Remote power supply and energy management system and method based on high power laser

Abstract

The present application provides a remote power supply and energy management system and method based on a high-power laser, which relates to the field of intelligent management technology, including: a loss model construction unit, used to construct a meteorological-related energy loss prediction model; an energy loss analysis unit, used to generate a transmission energy loss index; a back-end power supply duration prediction unit, used to obtain predicted power supply duration information; a meteorological monitoring and analysis unit, used to generate a predicted energy loss index sequence; a loss regression analysis unit, used to locate meteorological loss regression nodes; an energy management unit, used to perform power supply management. This application can solve the technical problem in the prior art that the lack of energy loss analysis during laser transmission leads to large energy loss, thereby affecting power supply efficiency and stability. By analyzing energy loss to perform power supply management, energy management of remote power supply modules can be achieved, achieving the technical effect of reducing energy loss and improving power supply stability.

Description

Technical Field

[0001] The present application relates to the field of intelligent management technology, and in particular to a remote power supply and energy management system and method based on high-power lasers. Background Art

[0002] With the advancement of science and technology, the demand for long-distance power supply and energy management in remote areas and complex environments is increasing. Traditional cable transmission has problems such as high energy loss and high cost, which limits its application scope. The long-distance power supply technology of high-power lasers uses laser beams to transmit light energy and converts it into electrical energy through high-efficiency photocells to achieve long-distance and efficient power supply. This method reduces the dependence on physical lines and has the advantages of low energy loss and strong anti-interference ability. It is suitable for applications in complex terrain and special environments, such as mountains, oceans and space.

[0003] However, long-distance power supply technology is affected by meteorological conditions, and this influence is difficult to avoid. Under severe meteorological conditions, the loss of light energy transmission is particularly large. At this time, long-distance power supply will result in large energy losses.

[0004] In summary, the prior art has a technical problem in that the lack of analysis on energy loss during laser transmission leads to large energy loss, thus affecting power supply efficiency and stability. Summary of the invention

[0005] The purpose of this application is to provide a remote power supply and energy management system and method based on a high-power laser, so as to solve the technical problem in the prior art that the lack of analysis of energy loss during laser transmission leads to large energy loss, thereby affecting the power supply efficiency and stability.

[0006] In view of the above problems, the present application provides a remote power supply and energy management system and method based on high-power lasers.

[0007] In the first aspect, the present application also provides a remote power supply and energy management system based on a high-power laser, including: a loss model construction unit, used to obtain a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and construct a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module; an energy loss analysis unit, used to perform meteorological monitoring of the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and analyze the meteorological monitoring data set through the meteorological-related energy loss prediction model to generate a transmission energy loss index; a back-end power supply duration prediction unit, used to perform meteorological monitoring of the back-end energy storage module when the transmission energy loss index is greater than a preset loss index. Energy storage information collection, predicting the power supply duration of the equipment to be powered by the remote power supply module according to the energy storage information, and obtaining the predicted power supply duration information; a meteorological monitoring and analysis unit, used to extract meteorological forecast information according to the predicted power supply duration information through the meteorological monitoring platform, generate a meteorological forecast time series, input the meteorological associated energy loss prediction model for analysis, and generate a predicted energy loss index sequence; a loss regression analysis unit, used to compare the predicted energy loss index sequence with the preset loss index, and locate the meteorological loss regression node; an energy management unit, used to power the equipment to be powered through the back-end energy storage module, and when the meteorological loss regression node is reached, start the high-power laser to perform remote laser beam emission, and perform power supply management through the DCDC power management circuit.

[0008] In the second aspect, the present application provides a remote power supply and energy management method based on a high-power laser, comprising: obtaining a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and constructing a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module; performing meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and analyzing the meteorological monitoring data set through the meteorological-related energy loss prediction model to generate a transmission energy loss index; when the transmission energy loss index is greater than a preset loss index, storing energy in the back-end energy storage module Information collection, predicting the power supply duration of the equipment to be powered by the remote power supply module according to the energy storage information, and obtaining the predicted power supply duration information; extracting meteorological forecast information according to the predicted power supply duration information through the meteorological monitoring platform, generating a meteorological forecast time series, inputting the meteorological-related energy loss prediction model for analysis, and generating a predicted energy loss index sequence; comparing the predicted energy loss index sequence with the preset loss index, and locating the meteorological loss regression node; supplying power to the equipment to be powered through the back-end energy storage module, and when reaching the meteorological loss regression node, starting the high-power laser for remote laser beam emission, and performing energy management through the DCDC power management circuit.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] A loss model construction unit is used to obtain a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module is constructed; an energy loss analysis unit is used to perform meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and analyze the meteorological monitoring data set through the meteorological-related energy loss prediction model to generate a transmission energy loss index; a back-end power supply duration prediction unit is used to collect energy storage information of the back-end energy storage module when the transmission energy loss index is greater than a preset loss index, and to perform energy storage information on the back-end energy storage module according to the energy storage information. The power supply duration of the equipment to be powered by the remote power supply module is predicted to obtain the predicted power supply duration information; the meteorological monitoring and analysis unit is used to extract meteorological forecast information according to the predicted power supply duration information through the meteorological monitoring platform, generate a meteorological forecast time series, input the meteorological related energy loss prediction model for analysis, and generate a predicted energy loss index sequence; the loss regression analysis unit is used to compare the predicted energy loss index sequence with the preset loss index and locate the meteorological loss regression node; the energy management unit is used to power the equipment to be powered through the back-end energy storage module, start the high-power laser to remotely emit the laser beam when reaching the meteorological loss regression node, and perform power supply management through the DCDC power management circuit. By constructing a meteorological related energy loss prediction model, analyzing the transmission energy loss index, and then locating the meteorological loss regression node, power supply management is performed based on energy loss, and energy management of the remote power supply module is realized, achieving the technical effect of reducing energy loss and improving power supply stability.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0013] Figure 1This is a schematic diagram of the structure of a remote power supply and energy management system based on high-power lasers in this application;

