New energy integrated power construction intelligent power supply system

Abstract

The invention discloses a new energy integrated intelligent power supply system for power construction. A solar photovoltaic panel and a wind driven generator are integrated to realize wind-solar complementary power generation, and a lithium battery pack and a hydrogen fuel cell are configured to form a dual-redundancy energy storage system. The system realizes real-time monitoring and intelligent scheduling of energy production and consumption through a multi-core heterogeneous processor carried by the central controller. The photovoltaic panel adopts a sun position tracking bracket, the fan is provided with variable pitch blades, and the power generation efficiency is improved by matching with the maximum power point tracking technology; the energy storage module uses a modularized lithium battery pack and active equalization management to guarantee power supply stability; the power output interface is integrated with multiple electrical protection and electric energy optimization circuits. The system realizes remote monitoring and fault diagnosis through the Internet of Things, and combines an edge computing AI prediction unit with a federal learning framework. The system significantly improves the construction power supply reliability, reduces the traditional energy dependence, and achieves the green construction target.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy power integration and intelligent power supply, and in particular to a new energy integrated power construction intelligent power supply system. BACKGROUND

[0002] The current temporary power supply in the field of power construction mainly relies on diesel generators or traditional grid access, and these two methods have obvious shortcomings in environmental protection, economy and flexibility. With the development of new energy technology, renewable energy such as solar energy and wind energy is gradually increasing in the application of power supply, but the integration and intelligent application in the construction field is still in its infancy. The existing new energy power supply system often has low energy conversion efficiency, poor system stability, and difficulty in adapting to complex construction environment.

[0003] The common power supply scheme currently used in power construction includes diesel generator power supply, which has the advantages of flexible deployment and stable output power, but has the disadvantages of high noise, serious pollution and high fuel transportation cost; grid direct access power supply, which has the advantages of stable and reliable power supply, but often cannot be realized in remote areas or temporary construction sites; single new energy power supply system, such as solar photovoltaic system, which is environmentally friendly but greatly affected by weather, difficult to meet the demand for continuous power supply, and cannot meet the working requirements of new energy power integration and intelligent power supply. Therefore, a new energy integrated power construction intelligent power supply system is proposed. SUMMARY

[0004] The present application provides the following technical scheme: a new energy integrated power construction intelligent power supply system, comprising: a new energy power generation module, an energy storage module, an intelligent control module and a power output module, the new energy power generation module being connected to the energy storage module through a transmission line, the intelligent control module being electrically connected to the new energy power generation module, the energy storage module and the power output module, and the power output module being electrically connected to the energy storage module; The new energy power generation module includes a solar photovoltaic panel and a wind turbine, and is used to convert light energy and wind energy into electrical energy through the solar photovoltaic panel and the wind turbine. The solar photovoltaic panel and the wind turbine are organically combined to realize wind-solar complementary power generation, which can fully utilize the light and wind resources in the construction area. The energy storage module is composed of a lithium battery pack, and is used to store the electrical energy output by the new energy power generation module through the lithium battery pack; The intelligent control module includes a central controller and a sensor group, which is used to monitor energy production and electricity demand in real time through the central controller and the sensor, and optimize energy distribution. Through real-time monitoring of energy production and electricity demand by the intelligent control module, the energy distribution strategy is dynamically adjusted to ensure efficient use of the electrical energy output by the new energy power generation module, achieving efficient integration and intelligent scheduling of new energy. The energy storage module uses lithium batteries, which can store the electrical energy output by the new energy power generation module and release it steadily when needed. The power output module includes an AC output interface and a DC output interface, which is used to provide stable power according to the needs of construction equipment. The hydrogen fuel cell backup power module is connected to the energy storage module through a switching circuit, which is used to supplement electrical energy when the new energy power generation module is insufficient. The hydrogen fuel cell backup power module can supplement electrical energy in time when the new energy power generation module is insufficient, ensuring that the power output module can continuously and stably provide power for construction equipment. This dual-power backup mechanism significantly improves the stability and continuity of the power supply system. The intelligent control module is integrated with an Internet of Things communication module, which is used to realize remote monitoring of system operation status and fault diagnosis through wireless networks. The intelligent control module is connected to a construction equipment energy consumption feedback module through an RFID identifier and an energy consumption meter. The intelligent control module is internally provided with an edge computing AI prediction unit. Through RFID identification and energy consumption meters, the construction equipment energy consumption feedback module can classify and upload equipment energy consumption data to the management platform, assisting in optimizing electricity consumption strategies. The edge computing AI prediction unit adjusts system parameters in advance based on prediction data to improve energy supply-demand matching. Multiple intelligent control methods work together to effectively improve energy utilization efficiency and reduce unnecessary energy waste.

