Photovoltaic cell-level dynamic reconfigurable energy generation method and system

Abstract

According to the photovoltaic cell-level dynamic reconfigurable energy generation method and system, each battery is independently packaged in a standard unit, and standardized integration of electrical, cooling and data interfaces is realized through a matrix type intelligent backboard, so that the battery pieces can be plugged on line like a blade server; a GaN-based chip-level power optimizer is arranged in each unit, a distributed energy routing network is formed through interconnection of a high-speed bus, and millisecond-level fault isolation and standby switching are achieved; according to the system, sheet-level electrical data, sensor data and inspection visual data are fused, battery sheet-level fault accurate positioning and service life prediction are achieved through AI diagnosis, and a robot is scheduled to execute non-stop hot plug replacement; battery piece-assembly-power station multi-time-scale cooperative control, inner ring millisecond-level MPPT, middle ring second-level coordinated reconstruction and outer ring minute-level global optimization are adopted. According to the architecture, a photovoltaic power station is converted from a static product into a dynamic ecological system capable of self-sensing and self-healing optimization, and the availability, the generating capacity and the full-life-cycle economy are remarkably improved.

Description

Technical Field

[0001] This project involves a highly interdisciplinary and integrated cluster of cutting-edge technologies, with its core being an advanced packaging and integration technology system for next-generation, highly reliable, and maintainable photovoltaic systems. This technology system primarily breaks through the traditional manufacturing paradigm of photovoltaic modules, which is centered on "lamination." Its key technological focus is on an open modular packaging structure, which constitutes the physical foundation and core innovation of the entire system. This field deeply integrates precision mechanical design, advanced materials engineering, and microfluidic thermal management technology. Specifically, the unit cell design involves high-reliability hermetically sealed packaging technology, requiring the development of transparent ceramic top cover molding and metallization packaging processes suitable for photovoltaic cells, exhibiting high light transmittance and excellent weather resistance, as well as methods for internal inert gas protection and long-term reliability verification. This falls within the technical scope of special ceramic packaging and vacuum electronic device packaging. The matrix backplane design directly draws upon and innovates upon high-density electronic device interconnect and backplane technologies. It requires the design and manufacture of a standardized electrical and fluid hybrid interface matrix with extremely high insertion / removal life and contact reliability. Key technical aspects include the design of high-precision multi-contact flexible connectors, the development of self-sealing quick-connect liquid-cooled joints, and the design of composite material backplane structures to ensure long-term outdoor stability. This is closely related to the fields of high-end server blade architecture and modular design of aerospace equipment. The three-dimensional active cooling system is crucial for ensuring system performance and safety. Its technological foundation lies in microscale flow and heat transfer, as well as advanced thermal-hydraulic control. This involves the precision machining of microchannel cold plates (such as laser processing or etching processes), the design of micro-pump valves suitable for deionized cooling media, and the integration of control systems to achieve precise temperature control for each independent power generation unit. This falls under the fields of advanced thermal management and precision fluid systems for electronic devices.

[0002] This open, modular packaging structure is not isolated; it provides a standardized and operable physical carrier and interface specifications for chip-level distributed power electronics (i.e., independent power optimization and management of each power generation unit), internal high-speed deterministic industrial communication networks (enabling unit status monitoring and reconfiguration command transmission), and automated robotic precision operation (enabling unmanned online module replacement). Therefore, the technical essence of this project is a cross-disciplinary systems engineering project centered on advanced packaging integration, deeply integrating power electronics, industrial IoT, artificial intelligence diagnostics, and automated operation and maintenance. Its aim is to redefine photovoltaic power generation equipment from a static "power generation panel" into a dynamically configurable, online-maintainable "intelligent energy node." Background Technology

[0003] Currently, traditional crystalline silicon photovoltaic (PV) power generation technology is based on a fixed and irreversible system architecture, the core of which lies in the "laminated encapsulation" process. This process connects multiple cells in series and parallel, then seals them within a sandwich structure consisting of glass, polymer film, and a backsheet, forming a rigid, indivisible module as the smallest power generation unit. While this architecture has achieved success in terms of environmental protection and long-term stability, it also brings fundamental limitations: once the module is encapsulated, any physical damage, performance degradation, or partial shading of any individual cell cannot be repaired or replaced without damaging the overall module structure, resulting in permanent power loss. At the electrical level, traditional solutions are limited to installing a small number of bypass diodes at the module level. Their function is to short-circuit the entire cell string in case of severe mismatch, a passive protection mechanism that sacrifices power generation and cannot achieve refined power optimization. In terms of thermal management, the system relies entirely on natural convection and radiation from the backsheet for passive heat dissipation, making hot spot effects not only a cause of efficiency loss but also a potential fire hazard. In terms of operation and maintenance, existing technologies rely on periodic inspections and overall replacement of modules as the smallest unit. This process is time-consuming, costly, and accompanied by power generation interruptions. Furthermore, the data monitoring granularity of the entire system is coarse, typically stopping at the string or inverter level, failing to provide insight into the operating status of individual cells within the modules. This makes predictive maintenance and accurate performance analysis difficult to achieve. This series of static operation, passive response, and extensive maintenance modes derived from static physical encapsulation collectively constitute the current state of the background technology that restricts photovoltaic systems from achieving higher reliability, better economic efficiency, and greater intelligence. Summary of the Invention

