Maximum power point tracking control software combined with grey wolf algorithm

Abstract

The invention relates to maximum power point tracking control software combined with a grey wolf algorithm, and aims to improve the efficiency and the stability of a photovoltaic power generation system. According to the software, efficient operation of a photovoltaic power generation system is achieved by integrating a photovoltaic array power generation system, an electric energy adjusting system, a control algorithm system, an energy storage module and a monitoring system. Wherein the control algorithm system adopts a grey wolf algorithm, the system load is accurately adjusted, the maximum power point is quickly tracked, and the photovoltaic system is ensured to always keep high-power output under a changing sunlight condition. The energy storage module effectively manages redundant electric energy, provides electric energy compensation, and enhances system stability. The monitoring system monitors the circuit state in real time, and safe operation of the system is guaranteed. The invention further provides detailed software operation environment requirements and a system structure, and high efficiency and stability of software in practical application are ensured. The software has high user definition, can be optimized according to different requirements, and is suitable for various photovoltaic power generation scenes.

Description

Technical Field

[0001] The present invention relates to the technical field of renewable energy power generation, and in particular to a technical solution of maximum power point tracking control software combined with a grey wolf algorithm for a photovoltaic power generation system. Background Art

[0002] With the continuous growth of global energy demand and the increasing awareness of environmental protection, new energy power generation technology, especially solar photovoltaic power generation, has become an important area of ​​extensive attention and research around the world. As a clean and renewable energy source, solar energy has unlimited potential and broad application prospects. However, photovoltaic power generation systems face many challenges in actual operation, the most critical of which is how to achieve efficient and stable power output.

[0003] The power generation of photovoltaic power generation systems directly depends on the environmental climate and sunshine conditions. Due to changes in natural conditions such as sunshine intensity, temperature, and humidity, the output power of photovoltaic power generation systems will fluctuate significantly. This fluctuation not only affects the quality of electric energy, but also poses challenges to the stable operation of the power system. Therefore, how to effectively manage electric energy and achieve efficient operation of photovoltaic power generation systems has become a key technical problem that needs to be solved in the industry.

[0004] To solve this problem, the industry has proposed a variety of maximum power point tracking (MPPT) control strategies. MPPT technology aims to improve the power generation efficiency of the system by adjusting the operating parameters of the photovoltaic system so that it always works in the working state with the maximum output power. However, traditional MPPT control strategies often have problems such as slow convergence speed and weak global search ability, and are difficult to adapt to complex and changing sunshine conditions.

[0005] As an emerging intelligent optimization algorithm, the Gray Wolf Algorithm has attracted much attention due to its strong global search capability and fast convergence speed. The algorithm optimizes the objective function by simulating the predation behaviors of gray wolves such as searching, encircling, and attacking. In MPPT control, the Gray Wolf Algorithm can accurately adjust the equivalent load of the photovoltaic system, allowing it to quickly adapt to the power output fluctuations caused by changes in light, thereby maximizing the system output power.

[0006] Based on the above background, the present invention proposes a maximum power point tracking control software combined with the Grey Wolf algorithm, aiming to improve the efficiency and stability of the photovoltaic power generation system through an intelligent control strategy and maximize the utilization of solar energy.

[0007] In order to solve the above problems, the applicant proposes a maximum power point tracking control software combined with the Grey Wolf algorithm. Summary of the invention

[0008] The object of the present invention is to provide a maximum power point tracking control software combined with the grey wolf algorithm to solve the problems in the prior art.

[0009] To achieve the above object, the present invention provides the following technical solutions: A maximum power point tracking control software combined with the grey wolf algorithm, which is designed specifically for controlling a photovoltaic power generation system and integrates the following key subsystems:

[0010] A photovoltaic array power generation system, which has the function of effectively capturing solar energy through photovoltaic panels and converting it into electrical energy for output.

