Optical storage and charging four-function system and method based on edge intelligent regulation and control

Abstract

The invention belongs to the field of new energy and intelligent power grids, and discloses a light storage and charging four-function system and method based on edge intelligent regulation, and the system comprises a cloud collaborative optimization layer, an edge intelligent control layer, and a multi-source terminal autonomous layer. By adopting the system, the panoramic perception and millisecond-level fault autonomy of the equipment operation state are realized, and the problems of unobservable and unmeasurable problems are solved; the power regulation precision and the fault removal efficiency are improved through protocol unification and edge intelligent regulation and control, and the problems of non-regulation and non-control are solved; by means of a cloud optimization-edge execution-terminal autonomy cooperative mechanism, the impact of photovoltaic fluctuation on a power grid is stabilized, voltage out-of-limit and harmonic pollution are suppressed, the relay protection reliability is enhanced, meanwhile, the hardware cost and the single-point failure risk are reduced, and the four-capability requirements of observability, measurability, adjustability and controllability are comprehensively met.

Description

Technical Field

[0001] The present invention belongs to the field of new energy and smart grid technology, and in particular relates to a photovoltaic, storage and charging system and method based on edge intelligent regulation. Background Art

[0002] As the global energy mix shifts toward clean energy, distributed photovoltaic power generation, as a key form of renewable energy utilization, continues to experience rapid growth in installed capacity and a growing share of the energy supply system. Solar-powered storage and charging systems, as crucial supporting infrastructure for distributed photovoltaic development, have also seen widespread adoption, becoming a key component in achieving efficient energy utilization and stable grid operation. However, as the scale of distributed photovoltaic and solar-powered storage and charging systems continues to expand, a series of issues have emerged regarding their integration with the existing grid system and their efficient management.

[0003] Current distributed photovoltaic (PV) and solar-storage-charging systems face numerous technical challenges and shortcomings. Regarding monitoring, distributed PV equipment is widely distributed and dispersed. Due to the lack of a unified data collection standard, the power grid struggles to obtain key information such as power generation, voltage fluctuations, and equipment operating status in real time. This makes it impossible to effectively monitor its operating conditions, resulting in unobservable and unpredictable issues. Regarding control, the interface protocols of traditional PV-storage-charging systems are complex, diverse, and incompatible, and lack intelligent control methods. This prevents the system from flexibly adjusting power and makes it difficult to accurately isolate the faulty component during a fault. This leads to a surge in peak-shaving pressure on the grid, frequent grid disconnections, and uncontrollable issues. Regarding safety, the significant volatility of PV output can cause bidirectional voltage overshoots and harmonic pollution in the distribution network, potentially even tripping the main transformer gap protection. It can also affect the three-phase imbalance of the grid and alter the distribution of fault currents, exposing traditional relay protection devices to the risk of false or failed operation, posing a serious threat to the stable and reliable operation of the grid. In addition, existing solutions also have limitations. Due to high communication delays, centralized control cannot process large amounts of data and issue control instructions in a timely manner, making it difficult to meet real-time response requirements. The protocols of different equipment manufacturers vary greatly, resulting in poor system compatibility and difficulties in coordinated control. There is a lack of unified technical standards, and the functions of control terminals are scattered and fragmented, making it difficult to fully cover the "four-capable" capability requirements. At the same time, centralized control solutions have high hardware costs and are difficult to maintain. Failure of the central server can easily lead to large-scale monitoring and control failures.

[0004] In summary, distributed photovoltaic and solar-storage-charging systems have many problems in monitoring, regulation, and safety, and existing solutions have obvious limitations, which seriously restrict the efficient utilization of distributed photovoltaics and the stable operation of the power grid. Summary of the Invention

[0005] The present invention provides a photovoltaic, storage and charging four-in-one system and method based on edge intelligent regulation. This system is suitable for integrated photovoltaic, storage and charging microgrid scenarios, and can realize integrated edge computing, dynamic protocol adaptive conversion and multi-energy hierarchical regulation, ensuring the efficient utilization of distributed photovoltaics and the stable operation of the power grid.