[0004] The invented photovoltaic cell-level dynamically reconfigurable energy generation method and system is an organic whole that deeply integrates advanced hardware packaging, distributed intelligent control, and networked collaborative management. Its core lies in constructing a cell-level dynamically reconfigurable energy network. Its characteristics are that the system is a unified entity composed of an open modular packaged hardware platform, an intelligent control core, an intelligent diagnostic and maintenance system, and a multi-timescale collaborative control architecture. Essentially, it is an intelligent photovoltaic micro-electric system that achieves independent control of the smallest power generation unit, software-defined energy flow, and online physical layer maintenance. The physical foundation of the system is the open modular packaged hardware platform. At the core of this platform is a standardized independent power generation unit, with each cell (including working and spare cells) packaged within an independent unit. This unit uses a transparent ceramic top cover and a metal base to form a hermetically sealed enclosure, filled with inert gas for long-term protection, and integrates micro-sensors. A large number of these units are integrated into a "smart motherboard" called a matrix backplane using a high-density plug-in method. The backplane is covered with standardized electrical and cooling interfaces, and its internal structure incorporates a sophisticated parallel microfluidic network connected to an independent external circulating cooling system, thus forming an active heat dissipation system for precise temperature control of each battery cell. This design allows the battery cells to be plugged in and replaced online, much like blade servers, achieving reconfigurable physical form. The intelligent control core of the system consists of a chip-level power optimizer, an internal control network, and an intelligent main controller. Each independent power generation unit integrates a gallium nitride (GaN)-based miniature DC-DC converter as a chip-level power optimizer, responsible for performing local maximum power point tracking and switching control of that battery cell. All optimizers are interconnected via a high-speed serial communication bus (such as CAN FD) embedded in the matrix backplane, forming a real-time internal control network. An intelligent main controller at the component level acts as the brain of this network, responsible for polling the real-time status data of each battery cell and issuing commands directly to the optimizer of any battery cell. This allows for dynamic adjustment of the internal electrical connection topology within milliseconds, enabling isolation of faulty battery cells and instantaneous switching in of backup battery cells, ensuring continuous and stable system power output. The system's perception and maintenance support is based on an intelligent diagnostic and maintenance system that integrates multi-source data. This system comprehensively utilizes refined electrical data from the cell-level power optimizer, sensor data integrated within the unit, and visual inspection data from the power plant level. Through cloud-based or edge AI analysis platforms, it performs fusion diagnostics to achieve precise location of cell-level faults, health assessment, and remaining life prediction. Combined with the pluggable physical design of the power generation units, the system can generate accurate maintenance work orders and supports robots or automated equipment to perform non-stop online hot-swap replacement operations using standard interfaces. Ultimately, the system's global optimization is achieved through a multi-timescale collaborative control architecture encompassing "cell-module-power plant."This architecture forms a multi-layered closed loop: at the fastest millisecond level, local control is achieved by a chip-level optimizer; at the second level, the main controller of the module coordinates the working status of all cells within the group and performs fault reconfiguration; and at the minute to hour level, the power station-level AI brain performs global power generation optimization and maintenance scheduling. This collaborative control enables the entire system to function like a living organism, achieving self-awareness, self-optimization, and self-repair.

[0005] The independent power generation unit is the minimum standard functional entity constituting the system. Its design focuses on achieving independent packaging at the cell level, controllable interfaces, and long-term reliable operation. Each unit corresponds precisely to one photovoltaic cell (whether a working cell or a spare), employing a standardized hermetically sealed packaging structure. This structure consists of an upper transparent microcrystalline ceramic protective cover and a lower metal composite functional base. The two are precisely laser-welded along the edges to form a permanently sealed cavity, which is filled with inert gas to isolate water and oxygen and assist in heat conduction. The metal base serves as the structural and functional carrier of the unit, using a copper-clad metal substrate with high thermal conductivity. On this substrate, miniaturized core functional devices are directly integrated using advanced system-in-package technology: including a power optimizer chip (GaN-based DC-DC converter and control logic) acting as the local "brain," and temperature and micro-strain sensors for real-time status monitoring. The cell itself is fixed to a designated area of ​​the base with highly reliable conductive adhesive and electrically interconnected with the integrated chip via micro-leads. The bottom of the unit features a precision-machined, standardized mating surface with multi-pin, highly reliable, flexible electrical contacts for external electrical connections, and a self-sealing, quick-connect miniature liquid-cooled interface for connecting to the cooling circuit. This interface employs a dual-redundant sealing design to ensure zero leakage of the cooling medium during insertion and removal. The entire unit's structural design highly integrates power generation, control, sensing, heat dissipation, and interface functions into a compact, robust, and independently operable module. Its strictly standardized shape and interface dimensions ensure that it can be precisely inserted into or removed from the corresponding slots on the matrix backplane by robots or automated equipment, much like a blade server, thereby enabling cell-level physical reconfiguration and maintenance of the entire photovoltaic system during operation.

[0006] The matrix backplane is the core carrier for the physical integration and functional interconnection of this system. Its specific design is a multi-layered composite intelligent integrated motherboard. The main structure of the backplane uses a high-strength, lightweight alloy or composite material frame to ensure overall mechanical stability and long-term outdoor weather resistance. Its core functional layer consists of three tightly coupled planes: the top layer is a high-density electrical interconnection layer, manufactured using multi-layer precision printed circuit board technology, on which a DC power bus shared by all slots and a data bus network based on a high-speed serial communication protocol are deployed; the middle layer is an embedded heat dissipation layer, consisting of a metal plate with a precision parallel microfluidic network etched inside, ensuring that the cooling medium can flow evenly and independently through the area corresponding to each unit slot; the bottom layer is a structural reinforcement and interface support layer. The front of the backplane features a standardized interface array arranged strictly in a matrix, with each interface position corresponding to an independent power generation unit slot. Each interface consists of three parts: first, a high-reliability, low-contact-resistance multi-pin electrical connector used to match the elastic contacts at the bottom of the unit for transmitting power and high-speed data signals; second, a self-sealing quick-connect liquid-cooled connector that directly connects to the microchannels of the heat dissipation layer, automatically establishing a sealed connection upon unit insertion to form a closed-loop cooling cycle; and third, a precision mechanical guiding and locking mechanism, typically employing a combination of guide pins and eccentric wheels or lever-type locking devices, ensuring precise alignment and insertion of the unit and maintaining extremely high connection stability during operation, while allowing maintenance tools to apply controlled unlocking force to safely remove the unit. The essence of the entire matrix backplane design lies in its integration of four fundamental functions—power aggregation, data exchange, active cooling, and mechanical support—through a standardized interface matrix. It is no longer a simple support board, but a highly integrated "socket" system, enabling each independent power generation unit that meets the packaging standards to be plug-and-play, thereby physically supporting the system's cell-level online hot-swapping, independent cooling, and dynamic reconfiguration capabilities.

