Multi-energy cooperative power supply method and system and storage medium

Abstract

The invention relates to the technical field of power supply, in particular to a multi-energy cooperative power supply method and system and a storage medium. According to the invention, a self-adaptive power supply strategy which is deeply bound with the first-aid repair process is constructed by dynamically sensing the first-aid repair operation stage and intelligently dividing the load priority. When the mains supply is interrupted, the system can automatically reduce the secondary load and preferentially guarantee the power supply of the core load on the basis of accurate energy prediction under the condition of insufficient energy, so that the reliability and toughness of the emergency power supply system are remarkably improved. Meanwhile, according to the method, through periodic monitoring and adjustment, fine scheduling of energy is achieved, the power supply duration of the key load is effectively prolonged, and the efficiency and the success rate of first-aid repair operation are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of power supply technology, specifically to a multi-energy coordinated power supply method, system, and storage medium. Background Technology

[0002] In power system fault repair operations, the emergency all-purpose cabin serves as the core command and operation platform, and must provide continuous power support for loads such as communication modules (satellite communication, 4G / 5G emergency communication), repair tools (portable welding machines, insulation testers), environmental control equipment (air conditioners, dehumidifiers) and emergency lighting.

[0003] However, most existing emergency all-purpose cabin power supply systems initially utilize renewable energy sources such as photovoltaic power, while simultaneously employing mains power as a supplementary energy source to ensure power supply stability, thus achieving coordinated power supply from mains and photovoltaic sources. However, this approach cannot guarantee continued power supply during power outages, meaning it cannot guarantee the continuity of power supply. Summary of the Invention

[0004] This invention provides a multi-energy collaborative power supply method, system, and storage medium to solve the problem that the power supply system of the emergency all-purpose cabin in the prior art cannot guarantee the continuity of power supply.

[0005] In a first aspect, the present invention provides a multi-energy coordinated power supply method, wherein the power supply energy includes mains power, photovoltaic power, and energy storage batteries, and the method includes: The emergency repair operation parameters are obtained, and the priority of each load is determined based on the emergency repair stage in the emergency repair operation parameters. The priority includes fixed core load, dynamic core load, secondary core load and non-core load. The emergency repair energy consumption is determined based on the aforementioned emergency repair parameters and the power of the load to be worked. When the mains power is interrupted, the energy supply is determined based on the relationship between the available supply of energy storage batteries, the predicted available supply of photovoltaic power, and the energy consumption for emergency repairs. When energy is insufficient, reduce the power supply to secondary core loads and non-core loads; At preset intervals, the system determines whether the emergency repair phase has changed based on the acquired emergency repair parameters, and adjusts the priority of each load if a change occurs.

[0006] This invention constructs an adaptive power supply strategy deeply integrated with the emergency repair process by dynamically sensing the repair operation stage and intelligently prioritizing loads. When the mains power is interrupted, the system can automatically reduce secondary loads based on accurate energy forecasting, prioritizing power supply to core loads, thereby significantly improving the reliability and resilience of the emergency power supply system. Simultaneously, this method achieves refined energy scheduling through periodic monitoring and adjustment, effectively extending the power supply duration of critical loads and significantly improving the efficiency and success rate of emergency repair operations.

[0007] In one optional implementation, when the mains power is interrupted, determining whether energy is sufficient based on the relationship between the available supply of energy storage batteries, the predicted available supply of photovoltaic power, and the energy consumption for emergency repairs includes: The available battery supply is determined based on the difference between the current capacity of the energy storage battery and the preset redundancy capacity. Based on photovoltaic data and meteorological data, a gray prediction and recurrent neural network fusion algorithm is used to obtain the photovoltaic predicted power, which is used as the predicted photovoltaic supply. When the mains power is interrupted, the energy availability is determined based on the relationship between the sum of the available energy storage and the predicted available photovoltaic energy and the emergency repair energy consumption and redundant energy consumption. When the sum of the available energy storage supply and the predicted available photovoltaic supply is greater than or equal to the sum of emergency repair energy consumption and redundant energy consumption, the energy supply is considered sufficient. When the predicted photovoltaic power is greater than the load power, the photovoltaic power is used to supply power to the load and charge the energy storage battery. When the predicted photovoltaic power is less than the load power, the photovoltaic power and the energy storage battery are used together to supply power to the load.

[0008] This invention upgrades emergency power supply from a passive response to proactive intelligent management through precise prediction and dynamic assessment. The method utilizes a fusion algorithm to predict photovoltaic output and combines it with real-time battery capacity to determine energy sufficiency in advance during mains power outages. When energy is abundant, green photovoltaic power is prioritized and intelligently charged; when energy is scarce, it automatically switches to a photovoltaic-storage collaborative power supply mode. This prediction-based decision-making mechanism effectively avoids the risk of power outages, maximizes the utilization of renewable energy, and significantly improves the reliability of power supply and energy efficiency in power restoration operations.

[0009] In one optional implementation, the method further includes: when the mains power is not interrupted, using the mains power to supply power to the load and using photovoltaic power to supply power to the energy storage battery; when the capacity of the energy storage battery is greater than a preset threshold, using photovoltaic power to supply power to the load.

[0010] In this invention, when the mains power is normal, the mains power is used first to ensure the stable operation of the load, while the photovoltaic power is used to charge the energy storage battery, which effectively improves the utilization efficiency of clean energy. When the energy storage battery has sufficient power, the photovoltaic power is automatically switched to supply power to the load, reducing the dependence on the mains power, thereby significantly reducing the cost of electricity while ensuring the reliability of power supply.

[0011] In an optional implementation, the method further includes: The current emergency repair scenario is determined based on the aforementioned emergency repair condition parameters, and the energy storage battery capacity threshold for the current emergency repair scenario is determined based on the relationship between the emergency repair scenario and the energy storage battery capacity threshold. When the mains power is interrupted and the photovoltaic supply is insufficient, the change in the capacity of the energy storage battery is predicted based on the current capacity of the energy storage battery, the real-time power of the load, and the parameters of the emergency repair conditions. When the mains power is interrupted, the photovoltaic supply is insufficient, and it is predicted that the capacity of the energy storage battery will reach the energy storage capacity threshold within a preset time in the future, the working state of the load is optimized. Real-time monitoring of energy storage battery capacity; when the energy storage battery capacity reaches the energy storage capacity threshold, power supply to the fixed core load is maintained.

[0012] This invention significantly improves the reliability and rationality of emergency power supply for power repairs through intelligent prediction and dynamic management. In extreme cases of mains power outages and insufficient photovoltaic power, battery thresholds are dynamically set based on the repair scenario, and the risk of power degradation is predicted in advance. This proactively optimizes the operating status of non-core loads before the actual power supply limit is reached. This predictive energy management strategy ensures that sufficient power is reserved for core loads during the most critical periods, effectively avoiding the risk of power outages and guaranteeing the continuity and success rate of repair operations.

[0013] In an optional implementation, the method further includes: before energy switching, controlling the output voltage of the new energy source to be consistent with the bus, and synchronizing the frequency and phase through a phase-locked loop; during energy switching, using a current-limiting resistor to control the access of the new energy source.

