status of the photovoltaic power modules. If a new photovoltaic power module is connected, it will be automatically included in the control scheduling. When any photovoltaic power module fails and exits operation, the remaining photovoltaic power modules automatically adjust their output to share the load and maintain stable operation of the system.

2. The MPPT-based photovoltaic hydrogen production power supply topology according to claim 1 is characterized in that: The DC bus adopts a voltage-current dual-sensing segmented current-sharing coordination structure, including segmented bus cables, with voltage sampling nodes and current sampling nodes respectively provided at both ends of each segment of the bus cable; The control unit includes a plurality of distributed current-sharing regulating controllers, each of which collects the voltage and current values ​​of the corresponding bus segment and controls the working state of the DC / DC converter connected to the bus segment; The control unit adjusts the output parameters of the corresponding current sharing controller through a closed-loop control algorithm according to the voltage difference and current imbalance between any two adjacent bus sections, thereby achieving balanced regulation of the output current of each photovoltaic power module or energy storage unit; Each current sharing controller has a communication function, which is used to exchange parameters with the control unit and update the regulation strategy when the photovoltaic power module or energy storage unit is connected or disconnected.

3. The MPPT-based photovoltaic hydrogen production power supply topology according to claim 1 is characterized in that: The electrolyzer protection control subunit estimates the operating health factor of the electrolyzer stack based on the voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack through an artificial neural network algorithm (ANN), and dynamically adjusts the current change rate threshold according to the operating health factor.

4. The MPPT-based photovoltaic hydrogen production power supply topology according to claim 3 is characterized by: The electrolytic cell protection control subunit constructs a loss function according to the difference between the electrolytic cell stack input current and the previous cycle in each control cycle, and adopts an online gradient descent algorithm to iteratively update the duty cycle change step of the DC / DC converter; When the input current change rate of the electrolytic cell stack exceeds the dynamically adjusted current change rate threshold, the duty cycle change step of the DC / DC converter is automatically shrunk.

5. The MPPT-based photovoltaic hydrogen production power supply topology according to claim 1, characterized in that: The energy management subunit is configured with a resource scheduling evaluation model constructed based on the unit power output cost, response time parameters and current available power of each DC power source; Based on the resource scheduling evaluation model, an objective function for optimized scheduling is constructed, with meeting the power demand of the electrolyzer stack as a constraint condition. Within each control cycle, the output power of various DC power sources including photovoltaic component strings, wind power generation, fuel cells, and supercapacitors is dynamically allocated according to the objective function, and an output power quota constraint is set during the allocation process to avoid long-term overload operation of any DC power source.

6. The MPPT-based photovoltaic hydrogen production power supply topology according to claim 1, characterized in that: The energy management subunit adopts a model predictive control strategy to predict the output power disturbance trend of the photovoltaic module string and the power demand of the electrolyzer stack in the next several time steps in each control cycle. Based on the prediction results, the optimal control variable is solved to adjust the charge and discharge power of the energy storage unit so that the DC bus voltage approaches the rated operating voltage of the electrolyzer stack. The objective function of the model predictive control strategy is as follows: ； Where, 、 Respectively Time, Energy storage charging and discharging power at each moment; To predict the time domain length, it is dynamically adjusted according to power fluctuations; 、 To adjust the weight factor; For the The predicted bus voltage at each moment; is the set electrolyzer stack operating voltage; For the Predicted PV power changes at all times.

7. The MPPT-based photovoltaic hydrogen production power supply topology according to claim 1, characterized in that: Each photovoltaic power module integrates unique module identification information and a status broadcast mechanism, and calculates the power capability parameters of the current maximum power point in real time, and periodically broadcasts a module status data frame containing module identification information, operating status, and power capability parameters to the control unit via a communication bus; The control unit automatically identifies newly added photovoltaic power modules and dynamically maintains a module status mapping table by monitoring module status data frames on the communication bus; The control unit further adopts a hash mapping algorithm or a distributed scheduling optimization mechanism to allocate corresponding MPPT scheduling resources according to the operating status and power capability parameters in the module status data frame, and constructs an MPPT control task queue according to the adaptive scheduling priority to achieve real-time optimization of multi-module power output; The control unit also includes a redundancy identification and fault tolerance mechanism. If the module status data frame of any photovoltaic power module is not continuously received within a preset time window, it is marked as a temporary offline state and the historical scheduling parameters of the photovoltaic power module are retained; when the photovoltaic power module resends the module status data frame, the control unit automatically identifies the reconnection state and restores the corresponding original scheduling resource allocation.

