Method, system, device and medium for electrical energy management of a light storage flexible building

Abstract

This invention relates to the field of power management technology, and discloses a power management method, system, equipment, and medium for photovoltaic-storage-direct-drive-flexible buildings. Based on the fluctuation rate of real-time power generation data of the photovoltaic power generation equipment, the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode is determined, thereby determining the initial priority of dispatch instructions for different power dispatch modes. Based on the real-time energy storage status data, fluctuation rate, operating mode, and initial priority of the energy storage equipment, the dynamic priority corresponding to the dispatch instruction for each power dispatch mode is obtained. The dynamic priority is set by the influencing factors of each power dispatch mode under the current operating mode, and is used to adjust the priority of each dispatch instruction. Based on the dynamic priority and real-time energy storage status data, a dynamic compensation instruction is obtained to dynamically compensate and adjust the energy storage equipment. The method of this application improves the flexibility, adaptability, and accuracy of power management.

Description

Technical Field

[0001] This invention relates to the field of power management technology, and in particular to a power management method, system, device and medium for photovoltaic-storage-direct-drive-flexible buildings. Background Technology

[0002] In existing power management methods, power dispatch generally adopts a multi-time-level decomposition strategy, dividing the dispatch process into independent time layers such as long-term power dispatch mode, short-term power dispatch mode, and real-time power dispatch mode. Each time layer makes power dispatch decisions based on different optimization cycles, and achieves coordination between different levels and different dispatch objects through a fixed-cycle command transmission mechanism. Although this model can simplify dispatch complexity to a certain extent, the fixed-cycle command transmission method is difficult to flexibly adapt to the dynamic characteristics of source-load fluctuations in the power system, which can easily lead to lags in the connection of dispatch commands at different time layers, affecting the overall optimization effect. Moreover, in the matching stage between energy storage systems and dispatch commands, in order to improve the matching accuracy between dispatch commands and actual energy storage discharge behavior, existing technologies usually need to establish a transfer function model of energy storage response delay. However, the time-varying nature of parameters and the difficulty in dynamic identification result in insufficient accuracy of the transfer function model.

[0003] Therefore, improving the flexibility, adaptability, and accuracy of power management has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] This invention provides a method, system, device, and medium for power management of photovoltaic-storage-direct-drive-flexible buildings, in order to solve the technical problem of how to improve the flexibility and accuracy of power management in photovoltaic-storage-direct-drive-flexible buildings, and achieve the effect of improving the flexibility and accuracy of power management in photovoltaic-storage-direct-drive-flexible buildings.

[0005] In a first aspect, the present invention provides a power management method for photovoltaic-storage-flexible buildings, the method comprising: Acquire real-time power generation data of photovoltaic power generation equipment and real-time energy storage status data of energy storage equipment within the target photovoltaic-storage-flexible building; Based on the fluctuation rate of the real-time power generation data, the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode is determined, and based on the operating mode, the initial priority of the dispatch instructions for different power dispatch modes is determined. Based on the real-time energy storage status data, the fluctuation rate, the operating mode, and the initial priority, the dynamic priority of the dispatch instruction corresponding to each power dispatch mode under the current operating mode of the photovoltaic power generation equipment is obtained. The dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode. Based on the dynamic priority and the real-time energy storage status data, a dynamic compensation value is obtained, and a dynamic compensation command is generated based on the dynamic compensation value to dynamically compensate and adjust the energy storage device.

[0006] Preferably, determining the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode based on the fluctuation rate of the real-time power generation data includes: When the absolute value of the fluctuation rate of the real-time power generation data is greater than the first fluctuation rate threshold, the operating state of the photovoltaic power generation equipment is determined to be the dramatic operation mode corresponding to the real-time power dispatch mode of the power dispatch mode. When the absolute value of the fluctuation rate is less than or equal to the first fluctuation rate threshold and greater than the second fluctuation rate threshold, the operating state of the photovoltaic power generation equipment is determined to be a slow-change operating mode corresponding to the short-term power dispatch mode of the power dispatch mode. When the absolute value of the fluctuation rate is less than or equal to the second fluctuation rate threshold, the operating state of the photovoltaic power generation equipment is determined to be a stable operating mode corresponding to the long-term power dispatch mode of the power dispatch mode.

[0007] Preferably, determining the initial priority of dispatch instructions for different power dispatch modes based on the operating mode includes: When the operating mode is the stable operating mode, a first initial priority is set for the long-term dispatching instructions of the long-term power dispatching mode, the short-term dispatching instructions of the short-term power dispatching mode, and the real-time dispatching instructions of the real-time power dispatching mode, wherein the long-term dispatching instructions have the highest long-term initial priority among the first initial priorities. When the operating mode is the gradual change operating mode, a second initial priority is set for the long-term scheduling instruction, the short-term scheduling instruction and the real-time scheduling instruction, wherein the short-term initial priority of the short-term scheduling instruction is the highest among the second initial priorities; When the operating mode is the dramatic change operating mode, a third initial priority is set for the long-term scheduling instruction, the short-term scheduling instruction and the real-time scheduling instruction, among which the real-time initial priority of the real-time scheduling instruction is the highest.

[0008] Preferably, the step of obtaining the dynamic priority of the dispatch instruction corresponding to each power dispatch mode of the photovoltaic power generation equipment under the current operating mode based on the real-time energy storage status data, the fluctuation rate, the operating mode, and the initial priority includes: Based on the initial priority, the fluctuation rate, and the battery state of charge of the real-time energy storage data, the real-time dynamic priority corresponding to the real-time scheduling instruction in each of the operating modes is obtained. Based on the initial priority, the battery state of charge, and the energy storage battery terminal temperature value of the real-time energy storage status data, the short-term dynamic priority corresponding to the short-term scheduling instruction in each of the operating modes is obtained. Based on the real-time dynamic priority and the short-term dynamic priority, the long-term dynamic priority corresponding to the long-term scheduling instruction in each of the operating modes is obtained.

[0009] Preferably, obtaining the dynamic compensation value based on the dynamic priority and the real-time energy storage status data includes: Based on the real-time dynamic priority, a real-time dynamic priority adjustment coefficient is obtained; based on the short-term dynamic priority, a short-term dynamic priority adjustment coefficient is obtained; and based on the long-term dynamic priority and the energy storage battery terminal temperature value, a long-term dynamic priority adjustment coefficient is obtained. The first dynamic compensation amount is obtained based on the ratio of the gain coefficient of the photovoltaic power generation equipment to the real-time dynamic priority adjustment coefficient. The second dynamic compensation amount is obtained by multiplying the short-term dynamic priority adjustment coefficient and the battery state of charge. Based on the long-term dynamic priority adjustment coefficient, the energy storage device aging attenuation coefficient of the real-time energy storage status data, and the cumulative number of completed charge-discharge cycles of the real-time energy storage status data, a dynamic compensation adjustment coefficient is constructed. The dynamic compensation value is obtained based on the first dynamic compensation amount, the second dynamic compensation amount, and the dynamic compensation amount adjustment coefficient.