[0014] In this invention, by precisely controlling the output voltage to match the bus voltage before energy switching, and utilizing a phase-locked loop to synchronize the frequency and phase, while introducing a current-limiting resistor at the moment of switching, a smooth and seamless switching between different energy sources is achieved. This method effectively suppresses current surges and voltage fluctuations generated during switching, greatly improving the stability and security of new energy grid connection, thereby ensuring the reliable operation of the entire power supply system.

[0015] In one optional implementation, the emergency repair parameters include the fault type, site terrain, and personnel configuration, and the emergency repair energy consumption is determined using the following formula:

[0016]

[0017] In the formula, T represents the working time. This indicates the base fault duration corresponding to the fault type. Represents the terrain coefficient. This represents the personnel coefficient corresponding to the personnel configuration. and Preset coefficients This indicates the energy consumption for emergency repairs.

[0018] This invention establishes a quantitative relationship between repair duration and fault type, terrain complexity, and personnel allocation, enabling rapid and accurate prediction of the total energy consumption of the entire repair task. This model transforms abstract repair conditions into specific mathematical parameters, providing a crucial data foundation for subsequent precise matching and intelligent scheduling of energy supply and demand. This significantly improves the scientific rigor and foresight of emergency power supply system planning, effectively preventing energy shortages or waste, and ensuring the continuity and reliability of repair operations.

[0019] Secondly, the present invention provides a multi-energy coordinated power supply system, wherein the power supply energy includes mains power, photovoltaic power, and energy storage batteries, and the system includes: The emergency repair condition sensing unit is used to acquire emergency repair condition parameters during emergency repair operations. A dynamic grading unit is used to determine the priority of each load based on the emergency repair stage in the emergency repair condition parameters. The priority includes fixed core load, dynamic core load, secondary core load and non-core load. The scheduling unit is used to determine the emergency repair energy consumption based on the emergency repair operating condition parameters and the priority of the loads to be worked; when the mains power is interrupted, it determines whether the energy is sufficient based on the relationship between the available energy supply of the energy storage battery and the predicted available photovoltaic energy supply and the emergency repair energy consumption; when the energy is insufficient, it reduces the load power supply of secondary core loads and non-core loads; every preset time period, it judges whether the emergency repair stage has changed based on the acquired emergency repair operating condition parameters, and adjusts the priority of each load when the change occurs.

[0020] In one optional implementation, the system further includes: an energy prediction unit and a redundant power management unit; The emergency repair condition sensing unit is also used to determine the current emergency repair scenario based on the emergency repair condition parameters; The energy prediction unit is used to obtain the photovoltaic predicted power based on photovoltaic data and meteorological data, using a gray prediction and recurrent neural network fusion algorithm. The photovoltaic predicted power is used as the predicted photovoltaic supply. The unit also predicts the change in energy storage battery capacity based on the current capacity of the energy storage battery, the real-time load power, and emergency repair parameters. The scheduling unit is also used to determine the available battery supply based on the difference between the current capacity of the energy storage battery and the preset redundant power; when the mains power is interrupted, it determines whether the energy is sufficient based on the relationship between the sum of the available energy storage supply and the predicted photovoltaic supply and the emergency repair energy consumption and the redundant energy consumption; when the sum of the available energy storage supply and the predicted photovoltaic supply is greater than or equal to the sum of the emergency repair energy consumption and the redundant energy consumption, it is determined that the energy is sufficient, and when the predicted photovoltaic power is greater than the load power, the photovoltaic is used to supply power to the load and charge the energy storage battery; when the predicted photovoltaic power is less than the load power, the photovoltaic and the energy storage battery are used together to supply power to the load. The redundant power management unit is used to determine the energy storage battery capacity threshold of the current emergency repair scenario based on the relationship between the emergency repair scenario and the energy storage battery capacity threshold; when it is predicted that the energy storage battery capacity will reach the energy storage capacity threshold within a preset time in the future, the load working state is optimized; the energy storage battery capacity is monitored in real time, and when the energy storage battery capacity reaches the energy storage capacity threshold, the power supply to the fixed core load is maintained.

[0021] In one optional implementation, the system further includes: a smoothing unit; the smoothing unit is used to control the output voltage of the new energy source to be consistent with the bus before energy switching, and to synchronize the frequency and phase through a phase-locked loop; during energy switching, a current-limiting resistor is used to control the access of the new energy source.

[0022] In one optional implementation, the system further includes: a multi-energy supply module, an energy conversion and adaptation module, an energy storage module, and a load access module; The multi-energy supply module includes a photovoltaic power supply unit, an energy storage battery unit, and a mains power access unit; The energy conversion and adaptation module includes a photovoltaic charge and discharge controller, a converter, a rectifier, and an inverter; The energy storage module includes a battery power unit; The load access module includes a fixed core load interface, a dynamic core load interface, a secondary core load interface, and a non-core load interface.

[0023] This invention achieves refined and intelligent power allocation by constructing a multi-source power supply system comprising photovoltaic, battery, and mains power, and by coordinating control through intelligent conversion and adaptation modules, as well as access interfaces that can distinguish between fixed core, dynamic core, secondary core, and non-core loads. This system can dynamically adjust power supply strategies based on energy conditions, prioritizing critical loads, thereby significantly improving the reliability, adaptability, and energy utilization efficiency of the emergency power supply system.

[0024] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the multi-energy coordinated power supply method described in the first aspect or any corresponding embodiment thereof.

[0025] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the multi-energy coordinated power supply method described in the first aspect or any corresponding embodiment thereof.

[0026] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the multi-energy coordinated power supply method described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 This is a flowchart illustrating a multi-energy coordinated power supply method according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a multi-energy coordinated power supply system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0029] As described in the background section, the power supply system of the existing emergency all-purpose power supply module cannot guarantee power continuity. Specifically, existing multi-energy collaborative and load-tiered power supply technologies (such as grid-photovoltaic-energy storage collaboration and static load tiering) still have the following key shortcomings in the special scenario of power system fault repair: 1. Load grading lacks scenario adaptability, and the rigidity of core load protection is insufficient. Existing technologies only statically prioritize loads based on grid capacity versus load capacity, without dynamically adjusting according to the stage of power repair operations and the irreplaceability of load functions. For example, during the middle of a repair operation, a welding machine is needed for line splicing (temporary core), but due to the fixed priority, insufficient power supply occurs, interrupting the line repair process.

[0030] 2. Power dispatch lacks predictability and is disconnected from emergency repair conditions. Existing solutions allocate power solely based on real-time energy status (PV power, battery SOC), without considering emergency repair duration predictions and changes in operating conditions (e.g., a change in fault type from a line short circuit to equipment burnout can prolong repair time). When repair time exceeds expectations, excessive power consumption by non-core loads in the early stages and insufficient power supply to core loads in the later stages can occur, leading to a decrease in repair efficiency of approximately 50%.

[0031] 3. Renewable energy consumption is difficult, and the impact of switching between multiple energy sources is significant. Existing solutions use a simple model of direct photovoltaic power supply to the load plus charging with surplus electricity, without considering the fluctuations in photovoltaic output in mountainous areas (such as sudden power drops due to cloud cover) and voltage surges during switching between multiple energy sources. Voltage fluctuations can easily trigger the restart of core loads (such as satellite communication equipment), disrupting emergency repair command links.

