CN117913886A - Intelligent rotation dormancy control method of modularized photovoltaic inverter - Google Patents
Intelligent rotation dormancy control method of modularized photovoltaic inverter Download PDFInfo
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Abstract
本申请涉及光伏发电系统领域，公开了一种模块化光伏逆变器的智能轮换休眠控制方法，包括以下步骤：S1、在光伏模块上采集电压、电流和温度；S2、计算模块的功率输出和效率；S3、确定模块的最优工作点功率输出；S4、计算模块的期望输出功率；S5、计算模块的工作时间比例；S6、确定模块的工作顺序；S7、根据模块的工作顺序，实施轮换休眠控制。本发明通过实时监测模块的实际输出功率，根据实际与期望输出功率之间的差异调整模块的工作时间比例，更新模块的优先级，重新确定工作顺序，并实施轮换休眠控制。通过这种方法，不仅可以提高光伏系统的整体效率和性能，还可以延长模块的寿命，并确保在各种环境条件下稳定地满足电力需求。
The present application relates to the field of photovoltaic power generation systems, and discloses an intelligent rotation sleep control method for a modular photovoltaic inverter, comprising the following steps: S1, collecting voltage, current and temperature on the photovoltaic module; S2, calculating the power output and efficiency of the module; S3, determining the optimal working point power output of the module; S4, calculating the expected output power of the module; S5, calculating the working time ratio of the module; S6, determining the working order of the module; S7, implementing rotation sleep control according to the working order of the module. The present invention monitors the actual output power of the module in real time, adjusts the working time ratio of the module according to the difference between the actual and expected output power, updates the priority of the module, redetermines the working order, and implements rotation sleep control. Through this method, not only the overall efficiency and performance of the photovoltaic system can be improved, but also the life of the module can be extended, and it can be ensured that the power demand is stably met under various environmental conditions.
Description
Technical Field
The invention relates to the technical field of photovoltaic power generation systems, in particular to the technical field related to a control strategy and a management method of a photovoltaic inverter, and specifically relates to an intelligent alternate dormancy control method of a modularized photovoltaic inverter.
Background
With the worldwide increasing demand for renewable energy, photovoltaic power generation systems have significantly increased in share in the energy market as a clean, sustainable energy solution. The photovoltaic inverter is used as one of core components of a photovoltaic system and is responsible for converting direct current generated by a photovoltaic module into alternating current which can be used by a power supply network or a load. However, the conventional photovoltaic inverter has some limitations such as inefficiency, insufficient management of the module, and failure to extend the service life of the module to the maximum extent.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent rotation dormancy control method of a modularized photovoltaic inverter, and the dynamic management and optimization of the working state of a photovoltaic module are realized through a control algorithm so as to adapt to the real-time change of the power demand.
In order to achieve the above purpose, the invention is realized by the following technical scheme: an intelligent alternate dormancy control method of a modularized photovoltaic inverter comprises the following steps:
S1, collecting voltage, current and temperature on a photovoltaic module;
s2, calculating the power output and efficiency of the module according to the voltage, current and temperature of the module;
S3, determining the optimal working point power output of the module according to the volt-ampere characteristic curve of the module and environmental factors;
s4, calculating expected output power of the module by combining the optimal working point power output of the module and environmental factors;
S5, calculating the working time proportion of the module according to the expected output power of the module and the total expected output power of the system;
s6, determining the working sequence of the modules by combining the working time proportion of the modules, the priority of the modules and constraint conditions;
S7, implementing alternate dormancy control according to the working sequence of the modules.
Preferably, the calculation formula of the power output of the optimal working point is as follows:
Popt＝Vmpp×Impp
Wherein, P opt represents the optimal working point power output of the module, V mpp represents the maximum power point voltage, I mpp represents the maximum power point current, and V mpp and I mpp are obtained by combining the volt-ampere characteristic curve of the module with the temperature correction factor.
Preferably, the calculation formula of the expected output power of the module is as follows:
Pexpected＝Popt×deratefactor
where P expected represents the desired output power of the module, P opt represents the optimal operating point power output of the module, and derate factor represents the power derating factor due to environmental factors.