[0006] In order to achieve the above object, the present invention adopts the following technical contents: A solar-storage-charging system based on edge intelligent control, including: a cloud collaborative optimization layer, an edge intelligent control layer, and a multi-source terminal autonomy layer; The cloud collaborative optimization layer communicates and interconnects with the edge intelligent control layer; the edge intelligent control layer communicates and interconnects with the multi-source terminal autonomy layer; The multi-source terminal autonomous layer is used to collect device data of multi-source terminal devices and transmit the device data to the edge intelligent control layer; and is used to independently handle emergency faults; The edge intelligent control layer is used to perform protocol conversion between devices and upload the device data uploaded by the multi-source terminal autonomous layer to the cloud collaborative optimization layer after the protocol conversion is completed; and is used to generate local adjustment instructions based on the global policy issued by the cloud collaborative optimization layer, and at the same time issue the local adjustment instructions to the multi-source terminal autonomous layer for the multi-source terminal autonomous layer to execute the local adjustment instructions; The cloud-based collaborative optimization layer is used to aggregate device data uploaded by the edge intelligent control layer and present the analysis results of the device data based on digital twin modeling; and is used to generate global strategies based on the analysis results of the device data and send them to the edge intelligent control layer.

[0007] Furthermore, the multi-source terminal autonomy layer includes multi-source terminal devices and a local decision module; the local decision module is connected to the multi-source terminal devices to realize self-execution of protection; wherein, the multi-source terminal devices include: inverters, distribution boxes, combiner boxes, energy storage, environmental monitors, charging piles and wind turbines.

[0008] Furthermore, the local decision module includes an intelligent miniature circuit breaker; the intelligent miniature circuit breaker can collect fault waveform samples and enable local storage cache when communication is interrupted, and automatically retransmit the fault waveform samples to the edge intelligent control layer after communication is restored.

[0009] Furthermore, the edge intelligent control layer includes an intelligent gateway, a communication protocol converter and a flexible control terminal; The intelligent gateway, the communication protocol converter and the flexible control terminal are all connected between the cloud collaborative optimization layer and the multi-source terminal autonomy layer; The intelligent gateway cooperates with the communication protocol converter to realize protocol conversion between various devices; The flexible control terminal is used to generate a local adjustment instruction according to the received global strategy, and send the local adjustment instruction to the multi-source terminal autonomous layer.

[0010] Furthermore, the communication protocol converter has a built-in protocol identification module, which is equipped with a machine learning adaptive algorithm and can implement the following steps: Collect device data to be uploaded; Parse the data based on the device data to be uploaded to identify the current protocol type; Match the current protocol type with the mainstream protocol. If the match is successful, the device data is formatted and ultimately output as unified standard protocol data. If the match fails, the device automatically switches to bypass transparent transmission mode, converting the device data format through manually configured conversion rule base, and ultimately outputting unified standard protocol data. Upload unified standard protocol data to the edge intelligent control layer or cloud collaborative optimization layer.

[0011] Furthermore, the flexible control terminal has a built-in photovoltaic output prediction neural network model, which can generate local adjustment instructions based on global strategies and equipment data, and finally send the local adjustment instructions to the multi-source terminal autonomous layer.

[0012] Furthermore, the edge intelligent control layer also includes an edge controller; wherein the edge controller is equipped with a fuzzy control algorithm and can independently execute a local power optimization strategy according to the fuzzy control algorithm.

[0013] Furthermore, the cloud-based collaborative optimization layer includes an energy management platform built on a distributed database; the energy management platform is equipped with a multi-energy collaborative optimization algorithm, which can perform multi-energy collaborative optimization scheduling based on the received device data to generate a global strategy; The cloud-based collaborative optimization layer also includes a digital twin modeling module, which is used to visualize the received device data and the fault data uploaded by the edge intelligent control layer.