[0010] Preferably, the method further includes: Acquire historical sequence mapping data including the fluctuation rate, the real-time energy storage status data, and the dynamic compensation value, and construct a dynamic compensation prediction model based on the historical sequence mapping data; Based on the dynamic compensation prediction model, the dynamic compensation prediction value at the current moment is obtained, and the dynamic compensation prediction command generated based on the dynamic compensation prediction value is used to perform the dynamic compensation adjustment on the energy storage device. Receive the dynamic compensation instruction and perform a threshold judgment on the error value between the dynamic compensation prediction value and the dynamic compensation value corresponding to the dynamic compensation instruction. If the error value is less than the preset error threshold, then end the current round of dynamic compensation adjustment. If the error value is greater than or equal to the error threshold, then based on the execution status of the dynamic compensation prediction instruction, and the dynamic compensation prediction value and the dynamic compensation value at the same time, a correction supplement value and an overcompensation value are obtained, and a correction supplement instruction generated based on the correction supplement value is sent to the energy storage device to correct and supplement the dynamic compensation prediction value. Based on the overcompensation value, the predicted dynamic compensation value for the next moment is corrected to obtain the corrected predicted dynamic compensation value for the next moment, so as to adjust the dynamic compensation of the energy storage device for the next moment. The number of overcompensation events within a preset time period is counted. If the number of overcompensation events exceeds a preset overcompensation event threshold, the dynamic compensation prediction model is optimized to obtain the optimized dynamic compensation prediction model.

[0011] Preferably, obtaining the corrected supplementary value and the overcompensation value based on the execution status of the dynamic compensation prediction instruction, and the dynamic compensation prediction value and the dynamic compensation value at the same time, includes: If the predicted value of dynamic compensation at the same time is less than the dynamic compensation value, then a corrected supplementary value is obtained based on the first difference between the dynamic compensation value and the predicted value of dynamic compensation. If the dynamic compensation prediction value at the same moment is greater than the dynamic compensation value, and the dynamic compensation prediction instruction has been executed completely or partially, then the execution amount is obtained, and a second difference between the dynamic compensation value and the execution amount is calculated. When the second difference is greater than zero, the energy storage device continues to execute according to the dynamic compensation instruction. When the second difference is equal to zero, the energy storage device stops executing. When the second difference is less than zero, the energy storage device stops executing, and the overcompensation value is obtained based on the second difference. If the predicted dynamic compensation value at the same time is greater than the predicted dynamic compensation value, and the predicted dynamic compensation instruction is not executed, then the energy storage device executes according to the predicted dynamic compensation instruction.

[0012] Secondly, the present invention also provides a power management system for a photovoltaic-storage-direct-drive-flexible building, which implements the power management method for the photovoltaic-storage-direct-drive-flexible building described above. The system includes: a data acquisition module, an initial priority determination module, a dynamic priority determination module, and a dynamic compensation adjustment module. The data acquisition module is used to acquire real-time power generation data of photovoltaic power generation equipment and real-time energy storage status data of energy storage equipment in the target photovoltaic-storage-flexible building; The initial priority determination module is used to determine the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode based on the fluctuation rate of the real-time power generation data, and to determine the initial priority of the dispatch instructions for different power dispatch modes based on the operating mode. The dynamic priority determination module is used to obtain the dynamic priority of the dispatch instruction corresponding to each power dispatch mode under the current operating mode of the photovoltaic power generation equipment based on the real-time energy storage status data, the fluctuation rate, the operating mode and the initial priority. The dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode. The dynamic compensation adjustment module is used to obtain a dynamic compensation value based on the dynamic priority and the real-time energy storage status data, and to perform dynamic compensation adjustment on the energy storage device based on the dynamic compensation value and the dynamic compensation command generated by the dynamic compensation value.

[0013] Thirdly, the present invention also provides a computer device, the computer device including a memory, a processor and a transceiver, which are connected to each other via a bus; the memory is used to store a set of computer program instructions and data, and to transmit the stored data to the processor, the processor executing the computer program instructions stored in the memory to execute the above-described power management method for photovoltaic-storage-flexible buildings.

[0014] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed, implements the above-described power management method for a photovoltaic-storage-flexible building.

[0015] This application provides a method, system, device, and medium for power management in a photovoltaic-storage-flexible building system. Compared with the prior art, the beneficial effects of the embodiments of this application are as follows: This application discloses a power management method for photovoltaic-storage-direct-current-flexible building systems. Based on the fluctuation rate of real-time power generation data, the method categorizes photovoltaic (PV) power generation equipment into operating modes corresponding to power dispatch modes. Then, based on these operating modes, it determines the weight benchmark values ​​for long-term dispatch commands in long-term power dispatch mode, short-term dispatch commands in short-term dispatch mode, and real-time dispatch commands in real-time power dispatch mode. This determines the initial priority of each command, enabling timely responses to second-level fluctuations in PV power and reducing the risk of bus voltage and / or frequency exceeding limits. During the operation of the PV-storage-direct-current-flexible building system, the weight benchmark values ​​of each power dispatch command in each operating mode are adjusted based on the real-time energy storage status data and fluctuation rate of the energy storage equipment to obtain dynamic priorities. This allows for dynamic adjustment of the priority of each power dispatch command to adapt to the dynamic changes of PV power generation equipment, improving the accuracy of power management. A nonlinear delay dynamic compensation model is constructed based on battery state of charge, energy storage battery terminal temperature, cumulative number of completed charge-discharge cycles, and dynamic priorities. This model dynamically correlates key variables, improving the adaptability of the energy storage equipment to PV power generation equipment. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the steps of a power management method for a photovoltaic-storage-flexible building according to a preferred embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a power management system for a photovoltaic-storage-flexible building according to a preferred embodiment of the present invention; Figure 3 This is an internal structural diagram of the computer device in an embodiment of the present invention; Figure label: 1-Data acquisition module, 2-Initial priority determination module, 3-Dynamic priority determination module, 4-Dynamic compensation adjustment module. Detailed Implementation