Preferably, the calculation formula of the total expected output power of the system is as follows:
Ptotal＝N×Wp×deratefactor×demandfactor
Where P total represents the total desired output power of the system, N represents the number of photovoltaic panels, wp represents the peak power of an individual photovoltaic panel, derate factor represents the power derating coefficient derived from environmental conditions, demand factor represents the demand coefficient derived from real-time power demand.
Preferably, the calculation formula of the working time proportion of the module is as follows:
where T ratio represents the on-time ratio of the modules, P expected represents the desired output power of the individual modules, and P total represents the total desired output power of the system.
Preferably, the constraints include maximum continuous operating time, predetermined maintenance period, failure rate and reliability, power output efficiency, environmental factors, overall power requirements of the photovoltaic array, energy storage device status.
Preferably, the determining of the working sequence includes the following steps:
1) Assigning an initial priority score to each photovoltaic module based on its nominal performance, historical performance data, and a predetermined maintenance period;
2) Updating the priority score of each module according to the real-time data and the historical working data;
3) Considering constraint conditions of the module;
4) Calculating the working time proportion of each module;
5) Sequencing the modules according to the priority scores, and ensuring that all constraint conditions are satisfied;
6) And generating the working sequence of the module according to the sequencing result and the working time proportion.
Preferably, the alternate sleep control is implemented by a control algorithm that dynamically adjusts the operating state of the modules according to the operating sequence and operating time ratio of the modules to ensure that the overall power output of the system meets the expectations and to optimize the operating efficiency and lifetime of each module.
Preferably, the control algorithm includes:
a) Monitoring real-time power demand of a power grid or load;
b) Determining a module which is supposed to work currently according to the working sequence and the working time proportion of each module;
c) Dynamically starting or closing the module, and adjusting the working state of the module;
d) Considering the dependence among the modules, ensuring that the dependence among the modules is properly managed when the working state is adjusted;
e) Updating the working time record of the module for future priority score updating;
f) Continuously monitoring the state of the module, and detecting and processing abnormal conditions;
g) Maintaining the quality of the overall power output of the system, and ensuring the stability of frequency and voltage;
h) Optimizing the operating efficiency and life of the module while ensuring that the overall power requirements of the system are met.
Preferably, the method further comprises:
S8, monitoring the actual output power of the module;
S9, adjusting the working time proportion of the module according to the difference between the actual output power and the expected output power of the module;
S10, updating the priority of the module according to the adjustment condition of the working time proportion of the module;
S11, redetermining the working sequence of the module according to the adjustment condition of the working time proportion of the module and other constraint conditions;
s12, implementing alternate dormancy control according to the updated working sequence.
The invention provides an intelligent alternate dormancy control method of a modularized photovoltaic inverter. The beneficial effects are as follows:
1. The intelligent control system is controlled intelligently, and the system always operates at the optimal working point, so that the power output is improved. Through alternate dormancy control, the continuous high-load work of the module is avoided, the abrasion is reduced, and the service life of the module is prolonged. Through alternate dormancy control, the continuous high-load work of the module is avoided, the abrasion is reduced, and the service life of the module is prolonged. The method of the invention maximizes the potential of each module, protects investment and ensures long-term, stable and efficient operation of the system.
2. The invention monitors the actual output power of the module in real time, adjusts the working time proportion of the module according to the difference between the actual output power and the expected output power, updates the priority of the module, re-determines the working sequence, and implements the alternate dormancy control. By this method, not only the overall efficiency and performance of the photovoltaic system can be improved, but also the life of the module can be prolonged, and the stable satisfaction of power requirements under various environmental conditions can be ensured.
3. According to the intelligent control method, the photovoltaic inverter is used for flexibly managing the working state of the photovoltaic module, the overall efficiency and performance of the system are improved, and meanwhile, the long-term health of each module and the reliability of the system are considered. This approach helps balance the load of the module, extend the module life, and ensure that the power requirements are met continuously and steadily under different conditions.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a schematic flow diagram of one embodiment of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention provides an intelligent rotation dormancy control method of a modularized photovoltaic inverter, which aims to optimize the power output of a photovoltaic system, improve the system efficiency and prolong the service life of a module.