[0007] The circulating cooling system is an active thermal management architecture specifically designed to match this modular, pluggable hardware platform. Its design aims to provide precise, reliable, and non-interfering heat dissipation for each independent power generation unit on the matrix backplane. The entire system is a closed-loop forced liquid cooling network, primarily composed of distributed intelligent cooling units, a parallel microchannel network integrated within the backplane, high-purity coolant, and a collaborative control system. The core of the system's power and regulation is the intelligent cooling unit located near each photovoltaic module. This unit is typically integrated within the module frame or a dedicated chassis and includes a frequency-controlled micro-magnetic levitation centrifugal pump, a plate heat exchanger, an expansion and makeup water tank, a fine filtration system, and an array of pressure, temperature, and flow sensors. Its core function is to drive the coolant circulation and precisely control its temperature, pressure, and flow parameters, while also transferring heat to the external environment. The physical channels for heat dissipation are a multi-branch parallel microchannel network integrated within the matrix backplane. The network is precision-machined within metal plates, and its topology ensures that the working fluid flowing from the intelligent cooling unit is synchronously and evenly distributed to the cooling channels corresponding to each unit slot on the backplane. The inlet and outlet of each channel are directly connected to the self-sealing quick-connect liquid-cooling connector on the front of the backplane. When an independent power generation unit is inserted into the backplane, its bottom liquid-cooling interface couples with the connector, and the unit's metal base becomes a highly efficient "cold plate." The heat generated by the internal battery cells and chips is directly transferred to the flowing cooling fluid through the base wall, achieving precise point-to-point heat dissipation. This parallel design ensures the independent heat dissipation of each unit, physically eliminating heat crosstalk and accumulation, which is key to preventing hot spots. The system's cooling fluid typically uses a special liquid with high specific heat capacity and low conductivity (such as a mixture of deionized water and ethylene glycol), with added corrosion inhibitors and antibacterial agents to ensure long-term chemical stability and electrical system safety. The entire circulating cooling system is managed by an intelligent controller, which, as part of the component-level main controller, dynamically adjusts the pump speed and heat exchanger fan start / stop in the intelligent cooling unit based on real-time temperature data reported by each independent power generation unit and the ambient temperature, thereby changing the working fluid flow rate and base temperature. This on-demand supply adjustment strategy ensures that all cells operate within their optimal temperature window to improve power generation efficiency while minimizing the system's own energy consumption. Furthermore, the system is designed with fault tolerance and maintainability in mind. For example, if the liquid cooling circuit of a unit on the backplane is temporarily interrupted due to interface failure or unit removal, the system can automatically isolate that branch via a built-in valve without affecting the normal circulation of other branches. The intelligent cooling unit also typically employs a modular design, supporting online hot-swappable replacement, thus aligning with the online maintenance concept of the power generation unit.

[0008] The chip-level power optimizer is a core intelligent power electronics component embedded within each independent power generation unit. Its design aims to provide independent power conversion, maximum power point tracking, and networked control capabilities for a single cell packaged within the unit. The core hardware of this optimizer is a high-frequency, high-efficiency DC-DC power conversion circuit based on gallium nitride (GaN) semiconductor devices. Considering the typical operating voltage range of monocrystalline silicon cells, the converter typically employs a synchronous buck-boost topology to achieve wide-range buck-boost regulation of the cell's output voltage, enabling precise matching of the grid bus voltage or adaptation to floating voltages required for dynamic reconfiguration. In terms of physical integration, the power optimizer utilizes a highly miniaturized system-in-package (SoC) or module-in-package (Module-in-Package). Its main power devices (GaN HEMT), high-frequency magnetic components, multilayer ceramic capacitors, and control chips are densely integrated and directly mounted inside the metal base of the power generation unit. This not only achieves a compact layout but, more importantly, utilizes the metal base as an efficient heat dissipation path, transferring the heat generated by the optimizer itself to an external circulating cooling system. Its control core is a dedicated controller chip integrating an analog front-end, a high-precision ADC, a PWM generator, and digital logic. This chip has a localized maximum power point tracking algorithm, an output closed-loop control law, and basic fault self-checking procedures embedded in it. The core functional logic of this optimizer consists of three aspects: First, as a local energy controller, it continuously executes the MPPT algorithm at millisecond speeds to dynamically adjust the converter's operating point to extract the maximum power generation potential of the corresponding solar cell under the current light and temperature conditions; second, as a networked intelligent terminal, it connects to the high-speed data bus in the matrix backplane through a standard electrical interface at the bottom of the unit, has a unique network address, and can upload key data such as the voltage, current, temperature, and health status of the solar cell in real time, and receive various instructions from the module-level main controller; finally, as a programmable switching node, it integrates low-loss bypass and access circuits implemented by solid-state relays or specific switching topologies. Upon receiving instructions from the controller, it can completely isolate the cell from the main power generation circuit (off state) or smoothly connect it to the circuit (power generation state) within microseconds. This is the direct actuator for achieving "dynamic reconfigurability" and "millisecond-level switching" at the cell level. Therefore, each cell-level power optimizer and the individual cell it manages together constitute a "smart power generation cell" with sensing, computing, execution, and communication capabilities. This independent control capability, extending to the cell level, is the cornerstone for the system to achieve precise, rapid, and seamless switching between working and standby cells, ultimately building a highly resilient and self-healing energy internet.

