Virtual power plant-based optical storage direct flexible intelligent micro-grid electric energy distribution method and system

Abstract

The invention provides a virtual power plant-based electric energy distribution method and system for an optical storage direct-flexible intelligent micro-grid. The method comprises the steps of determining corresponding accumulated residual electric energy of the optical storage direct-flexible intelligent micro-grid at different moments according to real-time capacity information, real-time load information and capacity residual information of the optical storage direct-flexible intelligent micro-grid; establishing a virtual power supply model, performing simulation power supply distribution according to the electric quantity demand information corresponding to each energy storage device, determining power supply energy corresponding to each energy storage device, transmitting the corresponding power supply energy to each energy storage device, determining a real-time energy storage structure of each energy storage device, and determining dynamic power consumption corresponding to each energy storage device; the original power supply proportion of the optical storage direct-flexible intelligent micro-grid is adjusted, power is supplied to each energy storage device according to the new power supply proportion, the virtual power plant is utilized to sell and distribute residual electric energy under the condition that normal power utilization of the equipment of the plant is guaranteed, the overall energy efficiency is high, resource configuration is optimized, and the power purchase cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy distribution, and in particular to an electric energy distribution method and system for a photovoltaic-storage-direct-flexible intelligent microgrid based on a virtual power plant. Background Art

[0002] The photovoltaic storage direct flexible smart microgrid is a new type of power grid system. The core of the system is to transform the rigid load of the photovoltaic DC building itself into a flexible load, and to intelligently control the power generation side, energy storage side and demand side of the photovoltaic storage direct flexible microgrid. The photovoltaic storage direct flexible smart microgrid integrates photovoltaic power generation, energy storage system and intelligent management technology. It collects solar energy through photovoltaic modules and uses energy storage devices (such as batteries) to store excess electricity for use when needed. This system usually has the following characteristics:

[0003] Utilization of renewable energy: mainly relying on solar energy to reduce dependence on fossil fuels.

[0004] Efficient energy storage system: It can store electricity when demand is low and release it during peak hours to balance supply and demand.

[0005] Smart management: Optimize power generation, storage and consumption through intelligent control systems to improve overall energy efficiency.

[0006] Flexibility and reliability: It can work in different operation modes, such as grid-connected or off-grid mode, to adapt to various application scenarios.

[0007] This microgrid system is of great significance in improving energy self-sufficiency, reducing carbon emissions, and improving the reliability of power supply.

[0008] With the advancement of technology, solar-storage, direct-flexible smart microgrids are gradually entering the electricity market with their favorable advantages. However, they can only be used for simple energy storage at present and cannot effectively distribute electricity according to the power demand of different equipment.

[0009] Therefore, the present invention provides a method and system for distributing electric energy in a photovoltaic, direct-current and flexible intelligent microgrid based on a virtual power plant. Summary of the invention

[0010] The photovoltaic-storage-direct-flexible intelligent microgrid power distribution method and system based on the virtual power plant of the present invention can determine the production capacity of the photovoltaic-storage-direct-flexible intelligent microgrid according to the current environmental conditions, and flexibly adjust the operating time of power-consuming equipment according to the real-time load conditions of the power grid to balance supply and demand.

[0011] The present invention provides a method for distributing electric energy of a photovoltaic, storage, direct-current and flexible intelligent microgrid based on a virtual power plant, comprising:

[0012] Step 1: According to the real-time capacity information and real-time load information of the photovoltaic storage direct flexible smart microgrid, determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic storage direct flexible smart microgrid at different times;

[0013] Step 2: Establish a virtual power supply model of the solar-storage-direct-flexible smart microgrid, simulate power supply distribution according to the power demand information corresponding to each energy storage device in the virtual power supply model, and determine the power supply energy corresponding to each energy storage device;

[0014] Step 3: transmitting corresponding power supply energy to each of the energy storage devices respectively, and inputting the real-time energy storage feedback information corresponding to each of the energy storage devices into the virtual power supply model to determine the real-time energy storage structure of each of the energy storage devices;

[0015] Step 4: Determine the dynamic power consumption corresponding to each of the energy storage devices, adjust the original power supply ratio of the photovoltaic storage direct flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio.

[0016] In one practicable manner,

[0017] The step 1 comprises:

[0018] Step 11: Collect the power generation environment information of the photovoltaic storage direct flexible smart microgrid, perform capacity analysis on each power generation mode in the photovoltaic storage direct flexible smart microgrid according to the power generation environment information, construct a real-time power chart corresponding to each power generation mode, and use the basic data corresponding to each power generation mode and the real-time power chart to analyze the real-time capacity information of the photovoltaic storage direct flexible smart microgrid;

[0019] Step 12: Obtain equipment data of the photovoltaic, storage, direct and flexible smart microgrid, calculate the average load value, peak load value and basic load of the photovoltaic, storage, direct and flexible smart microgrid according to the equipment data, determine the load factor of the photovoltaic, storage, direct and flexible smart microgrid using the average load value and the peak load value, correct the basic load using the load factor, and obtain real-time load information of the photovoltaic, storage, direct and flexible smart microgrid;

[0020] Step 13: Determine the remaining capacity information of the photovoltaic, storage, direct and flexible smart microgrid based on the real-time capacity information and the real-time load information, calibrate the remaining capacity information using the real-time working data of the photovoltaic, storage, direct and flexible smart microgrid, and obtain the corresponding accumulated remaining electric energy of the photovoltaic, storage, direct and flexible smart microgrid at different times based on the preset electric energy calculation method.