Referring to fig. 1, the method comprises the steps of:
Step S1: collecting data
The voltage, current and temperature data of the photovoltaic modules are collected in real time by sensors mounted on each module. These data are critical to the real-time power output and efficiency of the computing module.
Step S2: calculating power output and efficiency
And obtaining the instantaneous power output of the module through the product by utilizing the acquired voltage and current data. The efficiency is then obtained by comparing the actual power output with the rated power of the module under standard test conditions.
Step S3: determining an optimal operating point
The voltammetric characteristic of the module describes the relationship between voltage and current, which varies with environmental factors such as temperature and illumination intensity. By analyzing this curve, the Maximum Power Point (MPP), i.e. the optimal operating point, of the module under the current conditions is determined.
Step S4: calculating the desired output power
And (3) calculating the expected output power of the module under the current condition by combining the optimal working point power output determined in the step (S3) and the current environmental factors (such as temperature, illumination intensity and the like).
Step S5: calculating the proportion of working time
The proportion of operating time that each module should allocate is calculated from the proportion of the desired output power of each module to the total desired output power, taking into account the total desired output power of the system.
Step S6: determining work order
After determining the proportion of the operating time for each module, a prioritization algorithm is used to determine the order of operation of the modules in combination with the priority of the modules and constraint conditions (e.g., maintenance period, historical operating time, reliability of the modules, etc.).
Step S7: implementing alternate sleep control
And dynamically adjusting the working state of the module through the control system according to the working sequence determined in the step S6. The module with longer working time or lower efficiency enters the dormant state, and the module with high working efficiency and long dormant time is awakened to participate in power output.
Specifically, the system always operates at the optimal working point through intelligent control, so that the power output is improved. Through alternate dormancy control, the continuous high-load work of the module is avoided, the abrasion is reduced, and the service life of the module is prolonged. Through alternate dormancy control, the continuous high-load work of the module is avoided, the abrasion is reduced, and the service life of the module is prolonged. The method of the invention maximizes the potential of each module, protects investment and ensures long-term, stable and efficient operation of the system.
As an embodiment of the present invention, in a photovoltaic power generation system, the maximum power point (Maximum Power Point, MPP) refers to the maximum power output point that a photovoltaic module can generate under given environmental conditions (e.g., illumination, temperature). This point is determined by the volt-ampere characteristic Curve (I-V Curve) which represents the performance of the module at different voltages and currents.
Since the performance of the photovoltaic module is affected by temperature, the temperature needs to be corrected when calculating the maximum power point. Typically, as the temperature increases, the voltage of the photovoltaic module decreases, while the current does not change much, so the maximum power point voltage V mpp decreases as the temperature increases.
In an embodiment of the invention, the maximum power point voltage V mpp and the maximum power point current I mpp are determined by monitoring the performance of the photovoltaic module in real time in combination with a temperature correction factor. This temperature correction factor is typically based on a temperature coefficient provided by the module manufacturer or obtained through experimental data.
The formula for calculating the optimal operating point power output is as follows:
Popt＝Vmpp×Impp
Wherein, P opt represents the optimal working point power output of the module, V mpp represents the maximum power point voltage, I mpp represents the maximum power point current, and V mpp and I mpp are obtained by combining the volt-ampere characteristic curve of the module with the temperature correction factor.
This formula means that the optimal operating point power output is the product of the maximum power point voltage and the maximum power point current. In practice, photovoltaic inverters often incorporate maximum power point tracking (Maximum Power Point Tracking, MPPT) technology that dynamically adjusts the operating point of the photovoltaic modules connected to the inverter to ensure that they always operate at or near P opt under different environmental conditions.
The calculation and tracking technology of the power output of the optimal working point is applied to the intelligent rotation dormancy control method of the photovoltaic inverter, so that the overall performance and reliability of the photovoltaic power generation system are further improved.