[0032] 4. Lack of emergency repair safety redundancy design, making power supply easily interrupted in extreme scenarios. The existing solution lacks energy fault early warning function and has a fixed low power threshold (e.g., 20%), which cannot meet the needs of secondary dispatch support for emergency repairs in mountainous areas (requiring 3 hours). When there is a sudden mains power outage and the photovoltaic system is not outputting power, it can easily lead to a sudden power outage.

[0033] In summary, existing technologies cannot meet the special needs of power emergency repairs, which involve "dynamic changes in operating conditions, time-varying core loads, large energy fluctuations, and high requirements for safety redundancy." There is an urgent need to design a new type of power supply system that is "scenario-based, predictive, and highly redundant."

[0034] In this invention, for complex emergency repair scenarios (such as extreme weather in remote mountainous areas and long-term power outage repairs), an integrated power supply system of scenario perception, dynamic classification, predictive scheduling, and safety redundancy is constructed. It focuses on solving problems such as the difficulty of renewable energy consumption, insufficient rigidity of core load protection, disconnect between power dispatch and emergency repair conditions, and large impact of multi-energy switching in the emergency all-purpose cabin during the emergency repair process. It achieves high reliability, high efficiency, and low loss power supply in the emergency all-purpose cabin throughout the entire emergency repair cycle. It is suitable for emergency repair scenarios with no stable mains power coverage, extreme weather (heavy rain, heavy snow, strong winds), and long-term (more than 12 hours).

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0037] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0038] According to an embodiment of the present invention, a multi-energy coordinated power supply method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] This embodiment provides a multi-energy coordinated power supply method. Figure 1 This is a flowchart of a multi-energy coordinated power supply method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Obtain the emergency repair operating conditions parameters during the emergency repair operation, and determine the priority of each load based on the emergency repair stage in the emergency repair operating conditions parameters. The priority includes fixed core loads, dynamic core loads, secondary core loads, and non-core loads. It should be noted that this power supply method is applied to the power supply system of the emergency all-around compartment for power system fault repair, that is, the scheduling method of each energy source when using multiple energy sources (such as mains power, photovoltaic, and energy storage batteries) in the emergency all-around compartment for power system fault repair scenarios.

[0040] Before power is supplied, emergency repair parameters need to be collected to accurately determine the repair duration and the load requiring operation, thereby determining load energy consumption for energy dispatch. Specifically, this embodiment collects emergency repair parameters through emergency repair terminals such as industrial tablets. These parameters include the repair stage, fault type, site terrain, repair personnel configuration, and load operating status. The repair stage indicates the current stage of the repair, such as preparation, testing, repair, or acceptance. The fault type indicates the type of fault occurring during the repair, such as a short circuit, equipment burnout, or tower collapse. The site terrain indicates the location of the repair, such as plains, mountains, or canyons. The repair personnel configuration includes the number of personnel involved in the repair work, such as one or two repair teams. Different fault types, site terrain, and repair personnel configurations will affect the required repair duration, thus impacting load energy consumption.

[0041] Furthermore, unlike related technologies that employ static load grading (such as fixed priority based on load type), this embodiment uses dynamic priority based on the emergency repair phase, dividing the load priority into four levels: fixed core load, dynamic core load, secondary core load, and non-core load. The load division method for each level is shown in Table 1 below: Table 1 Load Classification

[0042] As can be seen from Table 1, the priority of some loads is not constant, but changes with the repair stage. For example, the repair stage of the welding machine is the core, thus realizing the dynamic classification of loads.

[0043] Step S102: Determine the emergency repair energy consumption based on the emergency repair operating parameters and the power of the load to be worked. Specifically, the working time required for this emergency repair can be determined first through the emergency repair operating parameters, and then the emergency repair energy consumption can be determined by combining the power of the load. It should be noted that when calculating the emergency repair energy consumption for the first time, the priority of the load can be ignored, that is, the power of all loads can be obtained for the calculation of emergency repair energy consumption.

[0044] Step S103: When the mains power is interrupted, determine whether the energy supply is sufficient based on the relationship between the available supply of the energy storage battery, the predicted available supply of photovoltaic power, and the emergency repair energy consumption. When using a power supply system including mains power, photovoltaic power, and energy storage batteries to supply power to the load, if the mains power is normal, the load can be powered; if the mains power is interrupted, only the energy storage battery and photovoltaic power can be used to supply power to the load. At this time, it is necessary to consider whether the available supply of the energy storage battery and the available supply of photovoltaic power meet the emergency repair energy consumption. If they do, the energy storage battery and photovoltaic power can be directly used to supply power to the load.

[0045] Step S104: When energy is insufficient, reduce the power supply to secondary core loads and non-core loads. Specifically, when energy storage batteries and photovoltaics cannot meet the energy consumption for emergency repairs, it is necessary to reduce the power supply to secondary core loads and non-core loads according to the load priority, such as reducing the secondary core load or disconnecting the non-core load.

[0046] Step S105: At preset intervals, determine whether the emergency repair stage has changed based on the acquired emergency repair condition parameters, and adjust the priority of each load if a change occurs. Specifically, steps S101 to S104 can be executed every preset interval, such as 15 minutes, to determine whether the current emergency repair stage has changed. If a change occurs, the priority of each load needs to be adjusted, and the emergency repair energy consumption needs to be recalculated to determine whether the energy supply is sufficient.

[0047] This embodiment provides a multi-energy coordinated power supply method, which includes the following steps: Step S201: Obtain the emergency repair operation parameters during the emergency repair operation, and determine the priority of each load based on the emergency repair stage in the emergency repair operation parameters. The priority includes fixed core load, dynamic core load, secondary core load, and non-core load; for details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0048] Step S202: Determine the emergency repair energy consumption based on the emergency repair operating parameters and the power of the load to be worked; specifically, the emergency repair energy consumption is determined using the following formula:

[0049]

[0050] In the formula, T represents the working time. This indicates the base fault duration corresponding to the fault type. Represents the terrain coefficient. This represents the personnel coefficient corresponding to the personnel configuration. and Preset coefficients This indicates the energy consumption for emergency repairs. It should be noted that the basic fault duration, terrain coefficient, and personnel coefficient, which determine the fault type, can be predetermined. For example, the basic fault duration for a line short circuit is 4 hours, for equipment burnout it is 8 hours, the terrain coefficient for plains is 0.5, for mountains it is 0.2, for valleys it is 0.3, and the personnel coefficient for one repair team is 0.1, for two repair teams it is 0.2, etc. (This refers to the preset coefficients.) and It can be determined by fitting historical data.

[0051] Step S203: When the mains power is interrupted, determine whether the energy supply is sufficient based on the relationship between the available supply of the energy storage battery, the predicted available supply of photovoltaic power, and the emergency repair energy consumption.

[0052] Specifically, step S203 includes: Step S2031: Determine the available battery supply based on the difference between the current capacity of the energy storage battery and the preset redundant capacity; wherein, the preset redundant capacity can be a redundant capacity to ensure the operation of fixed core load and dynamic core load for a preset number of hours, such as a 3-hour redundant capacity for core load. Remove this redundant capacity from the current capacity to ensure power supply to the core load in emergency situations.