[0014] Figure 2 This is a flow chart of the remote power supply and energy management method based on high-power laser in this application.

[0015] Description of reference numerals:

[0016] A loss model building unit 11, an energy loss analysis unit 12, a back-end power supply duration prediction unit 13, a meteorological monitoring and analysis unit 14, a loss regression analysis unit 15, and an energy management unit 16. DETAILED DESCRIPTION

[0017] This application solves the technical problem in the prior art that the lack of analysis of energy loss during laser transmission leads to large energy loss, which in turn affects power supply efficiency and stability by providing a remote power supply and energy management system and method based on high-power lasers. By constructing a meteorological-related energy loss prediction model, analyzing transmission energy loss indicators, and then locating meteorological loss regression nodes, power supply management is performed based on energy loss, and energy management of remote power supply modules is realized, achieving the technical effect of reducing energy loss and improving power supply stability.

[0018] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0019] For example, please refer to the attached Figure 1 , the present application provides a remote power supply and energy management system based on high-power laser, including:

[0020] The loss model construction unit 11 is used to obtain a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and construct a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module.

[0021] Specifically, the high-power laser is the core part of the entire remote power supply module, that is, the energy source. Responsible for providing the high optical power required for long-distance transmission, the high-power laser can emit a high-intensity laser beam, and by modulating the laser beam, transmit the light energy along a specified path to the remote end, that is, the photoelectric conversion module. The photoelectric conversion module is a photocell, which is used to receive the laser beam from the high-power laser and convert it into electrical energy. The photoelectric conversion module is usually made of high-efficiency semiconductor materials and can efficiently convert the received light energy into electrical energy.

[0022] The converted electric energy first enters the DCDC power management circuit. The main function of the DCDC power management circuit is to stabilize the output voltage to meet the needs of different loads. Through efficient voltage conversion and regulation, the DCDC module can provide a stable and appropriate voltage to ensure the normal operation of subsequent equipment. The back-end energy storage module is used to store the electric energy generated by the photoelectric conversion module. The energy storage module can be a battery or a supercapacitor, which is used to power the load when needed, provide stable energy support, and ensure the continuity and stability of power supply.

[0023] The relevant historical meteorological data and the historical energy loss index transmitted from the high-power laser to the photoelectric conversion module in history are collected through a meteorological station or a remote sensor. The energy loss index is the light energy loss index in the laser beam, that is, the ratio of the light energy received by the photoelectric conversion module to the light energy emitted by the high-power laser, such as atmospheric particulate matter content, gas content, haze state, cloud thickness, temperature and humidity, rain state and snowflake state. When a high-power laser is transmitted in the atmosphere, it will be affected by meteorological conditions, such as clouds, rain and fog, which may cause laser attenuation, thereby reducing the energy reaching the photoelectric conversion module. An energy loss prediction model is constructed using existing data analysis and machine learning algorithms. For example, a meteorological-related energy loss prediction model is constructed using an existing neural network model. The training input of the meteorological-related energy loss prediction model is historical meteorological data, and the output is the predicted laser energy loss index. The output of the meteorological-related energy loss prediction model is supervised and adjusted with the historical energy loss index, thereby training the meteorological-related energy loss prediction model to convergence, providing support for subsequent energy loss analysis.

[0024] The energy loss analysis unit 12 is used to perform meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and to analyze the meteorological monitoring data set through the meteorological-related energy loss prediction model to generate a transmission energy loss index.

[0025] Specifically, the meteorological monitoring platform refers to an existing meteorological forecasting platform, such as a meteorological station, etc. The laser transmission path from the high-power laser to the photoelectric conversion module is determined by professional and technical personnel in this field in combination with actual conditions. A connection with the meteorological monitoring platform is established to perform meteorological monitoring on the laser transmission path, monitor data such as temperature, humidity, wind speed, air pressure, rainfall, and cloud thickness, form a meteorological monitoring data set, and transmit the meteorological monitoring data set to the meteorological-related energy loss prediction model through a wireless or wired network.