As an embodiment of the present invention, in a photovoltaic power generation system, due to environmental factors (such as temperature, illumination intensity, dust accumulation, aging, etc.), the actual output power is generally lower than the maximum power point output of the module under standard test conditions. To more accurately predict the performance of a photovoltaic module under actual operating conditions, a power derating coefficient (derate factor) is typically used to modify the optimum operating point power output P opt.
The power derating factor is a value less than or equal to 1 to account for performance loss under actual operating conditions. It reflects the extent of influence of the actual environmental factors on the output power of the photovoltaic module. For example, if the module is operating at high temperature, its output power will drop, at which point the power derating factor will be below 1.
According to an embodiment of the present invention, the calculation formula of the module expected output power P expected is as follows:
Pexpected＝Popt×deratefactor
Where P expected is the output power that the module is expected to actually provide after considering environmental factors, P opt is the optimal operating point power output of the module under given environmental conditions, and derate factor is the power derating factor to account for performance loss under actual operating conditions.
By applying this formula, the actual contribution of each photovoltaic module under specific operating conditions is more accurately estimated, resulting in better system design and power management. This is important to maintain efficient operation of the system as a whole and to make accurate energy predictions. In addition, in implementing intelligent rotational sleep control, this calculation of the desired output power is also the basis for determining the module operating time scale and operating sequence.
As an embodiment of the present invention, in an embodiment of the present invention, the calculation of the total expected output power P total of the system is to estimate the total power that the entire photovoltaic power generation system is expected to be able to provide under specific environmental and demand conditions. This expected total power accounts for environmental factors resulting in power derating and adjustments that the system needs to make to meet real-time power demands. The calculation formula is as follows:
Ptotal＝N×Wp×deratefactor×demandfactor
Where P total is the total expected output power of the system, N is the number of photovoltaic panels, wp is the peak power of a single photovoltaic panel under standard test conditions (usually refers to the peak power at standard test conditions, i.e. the illumination intensity is 1000W/m 2, and the module temperature is 25 ℃), derate factor is the power derating coefficient obtained according to environmental conditions (such as factors of temperature, illumination intensity, dust accumulation, module aging, etc.), and is used to correct the actual output power of the module under non-standard test conditions, demand factor is the demand coefficient obtained according to the real-time power demand, and reflects the output power proportion required by the system to meet the current power demand.
The calculation of the total expected output power of the system is crucial to energy management and planning, and helps operators optimize the operation strategy of the photovoltaic power generation system, so that the system can operate as efficiently as possible under different environmental conditions and load demands. For example, when the real-time power demand is below the maximum capacity of the system, the system reduces the output power by reducing demand factor, thereby avoiding overproduction and energy waste.
As an embodiment of the invention, in an embodiment of the invention, the operating time ratio T ratio of the module is to determine the operating contribution of the individual photovoltaic modules with respect to the overall system. This ratio helps us decide how long each module should work within a certain period of time. This is important to achieve intelligent management and optimization of the system, especially in situations where rotation of module work is required to balance the load or extend the life of the module. The calculation formula is as follows:
Where T ratio denotes the operating time ratio of the modules, P expected denotes the desired output power of a single module, which is calculated based on the optimal operating point power of the module, the power derating factor, and other relevant factors, and P total denotes the total desired output power of the system, which is the sum of the desired output powers of all the modules, or the total output power calculated based on the system requirements.
By calculating T ratio, we know the amount of work that each module should take. For example, if P expected for a module is half of the overall system P total, then T ratio would be 0.5, meaning that the module should be responsible for half the work time or workload.
The calculation method is used for dynamically adjusting the working state of the photovoltaic module to respond to real-time energy demand change or to realize more balanced ageing and maintenance plan. This increases the efficiency and reliability of the overall system while maximizing the life and return on investment of each module.
As an embodiment of the present invention, in order to ensure efficient, reliable operation of the photovoltaic power generation system while taking into account long-term performance and maintainability, various constraints need to be taken into account in the system design and operation. The following are some detailed descriptions of these constraints:
Maximum continuous working time: each photovoltaic module or portion of the system has a prescribed maximum continuous operating time beyond which overheating or other forms of wear can result, affecting life and performance.