[0009] The internal control network is designed as an embedded system integrating deterministic communication, precise timing control, and distributed device management, forming the "digital nervous system" of the entire photovoltaic cell-level dynamically reconfigurable system. Physically, the network is built upon a high-speed serial communication bus embedded in the multi-layer circuitry of the matrix backplane, employing a master-slave architecture. Its physical layer typically utilizes differential signal transmission technology with strong anti-interference capabilities, and the communication medium is differential pairs printed on the backplane, ensuring reliable data transmission even in power electronic noise environments. The network protocol stack is crucial to the design, employing an optimized communication protocol for industrial real-time control. This protocol supports both periodic and event-triggered communication modes: during periodic communication periods, the component-level master controller acts as the master node, broadcasting a synchronization signal to the bus and then sequentially polling each chip-level power optimizer connected to the bus (each corresponding to an independent power generation unit), collecting its status data packets. These packets contain information such as the real-time voltage, current, temperature, health flags, and local MPPT status of the cells managed by the unit. During event-triggered periods, any node (including the master controller or authorized optimizers) can urgently send high-priority messages, such as fault alarms. Each cell-level power optimizer is assigned a unique hardware identifier at the factory and a logical address by the main controller based on its physical location after insertion into the backplane, enabling automatic network identification and topology discovery. The core function of the network is to achieve precise cell-level coordination and millisecond-level reconfiguration. The component-level main controller runs a real-time operating system, one of its core tasks being to analyze the status of all cells and execute control algorithms. When the system determines that a specific working cell has failed, the main controller does not switch the entire physical unit. Instead, it sends an "isolation" command to the power optimizer carrying the failed cell through the internal control network, and simultaneously sends a "switch in" command to the power optimizer of the designated backup cell (which may be located in another independent unit). These two commands, as a precisely coordinated pair, are synchronized via timestamps to ensure execution within the same communication cycle or adjacent cycles, thus electrically completing a seamless millisecond-level switch from a failed cell to a backup cell. The entire network design ensures that the end-to-end latency, from state awareness and decision calculation to command issuance, is strictly constrained to within milliseconds.

[0010] Furthermore, the internal control network design fully considers maintainability and scalability. It supports a "hot-swap" protocol; when a new independent power generation unit is inserted into the matrix backplane, its internal power optimizer automatically broadcasts its presence to the network upon power-up. The main controller detects the new node and performs initialization and logic configuration, quickly integrating it into the system. The entire process does not require interruption of network communication or the operation of other units. The network may also employ redundant bus or ring topology to provide fault tolerance at the communication link level, ensuring the continuous and reliable operation of this "digital nervous system."

[0011] The intelligent master controller is the regional coordination and decision-making center of the photovoltaic cell-level dynamic reconfigurable system. Its specific design aims to achieve fine-grained monitoring, energy management, and millisecond-level dynamic reconfiguration of hundreds of independent power generation units within the module. Physically deployed within the module's intelligent junction box, its hardware platform is based on a system-on-a-chip integrating a high-performance multi-core processor (such as the ARM Cortex-M series or RISC-V architecture), a large-capacity high-speed cache, a dedicated communication controller, and rich peripheral interfaces. Its design particularly emphasizes real-time processing capabilities and communication bandwidth to handle the data throughput and low-latency control requirements of massive cell-level nodes. In terms of software and functional architecture, the controller runs a lightweight real-time operating system and carries the following core task modules: First, the communication management and scheduling module, acting as the master station of the internal control network, strictly follows a time-triggered mechanism, periodically exchanging data with each cell-level power optimizer via the backplane high-speed bus, collecting the complete operating status of each independent cell, and issuing global synchronization signals and individualized control commands to ensure the determinism and reliability of network communication. Secondly, there is the status monitoring and health assessment module. This module performs real-time analysis of the collected cell-level big data, accurately identifying specific cells with performance degradation or failure through built-in diagnostic algorithms (such as IV curve feature analysis and temperature trend prediction), and continuously calculating the health status score of all cells to provide a basis for reconfiguration decisions. Its core decision-making function is embodied in the dynamic reconfiguration and energy optimization module. This module contains real-time algorithms. When the diagnostic module determines that a working cell has failed or needs to be decommissioned, the controller does not simply switch the entire physical package unit, but immediately executes precise cell-level reconfiguration logic. Based on preset or dynamically calculated redundancy mapping relationships, it issues coordinated instructions to two target objects through the control network within milliseconds: first, it commands the power optimizer carrying the faulty cell to safely isolate it from the series loop; second, it commands the power optimizer carrying the designated backup cell to seamlessly switch it into the same electrical position. This process undergoes strict timing synchronization to ensure the continuity of the total loop voltage and current. At the same time, this module also executes component-level global MPPT compensation and power balancing algorithms to optimize output characteristic changes caused by individual cell differences or partial reconfiguration. In addition, the controller integrates a thermal management coordination module and a host communication gateway. The thermal management module dynamically adjusts the operating parameters (such as pump speed and valve opening) of the intelligent cooling unit in the circulating cooling system based on cell temperature distribution data. The host communication gateway is responsible for communicating with the cloud AI platform via the power plant-level network, uploading refined component data, and receiving and executing optimization strategies and scheduling instructions from the system layer. The entire controller's hardware and software design emphasizes fault tolerance and scalability, supporting online hot-swappable identification and configuration of modules to ensure uninterrupted control functionality during system maintenance and upgrades.