[0026] The meteorological-related energy loss prediction model is used to analyze meteorological monitoring data and generate transmission energy loss indicators. Specifically, the meteorological monitoring data set collected by the meteorological monitoring platform is input into the meteorological-related energy loss prediction model. The meteorological-related energy loss prediction model automatically considers the impact of various meteorological factors on laser transmission, such as: weather conditions such as rain and fog will cause the scattering and absorption of laser energy; wind speed and air pressure changes will cause the drift of the laser beam, affecting the energy transmission efficiency, thereby outputting the transmission energy loss indicator and quantifying the energy loss in the laser transmission process under the current meteorological conditions. Real-time meteorological monitoring and energy loss analysis of the laser transmission path are realized, providing data support for subsequent power supply management.

[0027] The back-end power supply duration prediction unit 13 is used to collect energy storage information of the back-end energy storage module when the transmission energy loss index is greater than the preset loss index, and predict the power supply duration of the power supply device of the remote power supply module according to the energy storage information to obtain the predicted power supply duration information.

[0028] Specifically, the preset loss index is a threshold value pre-set by professional and technical personnel in this field based on actual experience, which is used to determine whether the transmission energy loss is within an acceptable range. The real-time monitored transmission energy loss index is compared with the preset loss index. If the transmission energy loss index is greater than the preset loss index, it means that the current energy loss is too large. At this time, the energy storage status of the back-end energy storage module, that is, the amount of electricity currently stored in the back-end energy storage module, is collected in real time through the sensor or monitoring equipment located in the back-end energy storage module.

[0029] The device to be powered refers to the device that needs to be powered by a remote power supply module, such as a sensor module for monitoring the environment located in remote areas and complex environments. The power consumption information of the device to be powered is obtained, including the rated power and actual power consumption of the device, and a power supply duration prediction model is established based on the current amount of power stored in the back-end energy storage module and the power consumption information of the device to be powered. The model can be calculated based on the following formula: the current stored amount of power divided by the actual power consumption. The predicted power supply duration information is obtained, that is, the time that the device to be powered can be continuously powered under the current energy storage state. The accurate prediction of the power supply duration of the device to be powered by the remote power supply module is realized, which is convenient for power supply management in the case of large energy loss.

[0030] The meteorological monitoring and analysis unit 14 is used to extract meteorological forecast information according to the predicted power supply duration information through the meteorological monitoring platform, generate a meteorological forecast time series, input the meteorological associated energy loss prediction model for analysis, and generate a predicted energy loss indicator sequence.

[0031] Specifically, the existing meteorological monitoring platform usually has the ability to predict the weather in the future. It is connected to the meteorological monitoring platform, and the corresponding meteorological information in the future is directly obtained according to the predicted power supply duration information, and the meteorological forecast time series is generated, including parameters such as temperature, humidity, wind speed, air pressure, rainfall and cloud thickness. The meteorological forecast time series is stored in the format of a time series, which contains various meteorological parameters at each time point. The generated meteorological forecast time series data is input into the meteorological-related energy loss prediction model to predict the energy loss at each time point in the future and generate a predicted energy loss indicator sequence. The prediction of future energy loss of the laser transmission path is realized, providing data support for power supply management.

[0032] The loss regression analysis unit 15 is used to compare the predicted energy loss index sequence with the preset loss index and locate the meteorological loss regression node.

[0033] Specifically, the predicted energy loss index sequence is compared with the preset loss index. The preset loss index represents the acceptable range of energy loss under normal meteorological conditions. The predicted energy loss index sequence is the predicted value of energy loss in the future time period generated by the meteorological-related energy loss prediction model to form a time series data set. Each time point of the predicted energy loss index sequence is compared with the preset loss index one by one to determine which time points have predicted energy loss values ​​exceeding the preset loss index. The meteorological loss regression node represents the time point when the energy loss returns to within the preset index after the meteorological conditions change and the energy loss exceeds the preset index. Find the time point when the first predicted energy loss value returns to within the preset loss index, which is the meteorological loss regression node.

[0034] The energy management unit 16 is used to power the device to be powered through the back-end energy storage module, start the high-power laser to perform remote laser beam emission when the meteorological loss return node is reached, and perform power supply management through the DCDC power management circuit.

[0035] Specifically, the back-end energy storage module (such as a battery or supercapacitor) stores electrical energy for temporary power supply to the equipment to be powered when laser transmission is blocked or energy loss is high. During the period when the transmission energy loss index is greater than the preset loss index, the back-end energy storage module starts to supply power to the equipment to be powered to ensure the normal operation of the equipment. At the meteorological loss regression node, the transmission energy loss index meets the preset loss index. At this time, the meteorological conditions have improved, and the energy loss has returned to an acceptable range. The high-power laser is started and the remote laser beam is emitted again. The high-power laser emits a laser beam and transmits energy to the photoelectric conversion module through the atmospheric medium. The DCDC power management circuit is responsible for managing the electrical energy output from the photoelectric conversion module, converting part of the electrical energy into a voltage and current suitable for the equipment to be powered, and transmitting the other part of the electrical energy to the back-end energy storage module, which is quickly released when needed to provide stable energy support.

[0036] Therefore, by real-time monitoring and analysis of meteorological conditions and identifying energy loss regression nodes, continuous power supply under different meteorological conditions is achieved, and the power supply strategy is dynamically adjusted to ensure the stability and efficiency of power supply.