[0053] Step S2032: Based on photovoltaic (PV) data and meteorological data, a fusion algorithm combining grey prediction and recurrent neural networks is used to obtain the predicted PV power, which serves as the predicted PV supply. Specifically, the PV data can be data collected by a light sensor, and the meteorological data can be data obtained from a weather station. During prediction, the grey prediction algorithm and the recurrent neural network can be used separately to predict the PV power, and then the prediction results of the two algorithms are fused to obtain the PV power predicted by the fusion algorithm. The prediction process of the two algorithms can be implemented with reference to relevant technologies. It should be noted that the grey prediction algorithm is more accurate when the data is relatively stable, while the recurrent neural network can cope with sudden changes in data. Therefore, fusing the prediction results of the two algorithms can obtain a more accurate prediction result.

[0054] In this embodiment, the fusion process is represented by the following formula:

[0055] In the formula, This indicates that the data at time t is used to pair The gray prediction output at time step. The identifier uses data pairs at time t. The output of the recurrent neural network at time step 1. Indicates the fused The photovoltaic power prediction at each time point, with weighting coefficients of 0.6 and 0.4, is obtained by training with historical data.

[0056] Step S2033: When the mains power is interrupted, determine whether the energy supply is sufficient based on the relationship between the sum of the available energy storage supply and the predicted available photovoltaic supply and the emergency repair energy consumption and redundant energy consumption. Specifically, when determining whether the energy supply is sufficient, in addition to the emergency repair energy consumption itself, redundant energy consumption is added. For example, the redundant energy consumption can be 10% of the emergency repair energy consumption to ensure the reliability of the load power supply.

[0057] Step S2034, when the available energy storage supply and the projected photovoltaic supply The sum of these values ​​is greater than or equal to the energy consumption for emergency repairs. and redundant energy consumption When the sum of the two values ​​is equal, it is determined that the energy is sufficient. If the predicted photovoltaic power is greater than the load power, the photovoltaic power is used to supply power to the load and charge the energy storage battery. If the predicted photovoltaic power is less than the load power, the photovoltaic power and the energy storage battery are used together to supply power to the load.

[0058] In the event of a mains power outage, if the following conditions are met... If the energy supply is sufficient, first determine whether the predicted photovoltaic power is greater than the load power. If it is greater, the photovoltaic power can be used directly to power the load, and the excess power can be used to power the energy storage battery. If the predicted photovoltaic power is less than the load power, the photovoltaic power should be used to power the load first, and the insufficient power should be supplemented by the energy storage battery.

[0059] Step S204: When energy is insufficient, reduce power supply to secondary core loads and non-core loads; see details below. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0060] Step S205: Every preset time interval, determine whether the emergency repair stage has changed based on the acquired emergency repair condition parameters, and adjust the priority of each load if a change occurs. For details, please refer to [link to relevant documentation]. Figure 1 Step S105 of the illustrated embodiment will not be described again here.

[0061] Step S206: When the mains power is uninterrupted, the mains power is used to supply power to the load, and the photovoltaic power is used to supply power to the energy storage battery; when the energy storage battery capacity is greater than a preset threshold, the photovoltaic power is used to supply power to the load. Specifically, when the mains power is normal and uninterrupted, and the energy storage battery capacity is insufficient, the mains power can be used to supply power to the load first, and the photovoltaic power can be used to charge the energy storage battery. When the energy storage battery is charged to a sufficient capacity, such as reaching 90% or 95% or more, the photovoltaic power can supply power to the load, and the mains power can be used as a supplement if the power supply is insufficient.

[0062] Step S207: Determine the current emergency repair scenario based on the emergency repair condition parameters, and determine the energy storage battery capacity threshold for the current emergency repair scenario based on the relationship between the emergency repair scenario and the energy storage battery capacity threshold.

[0063] Specifically, based on different emergency repair parameters, different emergency repair scenarios can be defined. For example, emergency repair scenarios can be divided into short-term simple scenarios (line short circuit, plains, ≤4 hours), long-term complex scenarios (equipment burnout, mountainous areas, 6-12 hours), and extremely long-term scenarios (tower collapse, canyons, ≥12 hours), with a classification accuracy of ≥95%. Different SOC thresholds for energy storage batteries can also be set for different emergency repair scenarios, such as a 20% SOC threshold for short-term scenarios, a 25% SOC threshold for long-term scenarios, and a 30% SOC threshold for extreme scenarios. These SOC thresholds can be adjusted according to actual conditions, but must meet the core load's 3-hour power supply requirement. Therefore, after obtaining the current emergency repair parameters, the corresponding emergency repair scenario can be determined first, and then the corresponding SOC threshold can be matched.

[0064] Step S208: Based on the current capacity of the energy storage battery, the real-time power of the load, and the emergency repair parameters, predict the change in the capacity of the energy storage battery. When the mains power is interrupted, the photovoltaic supply is insufficient, and it is predicted that the capacity of the energy storage battery will reach the energy storage capacity threshold within a preset time in the future, optimize the working state of the load.

[0065] Specifically, during the power supply process, the real-time energy consumption for emergency repairs can be determined based on the real-time load power and the repair duration determined by the emergency repair parameters. Then, combined with the scheduling scheme (i.e., the specific power supply strategy) determined in the above steps and the current capacity of the energy storage battery, the energy conservation principle is used to calculate the change in energy storage capacity over a certain period of time in the future, such as calculating the SOC change curve for the next 2 hours. This allows for the early identification of when the SOC will drop to the SOC threshold. For example, if it is identified that the energy storage battery SOC will drop to the threshold after 2 hours, and there is a mains power outage and insufficient photovoltaic power supply (such as low photovoltaic power at night that cannot meet the load power requirements), the load operating status can be optimized, such as adjusting the power supply to low-priority loads to extend the power supply time and avoid power outages.

[0066] Step S209: Monitor the energy storage battery capacity in real time. When the energy storage battery capacity reaches the energy storage capacity threshold, maintain power supply to the fixed core load. Additionally, in the event of a mains power outage and insufficient photovoltaic power supply, it is necessary to monitor the battery capacity in real time. Furthermore, when the energy storage battery's SOC reaches the threshold, power supply to only the core load can be maintained to further extend the power supply time.

[0067] In one optional implementation, when energy switching is required during the aforementioned energy dispatching process, the output voltage of the new energy source is controlled to be consistent with the bus voltage before the energy switching, and the frequency and phase are synchronized through a phase-locked loop; during the energy switching, a current-limiting resistor is used to control the connection of the new energy source. Here, "new energy source" refers to the energy source after the switch; for example, if switching from mains power to photovoltaic power, then photovoltaic power is the new energy source.

[0068] Specifically, the energy switching process can be divided into three stages: pre-charging, synchronization, and buffering, to ensure a smooth energy switching. In the pre-charging stage, the output voltage of the new energy source is pre-charged to match the bus voltage (error ≤1%). For example, a circuit controlled by a power semiconductor (such as an IGBT) can slowly boost the DC voltage after mains rectification to a level very close to the bus voltage maintained by the battery using a small current. In the synchronization stage, the frequency / phase (AC side) or voltage ripple (DC side) is synchronized using a phase-locked loop (PLL). For example, PLL technology can be used to ensure that the output of the new energy source is completely synchronized with the AC frequency and phase of the system, or consistent with the DC voltage ripple characteristics of the system. In the buffering stage, a current-limiting resistor is used to slowly output the new energy current. For example, a current-limiting resistor (e.g., 0.5Ω) can be connected in series in the circuit. This resistor limits the current surge from the new energy source to the bus. Once the current stabilizes, a switch short-circuits the current-limiting resistor, allowing the new energy source to connect at full power.