[0012] The intelligent diagnostic and maintenance system is designed as a closed-loop management system integrating multi-source heterogeneous data fusion, artificial intelligence analysis, and automated execution decision-making. Its core function is to achieve accurate health assessment, early fault warning, and autonomous operation and maintenance scheduling for each independent packaged power generation unit in the system. The system works collaboratively through three layers: a wide-area perception layer, a cloud-based intelligent analysis layer, and a field-based autonomous execution layer. The wide-area perception layer forms the system's data foundation, with its data sources exhibiting multi-dimensional and high-frequency characteristics. Core data comes from micro-sensors and chip-level power optimizers integrated within each independent power generation unit. These continuously upload detailed electrical parameters of the solar cells (including complete IV characteristic curve segments, DC impedance trends), temperature distribution, and minute stress changes in the package at millisecond to second frequencies. This data is aggregated to the module's intelligent main controller via the control network within the matrix backplane, and then uploaded after time synchronization and preprocessing. Meanwhile, automated inspection equipment deployed in the power plant (such as drones or tracked robots equipped with hyperspectral and infrared thermal imagers) periodically collects imagery and thermal distribution data at the component and cell levels, forming an external spatial verification and supplement to the internal electrical data, thereby constructing a comprehensive perception network from multiple physical fields of electricity, heat, and force to visual space. The cloud-based intelligent analysis layer is the system's decision-making brain. At this level, multi-dimensional time-series data streams from massive independent units across the entire power plant are connected to a high-performance computing platform. The core of the platform is a diagnostic engine that integrates trained deep learning and physical models. This engine first establishes a high-fidelity digital twin model for each cell unit. By comparing real-time data with the model's predicted normal behavior, it can detect latent defects such as microcracks leading to increased series resistance, local delamination leading to increased thermal resistance, or abnormal bypass diodes. More importantly, the engine uses convolutional neural networks to analyze the texture features of hot spots and EL (electroluminescent) images, combined with the gradual trend of electrical parameters. This allows it not only to diagnose existing faults (such as permanent physical damage) but also to predict performance degradation paths and potential failure risks, accurately distinguishing between permanent failures and reversible shading, and estimating remaining lifespan. The on-site autonomous execution layer translates diagnostic decisions into physical actions. When the diagnostic engine determines that a specific battery cell needs replacement, it automatically generates a structured maintenance work order and sends it to the on-site autonomous maintenance robot through the power station dispatch system. Upon receiving the instruction, the robot system navigates to the target location based on the precise component matrix coordinates and unit position information in the work order. The robot's vision system precisely locates the target independent power generation unit and its interface on the matrix backplane. The robotic arm then uses a special tool to unlock and safely remove the faulty unit, retrieves a new standardized unit from its spare parts library, precisely inserts it, and locks it in place. During this physical insertion and removal process, the intelligent main controller coordinates the logical offline and online state switching of the electrical node through its internal control network, ensuring uninterrupted power generation.The entire closed-loop process of "perception-diagnosis-decision-execution" is fully automated, achieving seamless connection from cellular-level fault identification to physical-level precise repair, enabling photovoltaic systems to possess self-repair and metabolism capabilities similar to living organisms.

[0013] The multi-timescale collaborative control architecture is a hierarchical closed-loop control system designed to coordinate the global operation from a single solar cell to the entire photovoltaic power plant. Its design relies heavily on the addressability of individual power generation units and the interconnectivity of the matrix backplane. The architecture consists of three nested control loops in time and space, each responsible for optimization objectives at different time scales, and transmitting commands and status bidirectionally through a standardized data interface. The innermost layer is the cell-level millisecond control loop, whose actuator is a cell-level power optimizer integrated within each independent power generation unit. This control loop operates on a millisecond cycle, and its core task is to achieve independent maximum power point tracking (MPPT) and precise closed-loop regulation of voltage / current output for its corresponding single cell. The optimizer samples the cell's voltage and current in real time, runs a high-frequency MPPT algorithm, and dynamically adjusts the duty cycle of the DC-DC converter to instantaneously respond to changes in local illumination and temperature, maximizing the instantaneous power generation efficiency of the independent unit. Simultaneously, as a network terminal, it continuously reports its operating status to the next higher level through the unit's electrical interface on the backplane. The middle layer is a module-level second-level control loop, with the main controller located within the module's intelligent junction box as its decision-making core. This control loop operates on a second-level cycle, responsible for coordination and reconfiguration within the module. The main controller aggregates and analyzes the real-time status of all independent power generation units (working and standby cells) within its jurisdiction via a high-speed communication network within the backplane. Based on a global view, it performs two key functions: first, it runs an intra-group power balancing algorithm, compensating for performance differences caused by aging and uneven shading by fine-tuning the operating points of each unit's optimizer, minimizing the "weakest link" effect; second, it executes dynamic reconfiguration logic. When the diagnostic system determines that a specific cell has failed, the main controller, within seconds or even milliseconds, precisely schedules through the control network to isolate the cell in the faulty unit from the electrical circuit and simultaneously seamlessly connects the cell in the designated standby unit, achieving uninterrupted power output recovery. Furthermore, this control loop also manages the microfluidic cooling system integrated into the matrix backplane, adjusting the coolant flow rate based on unit temperature distribution data. The outermost layer is a power plant-level minute / hour control loop, with its optimization center being an AI analysis platform deployed locally at the power plant or in the cloud. This control loop performs system-level macro-optimization and strategy scheduling on a timescale of minutes to hours. The platform performs multi-objective optimization calculations based on refined cell-level data streams from all components, equipment health prediction maps, ultra-short-term irradiance and weather forecasts, and grid dispatch instructions. Its output is a global operating strategy, such as setting a slightly increased operating voltage for component groups in slightly aging areas to balance system losses, or issuing rapid power regulation commands to strings participating in grid frequency regulation. These strategies are decomposed into specific setpoints and sent to the corresponding component-level master controllers via the communication network, which then decompose them to the corresponding cell-level optimizers for execution, thus forming a global closed loop of "strategy issuance - distributed execution - status feedback".The essence of this multi-timescale architecture is to decompose the traditional centralized and extensive control of photovoltaic power plants into distributed collaborative control based on standardized pluggable "cell" units. It maximizes the efficiency of cell units through the inner loop, enables the self-adaptation and self-healing of organs (components) through the middle loop, and achieves intelligent collaboration between the entire organism (power plant) and the environment and power grid through the outer loop. Thus, it achieves global optimization of system operating performance on the basis of physically reconfigurable hardware.

