An AI-based power generation device

Abstract

This invention relates to the field of power generation and energy management technology, and discloses an artificial intelligence-based power generation device, comprising: at least one power generation system; a micro wind turbine generator connected to a wind-solar hybrid controller; a lithium-ion energy storage battery for energy storage and power supply to electrical equipment; a cable management mechanism; and intelligent integrated components including a smart energy meter and remote smart sensors for collecting operational data and sending it to an edge intelligent unit; the edge intelligent unit processes the data, stores it in a model library, and outputs localized intervention strategies; a cloud management platform communicates bidirectionally with the edge intelligent unit to construct a twin model and distribute it to the model library. By collaboratively constructing and dynamically evolving an ideal energy consumption trajectory twin model through the cloud management platform and the edge intelligent unit, combined with non-intrusive load monitoring, dynamic time warping, and energy consumption density determination, the device achieves business status identification, abnormal energy consumption detection, and localized intervention strategy output, thereby improving energy-saving performance and operational safety.

Description

Technical Field

[0001] This invention relates to the field of power generation and energy management technology, specifically to a power generation device based on artificial intelligence. Background Technology

[0002] A power generation device typically refers to a device or system that converts one or more primary energy sources into electrical energy and outputs it for use by electrical equipment. Common forms include photovoltaic power generation, wind power generation, and wind-solar hybrid power generation. It generally consists of a power generation unit, a control and energy conversion unit, an energy storage unit, and a load end, used to realize the generation, distribution, and supply of electrical energy. Artificial intelligence-based power generation devices, on the basis of the above-mentioned power generation devices, introduce intelligent modules such as smart meters, sensors, edge intelligent units, and cloud management platforms. Through the collection, analysis, and decision-making of operating data, it realizes intelligent management and control of the power generation and energy consumption process. In practical applications, existing power generation devices mostly use preset rules or fixed thresholds for operation management to complete basic power generation control and power supply.

[0003] However, with current technology, monitoring and control based on preset rules or fixed thresholds are difficult to accurately identify and judge energy consumption behavior in combination with changes in the business status on the field side. This makes it difficult to detect abnormal energy consumption or unreasonable operating status in a timely manner, and also makes it impossible to output effective localized intervention strategies, thereby affecting energy saving effect and operational safety. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an artificial intelligence-based power generation device, which solves the problem that power generation devices struggle to identify abnormal energy consumption in conjunction with operational status and promptly output localized intervention strategies.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a power generation device based on artificial intelligence, comprising: At least one power generation system, the power generation system including solar cells, solar tracking control system, charge and discharge control, wind-solar hybrid controller, unloader, battery pack, off-grid inverter, DC load and AC load; The solar cells are used for photovoltaic power generation, the wind-solar hybrid controller is used for controlling and distributing energy from the wind and solar power generation, and the off-grid inverter is used to supply power to the AC load. A micro wind turbine generator set includes a wind turbine, a drum, a main shaft, a gearbox, a speed increaser, a low-speed shaft, a generator, a coupling, a brake, a power electronic system, and a speed control device, used to convert wind energy into electrical energy and connect it to the wind-solar hybrid controller; A lithium-ion energy storage battery is used to store the electrical energy generated by the power generation system and supply power to the terminal electrical equipment on the field side. A cable management mechanism is installed at the cable source inlet and outlet of the power generation device for managing and limiting the cables inside the power generation device. The intelligent integrated components, including smart meters and remote smart sensors, are used to collect real-time business status operation data of field-side application terminals and send it to the edge intelligent unit; The edge intelligence unit is communicatively connected to the intelligent integration component. It is used to classify, label, process, calculate, identify and correct the real-time business status operation data and store it in the model library. It also compares the ideal energy consumption trajectory twin model in the model library with the real-time data on the field side, calculates the deviation and implements localized intervention strategies. The cloud management platform, installed on the cloud server, communicates bidirectionally with the edge intelligent unit via network. It is used to receive data uploaded by the edge intelligent unit, construct the ideal energy consumption trajectory twin model, and distribute the ideal energy consumption trajectory twin model to the model library for the edge intelligent unit to call.

[0006] Preferably, the wind-solar hybrid controller is configured to enable the solar cells and the micro wind turbine generator to operate in a wind-solar hybrid mode, specifically including: At night or on cloudy days, the micro wind turbine generators will generate electricity preferentially. On sunny days, the solar cells generate electricity preferentially. When there is wind and sunlight, the micro wind turbine generator and the solar cell generate electricity simultaneously. When the power generation of the power generation device is greater than the power consumption of the DC load and the AC load, the excess electrical energy is converted into DC and stored in the lithium-ion energy storage battery.