[0017] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are provided for illustrative purposes only and should not be construed as limiting the invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of protection of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of this invention. In the description of this invention, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0018] In the description of this invention, it should be noted that the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0019] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0020] Please see Figure 1 The diagram illustrates the steps of a power management method for a photovoltaic-storage-direct-drive-flexible building. In an embodiment of the present invention, a power management method for a photovoltaic-storage-direct-drive-flexible building is provided, the method comprising: S1. Obtain real-time power generation data of the photovoltaic power generation equipment and real-time energy storage status data of the energy storage equipment within the target photovoltaic-storage-direct-flexible building. In the preferred embodiment of this application, the photovoltaic-storage-direct-flexible building refers to an innovative form that deeply integrates buildings and energy. With the "photovoltaic-storage-direct-flexible" technology system as its core, it upgrades traditional buildings from "energy consumption terminals" to smart energy nodes integrating "clean energy production, efficient storage, flexible electricity use, and grid interaction." "Photovoltaic" refers to the photovoltaic power generation system, which is the energy production end, converting solar energy into electrical energy to provide a clean power source for the building. "Storage" refers to the energy storage system, used to store surplus electricity from the photovoltaic power generation system and / or inexpensive electricity during off-peak hours, solving the intermittency and volatility problems of the photovoltaic power generation system and ensuring power supply stability; it is generally based on battery energy storage. "Direct" refers to the DC power distribution network, which serves as the energy transmission end. It uses DC power as the core to construct the building's internal power distribution network, reducing AC / DC conversion losses and improving energy efficiency. Photovoltaic equipment and energy storage devices naturally output DC power, whereas traditional buildings require multiple conversions from "AC to DC," resulting in losses of approximately 10%-15%. DC power distribution can directly connect to sources and loads, significantly reducing conversion energy consumption. "Flexible" refers to the flexible control system, which serves as the energy management end. It uses intelligent technology to achieve dynamic balance and flexible interaction between "source, storage, and load." A photovoltaic power generation system includes photovoltaic power generation equipment and a photovoltaic monitoring unit. The photovoltaic monitoring unit monitors the operating status of the photovoltaic power generation equipment, acquiring real-time power generation data, as well as operating temperature, loss levels, and meteorological data during photovoltaic power generation. An energy storage system includes energy storage equipment and a health management unit. The health management unit records real-time energy storage status data, which includes at least the energy storage equipment's aging degradation coefficient, the cumulative number of complete charge-discharge cycles completed by the energy storage equipment, the battery's state of charge, and the energy storage battery's terminal temperature.

[0021] S2. Based on the fluctuation rate of the real-time power generation data, determine the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode, and based on the operating mode, determine the initial priority of dispatch instructions for different power dispatch modes. In existing power management methods, a "hierarchical control + rolling optimization" framework is adopted to integrate the optimization objectives of long-term and short-term power dispatch modes to solve the problem of multi-timescale coordination. Generally, power system dispatch is decomposed into multiple independent time levels, such as long-term power dispatch mode, short-term power dispatch mode, and real-time power dispatch mode. Each level adopts a different optimization period, such as the optimization period of the long-term power dispatch mode being days, the optimization period of the short-term power dispatch mode being hours, and the optimization period of the real-time power dispatch mode being minutes. Instructions are transmitted through a fixed period. In the preferred embodiment of this application, the fluctuation rate of the real-time power generation is calculated by real-time monitoring of the real-time power generation data at the discharge end of the photovoltaic power generation equipment. The formula for calculating the fluctuation rate is: in, This represents the rate of change in the real-time power generation of photovoltaic power generation equipment. This indicates the real-time fluctuation in the power generation of photovoltaic (PV) power generation equipment. Indicates the change over time. This indicates the real-time fluctuation range of the photovoltaic power generation equipment. This indicates the reference power.

[0022] Based on the fluctuation rate of change, the operating status of photovoltaic power generation equipment is divided into stable operation mode, gradual change operation mode, and drastic change operation mode. Specifically, when the absolute value of the fluctuation rate of change of real-time power generation data is greater than the first fluctuation rate threshold, the operating status of the photovoltaic power generation equipment is determined to be the drastic change operation mode corresponding to the real-time power dispatch mode of the power dispatch mode. The first fluctuation rate threshold is 15% / s, which means that the real-time power generation fluctuates by 15 percentage points per second. When the absolute value of the fluctuation rate of change is less than or equal to the first fluctuation rate threshold and greater than the second fluctuation rate threshold, the operating status of the photovoltaic power generation equipment is determined to be the gradual change operation mode corresponding to the short-term power dispatch mode of the power dispatch mode. The second fluctuation rate threshold is 5% / s, which means that the real-time power generation fluctuates by 5 percentage points. When the absolute value of the fluctuation rate of change is less than or equal to the second fluctuation rate threshold, the operating status of the photovoltaic power generation equipment is determined to be the stable operation mode corresponding to the long-term power dispatch mode of the power dispatch mode.

[0023] In existing technologies, long-term power dispatching models generate 24-hour charging and discharging plans based on photovoltaic power generation forecasts and electricity price data. During periods of high electricity prices, priority is given to using energy from energy storage devices to ensure sufficient discharge. During periods of low electricity prices, priority is given to drawing power from the grid to charge the energy storage devices. Short-term power dispatching models dynamically adjust the charging and discharging rates of energy storage batteries by monitoring their terminal temperature and state of charge in real time. Real-time power dispatching models generate real-time dispatching instructions using a transfer function model of energy storage response delay to suppress grid fluctuations. When real-time dispatching instructions conflict with long-term dispatching instructions from the long-term power dispatching model (e.g., if the real-time dispatching instruction is for emergency discharge but the long-term dispatching instruction is for charging), the real-time dispatching instruction should be executed first. However, the fixed-period instruction transmission method used by these layers cannot respond promptly to photovoltaic fluctuations, leading to an increased risk of bus voltage and / or frequency exceeding limits.