[0005] Preferably, the solar photovoltaic panel adopts an adjustable angle tracking support structure, and the intelligent control module is internally provided with a sun position algorithm. The tracking support structure adjusts the orientation of the photovoltaic panel in real time to maximize light energy capture efficiency through the sun position algorithm. The wind turbine is internally provided with a variable pitch control blade, which is used to automatically adjust the blade angle according to the feedback data of the wind speed sensor. The power output ends of the solar photovoltaic panel and the wind turbine are both configured with maximum power point tracking controllers. By tracking the sun position and automatically adjusting the blade angle in real time, the wind and solar energy capture efficiency is maximized, and the power generation capacity is improved.

[0006] Preferably, the lithium battery pack of the energy storage module adopts a modular design, each battery cell of the lithium battery pack is equipped with an independent battery management system, the independent battery management system communicates with the intelligent control module through a CAN bus, the battery box of the battery cell is internally provided with an active balancing circuit, and the box of each battery cell of the lithium battery pack is filled with a phase change material. Through the modular battery management combined with the active balancing technology, the service life of the energy storage unit is prolonged, and the power supply stability is ensured.

[0007] Preferably, the central controller of the intelligent control module is internally provided with a multi-core heterogeneous processor, the multi-core heterogeneous processor includes an ARM Cortex-A series application core and an ARM Cortex-M series real-time core, the application core runs an energy management operating system based on FreeRTOS, the real-time core performs high-speed data acquisition and closed-loop control tasks, the sensor group includes an environmental temperature and humidity sensor, a Hall current sensor, a voltage transformer and an insulation monitoring unit, all sensor units in the sensor group are aggregated to the central controller through SPI / I2C buses, and real-time monitoring and accurate scheduling are realized through the dual-core processor, so that the system response speed and control accuracy are improved.

[0008] Preferably, each alternating current port of the alternating current output interface of the power output module is configured with an independent circuit breaker and a leakage protection device, the direct current output interface adopts a synchronous rectification technology to convert the voltage of the lithium battery pack into a voltage level suitable for equipment, and the output port of the direct current output interface is integrated with a power factor correction circuit. Through the combination of independent protection devices and synchronous rectification technology, the safety of electricity use is ensured and the interface energy consumption loss is reduced.

[0009] Preferably, the hydrogen fuel cell backup power module includes a hydrogen storage tank, a fuel cell stack and a power conversion device, the hydrogen storage tank adopts a type IV carbon fiber winding hydrogen storage bottle, is provided with a temperature and pressure double parameter safety valve and a hydrogen concentration sensor, the fuel cell stack adopts a proton exchange membrane technology, and the power conversion device includes a bidirectional DC / DC converter. Through the design of high-pressure hydrogen storage and intelligent power conversion, a second-level backup power supply response is realized, and the system redundancy is enhanced.

[0010] Preferably, the Internet of Things communication module is internally integrated with a 5G module and a LoRa module, the 5G module is used for high-definition video stream and large data packet transmission with a remote monitoring center, the LoRa module is used for constructing a self-organizing network of devices in a construction area, and the Internet of Things communication module is internally provided with an eSIM card. Through the cooperation of remote high-definition monitoring and local self-organizing network, the data transmission efficiency and system communication reliability are ensured.