[0007] Preferably, the cable management mechanism includes a fixed block, a rotating rod rotatably connected to the fixed block, an arc-shaped groove disposed on the rotating rod, a slider slidably engaged with the arc-shaped groove, a connecting block connected to the slider, and a support rod connected to the connecting block and used to adjust the cable spacing. The cable management mechanism further includes a limiting component for limiting the angle of the rotating rod and a tightening component for tightening the cable.

[0008] Preferably, the limiting component includes a ratchet, a pawl that cooperates with the ratchet, a spring and a spring plate for keeping the pawl engaged with the ratchet, and a paddle for driving the pawl to disengage from the ratchet, so as to limit the rotation angle of the rotating rod and prevent reverse rotation.

[0009] Preferably, the tightening component is disposed at the arc-shaped groove, and the tightening component is used to press and fix the cable passing through the arc-shaped groove, so that the cable is kept in a limited state within the arc-shaped groove.

[0010] Preferably, the edge intelligent unit is configured to perform load decomposition on the field-side data collected by the smart energy meter and remote smart sensor based on a non-intrusive load monitoring algorithm, so as to identify the operating status of the main back-end equipment and determine the current business status, and accordingly call the ideal energy consumption trajectory twin model in the model library corresponding to the business status.

[0011] Preferably, the edge intelligence unit includes: The energy consumption partial density is calculated by comparing the real-time energy consumption trajectory of the field side under the current business state with the ideal energy consumption trajectory corresponding to the ideal energy consumption trajectory twin model after dynamic time normalization. When the energy consumption density meets the preset threshold condition, a localized intervention strategy is output, and when the emergency conditions are abnormally met, an emergency power outage physical shutdown is triggered.

[0012] Preferably, the cloud management platform includes: The system receives real-time business status operation data and historical data uploaded by the edge intelligence unit, aggregates and processes the data to construct the ideal energy consumption trajectory twin model, and dynamically evolves the ideal energy consumption trajectory twin model. The cloud management platform is also configured to perform cross-regional spatiotemporal consistency verification and forward-looking energy consumption scheduling on the ideal energy consumption trajectory twin model or the data, and to distribute the updated ideal energy consumption trajectory twin model to the model library for the edge intelligent unit to call.

[0013] Preferably, the power generation device includes a housing for installation and protection, the housing comprising a stainless steel plate and having through holes; The solar cell is mounted on the outer surface of the housing, so that the housing provides a mounting base for the solar cell while also forming a shading device.

[0014] Preferably, the power generation device is suitable for installation in a micro-space location within a building and its ancillary facilities.

[0015] This invention provides a power generation device based on artificial intelligence. It has the following beneficial effects: 1. This invention constructs and dynamically evolves an ideal energy consumption trajectory twin model through collaboration between a cloud management platform and edge intelligent units. Combined with non-intrusive load monitoring, dynamic time warping, and energy consumption density determination, it enables business status identification, abnormal energy consumption detection, and localized intervention strategy output, thereby improving energy-saving effect and operational safety.

[0016] 2. By effectively utilizing the micro-space of the main building, this invention can adapt and install the device on the eaves, doors and windows, air conditioner outdoor units, etc., to realize wind and solar power generation and local energy supply in the space outside the roof, thereby improving the coverage and depth of clean energy utilization. Attached Figure Description

[0017] Figure 1 This is a perspective view of an artificial intelligence-based power generation device according to the present invention; Figure 2 This is an architectural diagram of an artificial intelligence-based power generation device according to the present invention; Figure 3 This is an example diagram of an artificial intelligence-based power generation device according to the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see the appendix Figure 1 - Appendix Figure 3 This invention provides an artificial intelligence-based power generation device, comprising: At least one power generation system, which includes solar cells, a solar tracking control system, a charge and discharge control system, a wind-solar hybrid controller, a load unloader, a battery bank, an off-grid inverter, a DC load, and an AC load; Among them, solar cells are used for photovoltaic power generation, wind-solar hybrid controllers are used for controlling and distributing energy from wind and solar power generation, and off-grid inverters are used to supply power to AC loads. A micro wind turbine generator set includes a wind turbine, a drum, a main shaft, a gearbox, a speed increaser, a low-speed shaft, a generator, a coupling, a brake, a power electronic system, and a speed control device, used to convert wind energy into electrical energy and connect it to a wind-solar hybrid controller; Lithium-ion energy storage batteries are used to store electrical energy generated by a power generation system and supply power to on-site terminal equipment. The intelligent integrated components, including smart meters and remote smart sensors, are used to collect real-time business status operation data of field-side application terminals and send it to the edge intelligent unit; The edge intelligence unit communicates with the intelligent integration component and is used to classify, label, process, calculate, identify and correct real-time business status operation data and store it in the model library. It also compares the ideal energy consumption trajectory twin model in the model library with the real-time data on the field side, calculates the deviation and implements localized intervention strategies. The cloud management platform, installed on a cloud server, communicates bidirectionally with the edge intelligent unit via network. It receives data uploaded by the edge intelligent unit, constructs an ideal energy consumption trajectory twin model, and distributes the ideal energy consumption trajectory twin model to the model library for the edge intelligent unit to use.