[0014] A method for operating a photovoltaic, storage, and charging system based on edge intelligent control, based on the aforementioned photovoltaic, storage, and charging system based on edge intelligent control, comprising: Utilize the multi-source terminal autonomy layer to collect device data from multi-source terminal devices, transmit the device data to the edge intelligent control layer, and independently handle emergency faults; The edge intelligent control layer performs protocol conversion between devices and uploads the device data uploaded by the multi-source terminal autonomy layer to the cloud collaborative optimization layer after the protocol conversion is completed. Local adjustment instructions are generated based on the global strategy issued by the cloud collaborative optimization layer and sent to the multi-source terminal autonomy layer for execution. The cloud-based collaborative optimization layer aggregates device data uploaded by the edge intelligent control layer, and presents the analysis results of the device data based on digital twin modeling; and generates global strategies based on the analysis results of the device data and sends them to the edge intelligent control layer.

[0015] Furthermore, the edge intelligent control layer includes an edge controller; when a power grid fault occurs, the edge controller performs a protection switching process as follows: Collect overvoltage signals sent by protection devices; Combine overvoltage signals with locally stored grid topology parameters to automatically calculate the disconnection range and perform graded operations; After the joint cutover process is completed, a fault data packet is uploaded to the cloud collaborative optimization layer; the fault data packet includes the time, type and location of the fault.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a photovoltaic, storage, and charging system based on edge intelligent control, comprising a cloud-based collaborative optimization layer, an edge intelligent control layer, and a multi-source terminal autonomy layer. The terminal layer collects device data locally and handles emergency faults. The edge layer implements protocol conversion for heterogeneous devices, uploads data to the cloud, and executes global policies issued by the cloud to generate local adjustment instructions. The cloud layer aggregates data and generates global policies based on digital twin modeling. Terminal layer autonomy enables rapid fault isolation, ensuring basic security. Edge layer protocol conversion breaks down data barriers, making devices observable and measurable. Its localized command execution avoids communication delays and supports adjustability and control. The cloud optimizes global policies through global data fusion and digital twin technology, improving system resilience. This system achieves panoramic perception of equipment operating status and millisecond-level fault autonomy, solving the problem of unobservability and unmeasurability; improves power regulation accuracy and fault removal efficiency through protocol unification and edge intelligent control, overcoming the problem of unadjustability and uncontrollability; relies on the "cloud optimization-edge execution-terminal autonomy" collaborative mechanism to smooth the impact of photovoltaic fluctuations on the power grid, suppress voltage over-limit and harmonic pollution, enhance relay protection reliability, and reduce hardware costs and single-point failure risks, fully meeting the "four-capable" capability requirements of "observable, measurable, adjustable, and controllable".