[0011] Preferably, the energy consumption meter of the construction equipment energy consumption feedback module is internally integrated with a current transformer and a voltage sampling circuit, the construction equipment energy consumption feedback module is internally provided with a Fourier transform algorithm, the feedback data of the construction equipment energy consumption feedback module is processed by the edge computing AI prediction unit to generate a device energy consumption portrait and an abnormal power consumption mode early warning, and through real-time energy consumption portrait generation and abnormal early warning, the construction equipment energy consumption feedback module helps the fine management of construction equipment energy.

[0012] Preferably, the edge computing AI prediction unit is internally provided with a lightweight convolutional neural network architecture, the input layer of the convolutional neural network architecture receives sensor data, device feedback data and weather forecast information, the hidden layer of the convolutional neural network architecture identifies the power consumption load mode through a feature extraction network, and the output layer generates a future 24-hour energy demand curve and a power generation prediction value, the model training of the edge computing AI prediction unit adopts a federated learning framework, and through the combination of edge-end accurate prediction and cloud-end model optimization, the intelligent level of energy dispatching is improved.

[0013] Preferably, the new energy power generation module, the energy storage module and the intelligent control module are connected through standardized quick plug electrical interfaces and mechanical interfaces, and the connection lines of the new energy power generation module, the energy storage module and the intelligent control module are provided with anti-misplug marks and waterproof joints, so that the construction process is simplified and the human operation risk is reduced through the modularization quick deployment and the waterproof and anti-misplug design.