[0011] An electric energy regulation system, which can dynamically adjust the overall load of the system according to the fluctuation of the output current, thereby ensuring the stability of the electric energy output;

[0012] A control algorithm system, which adopts the grey wolf algorithm, and its core lies in accurately adjusting the control step size of the overall load of the system, enabling the system to quickly respond to output changes and ensuring continuous optimal output;

[0013] A energy storage module, which is responsible for managing the excess electric energy in the system and providing necessary electric energy compensation during the low-demand period of electric energy.

[0014] A monitoring system, which provides real-time monitoring of key circuit states such as current, voltage, and power of each branch and loop inside the system.

[0015] Optionally, the software realizes the rapid adjustment of the equivalent load of the photovoltaic power transmission system by accurately modulating the duty cycle of the controller, so as to adapt to the power output fluctuation caused by the change of light intensity, thereby maintaining the high-power output state of the power transmission system and improving the overall electric energy output efficiency.

[0016] Optionally, the software further includes the following components:

[0017] A power conversion control system, which adjusts the DC power in real time according to the current output of the photovoltaic system;

[0018] A GWO duty cycle modulation module, which uses the grey wolf algorithm to achieve accurate modulation of the duty cycle, ensuring the locking and stable output of the maximum power point of the system;

[0019] An electric energy management system, which intelligently manages electric energy according to the electric energy flow condition of the system, including the storage of electric energy and the discharge during the low-demand period;

[0020] An I / O data observation and recording system, which is responsible for recording the environmental conditions and system output, and calculating the system efficiency.

[0021] Optionally, the grey wolf algorithm includes a complete process: from parameter setting, fitness calculation, sorting of the optimal solution, to updating the parameter values and the positions of the grey wolves, until the iteration terminates and the result is output, ensuring the high efficiency and accuracy of the algorithm.

[0022] Optionally, the software allows users to customize key parameters of the photovoltaic array, including illumination brightness, temperature, and material coefficient. The software will automatically optimize the system efficiency based on these parameters to meet the electrical energy requirements of users or loads.

[0023] Optionally, the software also integrates comprehensive error handling and remedial measures, as well as system maintenance design, to ensure the continuous stable operation of the software and data security.

[0024] Beneficial effects: Significantly improve power generation efficiency: By adopting the grey wolf algorithm, the present invention can quickly and accurately adjust the equivalent load of the photovoltaic power generation system to ensure that the system always operates near the maximum power point. This not only improves the utilization rate of photovoltaic cells but also maximally converts solar energy into electrical energy, thus significantly improving the overall power generation efficiency of the photovoltaic power generation system.

[0025] Enhance system stability: The power regulation system and energy storage module in the present invention cooperate together to effectively manage the power flow in the photovoltaic power generation system. When the sunlight intensity fluctuates or the load demand changes, the system can quickly adjust to ensure the stability of the power output. The energy storage module can also provide power compensation when the light is insufficient, further enhancing the stability and reliability of the system.

[0026] Improve energy utilization rate: Through intelligent maximum power point tracking and power management, the present invention maximizes the energy output of the photovoltaic power generation system. This not only helps to reduce the dependence on traditional energy sources but also promotes the wide application of clean energy, which is of great significance to environmental protection and sustainable development.

[0027] Reduce operation and maintenance costs: The monitoring system of the present invention can real-time monitor the operation status and power quality of the photovoltaic power generation system, and timely detect and warn potential problems. This greatly reduces the operation and maintenance costs of the system and improves the operation and maintenance efficiency.