Scheduled maintenance period: photovoltaic systems require periodic maintenance to maintain optimal performance, with maintenance periods being determined based on manufacturer recommendations, historical data, or predictive models.
Failure rate and reliability: the system design needs to take into account the failure rate of the components and the reliability of the overall system. The system failure rate is reduced through redundancy design, failure prediction and timely maintenance.
Power output efficiency: the efficiency of a photovoltaic module varies with environmental factors such as temperature, illumination intensity, etc. The system design should take these efficiency variations into account to optimize power output.
Environmental factors: including climate conditions, seasonal variations, solar time, etc., all of which affect the performance and power output of the photovoltaic system.
Overall power requirements of photovoltaic arrays: the design and operation of the system needs to be planned according to actual and anticipated power requirements to ensure that the user's requirements can be met without generating excess power.
State of energy storage device: if the system contains batteries or other forms of energy storage devices, the status of these devices can also affect the operation of the system. For example, the state of charge, health, and energy storage capacity of a battery are all factors to be considered.
In implementing these constraints, the operation of the system is dynamically adjusted by employing complex algorithms and control strategies. For example, intelligent monitoring and predictive maintenance systems are employed to predict and prevent faults, advanced energy management systems are used to optimize the use of energy storage devices, and meteorological data is utilized to predict and adapt to environmental changes.
The final objective is to achieve a photovoltaic power generation system that meets power requirements while maintaining high efficiency and long-term reliability. By considering these constraints during the design and operation phase, the system is made more robust, reduces unexpected downtime, prolongs the life of the equipment, and improves overall economic benefits.
As an embodiment of the present invention, the operation sequence of the photovoltaic module is determined through one detailed step to maximize the performance and lifetime of the entire photovoltaic power generation system. The following are the specific contents of these steps:
1) Each photovoltaic module is assigned an initial priority score: first, each photovoltaic module will obtain an initial priority score based on its nominal performance (e.g., maximum power point), historical performance data (e.g., average energy output, fault and maintenance history), and predetermined maintenance periods (e.g., manufacturer recommended maintenance schedule). This score helps the system identify which modules should be used preferentially at a particular point in time.
2) Updating the priority score of each module according to the real-time data and the historical working data: as the photovoltaic system operates, real-time performance data (e.g., current output power, temperature, etc.) and historical operating data (e.g., run time, power generation, etc.) will be used to update the priority score of each module to reflect its current operating state and efficiency.
3) Consider the constraint of the module: various constraints, such as maximum continuous operation time of the module, failure rate, maintenance period, and state of the energy storage device, etc., must be considered in determining the order of operation.
4) Calculating the working time proportion of each module: based on the priority scores of the modules and the overall power requirements of the system, the proportion of working time that each module should be responsible for, i.e., T ratio, is calculated.
5) The modules are ordered according to the priority scores, and all constraint conditions are ensured to be satisfied: the modules are ordered with a higher priority in front, but at the same time it is ensured that the constraints of all modules in the ordering process are met, e.g. that no module exceeds its maximum continuous working time.
6) Generating the working sequence of the module according to the sequencing result and the working time proportion: finally, a detailed work order is generated, in which it is specified which modules are working at what time and for how long, based on the priority ranking of the modules and the respective working time ratios. This working sequence will be used to control the actual operation of the photovoltaic system.
Through such a process, the photovoltaic system intelligently adjusts the operating state of each module to account for real-time energy demand changes, while taking into account the health of the module and the long-term reliability of the system. This increases the overall efficiency of the system, extends the life of the module, and ensures sustainable supply of energy.
As one implementation mode of the invention, the alternate dormancy control is realized by a control algorithm, and the control algorithm dynamically adjusts the working state of the modules according to the working sequence and the working time proportion of the modules so as to ensure that the overall power output of the system meets the expectations and optimize the working efficiency and the service life of each module.
In particular, by this alternate sleep control strategy, the photovoltaic power generation system operates more efficiently and intelligently. The energy utilization efficiency is improved, the waste is reduced, and the service life of the module can be prolonged by preventing excessive abrasion and advanced aging, so that the reliability is maintained, and the long-term operation cost is reduced.