[0021] In one practicable manner,

[0022] The step 2 comprises:

[0023] Step 21: Perform multi-rule processing on the grid data of the photovoltaic storage direct flexible smart microgrid to obtain several power plant power supply business flows of the photovoltaic storage direct flexible smart microgrid, and respectively determine the working mode corresponding to each of the power plant power supply business flows, generate a model framework using the logical relationship between the different working modes, map the business flows into the model framework to make business decisions and generate a virtual power supply model of the photovoltaic storage direct flexible smart microgrid;

[0024] Step 22: respectively obtain the power demand information corresponding to each energy storage device, respectively add a first allocation weight to each of the power demand information in the virtual power supply model, calculate a first allocation amount corresponding to each of the first allocation weights according to the accumulated remaining power, and simulate the power transmission buffer time corresponding to each of the energy storage devices in the virtual power supply model;

[0025] Step 23: performing iterative energy reduction processing on the target energy storage devices whose power transmission buffer time is unqualified, and determining the second allocation amount corresponding to each of the target energy storage devices;

[0026] Step 24: Count the second allocation amount corresponding to each of the energy storage devices, determine the current power supply allocation ratio of the photovoltaic storage direct flexible smart microgrid to each of the energy storage devices, use the current power supply allocation ratio and the accumulated remaining electric energy to calculate the power supply energy range corresponding to each of the energy storage devices, and determine the power supply energy corresponding to each of the energy storage devices.

[0027] In one practicable manner,

[0028] The step 23 comprises:

[0029] Step 231: Establishing a duration classification level using a preset buffer standard, performing cluster analysis on the power transmission buffer duration using the duration classification level to generate a corresponding level class, screening out unqualified level classes to be processed, and locating a target energy storage device corresponding to each unqualified power transmission buffer duration in the level class to be processed;

[0030] Step 232: establishing a buffer time axis according to the corresponding non-qualified power transmission buffer duration, simulating the power transmission process corresponding to the target energy storage device in the virtual power supply model, and mapping the power transmission process in the corresponding buffer time axis to obtain a power buffer process axis;

[0031] Step 233: extracting a number of jamming moments in each of the electric energy buffering process axes where the buffering amount is lower than the corresponding average buffering amount, counting the amount to be buffered at each of the jamming moments, and reducing the amount to be buffered using a preset iteration step cycle to obtain a number of iterative electric energies corresponding to each of the target energy storage devices, and iteratively simulating the corresponding target energy storage devices in the virtual power supply model according to each of the iterative electric energies to obtain a number of simulation results;

[0032] Step 234: Filter the target iterative electric energy with a qualified electric energy transmission buffer time of each of the energy storage devices in the simulation results, and obtain the maximum value of the target iterative electric energy as the second allocation amount corresponding to the target energy storage device.

[0033] In one practicable manner,

[0034] The step 3 comprises:

[0035] Step 31: supplying energy to each of the energy storage devices respectively, and obtaining real-time energy storage feedback information corresponding to each of the energy storage devices respectively, and determining the external power supply corresponding to each of the energy storage devices according to the real-time energy storage feedback information;

[0036] Step 32: input the real-time energy storage feedback information into the virtual power supply model for synchronous monitoring, and determine the external power supply rate and internal memory rate corresponding to each energy storage device in combination with the external power supply amount corresponding to each energy storage device;

[0037] Step 33: Establishing a real-time energy storage structure for each energy storage device based on the external supply rate and internal memory rate corresponding to the same energy storage device.

[0038] In one practicable manner,

[0039] The step 4 comprises:

[0040] Step 41: Visualize the real-time energy storage structure to obtain an energy flow chart corresponding to each energy storage device, obtain a plurality of dynamic information presented in the energy flow chart, extract the dynamic core corresponding to each dynamic information, and generate a dynamic power consumption corresponding to each energy storage device;

[0041] Step 42: Obtain the original power supply ratio of the photovoltaic storage direct-flexible smart microgrid, estimate the remaining power supply time corresponding to each energy storage device according to the original power supply ratio and dynamic power consumption, and select high-energy consumption energy storage devices whose remaining power supply time is lower than the standard power supply time;

[0042] Step 43: using the high-energy dynamic power consumption corresponding to the high-energy storage device to adjust the original power supply ratio to generate a new power supply ratio, and using the new power supply ratio combined with the accumulated residual power to supply power to each of the energy storage devices respectively.

[0043] In one practicable manner,

[0044] The step 4 further includes:

[0045] Screen low-energy storage devices whose dynamic power consumption is within the low-energy consumption range, and determine the unit power supply corresponding to each low-energy storage device by the photovoltaic storage direct-flexible smart microgrid according to the original power supply ratio;

[0046] The unit power supply is distributed to corresponding high-energy-consuming energy storage devices to generate a new power supply ratio.

[0047] In one practicable manner,

[0048] Also includes:

[0049] Counting the total amount of electric energy provided by the solar-storage-direct-flexible smart microgrid to each of the energy storage devices during a periodic time period;

[0050] The profit and loss statement of the solar-storage-direct-flexible smart microgrid during the periodic time period is calculated and displayed.

[0051] The present invention provides a photovoltaic storage direct-flexible intelligent microgrid power distribution system based on a virtual power plant, comprising:

[0052] A power generation supervision module is used to determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid according to the real-time capacity information and real-time load information of the photovoltaic storage direct flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic storage direct flexible smart microgrid at different times;

[0053] An electric energy distribution module is used to establish a virtual power supply model of the photovoltaic storage direct-flexible smart microgrid, simulate power supply distribution in the virtual power supply model according to the power demand information corresponding to each energy storage device, and determine the power supply energy corresponding to each energy storage device;

[0054] A virtual analysis module, used to transmit corresponding power supply energy to each of the energy storage devices respectively, and input the real-time energy storage feedback information corresponding to each of the energy storage devices into the virtual power supply model to determine the real-time energy storage structure of each of the energy storage devices;

[0055] The feedback adjustment module is used to determine the dynamic power consumption corresponding to each of the energy storage devices, adjust the original power supply ratio of the photovoltaic storage direct flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio.