[0028] Strong user customization: The present invention allows users to customize key parameters of the photovoltaic array according to actual needs, such as illumination brightness, temperature, material coefficient, etc. This high degree of customization enables the software to adapt to different application scenarios and user needs, improving the flexibility and practicality of the software. Description of the Drawings

[0029] Figure 1 is the schematic physical structure diagram of the system in the embodiment of the present invention;

[0030] Figure 2 is the schematic system framework diagram of the embodiment of the present invention;;

[0031] Figure 3 is the schematic overall process diagram of the system in the embodiment of the present invention;

[0032] Figure 4 It is a schematic flowchart of the photovoltaic power generation simulation system according to an embodiment of the present invention;

[0033] Figure 5 It is a schematic flowchart of the grey wolf algorithm according to an embodiment of the present invention;

[0034] Figure 6 It is a schematic diagram of the power management system according to an embodiment of the present invention;

[0035] Figure 7 It is a schematic diagram of the control block diagram according to an embodiment of the present invention. Specific embodiments

[0036] The following introduces the preferred embodiments of the present invention with reference to the accompanying drawings of the specification to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned in the text.

[0037] Embodiment 1

[0038] The maximum power point tracking control software combined with the grey wolf algorithm mainly consists of a photovoltaic array power generation system, a power conditioning system, a control algorithm system, an energy storage module, a monitoring system, a power conversion control system, a GWO duty cycle modulation module, a power management system, and an I / O data observation and recording system, etc. These subsystems cooperate with each other to jointly achieve the efficient operation and power management of the photovoltaic power generation system.

[0039] The photovoltaic array power generation system is the core part of the photovoltaic power generation system and is responsible for converting solar energy into electrical energy. This system consists of multiple photovoltaic panels, which are connected together in series or parallel to form a large photovoltaic array. The photovoltaic panels are made of high-efficiency photovoltaic materials and have excellent photoelectric conversion efficiency and stability. Under sunlight conditions, the photovoltaic panels absorb solar energy and convert it into direct current electrical energy for output.

[0040] The power conditioning system is used to dynamically adjust the overall load of the system by the output current fluctuation, and then adjust the output to ensure the stability of the output. This system monitors parameters such as the output current and voltage of the photovoltaic array in real time, and adjusts the load size of the system according to the preset control strategy, so as to achieve precise control of the electrical energy output. The power conditioning system adopts advanced power electronic technology and has advantages such as fast response speed and high control accuracy.

[0041] The control algorithm system is one of the core parts of the present invention, and the grey wolf algorithm is used to achieve maximum power point tracking control. The grey wolf algorithm is an intelligent optimization algorithm that simulates the predation behavior of a grey wolf group. By simulating the predation behaviors such as searching, surrounding, and attacking of grey wolves, it realizes the optimal solution of the objective function. In MPPT control, the grey wolf algorithm takes the equivalent load of the photovoltaic system as the optimization object and continuously adjusts the load size to track the maximum power point.

[0042] Specifically, the application process of the grey wolf algorithm in MPPT control is as follows:

[0043] (1) Parameter setting: Determine the value range of the parameters of the grey wolf algorithm, including the size of the wolf group, the number of iterations, and the setting of the fitness function, etc. At the same time, set the initial values for the vectors α, A, and C.

[0044] (2) Fitness calculation: Use the set parameter values to calculate the fitness of the grey wolf population. The fitness represents the quality of each grey wolf individual at the current position, and it is usually determined by comparing the actual output power of the system with the output power at the maximum power point.

[0045] (3) Sort the optimal solutions: According to the calculated fitness, sort the grey wolf individuals to find the optimal solution (α wolf), the sub-optimal solution (β wolf), and the sub-sub-optimal solution (δ wolf). These optimal solutions will be used as the guiding information in the subsequent iteration process.

[0046] (4) Update the parameter values: After each iteration, update the values of the vectors α, A, and C according to the position of the current optimal solution. The update of these vectors will affect the search direction and step size of the subsequent grey wolf individuals.

[0047] (5) Update the positions of the grey wolves: Update the positions of each grey wolf individual according to the optimal solution and the positions of other grey wolf individuals. This update process can be carried out through a competition and cooperation mechanism to find a better solution. When updating the positions, the grey wolf individuals will move a certain step length in the direction of the optimal solution, and at the same time consider the position information of other grey wolf individuals to avoid falling into a local optimal solution.