[0024] In a preferred embodiment of this application, the power dispatch mode is matched with the operating mode of the photovoltaic power generation equipment. For different photovoltaic power generation equipment, a stable operating mode corresponds to a long-term power dispatch mode, a gradually changing operating mode corresponds to a short-term power dispatch mode, and a drastic operating mode corresponds to a real-time power dispatch mode. When the photovoltaic power generation equipment is in a stable operating mode, a first initial priority is set for the long-term dispatch instructions of the long-term power dispatch mode, the short-term dispatch instructions of the short-term power dispatch mode, and the real-time dispatch instructions of the real-time power dispatch mode. The long-term initial priority of the long-term dispatch instructions is the highest among the first initial priorities, ensuring that the long-term dispatch instructions of the long-term power dispatch mode have the highest priority. When the photovoltaic power generation equipment is in a gradually changing operating mode, a second initial priority is set for the long-term dispatch instructions, short-term dispatch instructions, and real-time dispatch instructions. The short-term initial priority of the short-term dispatch instructions is the highest among the second initial priorities, ensuring that the short-term dispatch instructions of the short-term power dispatch mode have the highest priority. When the photovoltaic power generation equipment is in a drastic operating mode, a third initial priority is set for the long-term dispatch instructions, short-term dispatch instructions, and real-time dispatch instructions. The real-time initial priority of the real-time dispatch instructions is the highest among the third initial priorities, ensuring that the real-time dispatch instructions of the real-time power dispatch mode have the highest priority.For example, in this application, the initial priority is represented by a weighted benchmark value. For the stable operation mode of photovoltaic power generation equipment, in the first initial priority, the priority of the long-term power dispatch mode is represented by the first long-term weighted benchmark value, which is 0.6; the priority of the short-term power dispatch mode is represented by the first short-term weighted benchmark value, which is 0.2; and the priority of the real-time power dispatch mode is represented by the first real-time weighted benchmark value, which is 0.2. The flexible control system will determine that the long-term dispatch command has the highest priority based on the magnitude of the first long-term weighted benchmark value, the first short-term weighted benchmark value, and the first real-time weighted benchmark value, and freeze the short-term dispatch command and the real-time dispatch command. When the photovoltaic power generation equipment is in a gradually changing operation mode, in the second initial priority, the priority of the short-term power dispatch mode is set to the second short-term weighted benchmark value, which is 0.6; the priority of the long-term power dispatch mode is set to the second long-term weighted benchmark value, which is 0.2; and the priority of the real-time power dispatch mode is set to the first long-term weighted benchmark value, which is 0.6. The second real-time weighted benchmark value is 0.2. The flexible control system will determine the priority of short-term dispatch instructions based on the magnitude of the second long-term weighted benchmark value, the second short-term weighted benchmark value, and the second real-time weighted benchmark value. When the photovoltaic power generation equipment is in a drastic operation mode, the priority of the long-term power dispatch mode in the third initial priority is represented by the third long-term weighted benchmark value, which is 0.2. The priority of the short-term power dispatch mode is represented by the third short-term weighted benchmark value, which is 0.2. The priority of the real-time power dispatch mode is represented by the third real-time weighted benchmark value, which is 0.6. The flexible control system will determine the priority of real-time dispatch instructions in the real-time power dispatch mode, which is higher than that of long-term dispatch instructions in the long-term power dispatch mode and short-term dispatch instructions in the short-term power dispatch mode, based on the magnitude of the third long-term weighted benchmark value, the third short-term weighted benchmark value, and the third real-time weighted benchmark value. The real-time dispatch instructions in the real-time power dispatch mode will be executed first to suppress grid fluctuations.

[0025] S3. Based on the real-time energy storage status data, the fluctuation rate, the operating mode, and the initial priority, the dynamic priority of the dispatch instruction corresponding to each power dispatch mode under the current operating mode of the photovoltaic power generation equipment is obtained. The dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode. In the prior art, the dependence of power management on high-precision prediction of real-time power generation of photovoltaic power generation equipment is reduced by multi-time-scale rolling optimization and unsupervised fluctuation clustering. In the process of multi-time-scale rolling optimization and unsupervised fluctuation clustering, the weight allocation of long-term power dispatch mode, short-term power dispatch mode, and real-time power dispatch mode is fixed. However, the fixed weight allocation cannot adapt to the fluctuation of real-time power generation of photovoltaic power generation equipment.

[0026] In a preferred embodiment of this application, the weight values ​​of the dispatch instructions for each power dispatch mode are adjusted according to the operating mode of the photovoltaic power generation equipment and the influencing factors of each power dispatch mode under different operating modes of the photovoltaic power generation equipment, to obtain dynamic priorities. Specifically, the priorities of long-term, short-term, and real-time dispatch instructions are dynamically adjusted based on the long-term dynamic priority of long-term dispatch instructions in the long-term power dispatch mode, the short-term dynamic priority of short-term dispatch instructions in the short-term power dispatch mode, and the real-time dynamic priority of real-time dispatch instructions in the real-time power dispatch mode. In this application, dynamic priorities are represented by dynamic weight values. For example, the long-term dynamic priority of long-term dispatch instructions is represented by a long-term dynamic weight value, the short-term dynamic priority of short-term dispatch instructions is represented by a short-term dynamic weight value, and the long-term dynamic priority of real-time dispatch instructions is represented by a real-time dynamic weight value. If the long-term dynamic priority of a long-term dispatch instruction is the highest, then the long-term dispatch instruction is executed first. If the short-term dynamic priority of a short-term dispatch instruction is the highest, then the short-term dispatch instruction is executed first. If the real-time dynamic priority of a real-time dispatch instruction is the highest, then the real-time dispatch instruction is executed first. The operating mode, fluctuation rate, and battery state of charge (SOC) of the photovoltaic (PV) power generation equipment significantly influence the dynamic priority of the real-time power dispatch mode. Similarly, the operating mode, SOC, and battery terminal temperature of the PV power generation equipment significantly influence the dynamic priority of the short-term power dispatch mode. Therefore, in this preferred embodiment, the real-time dynamic priority corresponding to the real-time dispatch command under each operating mode is obtained based on the fluctuation rate, the initial priority under each operating mode, and the SOC of the battery in the real-time energy storage data. The formula for calculating the real-time dynamic priority is as follows: in, express The real-time dynamic weight value of the real-time dynamic priority corresponding to the real-time dispatch command of the photovoltaic power generation equipment in the current operating mode. This represents the real-time weighted benchmark value of the real-time dispatch command for photovoltaic power generation equipment under the current operating mode, including the first real-time weighted benchmark value for stable operation mode, the second real-time weighted benchmark value for gradually changing operation mode, and the third real-time weighted benchmark value for drastic change operation mode. This represents the first adjustment coefficient for the rate of change of volatility in relation to real-time dynamic priority. Represents the hyperbolic tangent function. express The rate of change of real-time power generation of photovoltaic power generation equipment. This represents the boundary value of the fluctuation rate of the current operating mode of the photovoltaic power generation equipment. It is taken as 15% / s in a rapidly changing mode, 10% / s in a gradually changing mode, and 5% / s in a stable mode. This represents the first suppression coefficient of battery state of charge on real-time dynamic priority. express The state of charge of the battery at any given time.