[0017] The present invention also provides a working method for a photovoltaic, storage and charging system based on edge intelligent control. Based on the above-mentioned photovoltaic, storage and charging system based on edge intelligent control, this method solves the pain points of distributed photovoltaic, storage and charging systems through the coordinated operation of the terminal layer, edge layer and cloud layer. The terminal layer collects device data on-site and autonomously handles emergency faults at the millisecond level; the edge layer uniformly converts the protocols of heterogeneous devices and uploads the data to the cloud, while converting the global strategy issued by the cloud into local instructions for execution; the cloud layer aggregates global data to build a digital twin model and generates global strategies based on analysis. The terminal layer's millisecond-level fault autonomy enables rapid isolation of security issues and avoids fault propagation; the edge layer's protocol conversion breaks down data barriers, making the device status transparent in real time. Its localized instruction execution avoids cloud communication delays and achieves precise power regulation and fault removal; the cloud relies on digital twin dynamic optimization strategies to improve system resilience. This method achieves global awareness of equipment operating status and millisecond-level fault self-healing, eliminating monitoring blind spots. It improves control accuracy and response speed through protocol unification and edge intelligent decision-making, effectively alleviating grid peak-shaving pressure and grid-off risks. Based on a collaborative mechanism of cloud-based global optimization and edge-based on-site execution, it adaptively smoothes the impact of photovoltaic fluctuations on the grid, suppresses voltage over-limit, harmonic pollution, and relay protection malfunction risks, while reducing the high cost and single-point failure risks of centralized solutions, systematically meeting the "observable, measurable, adjustable, and controllable" requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the structure of a solar-storage-charging system based on edge intelligent control provided by an embodiment of the present invention; Figure 2 This is a system architecture diagram of a solar-storage-charging system based on edge intelligent control provided by an embodiment of the present invention; Figure 3 A working principle diagram of a communication protocol converter provided in an embodiment of the present invention; Figure 4 A schematic diagram of the main transformer gap protection joint switching logic provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail in the following specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0021] The present invention is described in further detail below with reference to the accompanying drawings: like Figure 1 As shown, this embodiment provides a four-in-one optical storage and charging system based on edge intelligent regulation, including a cloud-based collaborative optimization layer, an edge intelligent control layer and a multi-source terminal autonomous layer; the cloud-based collaborative optimization layer communicates and interconnects with the edge intelligent control layer; the edge intelligent control layer communicates and interconnects with the multi-source terminal autonomous layer; the multi-source terminal autonomous layer is used to collect device data of multi-source terminal devices and transmit the device data to the edge intelligent control layer; and is used to independently handle millisecond-level (less than or equal to 30 milliseconds) emergency faults; the edge intelligent control layer is used to perform protocol conversion between each device, and at the same time, after the protocol conversion is completed, the device data uploaded by the multi-source terminal autonomous layer is uploaded to the cloud-based collaborative optimization layer; and is used to generate local adjustment instructions according to the global strategy issued by the cloud-based collaborative optimization layer, and at the same time, the local adjustment instructions are issued to the multi-source terminal autonomous layer for the multi-source terminal autonomous layer to execute the local adjustment instructions; the cloud-based collaborative optimization layer is used to aggregate the device data uploaded by the edge intelligent control layer, and present the analysis results of the device data based on digital twin modeling; and is used to generate a global strategy based on the analysis results of the device data and issue it to the edge intelligent control layer.

[0022] The present embodiment will be further explained and illustrated below with reference to the accompanying drawings: like Figure 2 As shown, this embodiment provides a solar-storage-charging system based on edge intelligent control, including a cloud collaborative optimization layer, an edge intelligent control layer, and a multi-source terminal autonomy layer. The specific structure and functions are as follows: Multi-source terminal autonomy layer: The multi-source terminal autonomy layer is the core of the system's data collection and local rapid response, including multi-source terminal devices and local decision-making modules.

[0023] Among them, multi-source terminal equipment includes compatible photovoltaic inverters (such as Growatt, Sungrow and other brands), energy storage converters, electric vehicle charging piles, distribution boxes, combiner boxes, environmental monitors and wind turbines, etc., which can realize minute-level data collection, covering key information such as equipment operating status, power output, environmental parameters, etc.

[0024] The local decision-making module, centered around an intelligent miniature circuit breaker, features built-in carrier (470-510MHz), WiFi (5GHz), and 4G communication modules, enabling transmission rates up to 150Mbps (WiFi). It boasts three core capabilities: First, it supports high-speed sampling of fault waveforms (10kHz sampling frequency, 16-bit resolution, and storage in CSV format); second, it enables local storage caching when communication is interrupted, automatically retransmitting fault data to the edge intelligent control layer upon restoration; and third, it enables millisecond-level automatic protection execution. For example, overcurrent protection can respond within milliseconds, and a combined tripping strategy supports graded overvoltage response (for mild overvoltages > 1.1Un, only PV is tripped; for severe overvoltages > 1.3Un, PV and energy storage are tripped, with tripping time ≤ 10ms).

[0025] Edge intelligent control layer: The edge intelligent control layer is responsible for protocol conversion, local control and rapid fault processing, and deploys intelligent gateways, communication protocol converters, flexible control terminals and edge controllers.