[0020] Specifically, the power generation device primarily uses wind-solar hybrid power generation, and uses an energy storage system to buffer energy. The intelligent integrated components collect on-site operating data, which is then analyzed and processed in real time by the edge intelligent unit. This data is then used in collaboration with the cloud management platform to build and update an ideal energy consumption trajectory twin model. This forms a closed-loop management system on-site for continuous monitoring of energy consumption status, deviation judgment, and output of localized intervention strategies. Through the above structural configuration, wind and solar power generation can be deployed in the micro-space of buildings or ancillary facilities for local power supply. Furthermore, with the collaboration of edge intelligence and cloud models, the device can identify abnormal energy consumption and unreasonable operating states, thereby reducing energy waste and improving the stability and safety of energy supply. In this embodiment, the power generation device is equipped with at least one power generation system, which includes solar cells, a solar tracking control system, a charge and discharge control system, a wind-solar hybrid controller, a load unloader, a battery bank, an off-grid inverter, a DC load, and an AC load. The solar cells are used to convert solar radiation energy into electrical energy output. The solar tracking control system is used to adjust the light-receiving state of the solar cells according to changes in sunlight to improve power generation efficiency. The charge and discharge control system is used to manage the charging and discharging of the battery bank and lithium-ion energy storage battery to avoid overcharging and over-discharging. The wind-solar hybrid controller is used to uniformly control and distribute the output of the wind power side and the photovoltaic side, and deliver electrical energy to the DC load, the off-grid inverter, or the energy storage side as needed. The load unloader is used to unload excess energy under sudden load changes or abnormal operating conditions to ensure system stability. The off-grid inverter is used to convert DC side electrical energy into AC electrical energy and supply power to the AC load. Through the coordinated configuration of this power generation system, the power supply needs of both DC and AC loads can be covered simultaneously, and the energy distribution can be kept stable when the wind and solar output fluctuates, thereby achieving more reliable on-site power supply. To achieve wind-solar hybrid power generation, a micro wind turbine generator unit is installed. This unit includes a wind turbine, a drum, a main shaft, a gearbox, a speed increaser, a low-speed shaft, a generator, a coupling, a brake, a power electronics system, and a speed control device. The wind turbine rotates under the action of natural wind and drives the main shaft to output mechanical energy. The mechanical energy is matched with the speed of the low-speed shaft, the gearbox, and the speed increaser to drive the generator to generate electricity. The coupling is used to connect the shaft system and absorb vibration and shock. The brake is used to implement braking protection in case of overspeed or maintenance. The speed control device is used to adjust the speed and output to adapt to changes in wind speed. The power electronics system is used to rectify and stabilize the output power and connect it to the power management link of the wind-solar hybrid controller. Through the above structure, wind energy can be stably converted into electrical energy and connected to the wind-solar hybrid controller, so that power can still be supplied continuously at night or on cloudy days when the photovoltaic output is insufficient, thereby improving the all-weather power supply capability and utilization efficiency of the overall power generation unit. In this embodiment, the power generation device is equipped with a lithium-ion energy storage battery to store the electrical energy generated by the power generation system and supply power to the terminal electrical equipment on the field side. When the output of the wind-solar hybrid power generation exceeds the on-site load demand, the wind-solar hybrid controller, in coordination with charge and discharge control, introduces the excess electrical energy into the lithium-ion energy storage battery to complete the energy storage. When the wind and solar output decreases or the load increases for a short time, the lithium-ion energy storage battery releases electrical energy to supply power to the DC side load, or replenishes the AC side load through the off-grid inverter, thereby smoothing the power supply instability caused by wind and solar fluctuations. Through the energy buffer on the energy storage side, the voltage fluctuation and power interruption risk caused by instantaneous output changes can be reduced, and the power supply continuity and reliability of the system under abnormal operating conditions can be improved. To achieve the perception of the on-site business status and energy consumption status, an intelligent integrated component is set up. The intelligent integrated component includes a smart energy meter and a remote smart sensor. The smart energy meter is used to collect electrical parameter information on the on-site side, including data such as voltage, current, power, and load. The remote smart sensor is used to collect environmental or equipment status information related to business operation, including environmental climate information, temperature information, humidity information, etc. The above-mentioned collected data is sent to the edge intelligent unit through a preset data link, so that the edge side can obtain multi-source information input representing the business status operation data. Through this intelligent integrated component, the power generation device not only has the ability to supply power, but also has the ability to measure and trace the energy supply and consumption process in real time, providing a data foundation for subsequent identification, comparison and intervention, thereby improving the precision of energy consumption management. The edge intelligent unit communicates with the intelligent integrated component to classify, label, process, calculate, identify, and correct real-time business status operation data collected by smart meters and remote smart sensors. The processed data is stored in the model library. The edge intelligent unit further compares the ideal energy consumption trajectory twin model in the model library with the real-time data on the field side to obtain the deviation information of the energy consumption trajectory. When the preset conditions are met, it outputs a localized intervention strategy to correct the energy consumption on the field side. Since the edge intelligent unit is deployed on the field side, it can quickly complete the analysis and response after the data is generated, reducing the delay caused by relying entirely on remote calculation. This enables the power generation device to take timely measures when abnormal energy consumption or unreasonable operating conditions occur, thereby reducing energy waste and improving operational safety and stability. The cloud management platform is installed on a cloud server and communicates bidirectionally with the edge intelligent unit. It receives data uploaded by the edge intelligent unit and builds an ideal energy consumption trajectory twin model based on long-term accumulated historical data and real-time data from the field. The cloud management platform can also update and improve the ideal energy consumption trajectory twin model according to the continuous aggregation of data, and distribute the updated ideal energy consumption trajectory twin model to the model library for the edge intelligent unit to use. Through the collaboration between the cloud management platform and the edge intelligent unit, a two-way closed-loop mechanism can be formed, which enables the cloud to build and update the model and the edge to compare and intervene in real time. This allows the ideal energy consumption trajectory to continuously evolve and conform to actual operation under different scenarios and business states, thereby improving the accuracy of deviation identification and the effectiveness of localized intervention strategies, and achieving more stable energy saving, consumption reduction and safe energy management results.