[0069] This embodiment also provides a multi-energy coordinated power supply system, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" or "unit" can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0070] This embodiment provides a multi-energy coordinated power supply system, wherein the power supply energy includes mains power, photovoltaic power, and energy storage batteries, such as... Figure 2 As shown, the system includes: The emergency repair condition sensing unit 21 is used to acquire emergency repair condition parameters during emergency repair operations. The dynamic grading unit 22 is used to determine the priority of each load based on the emergency repair stage in the emergency repair condition parameters. The priority includes fixed core load, dynamic core load, secondary core load and non-core load. The scheduling unit 23 is used to determine the emergency repair energy consumption based on the emergency repair condition parameters and the priority of the load to be worked; when the mains power is interrupted, it determines whether the energy is sufficient based on the relationship between the available energy supply of the energy storage battery and the predicted available photovoltaic energy supply and the emergency repair energy consumption; when the energy is insufficient, it reduces the load power supply of secondary core loads and non-core loads; every preset time period, it judges whether the emergency repair stage has changed based on the acquired emergency repair condition parameters, and adjusts the priority of each load when the change occurs.

[0071] In one optional implementation, the system further includes: an energy prediction unit and a redundant power management unit; The emergency repair condition sensing unit is also used to determine the current emergency repair scenario based on the emergency repair condition parameters; The energy prediction unit is used to obtain the photovoltaic predicted power based on photovoltaic data and meteorological data, using a gray prediction and recurrent neural network fusion algorithm. The photovoltaic predicted power is used as the predicted photovoltaic supply. The unit also predicts the change in energy storage battery capacity based on the current capacity of the energy storage battery, the real-time load power, and emergency repair parameters. The scheduling unit is also used to determine the available battery supply based on the difference between the current capacity of the energy storage battery and the preset redundant power; when the mains power is interrupted, it determines whether the energy is sufficient based on the relationship between the sum of the available energy storage supply and the predicted photovoltaic supply and the emergency repair energy consumption and the redundant energy consumption; when the sum of the available energy storage supply and the predicted photovoltaic supply is greater than or equal to the sum of the emergency repair energy consumption and the redundant energy consumption, it is determined that the energy is sufficient, and when the predicted photovoltaic power is greater than the load power, the photovoltaic is used to supply power to the load and charge the energy storage battery; when the predicted photovoltaic power is less than the load power, the photovoltaic and the energy storage battery are used together to supply power to the load. The redundant power management unit is used to determine the energy storage battery capacity threshold of the current emergency repair scenario based on the relationship between the emergency repair scenario and the energy storage battery capacity threshold; when it is predicted that the energy storage battery capacity will reach the energy storage capacity threshold within a preset time in the future, the load working state is optimized; the energy storage battery capacity is monitored in real time, and when the energy storage battery capacity reaches the energy storage capacity threshold, the power supply to the fixed core load is maintained.

[0072] In one optional implementation, the system further includes: a smoothing unit; the smoothing unit is used to control the output voltage of the new energy source to be consistent with the bus before energy switching, and to synchronize the frequency and phase through a phase-locked loop; during energy switching, a current-limiting resistor is used to control the access of the new energy source.

[0073] In one optional embodiment, the system further includes: a multi-energy supply module, an energy conversion and adaptation module, an energy storage module, and a load access module; the multi-energy supply module includes a photovoltaic power supply unit, an energy storage battery unit, and a mains power access unit; the energy conversion and adaptation module includes a photovoltaic charge and discharge controller, a converter, a rectifier, and an inverter; the energy storage module includes a battery power supply unit; and the load access module includes a fixed core load interface, a dynamic core load interface, a secondary core load interface, and a non-core load interface.

[0074] As one or more specific application embodiments of the present invention, the multi-energy collaborative power supply system includes a scene perception module, a multi-energy supply module, an energy conversion and adaptation module, an intelligent power dispatching module, an energy storage module, a load access module, and a safety redundancy module. These modules work together to achieve "scenario-based, predictive, and highly redundant" power supply. The specific scheme is as follows: 1. Scene Awareness Module. This module provides intelligent scheduling with dual-dimensional data support for emergency repair scenarios and energy trends, including an emergency repair condition awareness unit and an energy prediction unit.

[0075] 1.1 Emergency Repair Condition Sensing Unit, which includes two processes: data acquisition and scene classification.

[0076] During the data acquisition process, the emergency repair operation terminal (industrial flat panel) collects data on the emergency repair stage (preparation / inspection / repair / acceptance), fault type (line short circuit / equipment burnout / tower collapse), site terrain (plain / mountain / canyon), and personnel configuration (1 or 2 emergency repair teams); the load access module collects the real-time working status of each load (such as whether the welding machine is running).

[0077] In the scenario classification, emergency repair scenarios are divided into short-term simple scenarios (line short circuit, plains, ≤4 hours), long-term complex scenarios (equipment burnout, mountains, 6-12 hours), and extremely long-term scenarios (tower collapse, canyons, ≥12 hours), with a classification accuracy of ≥95%.

[0078] 1.2 Energy Prediction Unit, which is used to predict photovoltaic output and the SOC of energy storage batteries.

[0079] For short-term photovoltaic (PV) output forecasting, a fusion algorithm of "grey prediction-GRU neural network" is used based on on-site light sensor data (sampling frequency 1 time / minute) and real-time weather station data to predict PV output power for the next hour, with a prediction error ≤10%. The short-term PV forecast is expressed by the following formula: in, The output is gray prediction. The output of the GRU neural network has weight coefficients obtained through training with historical data.

[0080] When predicting battery SOC trends, the SOC change curve for the next 2 hours is calculated based on the current battery SOC, real-time load power, and repair time prediction results, so as to identify the risk of "SOC dropping to the threshold" in advance.

[0081] 2. Multi-energy supply module. This module includes a flexible photovoltaic power supply unit, a lead-acid-graphene composite battery energy storage unit, and a mains power access unit, providing diversified energy input for the system and adapting to the energy needs of emergency repair scenarios.

[0082] 2.1 The flexible photovoltaic power supply unit adopts a "flexible thin film + anti-fouling coating" photovoltaic panel, which is installed to fit the curved surface of the top of the cabin. The weight is ≤3kg / ㎡, the wind resistance level is ≥12, the seismic resistance level is ≥8, and the anti-fouling level is ≥IP68. The power of a single panel is ≥100W, the total power is ≥1000W, and the output is stable when the light intensity is ≥100W / ㎡.

[0083] 2.2 Lead-acid-graphene composite battery energy storage unit, with a total capacity of ≥200Ah (12V), energy density of ≥60Wh / kg, cycle life of ≥800 cycles, supports deep discharge (depth of discharge ≥80%), and can support the core load (power ≤200W) to work continuously for ≥15 hours on a single full charge.

