Power distribution method and system of photovoltaic storage direct-flexible intelligent microgrid based on virtual power plant

Abstract

The present invention provides a photovoltaic, storage, direct and flexible intelligent microgrid power distribution method and system based on a virtual power plant, including: determining the corresponding accumulated residual electric energy of the photovoltaic, storage, direct and flexible intelligent microgrid at different times according to the real-time production capacity information, real-time load information and residual production capacity information of the photovoltaic, storage, direct and flexible intelligent microgrid, establishing a virtual power supply model, simulating power supply distribution according to the power demand information corresponding to each energy storage device, determining the power supply energy corresponding to each energy storage device, transmitting the corresponding power supply energy to each energy storage device respectively, determining the real-time energy storage structure of each energy storage device, determining the dynamic power consumption corresponding to each energy storage device, adjusting the original power supply ratio of the photovoltaic, storage, direct and flexible intelligent microgrid, supplying power to each energy storage device according to the new power supply ratio, and utilizing the virtual power plant to sell and distribute the residual electric energy while ensuring the normal power consumption of the factory equipment, thereby improving the overall energy efficiency, optimizing resource allocation, and reducing the power procurement cost.

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-current and flexible intelligent microgrid based on a virtual power plant. Background Art

[0002] The PV-storage-direct-flexible smart microgrid is a new type of grid system. Its core is to transform the rigid load of the photovoltaic DC building itself into a flexible load, and to intelligently control the generation, storage, and demand sides of the PV-storage-direct-flexible microgrid. The PV-storage-direct-flexible smart microgrid integrates photovoltaic power generation, energy storage systems, and intelligent management technologies. It collects solar energy through photovoltaic panels and uses energy storage devices (such as batteries) to store excess electricity for use when needed. This system typically 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 during low-demand periods and release it during peak periods to balance supply and demand.

[0005] Intelligent 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 operating 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 have gradually entered 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 present invention is based on a photovoltaic, storage, direct-flexible intelligent microgrid power distribution method and system for a virtual power plant. It 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 electrical 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 in a photovoltaic, energy-storage, direct-current and flexible intelligent microgrid based on a virtual power plant, comprising:

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

[0013] Step 2: Establish a virtual power supply model for the solar-storage-direct-flexible smart microgrid, simulate power supply distribution in the virtual power supply model based on the power demand information corresponding to each energy storage device, 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 solar-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: Collecting power generation environment information of the PV-storage-direct-flexible smart microgrid, performing capacity analysis on each power generation mode in the PV-storage-direct-flexible smart microgrid based on the power generation environment information, constructing a real-time power chart corresponding to each power generation mode, and analyzing the real-time capacity information of the PV-storage-direct-flexible smart microgrid using the basic data corresponding to each power generation mode and the real-time power chart;

[0019] Step 12: Obtain device data of the solar-storage-direct-flexible smart microgrid, calculate the average load value, peak load value, and base load of the solar-storage-direct-flexible smart microgrid based on the device data, determine the load factor of the solar-storage-direct-flexible smart microgrid using the average load value and the peak load value, and correct the base load using the load factor to obtain real-time load information of the solar-storage-direct-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 PV-storage-direct-flexible smart microgrid to obtain several power plant power supply business flows of the PV-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 different working modes, map the business flows into the model framework, perform business decision-making, and generate a virtual power supply model of the PV-storage-direct-flexible smart microgrid;

[0024] Step 22: Obtain power demand information corresponding to each energy storage device, 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 based on 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 target energy storage devices with unqualified power transmission buffer time, and determining a second allocation amount corresponding to each target energy storage device;

[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 residual 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 includes:

[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 corresponding level classes, screening out unqualified level classes to be processed, and locating the target energy storage device corresponding to each unqualified power transmission buffer duration in the level classes 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 to the corresponding buffer time axis to obtain a power buffer process axis;

[0031] Step 233: extracting a number of pause moments in each of the electric energy buffering process axes where the buffer amount is lower than the corresponding average buffer amount, counting the amount to be buffered at each of the pause moments, and cyclically degrading the amount to be buffered using a preset iterative step size 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 for 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, obtaining real-time energy storage feedback information corresponding to each of the energy storage devices respectively, and determining the external energy supply amount 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 storage 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: Visualizing the real-time energy storage structure to obtain an energy flow chart corresponding to each energy storage device, obtaining multiple pieces of dynamic information presented in the energy flow chart, extracting the dynamic core corresponding to each piece of dynamic information, and generating a dynamic power consumption corresponding to each energy storage device;

[0041] Step 42: Obtain the original power supply ratio of the solar-storage-direct-flexible smart microgrid, estimate the remaining power supply time corresponding to each energy storage device based on the original power supply ratio and dynamic power consumption, and select high-energy-consuming 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] Screening low-consumption energy storage devices whose dynamic power consumption is within the low-consumption range, and determining the unit power supply corresponding to each low-consumption energy storage device by the solar-storage-direct-flexible smart microgrid according to the original power supply ratio;

[0046] The unit power supply is distributed to the 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 period;

[0050] Calculate and display the profit and loss statement of the solar-storage-direct-flexible smart microgrid during the period.

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

[0052] A power generation monitoring module is used to determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid based on 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 solar-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 is used to transmit corresponding power supply energy to each of the energy storage devices, 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] A first allocation execution unit is used to perform multi-rule processing on the grid data of the photovoltaic, storage, direct and flexible smart microgrid to obtain a plurality of power plant power supply business flows of the photovoltaic, storage, direct and 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 different working modes, map the business flows into the model framework, perform business decisions, and generate a virtual power supply model of the photovoltaic, storage, direct and flexible smart microgrid;

[0059] a second allocation execution unit, configured to respectively obtain 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 based on the accumulated remaining power amount, and simulate a power transmission buffer duration corresponding to each of the energy storage devices in the virtual power supply model;

[0060] a third allocation execution unit, configured to iteratively reduce the energy consumption of target energy storage devices whose power transmission buffer time is unqualified, 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, use the current power supply allocation ratio and the accumulated residual 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.