[0027] Based on the initial priority, battery state of charge, and real-time energy storage state data, the battery terminal temperature is used to obtain the short-term dynamic priority corresponding to the short-term scheduling command in each operating mode. The formula for calculating the short-term dynamic priority is as follows: in, express The short-term dynamic weight value of the short-term dynamic priority of the short-term dispatch command for photovoltaic power generation equipment under the current operating mode. express The short-term weighted benchmark values ​​of short-term dispatch instructions for photovoltaic power generation equipment under the current operating mode include the first short-term weighted benchmark value for stable operation mode, the second short-term weighted benchmark value for gradually changing operation mode, and the third short-term weighted benchmark value for drastic change operation mode. This represents the second adjustment coefficient indicating the impact of battery state-of-charge tracking error on short-term dynamic priority. This indicates the planned value of the battery's state of charge. This represents the second suppression coefficient indicating the impact of battery-side temperature tracking error on short-term dynamic priority. express The temperature value at the end of the energy storage battery at any given time. This indicates the optimal operating temperature of the energy storage battery, which is typically 25°C.

[0028] Then, based on the real-time dynamic weight value of the real-time dynamic priority and the short-term dynamic weight value of the short-term dynamic priority, the long-term dynamic weight value corresponding to the long-term scheduling instruction in each operating mode is obtained. The formula for calculating the long-term dynamic weight value is as follows: in, express The long-term dynamic weight value of the long-term dynamic priority of the long-term dispatch instructions for photovoltaic power generation equipment under the current operating mode.

[0029] In a preferred embodiment of this application, based on the obtained long-term dynamic priority of long-term dispatch instructions, short-term dynamic priority of short-term dispatch instructions, and real-time dynamic priority of real-time dispatch instructions under different operating modes of the photovoltaic power generation equipment, the long-term dispatch instructions, short-term dispatch instructions, and real-time dispatch instructions are adjusted. When the photovoltaic power generation equipment is in a rapidly changing operating mode, the weight of real-time dispatch instructions is increased to improve response speed and accuracy, achieve rapid compensation, and reduce the number of limit violations. When the photovoltaic power generation equipment is in a gradually changing operating mode, the weight of short-term dispatch instructions is increased, allowing the energy storage equipment to adjust slowly and extend its lifespan. When the photovoltaic power generation equipment is in a stable operating mode, the weight of long-term dispatch instructions is increased, prioritizing charging during low-price periods to reduce electricity costs. Compared to fixed weights, this approach offers greater flexibility, adapts to the dynamic changes of the photovoltaic power generation equipment, and improves the accuracy of power management.

[0030] S4. Based on the dynamic priority and the real-time energy storage status data, a dynamic compensation value is obtained, and a dynamic compensation command generated based on the dynamic compensation value is used to dynamically compensate and adjust the energy storage device. In the prior art, in the process of establishing a transfer function model of energy storage response delay to improve the matching accuracy between scheduling commands and actual discharge, the transfer function model generally adopts a simple linear model, and the parameters and fixed compensation time are experimentally calibrated. The linear model cannot reflect the time-varying hysteresis characteristics of the energy storage battery, such as the battery state of charge-corresponding delay coupling effect. The fixed compensation time leads to a large deviation between the charging and discharging command and the actual charging and discharging action, resulting in low accuracy of power dispatch. In the preferred embodiment of this application, a dynamic compensation value is obtained based on the dynamic priority and the real-time energy storage status data to generate a dynamic compensation command. Specifically, a real-time dynamic priority adjustment coefficient is obtained based on the real-time dynamic priority, a short-term dynamic priority adjustment coefficient is obtained based on the short-term dynamic priority, and a long-term dynamic priority adjustment coefficient is obtained based on the long-term dynamic priority and the energy storage battery terminal temperature value. The calculation formulas for the real-time dynamic priority adjustment coefficient, the short-term dynamic priority adjustment coefficient, and the long-term dynamic priority adjustment coefficient are as follows: in, express Real-time dynamic priority adjustment coefficient at any given moment. express The short-term dynamic priority adjustment coefficient at any given time. express The long-term dynamic priority adjustment coefficient at any given time.

[0031] Furthermore, the first dynamic compensation amount is obtained based on the ratio of the gain coefficient of the photovoltaic power generation equipment to the real-time dynamic priority adjustment coefficient; the second dynamic compensation amount is obtained based on the product of the short-term dynamic priority adjustment coefficient and the battery state of charge; the dynamic compensation adjustment coefficient is constructed based on the long-term dynamic priority adjustment coefficient, the energy storage equipment aging degradation coefficient of the real-time energy storage state data, and the cumulative number of completed charge-discharge cycles of the real-time energy storage state data; the dynamic compensation value is obtained based on the first dynamic compensation amount, the second dynamic compensation amount, and the dynamic compensation adjustment coefficient. The formula for calculating the dynamic compensation value is as follows: in, express The dynamic compensation value at any given time. express The first dynamic compensation amount at any given moment. This represents the gain coefficient of photovoltaic power generation equipment. express The second dynamic compensation amount at time. Represents a Laplace complex variable. This represents the aging and degradation coefficient of energy storage equipment. This indicates that the cumulative number of complete charge-discharge cycles has been completed. express The dynamic compensation adjustment coefficient at any given time. This represents the base delay time under standard operating conditions, which are defined as a battery terminal temperature of 25°C, zero charge / discharge cycles, and a state of charge (SOC) of 50%. Indicates the target number of iterations.

[0032] Dynamic compensation commands are generated based on dynamic compensation values ​​to act on energy storage devices, enabling them to perform dynamic compensation adjustments. This application constructs a nonlinear delay dynamic compensation model that dynamically correlates key variables with battery state of charge, energy storage battery terminal temperature, cumulative number of completed charge-discharge cycles, and dynamic priority, thereby improving the adaptability of energy storage devices to photovoltaic power generation devices.