[0026] The intelligent gateway uses an industrial-grade ARM processor (Cortex-A72 architecture), supports RS485 / HPLC interfaces, and has passed the State Grid EMC anti-interference test (GB / T17626.5 Level 4 surge protection). It can operate stably in high temperature (up to 60°C), high humidity (95% RH), and strong electromagnetic interference (compliant with GB / T17626.4 Level 4 immunity) environments. It also features topology recognition and physical positioning capabilities, enabling rapid identification of device locations and connections within the power grid. It also works with a communication protocol converter to achieve multi-protocol conversion.

[0027] For example, the communication protocol converter has a built-in protocol identification module and is equipped with a machine learning adaptive algorithm, which can automatically identify more than 95% of mainstream protocols (including IEC61850-9-2LE power protocol, Modbus, DL / T698.45, etc.). Figure 3 As shown, its workflow is as follows: after collecting the device data to be uploaded (inverter data in this embodiment), the data parsing module parses and identifies the current protocol type and matches it with the mainstream protocol; if the match is successful, it is converted into a unified standard protocol data (such as DL / T698.45); if the match fails, it automatically switches to the bypass transparent transmission mode and completes the conversion by manually configuring the conversion rule library. The data conversion success rate is ≥99.8%.

[0028] For example, the flexible control terminal integrates a high-performance edge computing chip, a built-in PV output prediction neural network model, and supports the local deployment of deep learning algorithms. The entire process, from data acquisition to power regulation, has a latency of ≤50ms. Local regulation commands are generated based on global policies and device data. For example, when the load factor of the substation exceeds 90%, three-level power regulation is automatically implemented (first limiting non-critical loads such as charging stations, then adjusting PV output to 80% of rated power, and finally disconnecting from the energy storage system).

[0029] Edge controller: Equipped with a fuzzy control algorithm, it can independently execute local power optimization strategies, such as automatically disconnecting the generator within 100ms after islanding detection. It also executes the protection inter-tripping process in the event of a grid fault, collects overvoltage signals from the protection device through a hard-wired channel (delay ≤ 5ms), calculates the inter-tripping range based on locally stored grid topology parameters, and performs hierarchical operations. Upon completion, it uploads a data packet containing the fault time, type, and location to the cloud.

[0030] Cloud collaborative optimization layer: The cloud-based collaborative optimization layer is responsible for global strategy generation and visualization management, including the energy management platform and digital twin modeling module.

[0031] For example, the energy management platform is built based on a distributed database (CockroachDB) and is equipped with a multi-energy collaborative optimization algorithm (photovoltaic-energy storage-charging pile joint scheduling model). It supports second-level data aggregation and policy issuance, and can perform multi-energy collaborative optimization scheduling based on device data uploaded from the edge layer to generate a global strategy.

[0032] Digital twin modeling module: Visualizes received device data and fault data uploaded by the edge layer (including fault waveforms and topology change records). Combined with the edge layer's multi-protocol acquisition capabilities, it achieves "observable" status parameters for more than 98% of equipment and supports dynamic visualization of the fault impact range.

[0033] This embodiment also provides a method for operating a solar-storage-charging system based on edge intelligent control. Based on the aforementioned "edge-cloud-end" three-layer architecture, the system's workflow is as follows: Multi-source terminal autonomous layer operation: Minute-level device data (such as photovoltaic output, charging pile load, etc.) is collected through multi-source terminal devices and transmitted to the edge intelligent control layer; at the same time, the local decision module (intelligent miniature circuit breaker) monitors the device status and independently executes protection actions in the event of millisecond-level emergency faults (such as overvoltage and overcurrent), caching the fault data and retransmitting it after communication is restored.

[0034] Operation of the edge intelligent control layer: The communication protocol converter converts the terminal data into a protocol (standard protocols such as DL / T698.45 are used in this embodiment) and uploads it to the cloud via the intelligent gateway; the flexible control terminal receives the global strategy from the cloud and generates local adjustment instructions (such as power adjustment when the load rate exceeds the threshold) based on the local photovoltaic output prediction model, which are then sent to the terminal for execution; the edge controller initiates protection interlocking in the event of a grid fault, quickly isolates the fault, and uploads the fault information.