[0014] Compared to traditional photovoltaic technology, this system achieves fundamental advantages in multiple dimensions through its cellular-level dynamic reconfigurable architecture. These advantages stem directly from its standardized independent power generation units, intelligent matrix backplane, and the overall system design working in tandem with them. Its most significant advantage lies in the qualitative leap in system availability and power generation guarantee. Because each cell is independently packaged and controlled, the failure, damage, or severe shading of any single cell no longer leads to power loss for the entire module or string. The system can isolate fault points within milliseconds through a cell-level dynamic network and instantly call upon backup cells to fill the gap, achieving "zero interruption" and "zero loss" in power output. This fundamentally solves the long-term power generation degradation problem caused by the "weakest link" effect and the coarse protection of bypass diodes in traditional modules, theoretically reducing annual power generation loss due to partial module failures to near zero. Secondly, the system achieves a revolutionary change in operation and maintenance mode and optimization of the entire life cycle cost. The standardized plug-and-play design of the independent power generation units allows for maintenance granularity to be refined from the "module level" to the "cell level." Combined with precise intelligent diagnostics, the system only requires replacing specific failed or severely degraded solar cells, rather than the entire module. This significantly reduces spare parts costs and material consumption. The ability to support automated online hot-swapping eliminates the need for power outages and manual high-altitude work during maintenance, greatly improving operational safety and efficiency, and significantly reducing maintenance costs. In the long run, through continuous partial replacements, the system enables the main structure of the power station to potentially exceed the traditional 25-year design life, achieving "system immortality," amortizing initial investment, and improving the economics throughout its entire lifecycle. Third, the system provides unprecedented data granularity and management precision. Each independent unit is a data node, providing real-time voltage, current, temperature, and health status data at the cell level. This transforms system management from a traditional "black box" or "gray box" model into a completely transparent "digital twin" era. Based on this refined data, the system's multi-timescale collaborative control can execute optimization strategies that traditional systems cannot achieve, such as cross-component global maximum power point tracking, preventative thermal management to completely eliminate hot spots, and predictive maintenance scheduling based on precise health status, thereby continuously maintaining the overall system efficiency near its theoretical peak. Finally, the system's active thermal management design brings additional performance and reliability gains. Precise heat dissipation for each individual unit through a microchannel liquid cooling system integrated into the matrix backplane ensures that all cells always operate within their optimal temperature range. This not only directly improves power generation efficiency (as cell efficiency decreases with increasing temperature) but also physically eliminates the conditions for hot spot formation, greatly enhancing the system's long-term operational safety and reliability.In summary, the advantages of this system are that it forms an organic whole: it achieves maintainability through hardware modularization, intelligent optimization and self-healing through software-based control, and precise management through data refinement. Ultimately, these factors lead to higher power generation revenue, lower operation and maintenance costs, longer system lifespan, and inherently safe operation, representing the direction of photovoltaic power plants towards high reliability, high intelligence, and extreme economic efficiency. Attached Figure Description

[0015] Appendix Figure 1 This is a schematic diagram of the composition of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0016] Appendix Figure 2 This is a schematic diagram of an independent power generation unit of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0017] Appendix Figure 3 This is a schematic diagram of the matrix backplane of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0018] Appendix Figure 4 This is a schematic diagram of the circulating cooling system of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0019] Appendix Figure 5 This is a schematic diagram of the chip-level power optimizer of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0020] Appendix Figure 6 This is a schematic diagram of the internal control network of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0021] Appendix Figure 7 This is a schematic diagram of the intelligent main controller of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0022] Appendix Figure 8 This is a schematic diagram of the intelligent diagnostic and maintenance system of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0023] Appendix Figure 9 This is a schematic diagram of the multi-timescale collaborative control architecture of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention.

[0024] Appendix Figure 10 This is a schematic flowchart of the photovoltaic cell-level dynamic reconfigurable energy generation method and system described in this invention. Detailed Implementation

[0025] The specific implementation of the aforementioned photovoltaic cell-level dynamically reconfigurable energy generation method and system is as follows.