[0037] Furthermore, the loss model building unit 11 in the system is also used for:

[0038] A meteorological correlation factor set is configured, wherein the meteorological correlation factor set includes at least atmospheric particulate matter content, gas content, haze status, cloud thickness, temperature and humidity, rain status and snowflake status; based on the meteorological correlation factor set, a historical laser beam transmission record data set of the remote power supply module is collected; and the meteorological correlation energy loss prediction model is constructed by training the historical laser beam transmission record data set.

[0039] Specifically, a meteorological correlation factor set is configured, which includes at least the following elements: atmospheric particulate matter content (concentration of suspended particulate matter in the air (such as PM2.5 and PM10)), gas content (concentration of gases such as carbon dioxide, oxygen, and nitrogen), haze state (liquid or solid particulate matter suspended in the atmosphere), cloud thickness (thickness of clouds in the atmosphere, which affects the transmittance of light), temperature and humidity (atmospheric temperature and humidity), (intensity of rainfall), and snowflake state (intensity of snowfall). The sensors and monitoring equipment installed on the remote power supply module are used to collect historical meteorological data and historical transmission efficiency data corresponding to the meteorological correlation factor set during the laser beam transmission process. The historical transmission efficiency data refers to the ratio of the light energy received by the photoelectric conversion module to the light energy of the laser beam emitted by the high-power laser. The historical meteorological data and historical transmission efficiency data constitute the historical laser beam transmission record data set.

[0040] The collected historical data is cleaned and preprocessed, including removing noise data, filling missing values ​​and standardizing, and a weather-related energy loss prediction model is trained using machine learning algorithms (such as linear regression, decision tree, random forest or neural network, etc.). Historical meteorological data is input, and output supervision adjustment is performed using historical transmission efficiency data. The model parameters are continuously optimized until the accuracy meets the requirements, and a weather-related energy loss prediction model is obtained. By collecting and using historical laser beam transmission record data sets, a weather-related energy loss prediction model is trained and constructed to accurately predict energy loss under different meteorological conditions and optimize remote power supply efficiency and reliability.

[0041] Further, the back-end power supply duration prediction unit 13 in the system is also used to include:

[0042] Collect historical power consumption records of the device to be powered and perform power consumption per unit time; perform discharge loss analysis on the power supply circuit from the back-end energy storage module to the device to be powered and generate a discharge loss index; combine the discharge loss index and the power consumption per unit time to predict and compensate for the power supply duration and generate the predicted power supply duration information.

[0043] Specifically, the historical power consumption data of the equipment, including the power consumption in each time period, is collected through the electric meter or monitoring equipment installed on the equipment to be powered, and the collected power consumption data is stored in the database to form a historical power consumption record data set. The historical power consumption record data is cleaned and preprocessed, including removing noise data and filling missing values. According to the processed data, the power consumption per unit time (such as every hour, every day) is calculated. The discharge loss of the power supply circuit from the back-end energy storage module to the equipment to be powered is analyzed, including resistance loss, heat loss, etc. The discharge loss is equal to the output power of the back-end energy storage module minus the received power of the equipment to be powered. The ratio of the discharge loss to the output power of the back-end energy storage module is calculated as the discharge loss indicator.

[0044] Furthermore, the power supply duration is predicted by combining the discharge loss index and the power consumption per unit time. In simple terms, the remaining power of the back-end energy storage module divided by the power consumption per unit time is the theoretical power supply duration. However, when the back-end energy storage module supplies power to the device to be powered, power loss will occur, which will shorten the actual power supply duration. Therefore, it is necessary to compensate and correct the theoretical power supply duration in combination with the discharge loss index. In simple terms, the power consumption per unit time is divided by the discharge loss index to obtain the power actually required to be output by the back-end energy storage module per unit time, and then the remaining power of the back-end energy storage module is divided by the power actually required to be output by the back-end energy storage module per unit time. The result is the predicted power supply duration information. Therefore, the discharge loss index and the power consumption per unit time are combined to predict and compensate the power supply duration, which is convenient for ensuring the stable power supply of the equipment under different conditions and improving the refinement of power supply management.

[0045] Furthermore, the energy management unit 16 in the system is also used for:

[0046] When the meteorological loss regression node is reached, a meteorological regression verification is performed. When the meteorological regression verification is passed, the high-power laser is started to perform remote laser beam emission, the light energy is converted into electrical energy through the photoelectric conversion module, and the voltage is stabilized and then powered after adjustment through the DCDC power management circuit; wherein the DCDC power management circuit includes a first circuit and a second circuit, the first circuit is used to transmit electrical energy to the back-end energy storage module, and the second circuit is used to supply power to the device to be powered; the first circuit and the second circuit are both provided with a voltage regulator for voltage stabilization adjustment.

[0047] Furthermore, the energy management unit 16 in the system is also used for:

[0048] When the meteorological loss regression node is reached, real-time meteorological information is received through the meteorological monitoring platform, and the meteorological-related energy loss prediction model is input for analysis to generate a real-time energy loss index; it is determined whether the real-time energy loss index meets the preset loss index, and if so, the meteorological regression verification passes; if not, the meteorological regression verification fails, and the meteorological forecast timing is updated through the meteorological monitoring platform to reposition the meteorological loss regression node by updating the meteorological forecast timing.