[0014] In summary, compared with the prior art, the present application provides a new energy integrated power construction intelligent power supply system, which has the following advantages: 1、The solar photovoltaic panel and the wind turbine are organically combined, the wind-solar complementary power generation is realized, the light and wind resources in the construction area can be fully utilized, the intelligent control module dynamically adjusts the energy distribution strategy by real-time monitoring of energy production and power demand, ensures that the electric energy output by the new energy power generation module is efficiently utilized, realizes efficient integration and intelligent scheduling of new energy, the energy storage module adopts lithium battery packs, can store the electric energy output by the new energy power generation module, and release stably when needed, at the same time, the hydrogen fuel cell backup power module can supplement electric energy in time when the new energy power generation module is insufficient, ensures that the power output module can continuously and stably provide power for the construction equipment, and this dual-power guarantee mechanism significantly improves the stability and continuity of the power supply system; 2、The present application takes clean energy as the main energy source, significantly reduces the consumption of fossil fuels and the emission of greenhouse gases, is conducive to reducing environmental pollution, and reduces the operating cost of the system through the optimized scheduling of the intelligent control module and the efficient use of energy, meets the requirements of green construction, and the intelligent control module dynamically adjusts the energy distribution strategy by real-time monitoring and analysis of the energy consumption of the construction equipment, combined with the output characteristics of the new energy generation module, to ensure that the electric energy is reasonably distributed and efficiently used. This intelligent control not only improves the energy utilization efficiency, but also effectively reduces energy waste. The construction equipment energy consumption feedback module can classify and upload the energy consumption data of each device to the management platform through RFID identification and energy consumption meters to assist in optimizing the power utilization strategy. The edge computing AI prediction unit adjusts the system parameters in advance based on the prediction data to improve the energy supply-demand matching degree. Multiple intelligent control methods work together to effectively improve the energy utilization efficiency and reduce unnecessary energy waste. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a system architecture diagram of the present application. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0017] Please refer to Figure 1 The present application provides a technical solution, a new energy integrated power construction intelligent power supply system, comprising: A new energy generation module, an energy storage module, an intelligent control module and a power output module, the new energy generation module is connected with the energy storage module through a transmission line, the intelligent control module is electrically connected with the new energy generation module, the energy storage module and the power output module, and the power output module is electrically connected with the energy storage module. The new energy generation module comprises a solar photovoltaic panel and a wind turbine, and is used for converting light energy and wind energy into electric energy through the solar photovoltaic panel and the wind turbine. The solar photovoltaic panel adopts an adjustable angle tracking support structure, and the intelligent control module is internally provided with a sun position algorithm. The tracking support structure adjusts the direction of the photovoltaic panel in real time through the sun position algorithm to maximize the light energy capture efficiency. The wind turbine is internally provided with a variable pitch control blade, which is used for automatically adjusting the blade angle according to the feedback data of the wind speed sensor. The power output ends of the solar photovoltaic panel and the wind turbine are both provided with a maximum power point tracking controller. The solar photovoltaic panel adopts an adjustable angle tracking support structure, which realizes the rotation of the photovoltaic panel in the horizontal and vertical directions through a motor drive device. The solar position algorithm built-in the intelligent control module calculates the real-time azimuth and altitude angle of the sun in the sky according to the current time, geographical location and astronomical calendar data. The control module converts the calculation results into specific rotation instructions and sends them to the drive motor of the tracking support through the communication line. The drive motor accurately adjusts the inclination angle and orientation of the photovoltaic panel according to the instructions, ensuring that the surface of the photovoltaic panel is always perpendicular to the sunlight, thereby maximizing the reception of solar radiation. During the entire period from sunrise to sunset, the adjustment process will continue, forming a closed-loop control, so that the photovoltaic panel always works in the best light receiving state; The wind turbine is equipped with a variable pitch control blade system inside, which realizes dynamic adjustment of the blade angle of attack through a precise mechanical structure. The wind speed sensor installed at the root of the blade monitors the incoming wind speed in real time and converts the wind speed signal into an electrical signal transmitted to the intelligent control module. The algorithm built-in the control module filters the wind speed data, combined with the generator speed and output power parameters, to calculate the optimal blade angle of attack under the current working condition. The control instruction drives the variable pitch bearing inside the blade through the actuator, so that the blade rotates around its longitudinal axis to change the angle of attack of the airflow on the blade. Under low wind speed conditions, the blade is adjusted to a larger angle of attack to increase lift; under high wind speed or gust conditions, the blade automatically reduces the angle of attack to limit power output and prevent the generator from overloading. This dynamic adjustment mechanism ensures that the wind turbine can maintain optimal aerodynamic performance under different wind conditions; The power output ends of the solar photovoltaic panel and the wind turbine are both configured with a maximum power point tracking controller. The controller uses control strategies such as perturbation and observation or incremental conductance, and monitors the output voltage and current of the power generation equipment in real time through a high-frequency sampling circuit. The comparator built-in the controller compares the output power of the current working point with the historical power to determine the power trend. When a power drop is detected, the controller adjusts the working voltage of the power generation equipment through the power conversion circuit to force it to deviate from the current working point. After multiple iterative adjustments, the system eventually stabilizes at the maximum power output state. For photovoltaic power generation systems, this controller can compensate for the effects of changes in environmental temperature and light intensity; for wind power generation systems, it can match the variable pitch control and generator speed to ensure that the wind energy conversion efficiency is always in the optimal range. The controllers of the two power generation units communicate with the intelligent control module through the bus to realize the coordinated optimization of the system's power generation power; The energy storage module is composed of lithium battery packs, and is used for storing the electric energy output by the new energy power generation module through the lithium battery packs. The lithium battery packs of the energy storage module adopt a modular design, each battery cell of the lithium battery packs is equipped with an independent battery management system, the independent battery management system communicates with the intelligent control module through a CAN bus, and the battery box of each battery cell is internally provided with an active balancing circuit. The box body of each battery cell of the lithium battery pack is filled with a phase change material; The intelligent control module includes a central controller and a sensor group. The intelligent control module is used for monitoring energy production and electricity demand in real time through the central controller and the sensors, and optimizing energy distribution. The central controller of the intelligent control module is internally provided with a multi-core heterogeneous processor. The multi-core heterogeneous processor includes an ARM Cortex-A series application core and an ARM Cortex-M series real-time core. The application core runs an energy management operating system based on FreeRTOS. The real-time core performs high-speed data acquisition and closed-loop control tasks. The sensor group includes an environment temperature and humidity sensor, a Hall current sensor, a voltage transformer and an insulation monitoring unit. All sensor units in the sensor group are aggregated to the central controller through SPI / I2C buses. The intelligent control module is the core decision unit of the new energy integrated power construction intelligent power supply system. Through the cooperative work of the central controller and the sensor group, a complete closed loop of data acquisition, state monitoring, demand prediction and energy optimization is constructed. The central controller adopts a multi-core heterogeneous processor architecture, integrates an ARM Cortex-A series application core and an ARM Cortex-M series real-time core, and forms a dual-core cooperation mechanism. The application core carries an energy management platform based on the FreeRTOS real-time operating system, and is responsible for upper layer strategy calculation and cross-module cooperation. The real-time core focuses on millisecond-level data acquisition and closed-loop control, and ensures the real-time performance of system response; The sensor group is composed of multiple types of sensing units, forming a three-dimensional monitoring network. The environment temperature and humidity sensor is deployed inside and outside the equipment cabin, and real-time acquisition of environmental parameters is realized through a thermistor and a capacitive humidity sensor, to provide basic data for system thermal management. The Hall current sensor is connected in series in the power generation, energy storage and power consumption circuits, and the current value is measured by using the Hall effect non-contact measurement, to synchronously monitor the output power of the new energy power generation