[0048] (6) Iteration termination condition: When the number of iterations reaches the set value, stop the iteration and output the optimal solution as the final result. At this time, the grey wolf algorithm has converged to the global optimal solution or a position close to the global optimal solution.

[0049] Through the above process, the grey wolf algorithm can accurately adjust the equivalent load of the photovoltaic system, enabling it to quickly adapt to the power output fluctuations caused by changes in light intensity, thereby achieving the maximization of the system output power.

[0050] The energy storage module is used to manage the surplus electric energy in the system and provide electric energy compensation when the output valley value occurs. The system consists of an energy storage battery, a bidirectional DC-DC converter, etc. The energy storage battery adopts high-performance lithium-ion batteries, lead-acid batteries, etc., which have the advantages of large capacity, high energy density, and long cycle life. The bidirectional DC-DC converter is responsible for converting the DC electric energy of the energy storage battery into DC electric energy matching the output of the photovoltaic array and providing electric energy compensation to the system when needed.

[0051] In a photovoltaic power generation system, due to the changes in sunlight intensity and load demand, the electric energy output by the system will fluctuate. When the electric energy output by the system exceeds the load demand, the excess electric energy will be stored in the energy storage module; when the electric energy output by the system is insufficient to meet the load demand, the energy storage module will release the stored electric energy to make up for the shortage of the system output. In this way, the energy storage module can effectively suppress the fluctuations of the system output and improve the stability and reliability of the system.

[0052] The monitoring system is used to display the circuit states such as current, voltage, and power of each branch and loop inside the system, and to monitor the operation status and power quality of the photovoltaic power generation system in real time. The system consists of a data acquisition module, a data processing module, a data display module, etc. The data acquisition module is responsible for collecting parameters such as current, voltage, and power of key parts such as the photovoltaic array, the power conditioning system, and the energy storage module; the data processing module processes and analyzes the collected data and extracts useful information; the data display module displays the processed data to the user in the form of charts or reports, facilitating the user to understand the operation status and power quality of the system.

[0053] Through the monitoring system, users can understand the operation status and power quality of the photovoltaic power generation system in real time, and discover and warn potential problems in a timely manner. At the same time, the monitoring system can also provide functions such as historical data query and report generation for users, facilitating users to comprehensively analyze and evaluate the operation of the system.

[0054] The power conversion control system realizes DC power regulation according to the magnitude of the current output of the photovoltaic system. The system is equipped with a current detection device, which can detect the current and voltage states of the photovoltaic array output in real time and send these state information to the GWO duty cycle modulation system. The GWO duty cycle modulation system calculates the control step size and generates a duty cycle modulation signal according to the received state information. This signal controls the equivalent load size of the photovoltaic array through a power converter, thereby realizing precise control of the system output power.

[0055] The power conversion control system adopts advanced power electronic technologies and control strategies, and has the advantages of fast response speed and high control accuracy. Through this system, the photovoltaic power generation system can quickly adapt to the changes in sunlight intensity and load demand, and maintain stable output power and power quality.

[0056] The GWO duty cycle modulation module is another core part of the present invention, responsible for generating a duty cycle modulation signal according to the calculation results of the grey wolf algorithm. This module receives the current and voltage status information from the power conversion control system, and calculates the optimal duty cycle value according to the optimization results of the grey wolf algorithm. Then, this module sends the duty cycle modulation signal to the power converter to control the on and off times of its switching tubes, so as to achieve precise adjustment of the equivalent load of the photovoltaic array.

[0057] The GWO duty cycle modulation module is implemented by a high-performance microprocessor such as a digital signal processor (DSP) or a field-programmable gate array (FPGA), and has high-speed and high-precision computing capabilities. Through this module, the photovoltaic power generation system can quickly respond to changes in light intensity and load demand, and achieve maximum power point tracking and stable control of power output.