[0035] Operation of the cloud-based collaborative optimization layer: Aggregates standardized data uploaded by the edge layer and visualizes the analysis results through the digital twin modeling module; the energy management platform generates global strategies (such as photovoltaic-energy storage-charging pile joint scheduling solutions) based on the multi-energy collaborative optimization algorithm and sends them to the edge layer in seconds.

[0036] For example, this embodiment also provides the implementation process of equipment deployment, protocol conversion and data integration, and fault emergency handling of the optical storage and charging system, which specifically includes: (1) Equipment deployment: Smart gateway installation: Select a well-ventilated location with low electromagnetic interference at the photovoltaic grid-connected point for installation. Connect the wires strictly according to the instructions (make sure the RS485 / HPLC interface is secure), and use professional tools for grounding to resist lightning strikes and electromagnetic interference.

[0037] Flexible Control Terminal Configuration: Configure the power control thresholds for the flexible control terminal based on grid operation requirements and substation load conditions. For example, when the substation load factor exceeds 90%, the inverter power is automatically limited to 80% of the rated power; when the load factor is less than 30%, the inverter power output is appropriately increased. During configuration, parameters are set through the terminal's human-machine interface or remote management platform, and relevant testing and verification are performed to ensure that the threshold settings are accurate.

[0038] (2) Protocol conversion and data integration: Protocol Conversion: A communication protocol converter converts the protocols of inverters from different manufacturers, such as Growatt and Sungrow, into the DL / T698.45 standard. During the conversion process, the data sent by the inverter is first parsed to identify its protocol type. Then, according to pre-set conversion rules, the data is converted to a standard format. Each batch of converted data is verified for integrity and accuracy to ensure no data loss or errors occur during the conversion process.

[0039] Data integration and upload: The converted data is integrated and uploaded to the cloud platform at regular intervals (e.g., every minute). Before upload, the data is encrypted using the AES encryption algorithm to prevent theft or tampering during transmission. Each piece of data is also timestamped and identified by the device to facilitate storage and analysis on the cloud platform.

[0040] (III) Emergency handling of faults, as follows Figure 4 As shown: Fault Monitoring and Identification: When the main transformer gap protection triggers, the edge gateway receives the trip signal in real time through its built-in monitoring module. Upon receiving the signal, the edge gateway quickly analyzes and identifies the fault type and location. If it determines that the main transformer gap is overvoltage, a trip command is triggered.

[0041] Fault-related disconnection: After the edge gateway triggers the disconnection command, it quickly disconnects the distributed generation grid connection point through an intelligent switch, isolating the faulty part from the grid and preventing further expansion. During the disconnection process, the intelligent switch operates within 10 milliseconds, ensuring rapid interruption of the fault current. Simultaneously, the edge gateway uploads fault information to the cloud platform, including fault time, type, and location, for subsequent analysis and resolution.

[0042] Recovery Process: After troubleshooting, equipment recovery is performed. First, the smart switch is reset. Then, a startup command is sent to the inverter via the edge gateway, gradually restoring normal distributed PV operation. During the recovery process, all equipment parameters are monitored in real time to ensure proper operation. After recovery is complete, a comprehensive performance test is conducted on the equipment, including power generation, power regulation capability, and device stability, to verify normal operation.

[0043] In summary, this embodiment provides a solar-storage-charging system based on edge intelligent control. Its technical innovations are: Integration of "four possible" capabilities: "observable, measurable, adjustable, and controllable" are achieved through edge-cloud dual closed-loop control. The three-level cascade switching logic is triggered within 10ms at the edge layer, and the fault topology is synchronously updated on the cloud to achieve dynamic visualization.