[0021] The wind-solar hybrid controller is configured to enable the solar cells and micro wind turbine generators to operate in a wind-solar hybrid mode, specifically including: At night or on cloudy days, power generation is prioritized from micro wind turbine generators; On sunny days, electricity is generated primarily by solar panels; When there is both wind and sunlight, the micro wind turbine generator and solar cells generate electricity simultaneously. When the power generation capacity of the power generation device exceeds the power consumption of the DC load and AC load, the excess electrical energy is converted into DC and stored in the lithium-ion energy storage battery.

[0022] Specifically, the wind-solar hybrid controller is electrically connected to solar cells, micro wind turbine generators, lithium-ion energy storage batteries, DC loads, AC loads, and off-grid inverters to uniformly control and distribute the output of the wind and solar sides, thereby enabling the power generation device to maintain continuous power supply under different climate and sunlight conditions. The wind-solar hybrid controller collects the output voltage and current of the solar cells and the micro wind turbine generators, and combines the power demand of the DC and AC loads to adjust the output and destination of each power source, thereby realizing priority power supply and surplus energy storage in the wind-solar hybrid mode. When operating under insufficient sunlight conditions such as nighttime or cloudy days, the output of solar cells decreases or is not stable. The wind-solar hybrid controller controls the micro wind turbine to enter the priority power generation state, and sends the electricity converted from wind energy to the DC power supply link to supply DC loads. When it is necessary to supply AC loads, the DC power is converted by the off-grid inverter and supplied to the AC loads. In this way, the basic operation of the on-site terminal equipment can still be maintained under no light or low light conditions, improving the continuity and applicability of power supply. When the solar panels are in a sunny or otherwise well-lit condition, they can generate a stable output of photovoltaic power. The wind-solar hybrid controller controls the solar panels to enter a priority power generation state, distributing the power output of the solar panels to the DC load and the off-grid inverter as needed. It also coordinates and manages the output of the micro wind turbine generator, so that the system can maintain a stable energy distribution while meeting the power demand of the load, reducing the impact of output fluctuations caused by wind speed fluctuations on the power supply quality of the load end, thereby improving the power generation efficiency and power supply stability under sunny conditions. When operating under both wind and solar conditions, the wind-solar hybrid controller simultaneously receives power output from both solar cells and micro wind turbines, and performs parallel scheduling and coordinated distribution of the two power sources, enabling both solar cells and micro wind turbines to generate electricity at the same time. At this time, the wind-solar hybrid controller prioritizes power supply to the load side based on the real-time power demand of the DC and AC loads, while coordinating and controlling the output to increase the total power generation per unit time and reduce the impact of single energy source output fluctuations on the overall power supply, thereby achieving the synergistic gain effect of wind-solar hybridization. In this embodiment, when the power generation of the generator exceeds the power consumption of the DC and AC loads, the wind-solar hybrid controller, in conjunction with charge and discharge control, converts the excess energy into DC and introduces it into the lithium-ion energy storage battery for storage, so that the excess energy is effectively stored rather than directly lost. When the subsequent power generation decreases or the load power increases, resulting in insufficient power supply, the lithium-ion energy storage battery releases the stored energy to supply power to the DC load, or after conversion by the off-grid inverter, it supplies power to the AC load, thereby achieving energy buffering under wind and solar power output fluctuations, reducing voltage fluctuations and power outage risks, and improving the reliability and safety of system operation.