[0084] 2.3 Mains power access unit, equipped with quick-connect plug and 50m cable, supports 220V / 380V input, has overvoltage, overcurrent and lightning protection (withstands impulse voltage 10kV), plug connection time ≤10 minutes, suitable for mountainous thunderstorm weather.

[0085] 3. Energy Conversion and Adaptation Module. This module enables the conversion and voltage adaptation of different energy types, ensuring power quality. Specifically, it includes a photovoltaic charge / discharge controller, converter, rectifier, and inverter.

[0086] 3.1 The photovoltaic charge / discharge controller adopts the MPPT control strategy, with a tracking accuracy of ≥99.5% and a conversion efficiency of ≥95%. It adds a "shading adaptive" function to reduce power loss caused by localized shading; and features overcharge, over-discharge, and short-circuit protection. To achieve the shading adaptive function, a controllable switch can be connected to the output of each submodule of the photovoltaic power supply unit. Thus, when shading occurs, the connection relationship of the submodules can be changed by controlling the switch, i.e., changing the topology of the photovoltaic power supply unit, thereby quickly determining a higher power point.

[0087] 3.2, a bidirectional DC-DC converter, connects the battery and the DC bus, with a conversion efficiency ≥96%, a voltage regulation range of 8V-60V, supports bidirectional battery charging and discharging control, and integrates a supercapacitor compensation interface (for photovoltaic fluctuation buffering). The supercapacitor has an extremely fast response speed, capable of instantly absorbing or releasing large currents to smooth out drastic fluctuations in photovoltaic power and prevent them from impacting the system voltage.

[0088] 3.3 The AC / DC rectifier has an input of 220V / 380V (AC) and an output of 12V / 24V / 48V (DC). It has a conversion efficiency of ≥94%, a power factor of ≥0.98, and is equipped with a lightning protection module, making it suitable for harsh mountainous environments.

[0089] 3.4 The DC / AC inverter input DC bus voltage, outputs 220V (AC), 50Hz, conversion efficiency ≥93%, waveform distortion ≤5%, meeting the power supply quality requirements of AC loads (air conditioners, welding machines).

[0090] 4. Intelligent Power Dispatch Module. This module is the core control unit of the system, realizing integrated management of "dynamic hierarchical scheduling, predictive dispatching, and smooth switching".

[0091] 4.1 Dynamic Hierarchical Unit. This unit prioritizes the load, dividing it into Fixed Core Load (FCL), Dynamic Core Load (DCL), Secondary Core Load (SCL), and Non-Core Load (NCL). Based on this priority division, the priority is adjusted within 1 second when the scene perception module's recognition phase changes.

[0092] 4.2 Predictive Scheduling Submodule. Its scheduling process is as follows: Step 1: Prediction of repair time and total energy consumption.

[0093] The repair time prediction adopts a scenario library matching + linear correction model, and is implemented using the following formula:

[0094] in, and These represent correction factors for the repair time.

[0095] Reserve 10% redundancy in total energy consumption calculations. .

[0096] Step 2: Forecasting the availability of multiple energy sources.

[0097] Available amount of mains power When the mains power is normal, calculate based on AC / DC rated power × T; when interrupted... .

[0098] Solar power supply Calculated based on the integral of the 1-hour photovoltaic power curve.

[0099] Battery supply Current battery capacity - 3 hours of redundant power for core load.

[0100] Step 3: Pre-scheduling scheme generation and dynamic correction.

[0101] If the mains power is not interrupted, Allocation is based on "PV power priority for load supply + surplus charging" and "mains power supplementing PV shortfall".

[0102] like Prioritize the protection of FCL and the current DCL, and reduce the energy consumption of SCL / NCL; adjust the plan every 15 minutes.

[0103] 4.3 Smooth Switching Unit. This unit adopts a three-stage switching strategy of "pre-charge-synchronization-buffering": During the pre-charging phase, the output voltage of the new energy source (mains power / photovoltaic) is pre-charged to be consistent with that of the bus (error ≤1%).

[0104] During the synchronization phase, the frequency / phase (AC side) or voltage ripple (DC side) is synchronized via a phase-locked loop. During the buffering phase, the current-limiting resistor (0.5Ω) is slowly connected, and the resistor is short-circuited after the current stabilizes. The switching time is ≤50ms, and the bus voltage fluctuation is ≤±3%.

[0105] 5. Energy Storage Module. This module uses a lead-acid-graphene composite battery as its core, and works with a battery management system (BMS) to achieve safe energy storage.

[0106] 5.1 The BMS is used to monitor the voltage (accuracy ±0.01V), temperature (accuracy ±1℃), and SOC (accuracy ±5%) of individual battery cells in real time; and is equipped with a low-temperature preheating function, that is, an additional heating element is added. When the ambient temperature is <-5℃, the heating element (50W) preheats to above 5℃, so that the low-temperature capacity decay is ≤10%; the circuit is cut off in case of overcharging (voltage >13.8V), over-discharging (voltage <10.5V), or overheating (temperature >45℃).

[0107] 5.2 Charging strategy: Three-stage charging (constant current 20A - constant voltage 13.8V - float charging 13.2V) is adopted. When the mains power + photovoltaic power are used for coordinated charging, the full charge time is ≤10 hours.

[0108] 6. Load Access Module. This module provides standardized, scenario-adaptive access interfaces for each load.

[0109] 6.1 The Fixed Core Load (FCL) interface includes an aviation connector (IP67), outputs 24V (DC), has two ports (satellite communication, 4G / 5G), and is protected against reverse connection.

[0110] 6.2 The Dynamic Core Load (DCL) interface includes one DC interface (12V / 24V, IP67) and one AC interface (220V, IP65); a new current waveform detection circuit is added to identify the welding status of the welding machine and automatically trigger priority adjustment.

[0111] 6.3 The secondary core / non-core load interfaces include three AC interfaces (220V, IP65); the SCL interface has derating control function, and the NCL interface has overload protection (overload current ≥10A cut-off).

[0112] 7. Safety Redundancy Module. This module provides the system with dual protection: power redundancy and fault warning.

[0113] 7.1 Redundant Power Management Unit. This unit is used for dynamic threshold setting, such as a SOC threshold of 20% for short-term scenarios, 25% for long-term scenarios, and 30% for extreme scenarios. The threshold power setting must meet the FCL's 3-hour power supply requirement. When multiple energy sources are insufficient, such as mains power outages, insufficient photovoltaic power, or when the energy storage battery capacity reaches the SOC threshold, redundant power is prioritized for supplying the FCL, while simultaneously reducing the SCL / NCL.

[0114] 7.2 Fault Early Warning Unit. This unit provides early warnings for various types of power output, including: photovoltaic power drop warning (power decrease of 30% or more within the next 15 minutes), battery degradation warning (≥500 cycles or capacity degradation ≥20%), and mains power outage warning (voltage fluctuation ≥±15% + grid fault information). Furthermore, it utilizes an in-cabin touchscreen, audible and visual alarms, and a remote command center (satellite communication) to simultaneously output warnings, with a response time ≤1 second.

[0115] As one or more specific application embodiments of the present invention, the following describes the specific implementation process of the multi-energy collaborative power supply system in conjunction with a "long-term emergency repair scenario for mountain equipment burnout" (repair time 8 hours, mains power outage, cloudy weather): 1. System deployment.