[0049] Specifically, when the predicted energy loss index sequence shows that the energy loss has returned to below the preset threshold, a meteorological regression verification is performed to ensure that the actual meteorological conditions have indeed improved. Specifically, real-time meteorological information can be received through a meteorological monitoring platform, input into the meteorological-related energy loss prediction model for analysis, and a real-time energy loss index can be generated to determine whether the real-time energy loss index meets the preset loss index. If so, the meteorological regression verification is passed.

[0050] After the meteorological regression verification is passed, the high-power laser is started to perform remote laser beam emission. The high-power laser emits a laser beam and transmits energy to the remote photoelectric conversion module through the atmospheric medium. The photoelectric conversion module receives the laser beam and converts it into electrical energy. The voltage is stabilized and adjusted through the DCDC power management circuit to ensure the stability of the output voltage. The DCDC power management circuit includes a first circuit and a second circuit. The first circuit is used to transmit the electrical energy generated by the photoelectric conversion module to the back-end energy storage module for electrical energy storage. The first circuit is provided with a voltage regulator to ensure the stability of the voltage input to the energy storage module. The second circuit is used to supply power to the device to be powered to ensure the normal operation of the device. The second circuit is also provided with a voltage regulator to ensure the stability of the supply voltage.

[0051] For example, the upper computer controls the laser to output a 1550nm laser, and after being transmitted through the optical fiber, the photocell in the photoelectric conversion module is used to convert the light energy into electrical energy, and then the DCDC power management circuit is used to transmit the electrical energy to the back-end energy storage module. If the output voltage of the photocell is higher than 3V, and the power supply voltage required by the device to be powered is 5V, a boost operation is required. The voltage regulator can be any type of SMD boost IC, so that the output voltage can reach up to 28V. By adjusting the output voltage of the boost circuit of the booster, the final power supply voltage is 5V.

[0052] Through the meteorological regression verification of the meteorological loss regression node, the high-power laser is started for remote power supply after the verification is passed, the light energy is converted into electrical energy through the photoelectric conversion module, and the voltage is stabilized and adjusted through the DCDC power management circuit including the first circuit and the second circuit to ensure the stability of power supply.

[0053] Furthermore, the steps of meteorological regression verification include: continuously receiving real-time meteorological information on the laser transmission path, including atmospheric particulate matter content, gas content, haze status, airflow status, cloud thickness, temperature and humidity, rain status and snowflake status, etc., inputting real-time meteorological information into the meteorological-related energy loss prediction model, analyzing the energy loss situation on the current laser transmission path, outputting real-time energy loss index, and quantifying the energy loss situation under current conditions. Compare the real-time energy loss index with the preset loss index. If the real-time energy loss index is lower than or equal to the preset loss index, it means that the meteorological conditions have improved to an acceptable level and the meteorological regression verification has passed.

[0054] If the real-time energy loss index is higher than the preset loss index, it means that the meteorological conditions have not yet recovered and the meteorological regression verification has failed. At this time, the meteorological forecast time series is updated through the meteorological monitoring platform. That is to say, the meteorological monitoring platform will update the meteorological data at different time points, connect to the meteorological monitoring platform, re-acquire the meteorological forecast data at future times, and obtain the updated meteorological forecast time series. The updated meteorological forecast time series is input into the meteorological-related energy loss prediction model to obtain the updated forecast loss index sequence. Based on the updated forecast loss index sequence, the new meteorological loss regression node is relocated to perform power supply management. Therefore, the meteorological forecast time series is updated through the meteorological monitoring platform, and the meteorological loss regression node is relocated to improve the refinement and stability of remote power supply.

[0055] Furthermore, the system further comprises a photoelectric conversion loss analysis unit, wherein the photoelectric conversion loss analysis unit is used for:

[0056] Perform a photoelectric conversion loss test on the photoelectric conversion module within a preset maintenance interval to generate a preset photoelectric conversion loss threshold; continuously monitor the photoelectric conversion loss of the photoelectric conversion module, and compare the continuous monitoring result with the preset photoelectric conversion loss threshold; if the continuous monitoring result does not meet the preset photoelectric conversion loss threshold, generate a photoelectric conversion abnormality reminder message and send it to the management personnel of the equipment to be powered.

[0057] Specifically, the laser beam may experience energy loss during transmission, resulting in electric energy loss. Similarly, the photoelectric conversion module also has photoelectric conversion losses. During the photoelectric conversion process, part of the energy is lost in the form of heat energy. There will definitely be losses in photoelectric conversion. However, when the existing losses are too large, it may be caused by a fault. Therefore, it is necessary to monitor the photoelectric conversion losses in order to detect abnormal losses in a timely manner. Specifically, the preset maintenance interval is a regular maintenance period set by professional and technical personnel in this field. For example, the photoelectric conversion module will be inspected and maintained every other month. The time zone from the time point when this maintenance is completed to the time point before the next maintenance is the preset maintenance interval. Within the preset maintenance interval, the energy conversion efficiency of the photoelectric conversion module is evaluated through experimental testing or simulated operation, and the ratio of light energy input to electric energy output is recorded. Based on the test results, the maximum acceptable loss value of the photoelectric conversion module under normal working conditions is calculated and set as the preset photoelectric conversion loss threshold.