module, the charge and discharge current of the energy storage module and the load condition of the power consumption equipment. The voltage transformer converts high voltage into a measurable low voltage signal in proportion by using the electromagnetic induction principle, to real-time track the DC bus voltage fluctuation and AC output stability. The insulation monitoring unit continuously detects the system ground insulation resistance by using the balance bridge method, and triggers a warning mechanism when the insulation performance decreases; All sensor units achieve data aggregation through SPI / I2C bus. The real-time core cycles through each sensor node at a microsecond level to obtain raw monitoring data and then pre-processes the data. The application core obtains the pre-processed data through a shared memory mechanism, combines the short-term load prediction results generated by the edge computing AI prediction unit, and runs a multi-objective optimization algorithm. The algorithm considers factors such as new energy generation prediction value, remaining capacity of energy storage module, priority of construction equipment power consumption, and hydrogen fuel cell backup power supply start threshold to generate a dynamic energy distribution strategy. At the control instruction execution level, the real-time core converts the optimization decision into specific PWM pulse signals or digital output. For the new energy generation module, the reference voltage of the maximum power point tracking controller is adjusted to realize coordinated power generation control of the photovoltaic panel and the fan. For the energy storage module, equalization charging instructions or discharge enable signals are sent to maintain the optimal working state of the lithium battery pack. For the power consumption side, the duty cycle of the synchronous rectification circuit of the DC output interface is adjusted to accurately control the output voltage level, and the compensation parameters of the power factor correction circuit are dynamically adjusted according to the load characteristics. During system operation, the central controller continuously monitors the working state of the sensor group. When data anomalies or communication interruptions are detected, the redundant sensor switching mechanism is immediately started to ensure the continuity of monitoring data. The application core regularly uploads key operation logs to the cloud through the Internet of Things communication module and matches fault modes with the expert knowledge base of the remote monitoring center. For temporary power demand mutations, the system updates the load prediction model parameters in real time through the online learning mechanism of the edge computing AI prediction unit, enabling the energy distribution strategy to have self-adaptive adjustment capability. This hardware and software collaborative control architecture enables the intelligent control module to continuously maintain the dynamic balance between energy production and consumption in complex and variable construction environments. The power output module includes an AC output interface and a DC output interface. The power output module is used to provide stable power according to the needs of construction equipment. Each AC port of the AC output interface of the power output module is configured with an independent circuit breaker and a leakage protection device. The DC output interface uses synchronous rectification technology to convert the voltage of the lithium battery pack into a voltage level suitable for equipment. The output port of the DC output interface integrates a power factor correction circuit. The hydrogen fuel cell backup power supply module is connected to the energy storage module through a switching circuit. The hydrogen fuel cell backup power supply module is used to supplement power when the new energy generation module is insufficient. The hydrogen fuel cell backup power supply module includes a hydrogen storage tank, a fuel cell stack, and a power conversion device. The hydrogen storage tank uses a type IV carbon fiber winding hydrogen storage bottle and is equipped with a temperature and pressure dual-parameter safety valve and a hydrogen concentration sensor. The fuel cell stack uses proton exchange membrane technology. The power conversion device includes a bidirectional DC / DC converter. The intelligent control module is internally integrated with an Internet of Things communication module, which is used to realize remote monitoring of the running state and fault diagnosis of the system through a wireless network. The Internet of Things communication module is internally integrated with a 5G module and a LoRa module. The 5G module is used to transmit high-definition video streams and large data packets with the remote monitoring center. The LoRa module is used to build a self-organizing network of devices in the construction area. The Internet of Things communication module is internally provided with an eSIM card. The intelligent control module is connected with a construction equipment energy consumption feedback module through an RFID identifier and an energy consumption meter. The intelligent control module is internally provided with an edge computing AI prediction unit. The energy consumption meter of the construction equipment energy consumption feedback module is internally integrated with a current transformer and a voltage sampling circuit. The construction equipment energy consumption feedback module is internally provided with a Fourier transform algorithm. After the feedback data of the construction equipment energy consumption feedback module is processed by the edge computing AI prediction unit, a device energy consumption portrait and an abnormal power consumption mode early warning are generated. The edge computing AI prediction unit is internally provided with a lightweight convolutional neural network architecture. The input layer of the convolutional neural network architecture receives sensor data, device feedback data and weather forecast information. The hidden layer of the convolutional neural network architecture identifies the power consumption load mode through a feature extraction network. The output layer generates a 24-hour energy demand curve and a power generation prediction value. The model training of the edge computing AI prediction unit adopts a federated learning framework. The intelligent control module builds a closed-loop monitoring system for the energy consumption of construction equipment through an RFID identifier and an energy consumption meter. When the construction equipment is connected to the power output module, the RFID identifier first reads the device electronic tag information through a radio frequency signal, and analyzes the basic data such as device type, rated power and historical energy consumption record. This identification process adopts an anti-collision algorithm, which can handle multiple device access scenarios at the same time, ensuring the real-time and accuracy of device identity recognition. The energy consumption meter realizes double-parameter synchronous acquisition through a current transformer and a voltage sampling circuit. The current transformer adopts a toroidal core structure, which uses electromagnetic induction principle to convert the device working current into a measurable secondary current signal in proportion. The voltage sampling circuit obtains the device input voltage through a resistance voltage dividing network, and realizes accurate measurement under non-sinusoidal waveform by combining a true RMS conversion chip. After the two groups of analog signals are removed by a low-pass filter, they are synchronously sampled by an analog-to-digital converter to form a digitized current-voltage time series. The Fourier transform algorithm performs frequency spectrum analysis on the sampling data. The algorithm decomposes the time domain signal into fundamental wave and harmonic components, and calculates the total harmonic distortion and power factor. By comparing the real-time frequency spectrum with the device standard spectrum template, the load change characteristics of motor-type devices can be identified. The processed data includes effective power, reactive power, cumulative power and harmonic content parameters. These characteristic quantities are transmitted to the edge computing AI prediction unit of the intelligent control module through an encrypted channel. The edge computing AI prediction unit adopts a lightweight convolutional neural network architecture. The input layer receives three types of data: the first type is environmental parameters such as temperature and humidity, light intensity, etc. collected by the sensor group; the second type is device power characteristics output by the energy consumption meter; the third type is weather forecast information obtained through the Internet of Things communication module. The data needs to be normalized before input to eliminate the influence of dimension difference on model training. The hidden layer is composed of multiple convolution modules, each module includes a depth separable convolution layer, a batch normalization layer and an activation function layer, which captures the time series pattern and periodicity of the power load through a feature extraction network; The model output layer generates two core prediction results: the future 24-hour energy demand curve adopts time series prediction method to depict the power demand change with 15-minute granularity; the power generation prediction value combines the real-time output of the new energy generation module and the weather prediction data to evaluate the potential supply capacity of wind and solar power generation. When the predicted electricity demand exceeds the supply capacity, the system automatically triggers the start-up prediction mechanism of the hydrogen fuel cell backup power supply; The model training adopts a federated learning framework to realize distributed collaborative optimization. The local model parameters of each construction system are uploaded to the cloud aggregation server after homomorphic encryption, the server executes a secure aggregation algorithm to generate global model updates, and then distributes them to each edge node to complete model iteration. This training method fully utilizes multi-scenario data to improve model generalization capability while ensuring data privacy. When the device power mode deviates from the normal profile, the system generates a three-level abnormal warning signal by comparing historical behavior characteristics with real-time data distribution, and pushes it to the mobile terminal of the field engineer through the Internet of Things communication module, forming a preventive maintenance response mechanism; The new energy generation module, energy storage module and intelligent control module are connected through standardized quick plug electrical interfaces and mechanical interfaces, and the connection harness of the new energy generation module, energy storage module and intelligent control module is provided with a mistaken insertion prevention mark and a waterproof connector.