[0116] 1.1 When deploying the scene perception module, install an emergency repair terminal (supporting touch input) inside the cabin, deploy a light-weather sensor next to the photovoltaic panel, and connect the energy prediction unit (STM32H743 microprocessor) to each module via CAN bus.

[0117] 1.2 When deploying the multi-energy supply module, four 250W flexible anti-fouling photovoltaic panels are attached to the top of the cabin (total area 4㎡), and two sets of 12V / 200Ah lead-acid-graphene batteries and 50m of mains power cable are installed in the equipment cabinet inside the cabin.

[0118] 1.3 When deploying the energy conversion and adaptation module, the photovoltaic charge and discharge controller, bidirectional DC-DC converter (with supercapacitor interface), AC / DC rectifier (with lightning protection), and DC / AC inverter are integrated into the equipment cabinet to form a 24V DC bus.

[0119] 1.4 Deploy the intelligent power dispatch module. Set up a dispatch controller (integrating dynamic hierarchical, predictive dispatch, and smooth switching algorithms) to communicate with each sensor, and equip it with a 10-inch touchscreen to display the status.

[0120] 1.5 When deploying the safety redundancy module, the redundant power management unit works in conjunction with the BMS, and the fault early warning unit accesses meteorological and power grid data.

[0121] 1.6 When deploying the load access module, connect the FCL (50W satellite communication + 30W 4G / 5G) to the FCL interface, the DCL (20W insulation tester, 500W welding machine) to the DCL interface, the SCL (800W air conditioner) to the SCL interface, and the NCL (50W backup lighting) to the NCL interface.

[0122] 2. Work process.

[0123] 2.1 Initial stage of emergency repair (0-2 hours, testing phase).

[0124] Scene awareness: The working condition terminal records "Equipment burnout - Mountainous area - Group 2", classifying it as a long-term scenario with a prediction duration of T=8 hours; the energy prediction unit predicts the total photovoltaic output for 8 hours. The battery's current SOC is 90%. (90% × 4800Wh - 600Wh redundancy), total supply = 6720Wh.

[0125] Dynamic grading: DCL is the insulation tester (priority = FCL), FCL + DCL power = 100W, SCL is the air conditioner (800W), and NCL is the backup lighting (50W).

[0126] Predictive scheduling: Total energy consumption (FCL 640Wh + DCL 40Wh + SCL 4800Wh + NCL 50Wh), Redundancy The total demand is 6083Wh ≤ 6720Wh, and the solution is "solar power supply + surplus charging".

[0127] Smooth switching: When the photovoltaic power drops from 400W to 300W, the supercapacitor discharges 100W, and the bus voltage is 23.8-24.2V, without any impact.

[0128] 2.2, Mid-stage of emergency repair (3-6 hours, repair phase).

[0129] Scene awareness: Switch to repair phase, DCL becomes welding machine (working for 2 hours, priority = FCL); Energy prediction correction. (Negative), Total supply = 6520Wh.

[0130] Dynamic grading: FCL + DCL power = 580W, NCL cuts off standby lighting; total energy consumption (FCL 640Wh + DCL 1000Wh + SCL 3200Wh), demand is met.

[0131] Fault warning: If the photovoltaic power drops to 100W in the next hour, the "Photovoltaic power insufficient warning" will be triggered, and the SCL (air conditioning running time will be reduced from 4 hours to 3 hours) will be reduced, reducing energy consumption by 800Wh.

[0132] 2.3, Later stage of emergency repair (7-8 hours, acceptance phase).

[0133] Scene awareness: Switching to the acceptance phase, DCL reverts to an insulation tester (operating for 1 hour); battery SOC = 28% (above the threshold of 25%). Total supply = 3544Wh.

[0134] Dynamic grading: SCL air conditioner off, FCL + DCL power = 100W; total energy consumption Supply is sufficient.

[0135] Redundancy guarantee: SOC=26% (above the threshold), reserved FCL power supply for 3 hours (600Wh), no risk of interruption.

[0136] 3. System recovery.

[0137] If mains power is restored one hour before the end of the emergency repair, the smooth switching unit will complete the "pre-charge-synchronization-buffering" switch within 50ms, with bus voltage fluctuations of ±0.8% and no FCL restart. At the same time, the early warning unit will cancel the photovoltaic early warning, and the scheduling module will prioritize charging the battery (from SOC from 26% to 35%), reserving redundancy for the next emergency repair.

[0138] This invention constructs a repair scenario perception-load dynamic classification mechanism, combining the repair operation stages (preparation-detection-repair-acceptance) with the irreplaceable function of the load, to dynamically adjust load priorities and ensure priority power supply to core loads (such as welding machines) during critical repair stages. Simultaneously, a repair duration prediction-multi-energy prediction scheduling algorithm is designed to predict the total repair time based on fault type, site environment, and personnel configuration. Combined with short-term photovoltaic output prediction (within 1 hour, accuracy ≥90%) and battery SOC change trends, power is allocated in advance, increasing energy utilization to over 85%. Furthermore, a flexible renewable energy consumption-multi-energy smooth switching scheme is proposed. Through photovoltaic output fluctuation compensation and a DC bus voltage stabilization module, bus voltage fluctuations are controlled within ±3%. A seamless switching strategy for "mains power-photovoltaic-energy storage" is designed with a switching time ≤50ms, avoiding core load restarts. In addition, a safety redundancy and energy failure early warning system for emergency repairs has been established, which sets redundant power during the emergency repair phase (such as the power supply for the core load for 3 hours) and dynamically adjusts the low battery threshold. Through multi-energy status trend analysis, an early warning system for energy failures is provided 15 minutes in advance to ensure that there are no sudden power outages.

[0139] This invention binds the power emergency repair operation process with load priority to achieve dynamic grading, solving the problem of traditional grading being out of touch with the scenario and adapting to the dynamic needs of emergency repairs. By combining emergency repair duration with short-term photovoltaic forecasts, power is allocated in advance, realizing the integration of operating condition forecasting and energy forecasting, avoiding waste in the early stage and insufficient power in the later stage, and improving power utilization by 10%-15%. A three-stage smooth switching strategy is set, with a switching time ≤50ms and fluctuation ≤±3%, to achieve low-impact switching and solve the risk of power outages caused by traditional switching. In addition, dynamic thresholds are set according to the scenario, and risks are predicted 15 minutes in advance to achieve proactive early warning and solve the problem of sudden power outages.

[0140] The multi-energy coordinated power supply system provided in this embodiment of the invention can execute the multi-energy coordinated power supply method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0141] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0142] The following is a detailed reference. Figure 3 This diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 11, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 12 or a program loaded from memory 18 into random access memory (RAM) 13. The RAM 13 also stores various programs and data required for the operation of the electronic device. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0143] Typically, the following devices can be connected to I / O interface 15: input devices 16 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 17 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 18 including, for example, magnetic tapes, hard disks, etc.; and communication devices 19. Communication device 19 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0144] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 19, or installed from a memory 18, or installed from a ROM 12. When the computer program is executed by the processor 11, it performs the functions defined in the multi-energy coordinated power supply method of the embodiments of the present invention.

[0145] Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0146] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the multi-energy coordinated power supply method shown in the above embodiments is implemented.