[0058] During the normal operation of the remote power supply module, the input light energy and output electric energy of the photoelectric conversion module are monitored in real time through sensors and monitoring equipment. According to the real-time monitoring data, the actual photoelectric conversion loss value is calculated as the continuous monitoring result. The actual photoelectric conversion loss value obtained by continuous monitoring is compared with the preset photoelectric conversion loss threshold to determine whether the actual photoelectric conversion loss value is within the preset photoelectric conversion loss threshold. If the continuous monitoring result shows that the actual photoelectric conversion loss value exceeds the preset photoelectric conversion loss threshold, it means that the photoelectric conversion module may have a fault or performance degradation, and generate photoelectric conversion abnormality reminder information, including the time of abnormal occurrence, monitoring data, etc. The photoelectric conversion abnormality reminder information is sent to the management personnel of the power supply equipment so that they can take timely measures for maintenance and repair. Similarly, the DCDC power management circuit can also be monitored for abnormal power loss and early warning reminders. By monitoring the conversion loss of the photoelectric conversion module, abnormalities can be discovered in time to improve the reliability and stability of the remote power supply system.

[0059] Furthermore, the system further comprises a loss reminder unit, wherein the loss reminder unit is used to:

[0060] The predicted energy loss index sequence is compared with the preset loss index. If there is no meteorological loss regression node, a first loss reminder message is generated; the first loss reminder message is sent to the manager of the power supply equipment for abnormal reminder.

[0061] Specifically, the loss value of each time point in the predicted energy loss index sequence is compared with the preset loss index one by one. During the comparison process, it is checked whether there is any time point whose predicted energy loss index is lower than or equal to the preset loss index. If there is no time point whose loss value in the predicted energy loss index sequence is lower than or equal to the preset loss index, it means that there is no meteorological loss regression node under the predicted power supply duration information, indicating that in the future, the energy loss of laser transmission will continue to exceed the preset threshold, and the back-end energy storage module can only complete the power supply under the time length corresponding to the predicted power supply duration information, and the subsequent power supply may be insufficient. At this time, the first loss reminder information is generated, including the predicted energy loss index sequence, the preset loss index, the time period and other information, so that the management personnel can understand the specific situation. The generated first loss reminder information is sent to the management personnel of the equipment to be powered by means of communication (such as email, SMS or dedicated management system). After the reminder information arrives, the management personnel can understand the situation in time and take corresponding measures, such as adjusting the power supply strategy, starting the backup power supply or performing system maintenance, etc., to identify and respond to potential power shortage problems in advance, thereby improving the reliability and stability of remote power supply.

[0062] In summary, the remote power supply and energy management system based on high-power laser provided in this application has the following technical effects:

[0063] A loss model construction unit is used to obtain a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module is constructed; an energy loss analysis unit is used to perform meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and analyze the meteorological monitoring data set through the meteorological-related energy loss prediction model to generate a transmission energy loss index; a back-end power supply duration prediction unit is used to collect energy storage information of the back-end energy storage module when the transmission energy loss index is greater than a preset loss index, and to perform energy storage information on the back-end energy storage module according to the energy storage information. The power supply duration of the equipment to be powered by the remote power supply module is predicted to obtain the predicted power supply duration information; the meteorological monitoring and analysis unit is used to extract meteorological forecast information according to the predicted power supply duration information through the meteorological monitoring platform, generate a meteorological forecast time series, input the meteorological related energy loss prediction model for analysis, and generate a predicted energy loss index sequence; the loss regression analysis unit is used to compare the predicted energy loss index sequence with the preset loss index and locate the meteorological loss regression node; the energy management unit is used to power the equipment to be powered through the back-end energy storage module, start the high-power laser to remotely emit the laser beam when reaching the meteorological loss regression node, and perform power supply management through the DCDC power management circuit. By constructing a meteorological related energy loss prediction model, analyzing the transmission energy loss index, and then locating the meteorological loss regression node, power supply management is performed based on energy loss, and energy management of the remote power supply module is realized, achieving the technical effect of reducing energy loss and improving power supply stability.

[0064] Embodiment 2: Based on the remote power supply and energy management system based on high-power laser in the above embodiment, the present application also provides a remote power supply and energy management method based on high-power laser, please refer to the attached Figure 2 , the remote power supply and energy management method based on high-power laser includes:

[0065] Step 1: Obtain a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and construct a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module.

[0066] Step 2: Perform meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and analyze the meteorological monitoring data set through the meteorological correlation energy loss prediction model to generate a transmission energy loss index.

[0067] Step three: When the transmission energy loss index is greater than the preset loss index, energy storage information is collected from the back-end energy storage module, and the power supply duration of the power supply device of the remote power supply module is predicted based on the energy storage information to obtain the predicted power supply duration information.