[0058] The power management system realizes the management and regulation of electric energy according to the electric energy flow situation of the system. This system has two operating modes: grid-connected operation of the photovoltaic-storage system and island operation of the photovoltaic-storage system. In the grid-connected operation mode, the power management system connects the electric energy of the photovoltaic power generation and the energy storage system to the grid, realizes the maximum utilization of energy and smooths the power fluctuations of renewable energy. At the same time, this system can also adjust the output power according to the needs of the grid to provide stable electric energy support for the grid. In the island operation mode, the power management system disconnects the photovoltaic power generation and the energy storage system from the grid to form an isolated microgrid system. This system can adjust the output power according to the load demand and provide necessary electric energy compensation when the light is insufficient or the load demand changes.

[0059] The power management system adopts advanced control strategies and optimization algorithms, and can perform intelligent adjustment according to the real-time electric energy flow situation and load demand. Through this system, the photovoltaic power generation system can maintain stable output power and power quality in different operating modes, and improve the reliability and stability of the system.

[0060] The I / O data observation and recording system is used to record the input environmental conditions (such as illuminance, temperature, humidity) and output parameters such as current, voltage, power, etc., and calculate the system efficiency. This system consists of a data acquisition module, a data storage module and a data display module, etc. The data acquisition module is responsible for collecting parameter information of key parts such as the photovoltaic array, environmental sensors and electric energy metering devices; the data storage module stores and manages the collected data to facilitate users to query and analyze historical data; the data display module displays the processed data to users in the form of charts or reports to facilitate users to understand the operation situation and efficiency level of the system.

[0061] Through the I / O data observation and recording system, users can comprehensively understand the operation status and efficiency level of the photovoltaic power generation system, providing strong data support for system optimization and improvement. At the same time, the system can also provide users with functions such as historical data query and report generation, facilitating users to conduct comprehensive analysis and evaluation of the system operation status.

[0062] The maximum power point tracking control software combined with the grey wolf algorithm of the present invention is designed to run in a specific hardware and operating system environment to ensure its performance, stability and compatibility. The following is a detailed description of the software operating environment:

[0063] Processor: A central processing unit (CPU) with a relatively high processing speed is required, such as Intel Core i5 / i7 or AMD Ryzen series, to ensure the efficient operation of the grey wolf algorithm and real-time data processing capabilities. A multi-core processor will be more conducive to improving computing efficiency and response speed.

[0064] Memory: At least 8GB of RAM is required to support multi-tasking and large data volume storage during software operation. For large-scale photovoltaic power generation systems or data recording and analysis tasks that require long-term operation, a larger memory capacity will be a better choice.

[0065] Storage: It is recommended to use a solid-state drive (SSD) as the system disk to improve the software startup speed and data read / write efficiency. At the same time, sufficient storage space is required to save historical data, log files and reports, etc.

[0066] Interface: The software needs to communicate with various components of the photovoltaic power generation system, so it is required that the computer has necessary interfaces, such as USB, RS232 / RS485, Ethernet, etc., to connect devices such as data acquisition modules, sensors and controllers.

[0067] Display device: A high-resolution display will be more conducive to presenting the software's graphical interface and data charts, improving the user experience.

[0068] Operating system: This software supports operating systems above Windows 7 or specific distributions of the Linux system (such as Ubuntu). These operating systems provide a stable operating environment and rich development tools, which are conducive to software deployment and maintenance.

[0069] Software dependencies: The software may depend on certain specific libraries or frameworks, such as.NET Framework, Java Runtime Environment (JRE) or Python interpreter, etc. When installing the software, these dependencies will be automatically checked and installed, or the user will be required to install them manually.

[0070] Security: The operating system should have basic security protection measures, such as firewalls, antivirus software, etc., to prevent the intrusion of malware and data leakage. At the same time, the software itself will also adopt encryption technology to protect the security of user data.

[0071] LAN Connection: The software needs to communicate with each component of the photovoltaic power generation system in real time. Therefore, it is required that the computer and these components are in the same local area network, or remote connection is achieved through technologies such as VPN.