[0147] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0148] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A multi-energy coordinated power supply method, characterized in that, The power supply energy includes mains power, photovoltaic power, and energy storage batteries, and the method includes: The emergency repair operation parameters are obtained, and the priority of each load is determined based on the emergency repair stage in the emergency repair operation parameters. The priority includes fixed core load, dynamic core load, secondary core load and non-core load. The emergency repair energy consumption is determined based on the aforementioned emergency repair parameters and the power of the load to be worked. When the mains power is interrupted, the energy supply is determined based on the relationship between the available supply of energy storage batteries, the predicted available supply of photovoltaic power, and the energy consumption for emergency repairs. When energy is insufficient, reduce the power supply to secondary core loads and non-core loads; At preset intervals, the system determines whether the emergency repair phase has changed based on the acquired emergency repair parameters, and adjusts the priority of each load if a change occurs.

2. The method according to claim 1, characterized in that, When the mains power is interrupted, the energy availability is determined based on the relationship between the available supply of energy storage batteries, the predicted available supply of photovoltaic power, and the energy consumption for emergency repairs, including: The available battery supply is determined based on the difference between the current capacity of the energy storage battery and the preset redundancy capacity. Based on photovoltaic data and meteorological data, a gray prediction and recurrent neural network fusion algorithm is used to obtain the photovoltaic predicted power, which is used as the predicted photovoltaic supply. When the mains power is interrupted, the energy availability is determined based on the relationship between the sum of the available energy storage and the predicted available photovoltaic energy and the emergency repair energy consumption and redundant energy consumption. When the sum of the available energy storage supply and the predicted available photovoltaic supply is greater than or equal to the sum of emergency repair energy consumption and redundant energy consumption, the energy supply is considered sufficient. When the predicted photovoltaic power is greater than the load power, the photovoltaic power is used to supply power to the load and charge the energy storage battery. When the predicted photovoltaic power is less than the load power, the photovoltaic power and the energy storage battery are used together to supply power to the load.

3. The method according to claim 1, characterized in that, The method further includes: When the mains power is not interrupted, the load is powered by the mains power and the energy storage battery is powered by photovoltaic power. When the capacity of the energy storage battery exceeds a preset threshold, photovoltaic power is used to supply power to the load.

4. The method according to claim 1, characterized in that, The method further includes: The current emergency repair scenario is determined based on the aforementioned emergency repair condition parameters, and the energy storage battery capacity threshold for the current emergency repair scenario is determined based on the relationship between the emergency repair scenario and the energy storage battery capacity threshold. When the mains power is interrupted and the photovoltaic supply is insufficient, the change in the capacity of the energy storage battery is predicted based on the current capacity of the energy storage battery, the real-time power of the load, and the parameters of the emergency repair conditions. When the mains power is interrupted, the photovoltaic supply is insufficient, and it is predicted that the capacity of the energy storage battery will reach the energy storage capacity threshold within a preset time in the future, the working state of the load is optimized. Real-time monitoring of energy storage battery capacity; when the energy storage battery capacity reaches the energy storage capacity threshold, power supply to the fixed core load is maintained.

5. The method according to claim 1, characterized in that, The method further includes: Before switching energy, the output voltage of the new energy source is controlled to be consistent with that of the bus, and the frequency and phase are synchronized through a phase-locked loop; When switching energy sources, current-limiting resistors are used to control the access of new energy sources.

6. The method according to claim 1, characterized in that, The emergency repair parameters include the fault type, site terrain, and personnel configuration. The emergency repair energy consumption is determined using the following formula: In the formula, T represents the working time. This indicates the base fault duration corresponding to the fault type. Represents the terrain coefficient. This represents the personnel coefficient corresponding to the personnel configuration. and Preset coefficients This indicates the energy consumption for emergency repairs.

7. A multi-energy coordinated power supply system, characterized in that, The power supply includes mains electricity, photovoltaic power, and energy storage batteries. The system includes: The emergency repair condition sensing unit is used to acquire emergency repair condition parameters during emergency repair operations. A dynamic grading unit is used to determine the priority of each load based on the emergency repair stage in the emergency repair condition parameters. The priority includes fixed core load, dynamic core load, secondary core load and non-core load. The scheduling unit is used to determine the emergency repair energy consumption based on the emergency repair operating condition parameters and the priority of the loads to be worked; when the mains power is interrupted, it determines whether the energy is sufficient based on the relationship between the available energy supply of the energy storage battery and the predicted available photovoltaic energy supply and the emergency repair energy consumption; when the energy is insufficient, it reduces the load power supply of secondary core loads and non-core loads; every preset time period, it judges whether the emergency repair stage has changed based on the acquired emergency repair operating condition parameters, and adjusts the priority of each load when the change occurs.

8. The system according to claim 7, characterized in that, The system also includes: an energy prediction unit and a redundant power management unit; The emergency repair condition sensing unit is also used to determine the current emergency repair scenario based on the emergency repair condition parameters; The energy prediction unit is used to obtain the photovoltaic predicted power based on photovoltaic data and meteorological data, using a gray prediction and recurrent neural network fusion algorithm. The photovoltaic predicted power is used as the predicted photovoltaic supply. The unit also predicts the change in energy storage battery capacity based on the current capacity of the energy storage battery, the real-time load power, and emergency repair parameters. The scheduling unit is also used to determine the available battery supply based on the difference between the current capacity of the energy storage battery and the preset redundant power; when the mains power is interrupted, it determines whether the energy is sufficient based on the relationship between the sum of the available energy storage supply and the predicted photovoltaic supply and the emergency repair energy consumption and the redundant energy consumption; when the sum of the available energy storage supply and the predicted photovoltaic supply is greater than or equal to the sum of the emergency repair energy consumption and the redundant energy consumption, it is determined that the energy is sufficient, and when the predicted photovoltaic power is greater than the load power, the photovoltaic is used to supply power to the load and charge the energy storage battery; when the predicted photovoltaic power is less than the load power, the photovoltaic and the energy storage battery are used together to supply power to the load. The redundant power management unit is used to determine the energy storage battery capacity threshold of the current emergency repair scenario based on the relationship between the emergency repair scenario and the energy storage battery capacity threshold; when it is predicted that the energy storage battery capacity will reach the energy storage capacity threshold within a preset time in the future, the load working state is optimized; the energy storage battery capacity is monitored in real time, and when the energy storage battery capacity reaches the energy storage capacity threshold, the power supply to the fixed core load is maintained.

9. The system according to claim 7, characterized in that, The system also includes: a smoothing unit; The smoothing unit is used to control the output voltage of the new energy source to be consistent with the bus before energy switching, and to synchronize the frequency and phase through a phase-locked loop; during energy switching, a current-limiting resistor is used to control the access of the new energy source.

10. The system according to claim 7, characterized in that, The system also includes: a multi-energy supply module, an energy conversion and adaptation module, an energy storage module, and a load access module; The multi-energy supply module includes a photovoltaic power supply unit, an energy storage battery unit, and a mains power access unit; The energy conversion and adaptation module includes a photovoltaic charge and discharge controller, a converter, a rectifier, and an inverter; The energy storage module includes a battery power unit; The load access module includes a fixed core load interface, a dynamic core load interface, a secondary core load interface, and a non-core load interface.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the multi-energy coordinated power supply method according to any one of claims 1 to 6.

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