[0068] Step 4: extract meteorological forecast information based on the predicted power supply duration information through the meteorological monitoring platform, generate a meteorological forecast time series, input the meteorological-related energy loss prediction model for analysis, and generate a predicted energy loss indicator sequence.

[0069] Step 5: Compare the predicted energy loss index sequence with the preset loss index to locate the meteorological loss regression node.

[0070] Step six: power the device to be powered through the back-end energy storage module, start the high-power laser to perform remote laser beam emission when the meteorological loss return node is reached, and perform energy management through the DCDC power management circuit.

[0071] Furthermore, step one of this application includes:

[0072] A meteorological correlation factor set is configured, wherein the meteorological correlation factor set includes at least atmospheric particulate matter content, gas content, haze status, cloud thickness, temperature and humidity, rain status and snowflake status; based on the meteorological correlation factor set, a historical laser beam transmission record data set of the remote power supply module is collected; and the meteorological correlation energy loss prediction model is constructed by training the historical laser beam transmission record data set.

[0073] Further, step three of this application includes:

[0074] Collect historical power consumption records of the device to be powered and perform power consumption per unit time; perform discharge loss analysis on the power supply circuit from the back-end energy storage module to the device to be powered and generate a discharge loss index; combine the discharge loss index and the power consumption per unit time to predict and compensate for the power supply duration and generate the predicted power supply duration information.

[0075] Furthermore, step six of this application includes:

[0076] When the meteorological loss regression node is reached, a meteorological regression verification is performed. When the meteorological regression verification is passed, the high-power laser is started to perform remote laser beam emission, the light energy is converted into electrical energy through the photoelectric conversion module, and the voltage is stabilized and then powered after adjustment through the DCDC power management circuit; wherein the DCDC power management circuit includes a first circuit and a second circuit, the first circuit is used to transmit electrical energy to the back-end energy storage module, and the second circuit is used to supply power to the device to be powered; the first circuit and the second circuit are both provided with a voltage regulator for voltage stabilization adjustment.

[0077] Furthermore, the present application also includes the following steps:

[0078] When the meteorological loss regression node is reached, real-time meteorological information is received through the meteorological monitoring platform, and the meteorological-related energy loss prediction model is input for analysis to generate a real-time energy loss index; it is determined whether the real-time energy loss index meets the preset loss index, and if so, the meteorological regression verification passes; if not, the meteorological regression verification fails, and the meteorological forecast timing is updated through the meteorological monitoring platform to reposition the meteorological loss regression node by updating the meteorological forecast timing.

[0079] Furthermore, the present application also includes the following steps:

[0080] Perform a photoelectric conversion loss test on the photoelectric conversion module within a preset maintenance interval to generate a preset photoelectric conversion loss threshold; continuously monitor the photoelectric conversion loss of the photoelectric conversion module, and compare the continuous monitoring result with the preset photoelectric conversion loss threshold; if the continuous monitoring result does not meet the preset photoelectric conversion loss threshold, generate a photoelectric conversion abnormality reminder message and send it to the management personnel of the equipment to be powered.

[0081] Furthermore, the present application also includes the following steps:

[0082] The predicted energy loss index sequence is compared with the preset loss index. If there is no meteorological loss regression node, a first loss reminder message is generated; the first loss reminder message is sent to the manager of the power supply equipment for abnormal reminder.

[0083] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1The remote power supply and energy management system based on high-power laser and the specific examples in the first embodiment are also applicable to the remote power supply and energy management method based on high-power laser in this embodiment. Through the above detailed description of the remote power supply and energy management system based on high-power laser, those skilled in the art can clearly know the remote power supply and energy management method based on high-power laser in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the system description.

[0084] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0085] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A remote power supply and energy management system based on high power laser, characterized in that: include: A loss model building unit, used to obtain a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and build a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module; An energy loss analysis unit, configured to perform meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and to analyze a meteorological monitoring data set through the meteorological correlation energy loss prediction model to generate a transmission energy loss index; A back-end power supply duration prediction unit is used to collect energy storage information of the back-end energy storage module when the transmission energy loss index is greater than a preset loss index, and to predict the power supply duration of the device to be powered by the remote power supply module according to the energy storage information to obtain the predicted power supply duration information; A meteorological monitoring and analysis unit, configured to extract meteorological forecast information according to the predicted power supply duration information through the meteorological monitoring platform, generate a meteorological forecast time series, input the meteorological-related energy loss prediction model for analysis, and generate a predicted energy loss indicator sequence; A loss regression analysis unit is used to compare the predicted energy loss index sequence with the preset loss index, locate the meteorological loss regression node, the preset loss index is the acceptable energy loss range under normal meteorological conditions, and the meteorological loss regression node represents the time point when the energy loss returns to within the preset index after the meteorological conditions change and the energy loss exceeds the preset index, compare each time point of the predicted energy loss index sequence with the preset loss index one by one, determine the time point when the predicted energy loss value exceeds the preset loss index, and find the first time point when the predicted energy loss value returns to within the preset loss index, which is the meteorological loss regression node; The energy management unit is used to supply power to the device to be powered through the back-end energy storage module, start the high-power laser to perform remote laser beam emission when the meteorological loss return node is reached, and perform power supply management through the DCDC power management circuit.