[0033] In a preferred embodiment of this application, the fluctuation rate of the energy storage device corresponding to the previous m dynamic compensations, the real-time energy storage status data, and the historical sequence mapping data of the dynamic compensation value are recorded. A dynamic compensation prediction model is constructed based on the historical sequence mapping data. For the framework of the dynamic compensation prediction model, XGBoost (Extreme Gradient Boosting Network), CNN (Convolutional Neural Network), LSTM network, DQN (Deep Q Network), PPO (Proximal Policy Optimization), PID (Proportional-Integral-Derivative Control Algorithm), MPC (Model Predictive Control), Least Squares algorithm, and LSTM network (Long Short-Term Memory Network) can be selected. There is no limitation on the specific model selection, as long as it can achieve the prediction of dynamic compensation value. The above models are all existing technologies and will not be described in detail here.

[0034] The real-time fluctuation rate and real-time energy storage status data are input into the dynamic compensation prediction model to predict the dynamic compensation value, resulting in the current dynamic compensation prediction value, denoted as f. m+1 At this point, the actual dynamic compensation value for the current moment has not yet been calculated, and will be based on the predicted dynamic compensation value f. m+1 The generated dynamic compensation prediction command is sent to the energy storage device in advance to dynamically supplement and adjust the energy storage device. After receiving the actually calculated dynamic compensation command, the dynamic compensation prediction value and the corresponding dynamic compensation value F are compared. m+1The error value between the two values ​​is used to determine a threshold. If the error value is less than the preset error threshold, the current round of dynamic compensation adjustment ends. If the error value is greater than or equal to the error threshold, a correction supplement value and an overcompensation value are obtained based on the execution status of the dynamic compensation prediction command and the dynamic compensation prediction value and the dynamic compensation value at the same time. Specifically, if the dynamic compensation prediction value at the same time is less than the dynamic compensation value, regardless of whether the dynamic compensation prediction value has been executed, the correction supplement value is obtained directly based on the first difference between the dynamic compensation value and the dynamic compensation prediction value. The correction supplement command generated based on the correction supplement value is then sent to the energy storage device to correct and supplement the dynamic compensation prediction value so that the dynamic compensation amount reaches the dynamic compensation value. If the dynamic compensation prediction value at the same time is greater than the dynamic compensation value, the correction supplement value is obtained. If the dynamic compensation prediction value has been fully or partially executed, then the execution amount is obtained, and the second difference between the dynamic compensation value and the execution amount is calculated. If the second difference is greater than zero, then execution continues according to the dynamic compensation value. If the second difference is zero, then execution stops. At this time, the execution amount is consistent with the dynamic compensation value, no correction is needed, and there is no overcompensation. If the second difference is less than zero, then execution stops. At this time, the execution amount is greater than the dynamic compensation value, and there is overcompensation. The second difference is the overcompensation value. If the dynamic compensation prediction value is greater than the dynamic compensation value at the same time, and the dynamic compensation prediction value has not been executed, then the dynamic compensation value is used to generate a dynamic compensation instruction to replace the dynamic compensation prediction instruction of the dynamic compensation prediction value. This can be achieved simply by setting the priority of the dynamic compensation instruction to be greater than the priority of the dynamic compensation prediction instruction.

[0035] Furthermore, the time and value of overcompensation are recorded. Based on the overcompensation value, the dynamic compensation prediction value for the next moment is corrected to obtain the corrected dynamic compensation prediction value for the next moment. Specifically, the third difference between the dynamic compensation prediction value for the next moment and the overcompensation value can be used as the corrected dynamic compensation prediction value for the next moment. Based on the corrected dynamic compensation prediction value, a dynamic compensation prediction command for the next moment is generated to adjust the dynamic compensation of the energy storage device for the next moment.

[0036] Furthermore, the number of overcompensation events within a preset time period is counted. If the number of overcompensation events exceeds a preset overcompensation event threshold, the dynamic compensation prediction model is refitted to correct the parameters of the dynamic compensation prediction model and improve the accuracy of the dynamic compensation prediction value.

[0037] In a preferred embodiment of the present invention, real-time power generation data of photovoltaic power generation equipment and real-time energy storage status data of energy storage equipment are acquired; based on the fluctuation rate of real-time power generation data, the operating mode of photovoltaic power generation equipment corresponding to the power dispatch mode is determined, and based on the operating mode, the initial priority of dispatch instructions for different power dispatch modes is determined; based on real-time energy storage status data, fluctuation rate, operating mode, and initial priority, the dynamic priority corresponding to the dispatch instruction of each power dispatch mode under the current operating mode of photovoltaic power generation equipment is obtained, and the dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode; based on the dynamic priority and real-time energy storage status data, a dynamic compensation value is obtained, and the energy storage equipment is dynamically compensated and adjusted based on the dynamic compensation instruction generated according to the dynamic compensation value. This application discloses a power management method for photovoltaic-storage-direct-current-flexible building systems. Based on the fluctuation rate of real-time power generation data, the method categorizes photovoltaic (PV) power generation equipment into operating modes corresponding to power dispatch modes. Then, based on these operating modes, it determines the weight benchmark values ​​for long-term dispatch commands in long-term power dispatch mode, short-term dispatch commands in short-term dispatch mode, and real-time dispatch commands in real-time power dispatch mode. This determines the initial priority of each command, enabling timely responses to second-level fluctuations in PV power and reducing the risk of bus voltage and / or frequency exceeding limits. During the operation of the PV-storage-direct-current-flexible building system, the weight benchmark values ​​of each power dispatch command in each operating mode are adjusted based on the real-time energy storage status data and fluctuation rate of the energy storage equipment to obtain dynamic priorities. This allows for dynamic adjustment of the priority of each power dispatch command to adapt to the dynamic changes of PV power generation equipment, improving the accuracy of power management. A nonlinear delay dynamic compensation model is constructed based on battery state of charge, energy storage battery terminal temperature, cumulative number of completed charge-discharge cycles, and dynamic priorities. This model dynamically correlates key variables, improving the adaptability of the energy storage equipment to PV power generation equipment.

[0038] Accordingly, such as Figure 2 The diagram shows the structure of the power management system for a photovoltaic-storage-direction-flexible building. Based on a power management method for a photovoltaic-storage-direction-flexible building, this embodiment of the invention also provides a power management system for a photovoltaic-storage-direction-flexible building, which implements the power management method for a photovoltaic-storage-direction-flexible building disclosed in this embodiment of the invention, including: a data acquisition module 1, an initial priority determination module 2, a dynamic priority determination module 3, and a dynamic compensation adjustment module 4. The data acquisition module 1 is used to acquire real-time power generation data of photovoltaic power generation equipment and real-time energy storage status data of energy storage equipment in the target photovoltaic-storage-flexible building; The initial priority determination module 2 is used to determine the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode based on the fluctuation rate of the real-time power generation data, and to determine the initial priority of the dispatch instructions for different power dispatch modes based on the operating mode. The dynamic priority determination module 3 is used to obtain the dynamic priority of the dispatch instruction corresponding to each power dispatch mode under the current operating mode of the photovoltaic power generation equipment based on the real-time energy storage status data, the fluctuation rate, the operating mode and the initial priority. The dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode. The dynamic compensation adjustment module 4 is used to obtain a dynamic compensation value based on the dynamic priority and the real-time energy storage status data, and to perform dynamic compensation adjustment on the energy storage device based on the dynamic compensation value and the dynamic compensation command generated by the dynamic compensation value.