[0023] The cable management mechanism is installed at the cable source inlet and outlet of the power generation device to manage and limit the cables inside the power generation device; The cable management mechanism includes a fixed block, a rotating rod rotatably connected to the fixed block, an arc-shaped groove provided on the rotating rod, a slider that slides with the arc-shaped groove, a connecting block connected to the slider, and a support rod connected to the connecting block and used to adjust the cable spacing. The cable management mechanism also includes a limiting component for limiting the angle of the rotating rod and a tightening component for tightening the cable.

[0024] Specifically, the cable management mechanism is installed at the cable source inlet and outlet of the power generation device. It is preferably located at the point where multiple cables from wind and solar power generation components, electrical conversion components, and intelligent integration components converge and need to pass through the outer casing. It is used to organize, guide, and limit the cables inside the power generation device. By arranging the cable management mechanism at this location, multiple cables can be arranged separately according to a predetermined path at the inlet and outlet, reducing cable cross-entanglement, squeezing friction, and wear on the outer sheath caused by wind swinging. This reduces abnormal electrical parameters and safety hazards caused by cable damage, and facilitates quick positioning and disassembly during later inspection and maintenance. In this embodiment, the cable management mechanism includes a fixed block, a rotating rod rotatably connected to the fixed block, and an arc-shaped groove disposed on the rotating rod. The fixed block is used to fix it to the housing or support structure of the power generation device, thereby providing a mounting base for the cable management mechanism. The rotating rod is rotatably disposed relative to the fixed block through a rotating connection, so that the orientation or position of the arc-shaped groove can be adjusted with the rotating rod. Several arc-shaped grooves are set along the length direction of the rotating rod and distributed in a linear array to guide different cables through different grooves. After the cables are passed through the corresponding arc-shaped grooves, they can be arranged separately between the arc-shaped grooves to avoid multiple cables squeezing or rubbing against each other. To achieve adjustable cable spacing, a slider is installed at the arc-shaped groove, which slides along the groove to accommodate different diameters or arrangements of the cable bundle. The slider is connected to a connecting block, which transmits the slider's displacement to a support rod. The support rod is connected to the connecting block and is used to adjust the cable spacing. Specifically, by changing the position or orientation of the support rod relative to the connecting block, the positions of the connecting block and the slider in the arc-shaped groove can be changed, thereby altering the distribution spacing of each cable within the cable management mechanism. This ensures that the cables are kept separated without excessive bending or compression, further improving the reliability and adaptability of the cable arrangement. In this embodiment, the cable management mechanism further includes a limiting component for limiting the angle of the rotating rod and a tightening component for tightening the cable. The limiting component is used to limit and hold the rotating rod after it is adjusted to the target angle, preventing the rotating rod from rotating under vibration or external force and causing the cable position to change, thereby ensuring the stability of the cable management state. The tightening component is used to press and fix the cable passing through the arc groove, keeping the cable in a limited state within the arc groove, reducing the relative displacement or shaking of the cable during operation. Through the cooperation of the limiting component and the tightening component, the cable can be stably fixed on the basis of cable management guidance and spacing adjustment, thereby improving the wiring safety and long-term operational reliability at the power generation device's line source inlet and outlet.

[0025] The limiting assembly includes a ratchet, a pawl that engages with the ratchet, a spring and a spring clip for keeping the pawl engaged with the ratchet, and a paddle for driving the pawl out of the ratchet, thereby limiting the rotation angle of the rotating rod and preventing reverse rotation.

[0026] Specifically, the limiting component is located at the rotational connection between the fixed block and the rotating rod. It includes a ratchet, a pawl that engages with the ratchet, a spring and a spring plate, and a lever. The ratchet rotates synchronously with the rotating rod. The pawl is installed on the fixed block and remains engaged with the ratchet under the preload of the spring and spring plate. This allows the rotating rod to adjust its angle across the teeth when it rotates in the permissible direction. When subjected to a reverse torque, the pawl locks against the ratchet teeth, thus limiting the rotation angle of the rotating rod and preventing reverse rotation. When it is necessary to release the limit for angle adjustment or maintenance, the lever is moved to drive the pawl to overcome the preload of the spring and spring plate and disengage from the ratchet. After the lock is released, the rotating rod can be readjusted. After the lever is released, the pawl automatically resets and re-engages to lock. This ensures adjustability while improving the locking stability and operational reliability of the cable management mechanism.