2. The remote power supply and energy management system based on high power laser as claimed in claim 1, characterized in that: The loss model building unit is also used for: Configuring a meteorological correlation factor set, wherein the meteorological correlation factor set at least includes atmospheric particulate matter content, gas content, haze state, cloud thickness, temperature and humidity, rain state, and snowflake state; Based on the meteorological correlation factor set, collecting a historical laser beam transmission record data set of the remote power supply module; The weather-related energy loss prediction model is constructed by training the historical laser beam transmission record data set.

3. The remote power supply and energy management system based on high power laser as claimed in claim 1, characterized in that: The back-end power supply duration prediction unit is also used for: Collect historical power consumption records of the equipment to be powered and calculate the power consumption per unit time; Performing a discharge loss analysis on the power supply circuit from the back-end energy storage module to the device to be powered, and generating a discharge loss index; The power supply duration is predicted and compensated by combining the discharge loss index and the power consumption per unit time to generate the predicted power supply duration information.

4. The remote power supply and energy management system based on high power laser as claimed in claim 1, characterized in that: The energy management unit is also used for: When the meteorological loss regression node is reached, a meteorological regression verification is performed. When the meteorological regression verification is passed, the high-power laser is started to perform remote laser beam emission, light energy is converted into electrical energy through the photoelectric conversion module, and voltage is stabilized and adjusted through the DCDC power management circuit for power supply; The DCDC power management circuit includes a first circuit and a second circuit, wherein the first circuit is used to transmit electric energy to the back-end energy storage module, and the second circuit is used to supply power to the device to be powered; The first circuit and the second circuit are both provided with a voltage regulator for performing voltage stabilization regulation.

5. The remote power supply and energy management system based on high power laser as claimed in claim 4, characterized in that: The energy management unit is also used for: When the meteorological loss regression node is reached, real-time meteorological information is received through the meteorological monitoring platform, input into the meteorological-related energy loss prediction model for analysis, and real-time energy loss indicators are generated; Determine whether the real-time energy loss index meets the preset loss index, and if so, the meteorological regression verification is passed; If not, the meteorological regression verification fails, and the meteorological forecast time series is updated through the meteorological monitoring platform to update the meteorological forecast time series to relocate the meteorological loss regression node.

6. The remote power supply and energy management system based on high power laser as claimed in claim 1, characterized in that: It also includes a photoelectric conversion loss analysis unit, which is used to: Performing a photoelectric conversion loss test on the photoelectric conversion module in a preset maintenance interval to generate a preset photoelectric conversion loss threshold; Continuously monitoring the photoelectric conversion loss of the photoelectric conversion module, and comparing the continuous monitoring result with the preset photoelectric conversion loss threshold; If the continuous monitoring result does not meet the preset photoelectric conversion loss threshold, a photoelectric conversion abnormality reminder message is generated and sent to the manager of the device to be powered.

7. The remote power supply and energy management system based on high power laser as claimed in claim 1, characterized in that: It also includes a loss reminder unit, which is used to: Comparing the predicted energy loss index sequence with the preset loss index, and generating first loss reminder information if there is no meteorological loss regression node; The first loss reminder information is sent to the management personnel of the power supply device for abnormal reminder.

8. A remote power supply and energy management method based on a high-power laser, characterized in that: The method is implemented by the high-power laser-based remote power supply and energy management system as described in any one of claims 1 to 7, comprising: Acquire a remote power supply module, wherein the remote power supply module includes a high-power laser, a photoelectric conversion module, a DCDC power management circuit and a back-end energy storage module, and construct a meteorological-related energy loss prediction model from the high-power laser to the photoelectric conversion module; Performing meteorological monitoring on the laser transmission path from the high-power laser to the photoelectric conversion module through a meteorological monitoring platform, and analyzing the meteorological monitoring data set through the meteorological correlation energy loss prediction model to generate a transmission energy loss index; When the transmission energy loss index is greater than the preset loss index, energy storage information is collected from the back-end energy storage module, and the power supply duration of the device to be powered by the remote power supply module is predicted according to the energy storage information to obtain the predicted power supply duration information; Extract meteorological forecast information based on the predicted power supply duration information through the meteorological monitoring platform to generate a meteorological forecast time series, input the meteorological-related energy loss prediction model for analysis, and generate a predicted energy loss indicator sequence; Compare the predicted energy loss index sequence with the preset loss index, locate the meteorological loss regression node, the preset loss index is the acceptable energy loss range under normal meteorological conditions, the meteorological loss regression node represents the time point when the energy loss returns to within the preset index after the meteorological conditions change and the energy loss exceeds the preset index, compare each time point of the predicted energy loss index sequence with the preset loss index one by one, determine the time point when the predicted energy loss value exceeds the preset loss index, and find the first time point when the predicted energy loss value returns to within the preset loss index, which is the meteorological loss regression node; The device to be powered is powered by the back-end energy storage module, and when the meteorological loss return node is reached, the high-power laser is started to perform remote laser beam emission, and energy management is performed through the DCDC power management circuit.

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