[0018] The present scheme realizes wind-solar complementary power generation by organically combining solar photovoltaic panels with wind turbines. The intelligent control module dynamically adjusts energy distribution strategies by real-time monitoring of energy production and power demand, ensuring efficient use of the power output by the new energy generation module, realizing efficient integration and intelligent scheduling of new energy, and the energy storage module adopts lithium battery packs to store the power output by the new energy generation module and release it stably when needed. At the same time, the hydrogen fuel cell backup power supply module can supplement power in time when the new energy generation module is insufficient, ensuring that the power output module can continuously and stably provide power for construction equipment. This dual power supply mechanism significantly improves the stability and continuity of the power supply system.

[0019] The scheme takes clean energy as the main energy source, significantly reduces the consumption of fossil fuels and the emission of greenhouse gases, is conducive to reducing environmental pollution, and at the same time, through the optimization scheduling of the intelligent control module and the efficient use of energy, the operation cost of the system is also reduced, which meets the requirements of green construction, and at the same time, the intelligent control module dynamically adjusts the energy distribution strategy by real-time monitoring and analyzing the energy consumption of the construction equipment, combined with the output characteristics of the new energy generation module, to ensure that the electric energy is reasonably distributed and efficiently used, such intelligent control not only improves the energy utilization efficiency, but also effectively reduces energy waste, and at the same time, the construction equipment energy consumption feedback module can classify and upload the equipment energy consumption data to the management platform through RFID identification and energy consumption meters, to assist in optimizing the power utilization strategy; the edge computing AI prediction unit adjusts the system parameters in advance combined with the prediction data, so that the energy supply and demand matching degree is improved, and multiple intelligent control means jointly act, effectively improving the energy utilization efficiency and reducing unnecessary energy waste.