[0039] Specific limitations regarding the power management system for a photovoltaic-storage-direct-drive-flexible building can be found in the above-described limitations regarding the power management method for such a building, and will not be repeated here. Those skilled in the art will recognize that the various modules and steps described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0040] like Figure 3 The diagram shows the internal structure of a computer device. An embodiment of the present invention provides a computer device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps described above in the embodiment of the power management method for photovoltaic-storage-flexible buildings. Figure 1 Steps S1 to S4 as described above.

[0041] Those skilled in the art will understand that the illustrations Figure 3 This is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0042] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the computer device, connecting various parts of the computer device via various interfaces and lines.

[0043] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0044] If the modules integrated into the computer device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0045] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0046] Accordingly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the steps described in the embodiments of the power management method for photovoltaic-storage-flexible buildings as described above, for example... Figure 1 Steps S1 to S4 as described above.

[0047] In summary, the present application provides a method, system, device, and medium for power management in a photovoltaic-storage-direct-drive-flexible building system, addressing the technical problem of improving the flexibility and accuracy of power management in such systems. The method includes: acquiring real-time power generation data of the photovoltaic power generation equipment and real-time energy storage status data of the energy storage equipment; determining the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode based on the fluctuation rate of the real-time power generation data, and determining the initial priority of dispatch instructions for different power dispatch modes based on the operating mode; obtaining the dynamic priority corresponding to the dispatch instruction of each power dispatch mode under the current operating mode of the photovoltaic power generation equipment based on the real-time energy storage status data, fluctuation rate, operating mode, and initial priority, wherein the dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode; obtaining a dynamic compensation value based on the dynamic priority and real-time energy storage status data, and dynamically compensating and adjusting the energy storage equipment based on the dynamic compensation instruction generated according to the dynamic compensation value. This application discloses a power management method for photovoltaic-storage-direct-current-flexible building systems. Based on the fluctuation rate of real-time power generation data, the method categorizes photovoltaic (PV) power generation equipment into operating modes corresponding to power dispatch modes. Then, based on these operating modes, it determines the weight benchmark values ​​for long-term dispatch commands in long-term power dispatch mode, short-term dispatch commands in short-term dispatch mode, and real-time dispatch commands in real-time power dispatch mode. This determines the initial priority of each command, enabling timely responses to second-level fluctuations in PV power and reducing the risk of bus voltage and / or frequency exceeding limits. During the operation of the PV-storage-direct-current-flexible building system, the weight benchmark values ​​of each power dispatch command in each operating mode are adjusted based on the real-time energy storage status data and fluctuation rate of the energy storage equipment to obtain dynamic priorities. This allows for dynamic adjustment of the priority of each power dispatch command to adapt to the dynamic changes of PV power generation equipment, improving the accuracy of power management. A nonlinear delay dynamic compensation model is constructed based on battery state of charge, energy storage battery terminal temperature, cumulative number of completed charge-discharge cycles, and dynamic priorities. This model dynamically correlates key variables, improving the adaptability of the energy storage equipment to PV power generation equipment.

[0048] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0049] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the scope of the claims.

Claims

1. A power management method for photovoltaic-storage-flexible buildings, characterized in that, The method includes: Acquire real-time power generation data of photovoltaic power generation equipment and real-time energy storage status data of energy storage equipment within the target photovoltaic-storage-flexible building; Based on the fluctuation rate of the real-time power generation data, the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode is determined, and based on the operating mode, the initial priority of the dispatch instructions for different power dispatch modes is determined. Based on the real-time energy storage status data, the fluctuation rate, the operating mode, and the initial priority, the dynamic priority of the dispatch instruction corresponding to each power dispatch mode under the current operating mode of the photovoltaic power generation equipment is obtained. The dynamic priority is set to be determined by the influencing factors of each power dispatch mode under the current operating mode. Based on the dynamic priority and the real-time energy storage status data, a dynamic compensation value is obtained, and a dynamic compensation command is generated based on the dynamic compensation value to dynamically compensate and adjust the energy storage device.

2. The power management method for photovoltaic-storage-flexible buildings as described in claim 1, characterized in that, The step of determining the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode based on the fluctuation rate of the real-time power generation data includes: When the absolute value of the fluctuation rate of the real-time power generation data is greater than the first fluctuation rate threshold, the operating state of the photovoltaic power generation equipment is determined to be the dramatic operation mode corresponding to the real-time power dispatch mode of the power dispatch mode. When the absolute value of the fluctuation rate is less than or equal to the first fluctuation rate threshold and greater than the second fluctuation rate threshold, the operating state of the photovoltaic power generation equipment is determined to be a slow-change operating mode corresponding to the short-term power dispatch mode of the power dispatch mode. When the absolute value of the fluctuation rate is less than or equal to the second fluctuation rate threshold, the operating state of the photovoltaic power generation equipment is determined to be a stable operating mode corresponding to the long-term power dispatch mode of the power dispatch mode.

3. The power management method for photovoltaic-storage-flexible buildings as described in claim 2, characterized in that, The step of determining the initial priority of dispatch instructions for different power dispatch modes based on the operating mode includes: When the operating mode is the stable operating mode, a first initial priority is set for the long-term dispatching instructions of the long-term power dispatching mode, the short-term dispatching instructions of the short-term power dispatching mode, and the real-time dispatching instructions of the real-time power dispatching mode, wherein the long-term dispatching instructions have the highest long-term initial priority among the first initial priorities. When the operating mode is the gradual change operating mode, a second initial priority is set for the long-term scheduling instruction, the short-term scheduling instruction and the real-time scheduling instruction, wherein the short-term initial priority of the short-term scheduling instruction is the highest among the second initial priorities; When the operating mode is the dramatic change operating mode, a third initial priority is set for the long-term scheduling instruction, the short-term scheduling instruction and the real-time scheduling instruction, among which the real-time initial priority of the real-time scheduling instruction is the highest.