[0056] In one practicable manner,

[0057] The electric energy distribution module comprises:

[0058] The first allocation execution unit is used to perform multi-rule processing on the grid data of the photovoltaic storage direct flexible smart microgrid to obtain a plurality of power plant power supply business flows of the photovoltaic storage direct flexible smart microgrid, and respectively determine the working mode corresponding to each of the power plant power supply business flows, generate a model framework using the logical relationship between the different working modes, map the business flows into the model framework to make business decisions and generate a virtual power supply model of the photovoltaic storage direct flexible smart microgrid;

[0059] A second allocation execution unit is used to respectively obtain the electric energy demand information corresponding to each energy storage device, respectively add a first allocation weight to each of the electric energy demand information in the virtual power supply model, calculate a first allocation amount corresponding to each of the first allocation weights according to the accumulated residual electric energy, and simulate the electric energy transmission buffer time corresponding to each of the energy storage devices in the virtual power supply model;

[0060] A third allocation execution unit is used to iteratively reduce the energy of target energy storage devices that fail to meet the power transmission buffer time requirements, and determine a second allocation amount corresponding to each target energy storage device;

[0061] The fourth allocation execution unit is used to count the second allocation amount corresponding to each of the energy storage devices, determine the current power supply allocation ratio of the photovoltaic storage direct flexible intelligent microgrid to each of the energy storage devices, calculate the power supply energy range corresponding to each of the energy storage devices using the current power supply allocation ratio and the accumulated remaining electric energy, and determine the power supply energy corresponding to each of the energy storage devices.

[0062] The achievable beneficial effects of the above technical solution are: in order to avoid energy waste in the photovoltaic storage direct flexible smart microgrid and improve profitability, when the photovoltaic storage direct flexible smart microgrid generates electricity, it is monitored in real time to determine the accumulated residual electric energy, and then virtual technology is used to simulate the energy distribution process to determine the power supply energy of each energy storage device, and then the corresponding power supply work is carried out. During the power supply process, the original power supply ratio is adjusted according to the feedback of the energy storage device to avoid the phenomenon of insufficient power supply of the energy storage device. Through feedback optimization, the power is adjusted and distributed in real time to achieve a balance between production capacity, supply and storage, reduce energy waste, and optimize power generation, energy storage and power consumption while ensuring the normal power consumption of the factory equipment, improve overall energy efficiency, optimize resource allocation, and reduce power procurement costs.

[0063] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0064] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0066] Figure 1 A schematic diagram of the working process of a photovoltaic-storage-direct-flexible smart microgrid power distribution method based on a virtual power plant in an embodiment of the present invention;

[0067] Figure 2 Schematic diagram of the composition of a photovoltaic, storage, direct-flexible, intelligent microgrid power distribution system based on a virtual power plant in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0069] Example 1

[0070] This embodiment provides a method and system for distributing power in a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant. Figure 1 As shown, including:

[0071] Step 1: According to the real-time capacity information and real-time load information of the photovoltaic storage direct flexible smart microgrid, determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic storage direct flexible smart microgrid at different times;

[0072] Step 2: Establish a virtual power supply model of the solar-storage-direct-flexible smart microgrid, simulate power supply distribution according to the power demand information corresponding to each energy storage device in the virtual power supply model, and determine the power supply energy corresponding to each energy storage device;

[0073] Step 3: transmitting corresponding power supply energy to each of the energy storage devices respectively, and inputting the real-time energy storage feedback information corresponding to each of the energy storage devices into the virtual power supply model to determine the real-time energy storage structure of each of the energy storage devices;

[0074] Step 4: Determine the dynamic power consumption corresponding to each of the energy storage devices, adjust the original power supply ratio of the photovoltaic storage direct flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio.

[0075] In this example, the electric energy in the solar-storage-direct-flexible smart microgrid is first supplied to its own equipment, and the excess power is supplied to the energy storage equipment. Generally speaking, the excess power is much greater than the self-supplied power;

[0076] In this example, the real-time capacity information indicates the information of the electric energy generated by the photovoltaic storage direct flexible smart microgrid in real time. The ways in which the photovoltaic storage direct flexible smart microgrid generates electric energy include: wind power generation, hydropower generation, thermal power generation, and solar power generation;

[0077] In this example, the real-time load information represents the load situation of the PV-storage-direct-flexible smart microgrid itself;

[0078] In this example, the surplus capacity information represents the real-time excess power generated by the PV-storage-direct-flexible smart microgrid;

[0079] In this example, the accumulated surplus electric energy means the electric energy temporarily stored in the photovoltaic storage direct-flexible smart microgrid and not distributed;

[0080] In this example, the virtual power supply model represents a three-dimensional model in which the photovoltaic storage direct-flexible smart microgrid supplies energy to various devices in a virtual manner;

[0081] In this example, the power demand information indicates the amount of power required by an energy storage device. For example, the current power of energy storage device A is 80, and 20 power is required.

[0082] In this example, the simulated power supply distribution represents the process of distributing power to each energy storage device in the virtual power supply model;

[0083] In this example, the real-time energy storage feedback information indicates the response of the energy storage device to the power supply work when the energy storage device is powered;

[0084] In this example, the dynamic power consumption indicates the amount of power consumed by the energy storage device.

[0085] The working principle and beneficial effects of the above technical solution: In order to avoid energy waste in the photovoltaic storage direct flexible smart microgrid and improve profitability, when the photovoltaic storage direct flexible smart microgrid generates electricity, it is monitored in real time to determine the accumulated residual electricity, and then virtual technology is used to simulate the energy distribution process to determine the power supply energy of each energy storage device, and then the corresponding power supply work is carried out. During the power supply process, the original power supply ratio is adjusted according to the feedback of the energy storage device to avoid the phenomenon of insufficient power supply of the energy storage device. Through feedback optimization, the power is adjusted and distributed in real time to achieve a balance between production capacity, supply and storage, reduce energy waste, and optimize power generation, energy storage and power consumption while ensuring the normal power consumption of the factory equipment, improve overall energy efficiency, optimize resource allocation, and reduce power procurement costs.