Further, the control algorithm implementation steps include:
a) Monitoring real-time power demand of the grid or load: the algorithm monitors the power demand of the grid or load connected to the photovoltaic system in real time. This requirement may change due to time or condition changes that the algorithm must keep track of to make appropriate adjustments.
B) Determining a module that should currently operate: the algorithm decides which modules should be activated to supply power according to a preset work order and a work time ratio of each module. This decision is based on the efficiency of the module, maintenance requirements, historical performance, and real-time system requirements.
C) Dynamically powering on or off the module: the algorithm dynamically starts or shuts down the modules as required. More modules will be activated when demand increases, and some modules will be put to sleep, or shut down entirely, when demand decreases.
D) Consider inter-module dependencies: when adjusting the working state of the modules, the algorithm must consider the dependency relationships existing between the modules, such as serial or parallel configuration, to ensure that the dependency relationships are properly managed to maintain the stability of the system.
E) Updating the working time record of the module: the algorithm will record the on-time of each module and update these records periodically. These data are critical to future priority score updates and maintenance planning.
F) Continuously monitoring the state of the module: algorithms continuously monitor the status of each module, including power output, temperature, efficiency, etc., to detect any anomalies and to handle them in time, such as module failure or performance degradation.
G) Maintaining the quality of the overall power output of the system: the algorithm ensures that the overall power output of the system meets quality criteria, including frequency and voltage stability, which is critical to the stable operation of the grid.
H) Optimizing the working efficiency and prolonging the service life of the module: while ensuring that the overall power requirements of the system are met, the algorithm also aims to optimize the working efficiency of each module and extend its lifetime, by reducing unnecessary workload and avoiding potential damaging factors such as sustained high temperatures or frequent switching operations.
Through the steps, the control algorithm can effectively manage the working state of the photovoltaic module while meeting the real-time power demand, and the high-efficiency operation and long-term stability of the system are realized.
Referring to fig. 2, as an embodiment of the present invention, the intelligent rotation sleep control method of the modular photovoltaic inverter further optimizes management of the photovoltaic module, specifically by the following steps:
S8, monitoring the actual output power of the module: the system monitors the output power of each photovoltaic module in real time. This is the basis for ensuring that the module is working properly and adjusting its working state in time.
S9, adjusting the working time proportion according to the difference between the actual output power and the expected output power: if there is a significant difference in the actual output power of the module from the desired output power, the system will adjust the duty cycle of the module based on this difference. For example, if the actual output power of a module continues to be lower than desired, the operating time ratio is reduced and more operating time is allocated to the better performing module.
S10, updating the priority of the module: the system updates the priority of each module according to the adjustment of the working time proportion of the module. Priority is based on a variety of factors including efficiency, reliability, historical performance, and maintenance requirements of the module.
S11, redetermining the working sequence of the module: the system may re-determine the order of operation of the modules in view of adjustments in the module's operating time scale and other constraints such as inter-module dependencies, preventive maintenance schedules, environmental factors, etc.
S12, implementing alternate dormancy control: and according to the updated working sequence, the system implements alternate dormancy control. This involves placing certain modules in a dormant state while other modules are activated, or making corresponding adjustments based on system requirements and module performance.
By the intelligent control method, the photovoltaic inverter can more flexibly manage the working state of the photovoltaic module, the overall efficiency and performance of the system are improved, and meanwhile, the long-term health of each module and the reliability of the system are considered. This approach helps balance the load of the module, extend the module life, and ensure that the power requirements are met continuously and steadily under different conditions.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The intelligent alternate dormancy control method of the modularized photovoltaic inverter is characterized by comprising the following steps of:
S1, collecting voltage, current and temperature on a photovoltaic module;
s2, calculating the power output and efficiency of the module according to the voltage, current and temperature of the module;
S3, determining the optimal working point power output of the module according to the volt-ampere characteristic curve of the module and environmental factors;
s4, calculating expected output power of the module by combining the optimal working point power output of the module and environmental factors;
S5, calculating the working time proportion of the module according to the expected output power of the module and the total expected output power of the system;
s6, determining the working sequence of the modules by combining the working time proportion of the modules, the priority of the modules and constraint conditions;
S7, implementing alternate dormancy control according to the working sequence of the modules.