[0027] The clamping assembly is located at the arc-shaped groove. The clamping assembly is used to press and fix the cable passing through the arc-shaped groove, so that the cable is kept in a limited state within the arc-shaped groove.

[0028] Specifically, the clamping component is installed at the arc-shaped groove. After the cable is inserted into the arc-shaped groove, the clamping component applies a clamping force to fix the cable in the arc-shaped groove and keep it in a limited state. This prevents the cable from shaking, displacing, or being squeezed and rubbed against each other under the operation of the equipment, vibration, or external force. It also reduces the risk of wear and damage to the cable sheath, thereby improving the safety and long-term operational reliability of the wiring at the power generation device's inlet and outlet.

[0029] The edge intelligence unit is configured to perform load decomposition on field-side data collected by smart meters and remote smart sensors based on a non-intrusive load monitoring algorithm, in order to identify the operating status of the main back-end equipment and determine the current business status, and accordingly call the ideal energy consumption trajectory twin model in the model library that corresponds to the business status.

[0030] Specifically, the edge intelligent unit communicates with smart meters and remote smart sensors. The edge intelligent unit is configured to perform load decomposition on electrical parameter data such as voltage, current, power, and load collected by smart meters, as well as operational data such as environmental climate information, temperature information, and humidity information collected by remote smart sensors, based on a non-intrusive load monitoring algorithm. This allows it to identify the operating status of the main backend equipment and determine the current business status. After determining the business status, the edge intelligent unit retrieves an ideal energy consumption trajectory twin model corresponding to that business status from a model library as a reference model. This model is then used for comparison and analysis with real-time energy consumption data from the field, providing a basis for identifying abnormal energy consumption and outputting localized intervention strategies, and improving the targeting and accuracy of energy consumption management under different business statuses.

[0031] Edge intelligence units include: The energy consumption partial density is calculated by comparing the real-time energy consumption trajectory of the field side under the current business status with the ideal energy consumption trajectory corresponding to the twin model of the ideal energy consumption trajectory after dynamic time normalization. When the energy consumption density meets the preset threshold, a localized intervention strategy is output, and when the emergency conditions are abnormally met, an emergency power outage is triggered.

[0032] Specifically, after determining the current business status based on the non-intrusive load monitoring algorithm and calling the ideal energy consumption trajectory twin model corresponding to the business status in the model library, the edge intelligent unit dynamically times-normalizes the real-time energy consumption trajectory of the field side under the current business status with the ideal energy consumption trajectory corresponding to the ideal energy consumption trajectory twin model. This aligns the two energy consumption trajectories in the time dimension before comparison and analysis, and calculates the energy consumption bias density to characterize the degree of deviation between the real-time energy consumption on the field side and the ideal energy consumption. When the calculated energy consumption bias density meets the preset threshold conditions, the edge intelligent unit outputs a localized intervention strategy to correct the deviation of energy consumption on the field side. Furthermore, when the anomaly further meets the emergency conditions, it triggers an emergency power outage to promptly cut off the power circuit when there is significant abnormal energy consumption or safety hazards, thereby reducing energy waste and operational risks and improving the safety and reliability of the power generation unit.

[0033] The cloud management platform includes: Receive real-time business status operation data and historical data uploaded by the edge intelligence unit, aggregate and process the data and construct an ideal energy consumption trajectory twin model, and dynamically evolve the ideal energy consumption trajectory twin model; The cloud management platform is also configured to perform cross-regional spatiotemporal consistency verification and forward-looking energy consumption scheduling on the ideal energy consumption trajectory twin model or data, and to distribute the updated ideal energy consumption trajectory twin model to the model library for edge intelligent units to call.

[0034] Specifically, the cloud management platform is installed on the cloud server and communicates bidirectionally with the edge intelligent unit. The cloud management platform is used to receive real-time business status operation data and historical data uploaded by the edge intelligent unit. After the data is aggregated and processed, an ideal energy consumption trajectory twin model is constructed. Based on the continuously aggregated multi-source data, the ideal energy consumption trajectory twin model is dynamically evolved, so that the ideal energy consumption trajectory twin model can be continuously updated and improved with the long-term accumulation of business status, environmental changes and operating rules. Meanwhile, the cloud management platform is also configured to perform cross-regional spatiotemporal consistency verification on the ideal energy consumption trajectory twin model or on the data, so as to improve the comparability and consistency of the model and data in different regions and at different time scales. On this basis, it performs forward-looking energy consumption scheduling to form predictions and scheduling decisions on subsequent energy consumption trends. Finally, the updated ideal energy consumption trajectory twin model is distributed to the model library for edge intelligent units to call, thereby forming a closed-loop collaborative mechanism of cloud-based model construction and evolution, real-time comparison and localized intervention at the edge, improving the accuracy of anomaly identification and the effectiveness of energy-saving management.