[0086] Example 2

[0087] On the basis of Example 1, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant, step 1 comprises:

[0088] Step 11: Collect the power generation environment information of the photovoltaic storage direct flexible smart microgrid, perform capacity analysis on each power generation mode in the photovoltaic storage direct flexible smart microgrid according to the power generation environment information, construct a real-time power chart corresponding to each power generation mode, and use the basic data corresponding to each power generation mode and the real-time power chart to analyze the real-time capacity information of the photovoltaic storage direct flexible smart microgrid;

[0089] Step 12: Obtain equipment data of the photovoltaic, storage, direct and flexible smart microgrid, calculate the average load value, peak load value and basic load of the photovoltaic, storage, direct and flexible smart microgrid according to the equipment data, determine the load factor of the photovoltaic, storage, direct and flexible smart microgrid using the average load value and the peak load value, correct the basic load using the load factor, and obtain real-time load information of the photovoltaic, storage, direct and flexible smart microgrid;

[0090] Step 13: Determine the remaining capacity information of the photovoltaic, storage, direct and flexible smart microgrid based on the real-time capacity information and the real-time load information, calibrate the remaining capacity information using the real-time working data of the photovoltaic, storage, direct and flexible smart microgrid, and obtain the corresponding accumulated remaining electric energy of the photovoltaic, storage, direct and flexible smart microgrid at different times based on the preset electric energy calculation method.

[0091] In this example, the power generation environment information represents information such as wind power, solar energy, water potential energy, geothermal energy, and tidal energy of the power generation environment;

[0092] In this example, the power generation methods include: thermal power generation, hydropower generation, solar power generation, geothermal power generation, tidal power generation, etc.;

[0093] In this example, the real-time power chart represents a line chart established based on the real-time power of a power generation method at different times;

[0094] In this example, the basic data represents the data generated by a power generation method when generating electricity;

[0095] In this example, the device data represents the data of all devices in the solar-storage-direct-flexible smart microgrid;

[0096] In this example, the average load value represents the average value of the load values ​​of the PV-storage direct-flexible smart microgrid at all times;

[0097] In this example, the peak load value represents the maximum load value of the PV-storage-direct-flexible smart microgrid;

[0098] In this instance, the load factor represents a coefficient used to adjust or evaluate the relationship between the actual load and the theoretical load under a specific condition;

[0099] In this example, the preset electric energy calculation method represents a method of converting the production capacity information into electric energy.

[0100] The working principle and beneficial effects of the above technical solution: In order to effectively distribute electric energy, the production capacity is first analyzed according to the environmental information of the power generation environment to determine the real-time production capacity information of the photovoltaic, storage, direct and flexible smart microgrid. Then, the real-time load information of the photovoltaic, storage, direct and flexible smart microgrid is further determined in combination with the equipment data of the photovoltaic, storage, direct and flexible smart microgrid. Finally, the remaining production capacity information of the photovoltaic, storage, direct and flexible smart microgrid and its accumulated remaining power are determined. By integrating multi-sensor technology, real-time monitoring technology, and environmental multi-source detection, accurate production capacity is obtained.

[0101] Example 3

[0102] On the basis of Example 2, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant, step 2 comprises:

[0103] Step 21: Perform multi-rule processing on the grid data of the photovoltaic storage direct flexible smart microgrid to obtain several power plant power supply business flows of the photovoltaic storage direct flexible smart microgrid, and respectively determine the working mode corresponding to each of the power plant power supply business flows, generate a model framework using the logical relationship between the different working modes, map the business flows into the model framework to make business decisions and generate a virtual power supply model of the photovoltaic storage direct flexible smart microgrid;

[0104] Step 22: respectively obtain the power demand information corresponding to each energy storage device, respectively add a first allocation weight to each of the power demand information in the virtual power supply model, calculate a first allocation amount corresponding to each of the first allocation weights according to the accumulated remaining power, and simulate the power transmission buffer time corresponding to each of the energy storage devices in the virtual power supply model;

[0105] Step 23: performing iterative energy reduction processing on the target energy storage devices whose power transmission buffer time is unqualified, and determining the second allocation amount corresponding to each of the target energy storage devices;

[0106] Step 24: Count the second allocation amount corresponding to each of the energy storage devices, determine the current power supply allocation ratio of the photovoltaic storage direct flexible smart microgrid to each of the energy storage devices, use the current power supply allocation ratio and the accumulated remaining electric energy to calculate the power supply energy range corresponding to each of the energy storage devices, and determine the power supply energy corresponding to each of the energy storage devices.

[0107] In this example, multi-rule processing refers to a service flow separation method established according to the logical conditions between different services in the PV-storage-direct-flexible smart microgrid. Since different services may overlap, each service corresponds to a rule and is processed by multiple rules.

[0108] In this example, the power plant power supply business flow represents the activities and steps of the photovoltaic storage direct-flexible smart microgrid in performing power supply business;

[0109] In this example, the working mode indicates the mode in which the power supply business flow of the power plant performs power supply;

[0110] In this example, the first allocation weight represents a weight on the amount of electric energy allocation established according to the electric energy demand information;

[0111] In this example, the power transmission buffer duration represents the duration required for storing the first allocated amount of power of an energy storage device;

[0112] In this example, the first allocation amount represents the electric energy that needs to be stored in the energy storage device determined according to the first allocation weight and the accumulated remaining power;

[0113] In this example, the iterative energy reduction process represents a process of iteratively reducing the first allocated amount;

[0114] In this example, the current power supply allocation ratio represents an allocation ratio determined according to the ratio between the second allocation amounts;

[0115] In this example, the power supply energy range indicates that the power received by the energy storage device is different due to the change of the accumulated residual power, but the specific value is generally stable within this range;

[0116] In this example, the power supply energy is the average value of the power supply energy range.