2. The intelligent rotation sleep control method of a modular photovoltaic inverter according to claim 1, wherein the calculation formula of the optimal operating point power output is:
Popt＝Vmpp×Impp
Wherein, P opt represents the optimal working point power output of the module, V mpp represents the maximum power point voltage, I mpp represents the maximum power point current, and V mpp and I mpp are obtained by combining the volt-ampere characteristic curve of the module with the temperature correction factor.
3. The intelligent rotational sleep control method of a modular photovoltaic inverter of claim 1, wherein the calculation formula of the module expected output power is:
Pexpected＝Popt×deratefactor
where P expected represents the desired output power of the module, P opt represents the optimal operating point power output of the module, and derate factor represents the power derating factor due to environmental factors.
4. The intelligent rotation sleep control method of a modular photovoltaic inverter according to claim 1, wherein the calculation formula of the total expected output power of the system is:
Ptotal＝N×Wp×deratefactor×demandfactor
Where P total represents the total desired output power of the system, N represents the number of photovoltaic panels, wp represents the peak power of an individual photovoltaic panel, derate factor represents the power derating coefficient derived from environmental conditions, demand factor represents the demand coefficient derived from real-time power demand.
5. The intelligent rotation dormancy control method of a modularized photovoltaic inverter according to claim 1, wherein the calculation formula of the working time proportion of the module is as follows:
where T ratio represents the on-time ratio of the modules, P expected represents the desired output power of the individual modules, and P total represents the total desired output power of the system.
6. The intelligent rotational sleep control method for a modular photovoltaic inverter of claim 1, wherein the constraints include maximum continuous operating time, predetermined maintenance period, failure rate and reliability, power output efficiency, environmental factors, overall power demand of the photovoltaic array, energy storage device status.
7. The intelligent rotational sleep control method for a modular photovoltaic inverter of claim 6, wherein the determining of the work sequence comprises the steps of:
1) Assigning an initial priority score to each photovoltaic module based on its nominal performance, historical performance data, and a predetermined maintenance period;
2) Updating the priority score of each module according to the real-time data and the historical working data;
3) Considering constraint conditions of the module;
4) Calculating the working time proportion of each module;
5) Sequencing the modules according to the priority scores, and ensuring that all constraint conditions are satisfied;
6) And generating the working sequence of the module according to the sequencing result and the working time proportion.
8. The intelligent alternate sleep control method of a modular photovoltaic inverter of claim 1, wherein the alternate sleep control is implemented by a control algorithm that dynamically adjusts the operating state of the modules according to the operating sequence and operating time ratio of the modules to ensure that the overall power output of the system meets expectations and to optimize the operating efficiency and lifetime of each module.
9. The intelligent rotational sleep control method for a modular photovoltaic inverter of claim 8, wherein the control algorithm comprises:
a) Monitoring real-time power demand of a power grid or load;
b) Determining a module which is supposed to work currently according to the working sequence and the working time proportion of each module;
c) Dynamically starting or closing the module, and adjusting the working state of the module;
d) Considering the dependence among the modules, ensuring that the dependence among the modules is properly managed when the working state is adjusted;
e) Updating the working time record of the module for future priority score updating;
f) Continuously monitoring the state of the module, and detecting and processing abnormal conditions;
g) Maintaining the quality of the overall power output of the system, and ensuring the stability of frequency and voltage;
h) Optimizing the operating efficiency and life of the module while ensuring that the overall power requirements of the system are met.
10. The intelligent rotational sleep control method for a modular photovoltaic inverter of any of claims 1-9, further comprising:
S8, monitoring the actual output power of the module;
S9, adjusting the working time proportion of the module according to the difference between the actual output power and the expected output power of the module;
S10, updating the priority of the module according to the adjustment condition of the working time proportion of the module;
S11, redetermining the working sequence of the module according to the adjustment condition of the working time proportion of the module and other constraint conditions;
s12, implementing alternate dormancy control according to the updated working sequence.
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