[0072] Internet Access: In order to obtain real-time weather data, update software versions or access remote databases, etc., the computer needs to have the ability to access the Internet. It is recommended to configure a stable network connection and sufficient bandwidth to ensure the timely transmission of data and the normal operation of the software.

[0073] Backup and Recovery: It is recommended that users regularly back up important data and configuration files of the software to prevent data loss or damage. The software will provide backup and recovery functions to facilitate users' data management.

[0074] Update and Maintenance: The software will regularly release updated versions to fix known problems, add new features or improve performance. Users should pay attention to the software update notifications and install the updated versions in a timely manner.

[0075] User Permissions: To ensure the normal operation of the software and the security of data, it is recommended that users run the software as an administrator and set appropriate user permissions to restrict access to and operations on sensitive data.

[0076] In summary, the maximum power point tracking control software combining the grey wolf algorithm of the present invention has certain requirements for hardware, operating system, network and other environments. Users should configure a suitable operating environment according to the actual situation to ensure the normal operation and optimal performance of the software. At the same time, users should also pay attention to the update and maintenance of the software to obtain new features and performance improvements in a timely manner.

[0077] The above has shown and described the basic principles, main features and advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to embrace all changes falling within the meaning and scope of the equivalent elements of the claims in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

[0078] In addition, it should be understood that although this specification is described in terms of embodiments, not every embodiment contains only one independent technical solution. This narrative style of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A maximum power point tracking control software combined with the Grey Wolf algorithm, characterized in that: The software is designed specifically for controlling photovoltaic power generation systems and integrates the following key subsystems: Photovoltaic array power generation system has the function of effectively capturing solar energy through photovoltaic panels and converting it into electrical energy output. Power regulation system, which can dynamically adjust the overall system load according to the fluctuation of output current, so as to ensure the stability of power output; Control algorithm system, which uses the Grey Wolf algorithm, the core of which is to accurately adjust the control step length of the total system load, so that the system can respond quickly to output changes and ensure continuous optimal output; Energy storage module, which is responsible for managing excess power within the system and providing necessary power compensation when power demand is low. The monitoring system provides real-time monitoring of key circuit states such as current, voltage, power, etc. of each branch and loop within the system.

2. According to claim 1, the maximum power point tracking control software combined with the grey wolf algorithm is characterized in that: The software achieves rapid adjustment of the equivalent load of the photovoltaic power transmission system by precisely modulating the duty cycle of the controller to adapt to power output fluctuations caused by changes in light, thereby maintaining a high power output state of the power transmission system and improving the overall power output efficiency.

3. According to claim 1, the maximum power point tracking control software combined with the grey wolf algorithm is characterized in that: The software also includes the following components: Power conversion control system, which adjusts DC power in real time according to the current output of the photovoltaic system; GWO duty cycle modulation module uses the Grey Wolf algorithm to achieve precise duty cycle modulation, ensuring the locking of the system's maximum power point and stable output; The power management system intelligently manages power according to the power flow of the system, including power storage and discharge during low periods; The I / O data observation and recording system is responsible for recording environmental conditions and system output, and calculating system efficiency.

4. According to claim 1, the maximum power point tracking control software combined with the grey wolf algorithm is characterized in that: The gray wolf algorithm includes a complete process: from parameter setting, fitness calculation, sorting optimal solutions, to updating parameter values ​​and gray wolf positions, until iteration termination and output of results, to ensure the efficiency and accuracy of the algorithm.

5. According to claim 1, the maximum power point tracking control software combined with the grey wolf algorithm is characterized in that: The software allows users to customize key parameters of the photovoltaic array, including light illumination, temperature, and material coefficients. The software will automatically optimize system efficiency based on these parameters to meet the power needs of users or loads.

6. According to claim 1, the maximum power point tracking control software combined with the grey wolf algorithm is characterized in that: The software also integrates comprehensive error handling and remediation measures, as well as system maintenance design to ensure the continuous stable operation of the software and data security.

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