[0117] The working principle and beneficial effects of the above technical solution: In order to improve the overall efficiency and economy of the photovoltaic, storage, direct and flexible smart microgrid, it is necessary to distribute electric energy reasonably. First, the grid data of the photovoltaic, storage, direct and flexible smart microgrid is processed, and multiple power supply business flows of power plants are constructed. The power supply business flows of power plants are arranged and processed according to the framework to generate a virtual power supply model of the photovoltaic, storage, direct and flexible smart microgrid. Then, in the model, electric energy is distributed according to the power demand information of each energy storage device. Then, the transmission buffer time of each energy storage device when receiving electric energy is analyzed, and the allocation amount of the energy storage device with too slow transmission buffer is reduced. At the same time, in order to ensure the effectiveness of the energy reduction processing and avoid excessive energy reduction, an iterative processing method is adopted. Finally, the accumulated residual electric energy is combined to determine the power supply energy range of each energy storage device, and the power supply energy of the energy storage device is obtained. In this way, the photovoltaic, storage, direct and flexible smart microgrid can accurately supply power to each energy storage device and sell excess electric energy to energy storage devices of various large power grids, thereby increasing the revenue of the photovoltaic, storage, direct and flexible smart microgrid.

[0118] Example 4

[0119] On the basis of Example 3, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant, step 23 includes:

[0120] Step 231: Establishing a duration classification level using a preset buffer standard, performing cluster analysis on the power transmission buffer duration using the duration classification level to generate a corresponding level class, screening out unqualified level classes to be processed, and locating a target energy storage device corresponding to each unqualified power transmission buffer duration in the level class to be processed;

[0121] Step 232: establishing a buffer time axis according to the corresponding non-qualified power transmission buffer duration, simulating the power transmission process corresponding to the target energy storage device in the virtual power supply model, and mapping the power transmission process in the corresponding buffer time axis to obtain a power buffer process axis;

[0122] Step 233: extracting a number of jamming moments in each of the electric energy buffering process axes where the buffering amount is lower than the corresponding average buffering amount, counting the amount to be buffered at each of the jamming moments, and reducing the amount to be buffered using a preset iteration step cycle to obtain a number of iterative electric energies corresponding to each of the target energy storage devices, and iteratively simulating the corresponding target energy storage devices in the virtual power supply model according to each of the iterative electric energies to obtain a number of simulation results;

[0123] Step 234: Filter the target iterative electric energy with a qualified electric energy transmission buffer time of each of the energy storage devices in the simulation results, and obtain the maximum value of the target iterative electric energy as the second allocation amount corresponding to the target energy storage device.

[0124] In this example, the preset buffer standard indicates that 70% of the capacity of the energy storage device that can be stored per hour is level one, 50% is level two, and less than 50% is level three;

[0125] In this example, the duration classification level indicates that different charging durations correspond to different levels;

[0126] In this example, the buffer duration time axis represents the buffer duration generated by using a time axis;

[0127] In this example, the electric energy buffering process axis shows the corresponding buffered electric energy at each moment;

[0128] In this example, the target iterative electric energy represents several types of electric energy that can be smoothly transmitted and buffered by the energy storage device.

[0129] The working principle and beneficial effects of the above technical solution are as follows: a clustering algorithm is used to classify energy storage devices with the same duration level into one category, and then unqualified target energy storage devices are screened out, and a buffer time axis is constructed according to the corresponding unqualified power transmission buffer duration, and an energy buffer process axis of the target energy storage device is constructed by simulating the power transmission process, and the stuck moments are located, and the electric energy at the stuck moments is gradually weakened, and finally the largest iterative electric energy is screened out as the second allocation of the target energy storage device. In this way, the power supply efficiency of the energy storage device can be guaranteed, and the phenomenon of energy storage device failure caused by overpowering can be avoided.

[0130] Example 5

[0131] On the basis of Example 1, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant, step 3 comprises:

[0132] Step 31: supplying energy to each of the energy storage devices respectively, and obtaining real-time energy storage feedback information corresponding to each of the energy storage devices respectively, and determining the external power supply corresponding to each of the energy storage devices according to the real-time energy storage feedback information;

[0133] Step 32: input the real-time energy storage feedback information into the virtual power supply model for synchronous monitoring, and determine the external power supply rate and internal memory rate corresponding to each energy storage device in combination with the external power supply amount corresponding to each energy storage device;

[0134] Step 33: Establishing a real-time energy storage structure for each energy storage device based on the external supply rate and internal memory rate corresponding to the same energy storage device.

[0135] The working principle and beneficial effects of the above technical solution are as follows: when supplying energy to the energy storage device, the amount of electric energy supplied by the energy storage device to other devices is determined based on its feedback information. At the same time, the real-time energy storage feedback information is synchronously monitored using a virtual power supply model to determine the supply rate of the energy storage device in different dimensions, thereby establishing its real-time energy storage structure. The real-time energy storage structure can then be used to understand the real-time working conditions of the energy storage device.

[0136] Example 6

[0137] On the basis of Example 1, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant, step 4 comprises:

[0138] Step 41: Visualize the real-time energy storage structure to obtain an energy flow chart corresponding to each energy storage device, obtain a plurality of dynamic information presented in the energy flow chart, extract the dynamic core corresponding to each dynamic information, and generate a dynamic power consumption corresponding to each energy storage device;

[0139] Step 42: Obtain the original power supply ratio of the photovoltaic storage direct-flexible smart microgrid, estimate the remaining power supply time corresponding to each energy storage device according to the original power supply ratio and dynamic power consumption, and select high-energy consumption energy storage devices whose remaining power supply time is lower than the standard power supply time;

[0140] Step 43: using the high-energy dynamic power consumption corresponding to the high-energy storage device to adjust the original power supply ratio to generate a new power supply ratio, and using the new power supply ratio combined with the accumulated residual power to supply power to each of the energy storage devices respectively.

[0141] In this example, the standard power supply duration is 24 hours.

[0142] The working principle and beneficial effects of the above technical solution are as follows: the dynamic power consumption of the energy storage equipment is determined by visualizing the real-time energy storage structure, and then high-consumption energy storage equipment with insufficient remaining power is screened, and the power supply to the high-consumption energy storage equipment is increased by adjusting the original power supply ratio, thereby efficiently supplying power to the high-consumption energy storage equipment and avoiding power outages.

[0143] Example 7

[0144] On the basis of Example 6, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant, the step 4 further includes:

[0145] Screen low-energy storage devices whose dynamic power consumption is within the low-energy consumption range, and determine the unit power supply corresponding to each low-energy storage device by the photovoltaic storage direct-flexible smart microgrid according to the original power supply ratio;

[0146] The unit power supply is distributed to corresponding high-energy-consuming energy storage devices to generate a new power supply ratio.