8. A control method for the MPPT-based photovoltaic hydrogen production power supply topology structure according to any one of claims 1 to 7, characterized in that: The method comprises: Collect the output voltage, current and operating status of the photovoltaic module string, and control each DC / DC converter separately through the MPPT control subunit to make each photovoltaic power module operate at its respective maximum power point; The energy management subunit uses a model predictive control strategy to coordinate the charge and discharge status of the energy storage unit. Alternatively, it builds a resource scheduling evaluation model based on the difference between the photovoltaic output power and the electrolyzer stack power demand to schedule the output power of other DC power sources connected in parallel to the DC bus to achieve dynamic balance of bus power. Collecting the voltage, current, internal resistance, temperature, and hydrogen yield of the electrolyzer stack, estimating the operational health factor of the electrolyzer stack using an artificial neural network algorithm (ANN), and dynamically setting a current change rate threshold based on the operational health factor; The electrolyzer protection control subunit constructs a loss function based on the difference in electrolyzer stack input current between adjacent cycles within each control cycle, and uses an online gradient descent algorithm to iteratively update the duty cycle change step size of the DC / DC converter. The duty cycle change step size is automatically reduced when the rate of change of the electrolyzer stack input current exceeds a set current change rate threshold. The photovoltaic power module calculates the power capability parameters of the current maximum power point in real time and periodically broadcasts module status data frames through the communication bus, including module identification information, operating status and power capability parameters. The control unit receives the module status data frames, automatically identifies the access or exit status of the photovoltaic power module, updates the scheduling resource allocation, and restores the scheduling status of the faulty module through the redundancy identification mechanism.

9. The control method according to claim 8, characterized in that: The energy management subunit builds a resource scheduling evaluation model based on the unit power output cost, response time parameters and current available power of each DC power source, and dynamically allocates the output power of multiple DC power sources including photovoltaic component strings, wind power generation, fuel cells, and supercapacitors; The objective function of the resource scheduling evaluation model is expressed as: ； Where, Indicates the assignment to The output power of a DC power supply; is the total number of DC power sources participating in the dispatch; is the adjustment coefficient related to the output cost weight, For the The output power of a DC power supply is Unit power output cost function when ; is the adjustment coefficient related to the response time weight, For the The dynamic response time of a DC power supply in seconds; is the total load power currently required by the electrolyzer stack.

10. The control method according to claim 8, characterized in that: The electrolyzer protection control subunit inputs the voltage, current, internal resistance, temperature and hydrogen yield of the electrolyzer stack into a pre-trained artificial neural network model. The artificial neural network model is a three-layer feedforward structure. The input layer contains the above five parameters, and the output layer is the normalized operation health factor. , used to characterize the operational aging status of the current electrolyzer stack; Based on the operational health factor Dynamically calculate the maximum allowable current change rate threshold , the formula is: ； Where, The maximum current change rate initially set for the system; 、 is the adjustable weight coefficient; 、 They are The operating health factor and current change rate threshold at each moment; In each control cycle, calculate the difference in the electrolytic cell stack input current , and construct the loss function ,in, , , 、 Input current to the electrolyzer stack of adjacent cycles; An online gradient descent algorithm is used to iteratively update the duty cycle change step size of the DC / DC converter , the update rule is: ； when When , the forced contraction duty cycle change step is: ； Where, is the learning rate; is the contraction factor, which is dynamically adjusted according to the excess amplitude; The MPPT control subunit adopts a maximum power point tracking strategy that includes feedback of the operating health factor. The objective function is as follows: ； Where, is the optimized maximum power point target voltage; Indicates voltage Find the voltage point in the space that maximizes the expression in the brackets; is the photovoltaic module efficiency function; is the life protection weight factor; The MPPT control subunit outputs a target voltage according to the target function Real-time adjustment of the operating voltage of the photovoltaic module string, balancing the photovoltaic output efficiency and the electrolyzer stack life protection requirements, and real-time calculation of the power capability parameters of the current maximum power point , the formula is: ,in is the output current at the current voltage.

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