[0035] The power generation unit includes a housing for installation and protection, the housing comprising a stainless steel plate and having wiring holes; The solar cells are mounted on the outer surface of the casing so that the casing provides a mounting base for the solar cells while also forming a shading device.

[0036] Specifically, the power generation device includes a housing for installation and protection. The housing is made of stainless steel plate with several through holes on the upper surface. These through holes are used for the wind turbine generator wires and the internal power wires of the device to pass through and lead out, thereby realizing the electrical connection between the internal components of the housing and the external load end and facilitating the orderly layout of the power supply. At the same time, the solar cells are mounted on the outer surface of the housing, so that the housing provides a mounting base and protective support for the solar cells while also forming a sunshade device. When installed in micro-space locations such as building doors and windows, building eaves, and the outside of equipment, it can provide sunshade for the shaded areas. Based on the structural support and protection provided by the housing for the solar cells, it realizes the combined utilization of photovoltaic power generation and sunshade functions, thereby improving the device's scene adaptability and comprehensive use value.

[0037] The power generation device is suitable for installation in micro-space locations within buildings and their ancillary facilities.

[0038] Specifically, the power generation device is suitable for installation in micro-space locations within buildings and their ancillary facilities. These micro-space locations include one or more of the following: building eaves, building doors and windows, air conditioner outdoor unit installation locations, central air conditioner outdoor unit installation locations, solar water heater installation locations, outdoor acrylic billboard installation locations, LED display screen installation locations, 5G signal tower installation locations, lighting spotlight installation locations, traffic signal light installation locations, and station display screen and outdoor monitoring installation locations. During installation, the power generation device can be supported by a galvanized steel support body and fixed to the corresponding mounting surface using self-tapping screws, expansion screws, clips, nails, or rivets. The specific fixing locations and quantities are determined based on the site structural conditions. This allows the device to utilize the eaves, doors and windows, and surrounding space of various outdoor equipment to complete the deployment of wind and solar power generation components and shells without occupying a large area of ​​roof space, achieving on-site power generation and supply, and improving the applicability and installation convenience of multi-scenario deployment.

[0039] Example 1 The power generation unit is installed in a usable micro-space area outside or above the installation location of the central air conditioning outdoor unit, so that the casing provides a mounting base for the solar cells while also forming a sunshade. The main frame of the power generation unit is made of galvanized steel. When fixing the frame to the on-site mounting surface, self-tapping screws, expansion screws, clips, bolts, or rivets are used for fixation. The specific fixing positions and quantities are determined based on the surrounding structural conditions of the outdoor unit. The unit's power supply is led out through the wiring holes in the casing, and after being organized by the wiring mechanism, it is connected to the energy storage and power consumption terminals, prioritizing power supply to the on-site terminal equipment related to the outdoor unit. Through this installation method, clean energy can be generated and consumed locally using the micro-space around the outdoor unit without occupying additional roof area. At the same time, the casing forming a sunshade helps reduce the impact of direct sunlight heat load on the outdoor unit, improving the adaptability of the scenario and the overall use value.

[0040] Example 2 The power generation device is installed in the micro-spaces outside building doors and windows. Solar cells are mounted on the outer surface of the casing, forming a sunshade to protect the door and window area from the sun while simultaneously generating photovoltaic power. The main frame of the power generation device is constructed of galvanized steel and is fixed to the wall, window frame structure, or load-bearing structure above the door and window using self-tapping screws, expansion bolts, clips, nails, or rivets. The location and number of fixing points are determined based on the site's load-bearing conditions. The electricity generated by the device, after being managed by a wind-solar hybrid controller and energy storage system, can supply power to on-site terminal equipment around the doors and windows, such as access control, lighting, and monitoring systems. This scenario demonstrates the refined utilization of micro-space resources around doors and windows, combining power generation and sunshade functions to improve both micro-space utilization and the convenience and reliability of power supply to on-site terminal equipment.