[0020] It should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device.

[0021] Although the embodiments of the present application have been shown and described, it can be understood by those of ordinary skill in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A new energy integrated power construction intelligent power supply system, characterized in that, Comprise: New energy power generation module, energy storage module, intelligent control module and power output module, the new energy power generation module is connected with the energy storage module through the transmission line, the intelligent control module is connected with the new energy power generation module, energy storage module and power output module respectively, the power output module is connected with the energy storage module; New energy power generation module, including solar photovoltaic panel and wind turbine, the new energy power generation module is used to convert light energy and wind energy into electric energy through solar photovoltaic panel and wind turbine, the energy storage module is composed of lithium battery pack, the energy storage module is used to store the electric energy output by the new energy power generation module through lithium battery pack; Intelligent control module, including central controller and sensor group, the intelligent control module is used to monitor energy production and power demand in real time through central controller and sensor, and optimize energy distribution, the power output module includes AC output interface and DC output interface, the power output module is used to provide stable power according to the demand of construction equipment; Hydrogen fuel cell backup power module is connected with the energy storage module through the switching circuit, the hydrogen fuel cell backup power module is used to supplement electric energy when the new energy power generation module power supply is insufficient, the intelligent control module is integrated with the internet of things communication module, the internet of things communication module is used to realize remote monitoring system running state and fault diagnosis through wireless network, the intelligent control module is connected with construction equipment energy consumption feedback module through RFID identifier and energy consumption meter, the intelligent control module is internally provided with edge computing AI prediction unit.

2. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The solar photovoltaic panel adopts adjustable angle tracking support structure, the intelligent control module is built-in solar position algorithm, the tracking support structure adjusts the photovoltaic panel direction in real time through the solar position algorithm to maximize the light energy capture efficiency, the wind turbine is internally provided with variable pitch control blade, the variable pitch control blade is used to automatically adjust the blade angle according to the wind speed sensor feedback data, the power output end of the solar photovoltaic panel and wind turbine is configured with maximum power point tracking controller.

3. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The lithium battery pack of the energy storage module adopts modular design, each battery unit of the lithium battery pack is equipped with independent battery management system, the independent battery management system communicates with the intelligent control module through CAN bus, the battery box body of the battery unit is internally built-in active equalization circuit, the box body of each battery unit of the lithium battery pack is filled with phase change material.

4. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The central controller of the intelligent control module is internally provided with a multi-core heterogeneous processor, the multi-core heterogeneous processor includes an ARM Cortex-A series application core and an ARM Cortex-M series real-time core, the application core runs an energy management operating system based on FreeRTOS, the real-time core executes high-speed data acquisition and closed-loop control tasks, the sensor group includes an environmental temperature and humidity sensor, a Hall current sensor, a voltage transformer and an insulation monitoring unit, and all sensor units inside the sensor group are aggregated to the central controller through SPI / I2C buses.

5. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: Each AC port of the AC output interface of the power output module is configured with an independent circuit breaker and a leakage protection device, the DC output interface adopts synchronous rectification technology to convert the voltage of the lithium battery pack into a voltage level suitable for the equipment, and the output port of the DC output interface is integrated with a power factor correction circuit.

6. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The hydrogen fuel cell backup power module includes a hydrogen storage tank, a fuel cell stack and a power conversion device, the hydrogen storage tank adopts a type IV carbon fiber winding hydrogen storage bottle, is provided with a temperature and pressure double-parameter safety valve and a hydrogen concentration sensor, the fuel cell stack adopts a proton exchange membrane technology, and the power conversion device includes a bidirectional DC / DC converter.

7. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The Internet of Things communication module is internally integrated with a 5G module and a LoRa module, the 5G module is used for high-definition video stream and large data packet transmission with a remote monitoring center, the LoRa module is used for constructing a self-organizing network of equipment in a construction area, and the Internet of Things communication module is built-in with an eSIM card.

8. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The energy consumption meter of the construction equipment energy consumption feedback module is internally integrated with a current transformer and a voltage sampling circuit, the construction equipment energy consumption feedback module is internally provided with a Fourier transform algorithm, and after the feedback data of the construction equipment energy consumption feedback module is processed by an edge computing AI prediction unit, a device energy consumption portrait and an abnormal power consumption mode early warning are generated.

9. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The edge computing AI prediction unit is internally provided with a lightweight convolutional neural network architecture, an input layer of the convolutional neural network architecture receives sensor data, device feedback data and weather forecast information, a hidden layer of the convolutional neural network architecture identifies a power consumption load mode through a feature extraction network, an output layer generates a future 24-hour energy demand curve and a power generation prediction value, and model training of the edge computing AI prediction unit adopts a federated learning framework.

10. The intelligent power supply system for new energy integrated power construction according to claim 1, characterized in that: The new energy power generation module, the energy storage module and the intelligent control module are connected through standardized quick plug electrical interfaces and mechanical interfaces, and the connection harnesses of the new energy power generation module, the energy storage module and the intelligent control module are provided with anti-misplug marks and waterproof joints.

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