4. The power management method for photovoltaic-storage-flexible buildings as described in claim 3, characterized in that, The step of obtaining the dynamic priority of the dispatch instruction corresponding to each power dispatch mode of the photovoltaic power generation equipment under the current operating mode, based on the real-time energy storage status data, the fluctuation rate, the operating mode, and the initial priority, includes: Based on the initial priority, the fluctuation rate, and the battery state of charge of the real-time energy storage data, the real-time dynamic priority corresponding to the real-time scheduling instruction in each of the operating modes is obtained. Based on the initial priority, the battery state of charge, and the energy storage battery terminal temperature value of the real-time energy storage status data, the short-term dynamic priority corresponding to the short-term scheduling instruction in each of the operating modes is obtained. Based on the real-time dynamic priority and the short-term dynamic priority, the long-term dynamic priority corresponding to the long-term scheduling instruction in each of the operating modes is obtained.

5. The power management method for photovoltaic-storage-flexible buildings as described in claim 4, characterized in that, The step of obtaining the dynamic compensation value based on the dynamic priority and the real-time energy storage status data includes: Based on the real-time dynamic priority, a real-time dynamic priority adjustment coefficient is obtained; based on the short-term dynamic priority, a short-term dynamic priority adjustment coefficient is obtained; and based on the long-term dynamic priority and the energy storage battery terminal temperature value, a long-term dynamic priority adjustment coefficient is obtained. The first dynamic compensation amount is obtained based on the ratio of the gain coefficient of the photovoltaic power generation equipment to the real-time dynamic priority adjustment coefficient. The second dynamic compensation amount is obtained by multiplying the short-term dynamic priority adjustment coefficient and the battery state of charge. Based on the long-term dynamic priority adjustment coefficient, the energy storage device aging attenuation coefficient of the real-time energy storage status data, and the cumulative number of completed charge-discharge cycles of the real-time energy storage status data, a dynamic compensation adjustment coefficient is constructed. The dynamic compensation value is obtained based on the first dynamic compensation amount, the second dynamic compensation amount, and the dynamic compensation amount adjustment coefficient.

6. The power management method for photovoltaic-storage-flexible buildings as described in claim 1, characterized in that, The method further includes: Acquire historical sequence mapping data including the fluctuation rate, the real-time energy storage status data, and the dynamic compensation value, and construct a dynamic compensation prediction model based on the historical sequence mapping data; Based on the dynamic compensation prediction model, the dynamic compensation prediction value at the current moment is obtained, and the dynamic compensation prediction command generated based on the dynamic compensation prediction value is used to perform the dynamic compensation adjustment on the energy storage device. Receive the dynamic compensation instruction and perform a threshold judgment on the error value between the dynamic compensation prediction value and the dynamic compensation value corresponding to the dynamic compensation instruction. If the error value is less than the preset error threshold, then end the current round of dynamic compensation adjustment. If the error value is greater than or equal to the error threshold, then based on the execution status of the dynamic compensation prediction instruction, and the dynamic compensation prediction value and the dynamic compensation value at the same time, a correction supplement value and an overcompensation value are obtained, and a correction supplement instruction generated based on the correction supplement value is sent to the energy storage device to correct and supplement the dynamic compensation prediction value. Based on the overcompensation value, the predicted dynamic compensation value for the next moment is corrected to obtain the corrected predicted dynamic compensation value for the next moment, so as to adjust the dynamic compensation of the energy storage device for the next moment. The number of overcompensation events within a preset time period is counted. If the number of overcompensation events exceeds a preset overcompensation event threshold, the dynamic compensation prediction model is optimized to obtain the optimized dynamic compensation prediction model.

7. The power management method for photovoltaic-storage-flexible buildings as described in claim 6, characterized in that, The step of obtaining the corrected supplementary value and the overcompensation value based on the execution status of the dynamic compensation prediction instruction, and the dynamic compensation prediction value and the dynamic compensation value at the same time, includes: If the predicted value of dynamic compensation at the same time is less than the dynamic compensation value, then a corrected supplementary value is obtained based on the first difference between the dynamic compensation value and the predicted value of dynamic compensation. If the dynamic compensation prediction value at the same moment is greater than the dynamic compensation value, and the dynamic compensation prediction instruction has been executed completely or partially, then the execution amount is obtained, and a second difference between the dynamic compensation value and the execution amount is calculated. When the second difference is greater than zero, the energy storage device continues to execute according to the dynamic compensation instruction. When the second difference is equal to zero, the energy storage device stops executing. When the second difference is less than zero, the energy storage device stops executing, and the overcompensation value is obtained based on the second difference. If the predicted dynamic compensation value at the same time is greater than the predicted dynamic compensation value, and the predicted dynamic compensation instruction is not executed, then the energy storage device executes according to the predicted dynamic compensation instruction.

8. A power management system for a photovoltaic-storage-direct-drive-flexible building, used to implement the power management method for a photovoltaic-storage-direct-drive-flexible building as described in any one of claims 1-7, characterized in that, The system includes: a data acquisition module, an initial priority determination module, a dynamic priority determination module, and a dynamic compensation adjustment module; The data acquisition module is used to acquire real-time power generation data of photovoltaic power generation equipment and real-time energy storage status data of energy storage equipment; The initial priority determination module is used to determine the operating mode of the photovoltaic power generation equipment corresponding to the power dispatch mode based on the fluctuation rate of the real-time power generation data, and to determine the initial priority of the dispatch instructions for different power dispatch modes based on the operating mode. The dynamic priority determination module is used to obtain the dynamic priority of the dispatching instruction corresponding to each power dispatching mode under the current operating mode of the photovoltaic power generation equipment based on the real-time energy storage status data, the fluctuation rate, the operating mode and the initial priority. The dynamic priority is set to be determined by the influencing factors of each power dispatching mode under the current operating mode, and is used to adjust the priority of each dispatching instruction. The dynamic compensation adjustment module is used to obtain a dynamic compensation value based on the dynamic priority and the real-time energy storage status data, and to perform dynamic compensation adjustment on the energy storage device based on the dynamic compensation value and the dynamic compensation command generated by the dynamic compensation value.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a transceiver, which are connected to each other via a bus; the memory is used to store a set of computer program instructions and data, and to transmit the stored data to the processor, the processor executing the computer program instructions stored in the memory to perform the power management method of the photovoltaic-storage-direct-flex building as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that, when executed, implements the power management method for a photovoltaic-storage-flexible building as described in any one of claims 1 to 7.

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