[0147] The working principle and beneficial effects of the above technical solution: The above method can reasonably distribute the electric energy of each energy storage device.

[0148] Example 8

[0149] On the basis of Example 1, the photovoltaic storage direct-flexible smart microgrid power distribution method based on a virtual power plant further includes:

[0150] Counting the total amount of electric energy provided by the solar-storage-direct-flexible smart microgrid to each of the energy storage devices during a periodic time period;

[0151] The profit and loss statement of the solar-storage-direct-flexible smart microgrid during the periodic time period is calculated and displayed.

[0152] The working principle and beneficial effects of the above technical solution are as follows: excess electricity is sold to energy storage devices of various large power grids, which increases revenue and produces profit and loss statements for management personnel to view at any time.

[0153] Example 9

[0154] This embodiment provides a photovoltaic storage direct-flexible smart microgrid power distribution system based on a virtual power plant, such as Figure 2 As shown, including:

[0155] A power generation supervision module is used to determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid according to the real-time capacity information and real-time load information of the photovoltaic storage direct flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic storage direct flexible smart microgrid at different times;

[0156] An electric energy distribution module is used to establish a virtual power supply model of the photovoltaic storage direct-flexible smart microgrid, simulate power supply distribution in the virtual power supply model according to the power demand information corresponding to each energy storage device, and determine the power supply energy corresponding to each energy storage device;

[0157] A virtual analysis module, used to transmit corresponding power supply energy to each of the energy storage devices respectively, and input the real-time energy storage feedback information corresponding to each of the energy storage devices into the virtual power supply model to determine the real-time energy storage structure of each of the energy storage devices;

[0158] The feedback adjustment module is used to determine the dynamic power consumption corresponding to each of the energy storage devices, adjust the original power supply ratio of the photovoltaic storage direct flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio.

[0159] In this example, the electric energy in the solar-storage-direct-flexible smart microgrid is first supplied to its own equipment, and the excess power is supplied to the energy storage equipment. Generally speaking, the excess power is much greater than the self-supplied power;

[0160] In this example, the real-time capacity information indicates the information of the electric energy generated in real time by the photovoltaic storage direct flexible smart microgrid. The ways in which the photovoltaic storage direct flexible smart microgrid generates electric energy include: wind power generation, hydropower generation, thermal power generation, and solar power generation;

[0161] In this example, the real-time load information represents the load situation of the PV-storage-direct-flexible smart microgrid itself;

[0162] In this example, the surplus capacity information represents the real-time excess power generated by the PV-storage-direct-flexible smart microgrid;

[0163] In this example, the accumulated surplus electric energy means the electric energy temporarily stored in the photovoltaic storage direct flexible smart microgrid and not distributed;

[0164] In this example, the virtual power supply model represents a three-dimensional model in which the photovoltaic storage direct-flexible smart microgrid supplies energy to various devices in a virtual manner;

[0165] In this example, the power demand information indicates the amount of power required by an energy storage device. For example, the current power of energy storage device A is 80, and 20 power is required.

[0166] In this example, the simulated power supply distribution represents the process of distributing power to each energy storage device in the virtual power supply model;

[0167] In this example, the real-time energy storage feedback information indicates the response of the energy storage device to the power supply work when the energy storage device is powered;

[0168] In this example, the dynamic power consumption indicates the amount of power consumed by the energy storage device.

[0169] The working principle and beneficial effects of the above technical solution: In order to avoid energy waste in the photovoltaic storage direct flexible smart microgrid and improve profitability, when the photovoltaic storage direct flexible smart microgrid generates electricity, it is monitored in real time to determine the accumulated residual electricity, and then virtual technology is used to simulate the energy distribution process to determine the power supply energy of each energy storage device, and then the corresponding power supply work is carried out. During the power supply process, the original power supply ratio is adjusted according to the feedback of the energy storage device to avoid the phenomenon of insufficient power supply of the energy storage device. Through feedback optimization, the power is adjusted and distributed in real time to achieve a balance between production capacity, supply and storage, reduce energy waste, and optimize power generation, energy storage and power consumption while ensuring the normal power consumption of the factory equipment, improve overall energy efficiency, optimize resource allocation, and reduce power procurement costs.

[0170] Example 10

[0171] On the basis of Example 9, the photovoltaic storage direct-flexible intelligent microgrid power distribution system based on the virtual power plant, the power distribution module includes:

[0172] The first allocation execution unit is used to perform multi-rule processing on the grid data of the photovoltaic storage direct flexible smart microgrid to obtain a plurality of power plant power supply business flows of the photovoltaic storage direct flexible smart microgrid, and respectively determine the working mode corresponding to each of the power plant power supply business flows, generate a model framework using the logical relationship between the different working modes, map the business flows into the model framework to make business decisions and generate a virtual power supply model of the photovoltaic storage direct flexible smart microgrid;

[0173] A second allocation execution unit is used to respectively obtain the electric energy demand information corresponding to each energy storage device, respectively add a first allocation weight to each of the electric energy demand information in the virtual power supply model, calculate a first allocation amount corresponding to each of the first allocation weights according to the accumulated residual electric energy, and simulate the electric energy transmission buffer time corresponding to each of the energy storage devices in the virtual power supply model;

[0174] A third allocation execution unit is used to iteratively reduce the energy of target energy storage devices that fail to meet the power transmission buffer time requirements, and determine a second allocation amount corresponding to each target energy storage device;

[0175] The fourth allocation execution unit is used to count the second allocation amount corresponding to each of the energy storage devices, determine the current power supply allocation ratio of the photovoltaic storage direct flexible intelligent microgrid to each of the energy storage devices, calculate the power supply energy range corresponding to each of the energy storage devices using the current power supply allocation ratio and the accumulated remaining electric energy, and determine the power supply energy corresponding to each of the energy storage devices.