[0044] Breakthrough in protocol compatibility: The communication protocol converter automatically recognizes more than 90% of mainstream protocols, with a 92% success rate in the recognition of 100 inverter protocols tested, with recognition time ≤ 5 seconds, and supports online updates of new protocols.

[0045] Main transformer gap protection inter-tripping technology: The edge controller directly samples overvoltage signals (delay ≤ 5ms), automatically calculates the inter-tripping range based on local topology parameters, and uploads time-stamped fault data packets after inter-tripping, supporting fault backtracking and strategy optimization.

[0046] Based on the above technical innovations, the system provided by this embodiment has the following advantages: First, it improves access carrying capacity: the access capacity of distributed new energy has increased by more than 40%, the peak-shaving response speed of the substation is ≤30 seconds, and the fault location accuracy rate reaches 99.5%; the localized processing of the edge layer reduces the cloud data transmission volume by 60% and the operation and maintenance costs by 50%.

[0047] Second, it can achieve rapid response and precise positioning: the response speed of the substation peak-shaving demand is ≤50 seconds, and the fault positioning accuracy is ≥98%, shortening the power outage time and improving the power supply reliability.

[0048] Third, it reduces multi-source coordination and costs: It achieves coordinated control of photovoltaics, energy storage, and charging piles, reduces operation and maintenance costs by 45%, and improves equipment utilization and energy efficiency.

[0049] In summary, the present invention provides a solar-storage-charging system and method based on edge intelligent control, which has the following advantages over existing systems: This system adopts a three-layer architecture design consisting of a cloud-based collaborative optimization layer, an edge-based intelligent control layer, and a multi-source terminal autonomy layer. The multi-source terminal autonomy layer enables device data collection and independent processing of emergency faults. The edge-based intelligent control layer completes protocol conversion and generates local adjustment instructions. The cloud-based collaborative optimization layer performs data aggregation analysis and global strategy formulation. Combined with the multi-source terminal devices, intelligent gateways, communication protocol converters, flexible control terminals, energy management platforms, digital twin modeling modules, and related algorithms contained in each layer, it can achieve efficient collaborative operation of the photovoltaic storage and charging system, improve data processing and transmission efficiency, enhance the timeliness and accuracy of fault handling, optimize energy scheduling and power control, and realize visual management through digital twins, comprehensively improving the reliability, stability, and intelligence level of the system.

[0050] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention.

Claims

1. A solar-storage-charging system based on edge intelligent control, characterized by: include: Cloud collaborative optimization layer, edge intelligent control layer, and multi-source terminal autonomy layer; The cloud collaborative optimization layer and the edge intelligent control layer communicate and interconnect; The edge intelligent control layer is communicated and interconnected with the multi-source terminal autonomous layer; The multi-source terminal autonomous layer is used to collect device data of multi-source terminal devices and transmit the device data to the edge intelligent control layer; and is used to independently handle emergency faults; The edge intelligent control layer is used to perform protocol conversion between devices, and after the protocol conversion is completed, the device data uploaded by the multi-source terminal autonomous layer is uploaded to the cloud collaborative optimization layer; and generating local adjustment instructions according to the global strategy issued by the cloud collaborative optimization layer, and simultaneously issuing the local adjustment instructions to the multi-source terminal autonomous layer for the multi-source terminal autonomous layer to execute the local adjustment instructions; The cloud collaborative optimization layer is used to aggregate the device data uploaded by the edge intelligent control layer and present the analysis results of the device data based on digital twin modeling; It is also used to generate global strategies based on the analysis results of device data and send them to the edge intelligent control layer.

2. The solar-storage-charging system based on edge intelligent control according to claim 1 is characterized in that: The multi-source terminal autonomy layer includes multi-source terminal devices and a local decision module; the local decision module is connected to the multi-source terminal devices to realize self-execution of protection; wherein, the multi-source terminal devices include: inverters, distribution boxes, combiner boxes, energy storage, environmental monitors, charging piles and wind turbines.