[0026] The implementation of this system began with the construction of a modular packaging hardware platform. A standard independent power generation unit measuring 50 mm × 50 mm × 8 mm was fabricated. Its transparent ceramic top cover was made of 3 mm thick high-transparency alumina microcrystalline glass, and the metal base was a 4 mm thick copper-aluminum composite substrate. The two were laser-welded to form an airtight cavity, which was filled with 99.99% pure argon gas to 1.2 atmospheres. Each unit encapsulated a 156 mm × 78 mm monocrystalline silicon solar cell (working or spare), which was bonded to the metal base with conductive adhesive. Inside the base, a 5 mm × 5 mm gallium nitride-based DC-DC power converter chip, two thin-film platinum resistance temperature sensors (arranged at the center and edge of the solar cell, respectively), and four micro-strain sensors were integrated using system-in-package technology. The bottom of the unit was precision-machined with 12 gold-plated elastic contacts (1.2 mm in diameter, arranged in a 4 × 3 matrix) and two stainless steel self-sealing liquid-cooling interfaces with rupture valves.

[0027] Subsequently, a matrix-style intelligent backplane was fabricated, with overall dimensions of 1760 mm × 1040 mm × 20 mm. The front of the backplane features 176 standardized slots arranged in a 22x8 matrix, with a center-to-center distance of 80 mm between each slot. Each slot contains 12 phosphor bronze spring contact points (with a contact resistance of less than 2 milliohms) corresponding to the bottom contacts of the unit, two self-sealing liquid-cooled quick-connect fittings (using a double O-ring sealing structure), and an eccentric wheel-type mechanical locking mechanism (locking torque of 0.6 Nm). The backplate has a multi-layered composite structure: the top layer is the interface layer, with all contact points and connectors embedded in a 2mm thick glass fiber reinforced PEEK insulating board; the second layer is the electrical layer, with four independent DC power buses (105 micrometers thick copper, 30 amps current carrying capacity per bus) and a high-speed serial bus based on the CAN FD protocol (1 megabits per second) arranged within a 1.6mm thick 12-layer high-density interconnect printed circuit board; the third layer is the cooling layer, with a parallel microchannel network formed by precision machining within an 8mm thick 6061 aluminum alloy plate, with a channel width of 0.8mm and a depth of 4mm, and each slot corresponding to an independent inlet and outlet channel branch; the bottom layer is the structural layer, with a 3mm thick carbon fiber composite board providing overall support. Inlet and outlet manifolds are respectively located on both sides of the backplate, connecting to the various branches of the cooling layer.

[0028] The external circulation cooling system consists of 176 modules (each module corresponding to a backplate) sharing a power plant-level cooling station. Each module is equipped with an intelligent cooling unit measuring 400 mm × 200 mm × 150 mm, containing a brushless DC magnetic levitation centrifugal pump (rated flow rate 8 L / min, head 15 m), a plate heat exchanger (heat exchange area 0.8 m²), a 2-liter expansion tank, a conductivity monitor, and flow and temperature sensors. The cooling medium is a mixture of 60% deionized water and 40% propylene glycol. The intelligent cooling unit is connected to the inlet and outlet manifolds of the backplate via flexible piping, forming a closed-loop circulation.

[0029] During assembly, 176 independent power generation units (160 working units and 16 spare units) are sequentially inserted into the backplane slots. After mechanical locking, electrical connections and liquid cooling pathways are automatically established. The elastic contacts at the bottom of each unit press against the backplane contact seat, and its liquid cooling connector pierces the sealing membrane inside the backplane connector, forming a closed-loop circulation. The backplane output connects to the component junction box, which houses the intelligent main controller. The main controller uses an ARM Cortex-M7 core-based processor (400 MHz), equipped with 512 kilobytes of flash memory, 128 kilobytes of random access memory, and four CAN FD controllers.

[0030] The distributed power routing and communication network is implemented as follows: Each independent power generation unit integrates a gallium nitride-based high-frequency switching array (1.5 MHz switching frequency), a synchronous buck-boost converter circuit, a digital signal processor core (with embedded perturbation-observation (MPPT) algorithm), a 12-bit analog-to-digital converter, and a CAN FD physical layer transceiver. The optimizer input is connected to the cell within the unit, and the output is connected to the DC bus via backplane electrical contacts. The communication end is connected to the backplane data bus via contacts. The bus connects all 176 optimizers to the main controller within the module junction box. The main controller polls all optimizers every 10 milliseconds, collecting real-time voltage (1 mV resolution), current (1 mA resolution), temperature (0.1°C resolution), health status code (0-100), and local MPPT operating point for each cell. Simultaneously, the main controller can issue cut-in, cut-out, or voltage / current setpoint commands to any optimizer, with a command response time of less than 1 millisecond.

[0031] The implementation of the intelligent diagnostic and maintenance system is based on multi-source data fusion. Each power optimizer uploads complete IV curve feature data of the solar cell every second (using 20 sampling points); the temperature sensor within the cell uploads data every 100 milliseconds, and the stress sensor uploads data every second. The power station deploys four inspection drones, which perform infrared thermal imaging and hyperspectral image acquisition on all 176 components every two hours, achieving a spatial resolution of 2 mm × 2 mm per pixel. All data is uploaded in real time to the power station's edge server (configured with four GPUs, running a fusion diagnostic model based on convolutional neural networks and long short-term memory networks). The server establishes a digital twin model for each solar cell, calculates the health index in real time, predicts the remaining lifespan, and distinguishes between permanent damage and reversible occlusion. When the diagnostic model determines that the health index of a working cell is below a threshold (e.g., 60 points) or irreversible damage has occurred, a maintenance work order is automatically generated. The work order includes the component number of the faulty unit (e.g., component A-12) and the slot coordinates (e.g., row 5, column 3). Two track-mounted maintenance robots were deployed on-site. Each robot is equipped with a vision system (5-megapixel resolution) and a six-degree-of-freedom robotic arm, with an end-effector compatible with the unit locking mechanism. After receiving a work order, the robot navigates to the target component, locates the faulty unit via a QR code, and completes the entire process of unlocking, removing, and inserting a new unit within 30 seconds. During this time, the component's main controller automatically registers the new unit as a standby unit or directly switches it to working mode. The system continuously generates power throughout the entire replacement process without interruption.