[0041] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A power generation device based on artificial intelligence, characterized in that, include: At least one power generation system, the power generation system including solar cells, solar tracking control system, charge and discharge control, wind-solar hybrid controller, unloader, battery pack, off-grid inverter, DC load and AC load; The solar cells are used for photovoltaic power generation, the wind-solar hybrid controller is used for controlling and distributing energy from the wind and solar power generation, and the off-grid inverter is used to supply power to the AC load. A micro wind turbine generator set includes a wind turbine, a drum, a main shaft, a gearbox, a speed increaser, a low-speed shaft, a generator, a coupling, a brake, a power electronic system, and a speed control device, used to convert wind energy into electrical energy and connect it to the wind-solar hybrid controller; A lithium-ion energy storage battery is used to store the electrical energy generated by the power generation system and supply power to the terminal electrical equipment on the field side. A cable management mechanism is installed at the cable source inlet and outlet of the power generation device for managing and limiting the cables inside the power generation device. The intelligent integrated components, including smart meters and remote smart sensors, are used to collect real-time business status operation data of field-side application terminals and send it to the edge intelligent unit; The edge intelligence unit is communicatively connected to the intelligent integration component. It is used to classify, label, process, calculate, identify and correct the real-time business status operation data and store it in the model library. It also compares the ideal energy consumption trajectory twin model in the model library with the real-time data on the field side, calculates the deviation and implements localized intervention strategies. The cloud management platform, installed on the cloud server, communicates bidirectionally with the edge intelligent unit via network. It is used to receive data uploaded by the edge intelligent unit, construct the ideal energy consumption trajectory twin model, and distribute the ideal energy consumption trajectory twin model to the model library for the edge intelligent unit to call.

2. The artificial intelligence-based power generation device according to claim 1, characterized in that, The wind-solar hybrid controller is configured to enable the solar cells and the micro wind turbine generator to operate in a wind-solar hybrid mode, specifically including: At night or on cloudy days, the micro wind turbine generators will generate electricity preferentially. On sunny days, the solar cells generate electricity preferentially. When there is wind and sunlight, the micro wind turbine generator and the solar cell generate electricity simultaneously. When the power generation of the power generation device is greater than the power consumption of the DC load and the AC load, the excess electrical energy is converted into DC and stored in the lithium-ion energy storage battery.

3. The artificial intelligence-based power generation device according to claim 1, characterized in that, The cable management mechanism includes a fixed block, a rotating rod rotatably connected to the fixed block, an arc-shaped groove disposed on the rotating rod, a slider slidably engaged with the arc-shaped groove, a connecting block connected to the slider, and a support rod connected to the connecting block and used to adjust the cable spacing. The cable management mechanism further includes a limiting component for limiting the angle of the rotating rod and a tightening component for tightening the cable.

4. The artificial intelligence-based power generation device according to claim 3, characterized in that, The limiting assembly includes a ratchet, a pawl that engages with the ratchet, a spring and a spring plate for keeping the pawl engaged with the ratchet, and a paddle for driving the pawl to disengage from the ratchet, thereby limiting the rotation angle of the rotating rod and preventing reverse rotation.

5. The artificial intelligence-based power generation device according to claim 3, characterized in that, The tightening component is disposed at the arc-shaped groove, and the tightening component is used to press and fix the cable passing through the arc-shaped groove, so that the cable is kept in a limited state within the arc-shaped groove.

6. The artificial intelligence-based power generation device according to claim 1, characterized in that, The edge intelligent unit is configured to perform load decomposition on the field-side data collected by the smart energy meter and remote smart sensor based on a non-intrusive load monitoring algorithm, so as to identify the operating status of the main back-end equipment and determine the current business status, and accordingly call the ideal energy consumption trajectory twin model in the model library corresponding to the business status.

7. The artificial intelligence-based power generation device according to claim 1, characterized in that, The edge intelligence unit includes: The energy consumption partial density is calculated by comparing the real-time energy consumption trajectory of the field side under the current business state with the ideal energy consumption trajectory corresponding to the ideal energy consumption trajectory twin model after dynamic time normalization. When the energy consumption density meets the preset threshold condition, a localized intervention strategy is output, and when the emergency conditions are abnormally met, an emergency power outage physical shutdown is triggered.

8. The artificial intelligence-based power generation device according to claim 1, characterized in that, The cloud management platform includes: The system receives real-time business status operation data and historical data uploaded by the edge intelligence unit, aggregates and processes the data to construct the ideal energy consumption trajectory twin model, and dynamically evolves the ideal energy consumption trajectory twin model. The cloud management platform is also configured to perform cross-regional spatiotemporal consistency verification and forward-looking energy consumption scheduling on the ideal energy consumption trajectory twin model or the data, and to distribute the updated ideal energy consumption trajectory twin model to the model library for the edge intelligent unit to call.

9. A power generation device based on artificial intelligence according to claim 1, characterized in that, The power generation device includes a housing for installation and protection, the housing comprising a stainless steel plate and having through holes; The solar cell is mounted on the outer surface of the housing, so that the housing provides a mounting base for the solar cell while also forming a shading device.

10. A power generation device based on artificial intelligence according to claim 1, characterized in that, The power generation device is suitable for installation in micro-space locations within buildings and their ancillary facilities.

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