3. The optical storage and charging system based on edge intelligent control according to claim 2 is characterized in that: The local decision module includes an intelligent miniature circuit breaker; the intelligent miniature circuit breaker can collect fault waveform samples, enable local storage cache when communication is interrupted, and automatically retransmit the fault waveform samples to the edge intelligent control layer after communication is restored.

4. The solar-storage-charging system based on edge intelligent control according to claim 1 is characterized in that: The edge intelligent control layer includes an intelligent gateway, a communication protocol converter and a flexible control terminal; The intelligent gateway, the communication protocol converter and the flexible control terminal are all connected between the cloud collaborative optimization layer and the multi-source terminal autonomy layer; The intelligent gateway cooperates with the communication protocol converter to realize protocol conversion between various devices; The flexible control terminal is used to generate a local adjustment instruction according to the received global strategy, and send the local adjustment instruction to the multi-source terminal autonomous layer.

5. The solar-storage-charging system based on edge intelligent control according to claim 4 is characterized in that: The communication protocol converter has a built-in protocol identification module, which is equipped with a machine learning adaptive algorithm and can implement the following steps: Collect device data to be uploaded; Parse the data based on the device data to be uploaded to identify the current protocol type; Match the current protocol type with the mainstream protocol. If the match is successful, the device data is formatted and ultimately output as unified standard protocol data. If the match fails, the device automatically switches to bypass transparent transmission mode, converting the device data format through manually configured conversion rule base, and ultimately outputting unified standard protocol data. Upload unified standard protocol data to the edge intelligent control layer or cloud collaborative optimization layer.

6. The solar-storage-charging system based on edge intelligent control according to claim 4 is characterized in that: The flexible control terminal has a built-in photovoltaic output prediction neural network model, which can generate local adjustment instructions based on global strategies and equipment data, and finally send the local adjustment instructions to the multi-source terminal autonomous layer.

7. The solar-storage-charging system based on edge intelligent control according to claim 4 is characterized in that: The edge intelligent control layer also includes an edge controller; wherein the edge controller is equipped with a fuzzy control algorithm and can independently execute a local power optimization strategy according to the fuzzy control algorithm.

8. The solar-storage-charging system based on edge intelligent control according to claim 1 is characterized in that: The cloud-based collaborative optimization layer includes an energy management platform built on a distributed database; the energy management platform is equipped with a multi-energy collaborative optimization algorithm that can perform multi-energy collaborative optimization scheduling based on received device data to generate a global strategy; The cloud-based collaborative optimization layer also includes a digital twin modeling module, which is used to visualize the received device data and the fault data uploaded by the edge intelligent control layer.

9. A method for operating a solar-storage-charging system based on edge intelligent control, characterized in that: The optical-storage-charging system based on edge intelligent control according to any one of claims 1 to 8 comprises: Utilize the multi-source terminal autonomy layer to collect device data from multi-source terminal devices, transmit the device data to the edge intelligent control layer, and independently handle emergency faults; The edge intelligent control layer performs protocol conversion between devices and uploads the device data uploaded by the multi-source terminal autonomy layer to the cloud collaborative optimization layer after the protocol conversion is completed. Local adjustment instructions are generated based on the global strategy issued by the cloud collaborative optimization layer and sent to the multi-source terminal autonomy layer for execution. The cloud-based collaborative optimization layer aggregates device data uploaded by the edge intelligent control layer, and presents the analysis results of the device data based on digital twin modeling; and generates global strategies based on the analysis results of the device data and sends them to the edge intelligent control layer.

10. The method for operating a solar-storage-charging system based on edge intelligent control according to claim 9, characterized in that: The edge intelligent control layer includes an edge controller. When a power grid fault occurs, the edge controller performs a protection switching process as follows: Collect overvoltage signals sent by protection devices; Combine overvoltage signals with locally stored grid topology parameters to automatically calculate the disconnection range and perform graded operations; After the joint cutover process is completed, a fault data packet is uploaded to the cloud collaborative optimization layer; the fault data packet includes the time, type and location of the fault.

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