[0032] The implementation of the multi-timescale collaborative control architecture is divided into three levels. The cell-level control loop operates on a 1-millisecond cycle: each power optimizer independently executes the MPPT algorithm, adjusting the switching duty cycle in real time to ensure the cell operates at its maximum power point, while stabilizing the output voltage / current at its local setpoint. The module-level control loop operates on a 100-millisecond cycle: the main controller aggregates the status of all 176 cells, runs the intra-group power balancing algorithm, and fine-tunes the MPPT operating point (adjustment range ±5%) for cells with high aging levels or partial shading, making the series output current of each cell more consistent. Simultaneously, the main controller continuously monitors for faults. When it detects a sudden power drop of more than 30% in a working cell that lasts for 200 milliseconds, it immediately performs a reconfiguration: sending a shutdown command to the faulty cell optimizer and a switch-in command to the pre-assigned backup cell optimizer, with an interval of less than 2 milliseconds between the two commands, and a bus voltage fluctuation of less than 3% during the switching process. The main controller also sends a flow regulation command to the intelligent cooling unit every 10 seconds based on temperature distribution data, controlling the cell temperature within the range of 45±2 degrees Celsius. The power plant-level control loop operates on a 15-minute cycle: The edge server, based on health data from all 176 modules (30,976 cells) across the plant, hourly irradiance forecasts, and grid dispatch instructions (such as frequency regulation requirements), runs a global optimization algorithm to calculate the optimal operating voltage offset for each module (e.g., increasing the voltage of modules in severely aged areas by 2%). This calculation is then transmitted to the main controllers of each module via the power plant Ethernet. The main controllers decompose this offset into setpoint adjustments for each cell's optimizer, forming a complete closed loop. When the grid issues an emergency power regulation command, the power plant-level control loop can adjust the total output power of all modules within one second via broadcast instructions, meeting frequency regulation requirements in terms of response speed.

[0033] After the entire system was assembled, it was debugged under standard test conditions (1000 watts per square meter irradiance, 25 degrees Celsius). First, it was verified that the communication between each unit was normal, and the main controller could correctly read the voltage (within the range of 0.5-0.7 volts) and temperature of all 176 solar cells. Then, a fault switching test was performed: the electrical connection of one working cell was manually disconnected, and it was observed whether the spare cell automatically switched in within 5 milliseconds; the total system output power fluctuation should be less than 2%. Next, a cooling system test was conducted: the modules were placed in a 50-degree Celsius environmental chamber, and it was observed whether the intelligent cooling unit could stabilize the temperature of all solar cells at 45±2 degrees Celsius within 5 minutes. Finally, a robot replacement test was performed: a replacement command was issued, and the time it took for the robot to complete the replacement of the faulty unit and restore the system was recorded (it should be less than 60 seconds). After passing the tests, this photovoltaic cell-level dynamically reconfigurable energy generation network can be put into actual operation.

Claims

1. A photovoltaic cell-level dynamically reconfigurable energy generation method and system, characterized in that: The design employs an open, modular packaging architecture, independently encapsulating each photovoltaic cell within a standard unit. Plug-and-play functionality is achieved through standardized electrical and cooling interfaces on the matrix backplane, transforming the photovoltaic module from a rigid laminate into a dynamically reconfigurable blade server architecture. This design revolutionizes the unmaintainable physical form of photovoltaic modules, extending maintenance granularity from the module level to the cell level. Control granularity is further reduced to the individual cell level, with each standard unit integrating a micro-power optimizer, making each cell an independently addressable, controllable, and scheduleable intelligent power generation node. This represents a leap from "module-level optimization" to "cell-level routing." A cell-level dynamic energy routing network is constructed, allowing the module's main controller to perceive the status of each cell in real time within milliseconds, accurately isolating faulty cells and simultaneously switching to backup cells, achieving uninterrupted power output recovery with zero loss, upgrading fault response from "passive sacrifice" to "active reconfiguration." The standardized interfaces of independent power generation units are deeply coupled with a robotic maintenance system, enabling precise fault location through AI diagnostics. After a cell fails, a robot is directly dispatched to perform online hot-swap replacement, eliminating the need for manual climbing and system shutdown. This represents a revolutionary shift from "planned manual inspection" to "on-demand automated surgical maintenance." Through sensors and optimizers built into each unit, voltage, current, temperature, stress, and complete IV curve characteristics at the cell level are acquired, constructing a refined digital twin covering hundreds of thousands of cells. Combined with an AI diagnostic engine that fuses multi-source heterogeneous data, this achieves a leap from "macro-state estimation" to "micro-cellular-level precise prediction." An innovative three-level dual-closed-loop collaborative control architecture is constructed: the inner loop achieves millisecond-level local MPPT through optimizers within each unit; the middle loop achieves second-level intra-group power balancing and fault reconfiguration through the module's main controller; and the outer loop achieves minute-level global optimization and health scheduling through the power station's AI platform. This architecture extends the control level from the macro level of the distribution network to the micro level of the cell, forming a complete control closed loop from "cell" to "organ" to "living organism." Its core innovation lies in transforming photovoltaic power plants from static, unmaintainable "power generation hardware" into "energy life forms" that can be self-sensing, dynamically reconfigured, and repaired online.

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