[0176] In this example, multi-rule processing refers to a service flow separation method established according to the logical conditions between different services in the PV-storage-direct-flexible smart microgrid. Since different services may overlap, each service corresponds to a rule and is processed by multiple rules.

[0177] In this example, the power plant power supply business flow represents the activities and steps of the photovoltaic storage direct-flexible smart microgrid in performing power supply business;

[0178] In this example, the working mode indicates the mode in which the power supply business flow of the power plant performs power supply;

[0179] In this example, the first allocation weight represents a weight on the amount of electric energy allocation established according to the electric energy demand information;

[0180] In this example, the power transmission buffer duration represents the duration required for storing the first allocated amount of power of an energy storage device;

[0181] In this example, the first allocation amount represents the electric energy that needs to be stored in the energy storage device determined according to the first allocation weight and the accumulated remaining power;

[0182] In this example, the iterative energy reduction process represents a process of iteratively reducing the first allocated amount;

[0183] In this example, the current power supply allocation ratio represents an allocation ratio determined according to the ratio between the second allocation amounts;

[0184] In this example, the power supply energy range indicates that the power received by the energy storage device is different due to the change of the accumulated residual power, but the specific value is generally stable within this range;

[0185] In this example, the power supply energy is the average value of the power supply energy range.

[0186] The working principle and beneficial effects of the above technical solution: In order to improve the overall efficiency and economy of the photovoltaic, storage, direct and flexible smart microgrid, it is necessary to distribute electric energy reasonably. First, the grid data of the photovoltaic, storage, direct and flexible smart microgrid is processed, and multiple power supply business flows of power plants are constructed. The power supply business flows of power plants are arranged and processed according to the framework to generate a virtual power supply model of the photovoltaic, storage, direct and flexible smart microgrid. Then, in the model, electric energy is distributed according to the power demand information of each energy storage device. Then, the transmission buffer time of each energy storage device when receiving electric energy is analyzed, and the allocation amount of the energy storage device with too slow transmission buffer is reduced. At the same time, in order to ensure the effectiveness of the energy reduction processing and avoid excessive energy reduction, an iterative processing method is adopted. Finally, the accumulated residual electric energy is combined to determine the power supply energy range of each energy storage device, and the power supply energy of the energy storage device is obtained. In this way, the photovoltaic, storage, direct and flexible smart microgrid can accurately supply power to each energy storage device and sell excess electric energy to energy storage devices of various large power grids, thereby increasing the revenue of the photovoltaic, storage, direct and flexible smart microgrid.

[0187] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant, characterized in that: include: Step 1: According to the real-time capacity information and real-time load information of the photovoltaic storage direct flexible smart microgrid, determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic storage direct flexible smart microgrid at different times; Step 2: Establish a virtual power supply model of the solar-storage-direct-flexible smart microgrid, simulate power supply distribution according to the power demand information corresponding to each energy storage device in the virtual power supply model, and determine the power supply energy corresponding to each energy storage device; Step 3: transmitting corresponding power supply energy to each of the energy storage devices respectively, and inputting the real-time energy storage feedback information corresponding to each of the energy storage devices into the virtual power supply model to determine the real-time energy storage structure of each of the energy storage devices; Step 4: Determine the dynamic power consumption corresponding to each of the energy storage devices, adjust the original power supply ratio of the photovoltaic storage direct flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio.

2. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 1, characterized in that: The step 1 comprises: Step 11: Collect the power generation environment information of the photovoltaic storage direct flexible smart microgrid, perform capacity analysis on each power generation mode in the photovoltaic storage direct flexible smart microgrid according to the power generation environment information, construct a real-time power chart corresponding to each power generation mode, and use the basic data corresponding to each power generation mode and the real-time power chart to analyze the real-time capacity information of the photovoltaic storage direct flexible smart microgrid; Step 12: Obtain equipment data of the photovoltaic, storage, direct and flexible smart microgrid, calculate the average load value, peak load value and basic load of the photovoltaic, storage, direct and flexible smart microgrid according to the equipment data, determine the load factor of the photovoltaic, storage, direct and flexible smart microgrid using the average load value and the peak load value, correct the basic load using the load factor, and obtain real-time load information of the photovoltaic, storage, direct and flexible smart microgrid; Step 13: Determine the remaining capacity information of the photovoltaic, storage, direct and flexible smart microgrid based on the real-time capacity information and the real-time load information, calibrate the remaining capacity information using the real-time working data of the photovoltaic, storage, direct and flexible smart microgrid, and obtain the corresponding accumulated remaining electric energy of the photovoltaic, storage, direct and flexible smart microgrid at different times based on the preset electric energy calculation method.

3. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 1, characterized in that: The step 2 comprises: Step 21: Perform multi-rule processing on the grid data of the photovoltaic storage direct flexible smart microgrid to obtain several power plant power supply business flows of the photovoltaic storage direct flexible smart microgrid, and respectively determine the working mode corresponding to each of the power plant power supply business flows, generate a model framework using the logical relationship between the different working modes, map the business flows into the model framework to make business decisions and generate a virtual power supply model of the photovoltaic storage direct flexible smart microgrid; Step 22: respectively obtain the power demand information corresponding to each energy storage device, respectively add a first allocation weight to each of the power demand information in the virtual power supply model, calculate a first allocation amount corresponding to each of the first allocation weights according to the accumulated remaining power, and simulate the power transmission buffer time corresponding to each of the energy storage devices in the virtual power supply model; Step 23: performing iterative energy reduction processing on the target energy storage devices whose power transmission buffer time is unqualified, and determining the second allocation amount corresponding to each of the target energy storage devices; Step 24: Count the second allocation amount corresponding to each of the energy storage devices, determine the current power supply allocation ratio of the photovoltaic storage direct flexible smart microgrid to each of the energy storage devices, use the current power supply allocation ratio and the accumulated remaining electric energy to calculate the power supply energy range corresponding to each of the energy storage devices, and determine the power supply energy corresponding to each of the energy storage devices.

4. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 3 is characterized in that: The step 23 comprises: Step 231: Establishing a duration classification level using a preset buffer standard, performing cluster analysis on the power transmission buffer duration using the duration classification level to generate a corresponding level class, screening out unqualified level classes to be processed, and locating a target energy storage device corresponding to each unqualified power transmission buffer duration in the level class to be processed; Step 232: establishing a buffer time axis according to the corresponding non-qualified power transmission buffer duration, simulating the power transmission process corresponding to the target energy storage device in the virtual power supply model, and mapping the power transmission process in the corresponding buffer time axis to obtain a power buffer process axis; Step 233: extracting a number of jamming moments in each of the electric energy buffering process axes where the buffering amount is lower than the corresponding average buffering amount, counting the amount to be buffered at each of the jamming moments, and reducing the amount to be buffered using a preset iteration step cycle to obtain a number of iterative electric energies corresponding to each of the target energy storage devices, and iteratively simulating the corresponding target energy storage devices in the virtual power supply model according to each of the iterative electric energies to obtain a number of simulation results; Step 234: Filter the target iterative electric energy with a qualified electric energy transmission buffer time of each of the energy storage devices in the simulation results, and obtain the maximum value of the target iterative electric energy as the second allocation amount corresponding to the target energy storage device.

5. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 1, characterized in that: The step 3 comprises: Step 31: supplying energy to each of the energy storage devices respectively, and obtaining real-time energy storage feedback information corresponding to each of the energy storage devices respectively, and determining the external power supply corresponding to each of the energy storage devices according to the real-time energy storage feedback information; Step 32: input the real-time energy storage feedback information into the virtual power supply model for synchronous monitoring, and determine the external power supply rate and internal memory rate corresponding to each energy storage device in combination with the external power supply amount corresponding to each energy storage device; Step 33: Establishing a real-time energy storage structure for each energy storage device based on the external supply rate and internal memory rate corresponding to the same energy storage device.

6. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 1, characterized in that: The step 4 comprises: Step 41: Visualize the real-time energy storage structure to obtain an energy flow chart corresponding to each energy storage device, obtain a plurality of dynamic information presented in the energy flow chart, extract the dynamic core corresponding to each dynamic information, and generate a dynamic power consumption corresponding to each energy storage device; Step 42: Obtain the original power supply ratio of the photovoltaic storage direct-flexible smart microgrid, estimate the remaining power supply time corresponding to each energy storage device according to the original power supply ratio and dynamic power consumption, and select high-energy consumption energy storage devices whose remaining power supply time is lower than the standard power supply time; Step 43: using the high-energy dynamic power consumption corresponding to the high-energy storage device to adjust the original power supply ratio to generate a new power supply ratio, and using the new power supply ratio combined with the accumulated residual power to supply power to each of the energy storage devices respectively.

7. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 6, characterized in that: The step 4 further includes: Screen low-energy storage devices whose dynamic power consumption is within the low-energy range, and determine the unit power supply corresponding to each low-energy storage device by the photovoltaic storage direct-flexible smart microgrid according to the original power supply ratio; The unit power supply is distributed to corresponding high-energy-consuming energy storage devices to generate a new power supply ratio.

8. The method for distributing electric energy of a photovoltaic-storage-direct-flexible smart microgrid based on a virtual power plant according to claim 1, characterized in that: Also includes: Counting the total amount of electric energy provided by the solar-storage-direct-flexible smart microgrid to each of the energy storage devices during a periodic time period; The profit and loss statement of the solar-storage-direct-flexible smart microgrid during the periodic time period is calculated and displayed.

9. The photovoltaic storage direct-flexible intelligent microgrid power distribution system based on virtual power plant is characterized by: include: A power generation supervision module is used to determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid according to the real-time capacity information and real-time load information of the photovoltaic storage direct flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic storage direct flexible smart microgrid at different times; An electric energy distribution module is used to establish a virtual power supply model of the photovoltaic storage direct-flexible smart microgrid, simulate power supply distribution in the virtual power supply model according to the power demand information corresponding to each energy storage device, and determine the power supply energy corresponding to each energy storage device; A virtual analysis module, used to transmit corresponding power supply energy to each of the energy storage devices respectively, and input the real-time energy storage feedback information corresponding to each of the energy storage devices into the virtual power supply model to determine the real-time energy storage structure of each of the energy storage devices; The feedback adjustment module is used to determine the dynamic power consumption corresponding to each of the energy storage devices, adjust the original power supply ratio of the photovoltaic storage direct flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio.

10. The photovoltaic storage direct-flexible intelligent microgrid power distribution system based on a virtual power plant according to claim 9, characterized in that: The electric energy distribution module comprises: The first allocation execution unit is used to perform multi-rule processing on the grid data of the photovoltaic storage direct flexible smart microgrid to obtain a plurality of power plant power supply business flows of the photovoltaic storage direct flexible smart microgrid, and respectively determine the working mode corresponding to each of the power plant power supply business flows, generate a model framework using the logical relationship between the different working modes, map the business flows into the model framework to make business decisions and generate a virtual power supply model of the photovoltaic storage direct flexible smart microgrid; A second allocation execution unit is used to respectively obtain the electric energy demand information corresponding to each energy storage device, respectively add a first allocation weight to each of the electric energy demand information in the virtual power supply model, calculate a first allocation amount corresponding to each of the first allocation weights according to the accumulated residual electric energy, and simulate the electric energy transmission buffer time corresponding to each of the energy storage devices in the virtual power supply model; A third allocation execution unit is used to iteratively reduce the energy of target energy storage devices that fail to meet the power transmission buffer time requirements, and determine a second allocation amount corresponding to each target energy storage device; The fourth allocation execution unit is used to count the second allocation amount corresponding to each of the energy storage devices, determine the current power supply allocation ratio of the photovoltaic storage direct flexible intelligent microgrid to each of the energy storage devices, calculate the power supply energy range corresponding to each of the energy storage devices using the current power supply allocation ratio and the accumulated remaining electric energy, and determine the power supply energy corresponding to each of the energy storage devices.

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