[0062] The achievable beneficial effects of the above technical solution are: in order to avoid energy waste in the photovoltaic, storage, direct and flexible smart microgrid and improve profitability, when the photovoltaic, storage, direct and 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, energy supply and energy 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 in part will become apparent from the description, or will be 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 Schematic diagram of the working process of the solar-storage-direct-flexible smart microgrid power distribution method based on a virtual power plant in an embodiment of the present invention;

[0067] Figure 2 This is a schematic diagram of the composition of a solar-storage-direct-flexible smart 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 with reference to 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 smart microgrid with solar-storage and direct-flexible power plants based on a virtual power plant. Figure 1 As shown, including:

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

[0072] Step 2: Establish a virtual power supply model for the solar-storage-direct-flexible smart microgrid, simulate power supply distribution in the virtual power supply model based on the power demand information corresponding to each energy storage device, 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 solar-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 power in the PV-storage-direct-flexible smart microgrid is first supplied to its own devices, and the excess power is supplied to the energy storage device. Generally speaking, the excess power is much greater than the self-supplied power.

[0076] In this example, the real-time energy production information represents the real-time energy generated by the PV-storage-direct-flexible smart microgrid. The PV-storage-direct-flexible smart microgrid generates energy in various ways, including 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 refers to the electric energy temporarily stored in the solar-storage-direct-flexible smart microgrid and not distributed;

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

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

[0082] In this example, simulated power 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 operation when the energy storage device is powered;

[0084] In this example, the dynamic power consumption represents the amount of electric energy 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 and flexible smart microgrid and improve profitability, when the photovoltaic, storage, direct and 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 electricity 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, energy supply and energy 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 electricity procurement costs.

[0086] Example 2

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

[0088] Step 11: Collecting power generation environment information of the PV-storage-direct-flexible smart microgrid, performing capacity analysis on each power generation mode in the PV-storage-direct-flexible smart microgrid based on the power generation environment information, constructing a real-time power chart corresponding to each power generation mode, and analyzing the real-time capacity information of the PV-storage-direct-flexible smart microgrid using the basic data corresponding to each power generation mode and the real-time power chart;

[0089] Step 12: Obtain device data of the solar-storage-direct-flexible smart microgrid, calculate the average load value, peak load value, and base load of the solar-storage-direct-flexible smart microgrid based on the device data, determine the load factor of the solar-storage-direct-flexible smart microgrid using the average load value and the peak load value, and correct the base load using the load factor to obtain real-time load information of the solar-storage-direct-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 on wind power, solar power, water potential energy, geothermal energy, tidal energy, etc. 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, basic data represents data generated by a power generation method when generating electricity;

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

[0096] In this example, the average load value represents the average load value 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 based on 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 and real-time monitoring technology, and multi-source detection of the environment, accurate production capacity is obtained.

[0101] Example 3

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

[0103] Step 21: Perform multi-rule processing on the grid data of the PV-storage-direct-flexible smart microgrid to obtain several power plant power supply business flows of the PV-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 different working modes, map the business flows into the model framework, perform business decision-making, and generate a virtual power supply model of the PV-storage-direct-flexible smart microgrid;

[0104] Step 22: Obtain power demand information corresponding to each energy storage device, 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 based on 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 target energy storage devices with unqualified power transmission buffer time, and determining a second allocation amount corresponding to each target energy storage device;

[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 residual 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 represents a service flow separation method based on the logical conditions between different services in the PV-storage-direct-flexible smart microgrid. Because different services may overlap, each service corresponds to a rule, resulting in multi-rule processing.

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

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

[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 in an energy storage device;

[0112] In this example, the first allocation amount represents the electric energy that the energy storage device needs to store, determined based on 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 quantities;

[0115] In this example, the power supply energy range indicates that the amount of power received by the energy storage device varies due to changes in 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 plant power supply business flows are constructed. The power plant power supply business flows 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 income of the photovoltaic, storage, direct and flexible smart microgrid.

[0118] Example 4

[0119] On the basis of Example 3, the solar-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 corresponding level classes, screening out unqualified level classes to be processed, and locating the target energy storage device corresponding to each unqualified power transmission buffer duration in the level classes 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 to the corresponding buffer time axis to obtain a power buffer process axis;

[0122] Step 233: extracting a number of pause moments in each of the electric energy buffering process axes where the buffer amount is lower than the corresponding average buffer amount, counting the amount to be buffered at each of the pause moments, and cyclically degrading the amount to be buffered using a preset iterative step size 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 for 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 expressed in a time axis manner;

[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. 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. The stuck moments are located, and the electric energy at the stuck moments is gradually weakened. Finally, the largest iterative electric energy is screened out as the second allocation of the target energy storage device. This can ensure the power supply efficiency of the energy storage device and avoid the phenomenon of energy storage device failure caused by overpowering.

[0130] Example 5

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

[0132] Step 31: supplying energy to each of the energy storage devices respectively, obtaining real-time energy storage feedback information corresponding to each of the energy storage devices respectively, and determining the external energy supply amount 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 storage 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 electricity 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 solar-storage-direct-flexible smart microgrid power distribution method based on a virtual power plant, step 4 includes:

[0138] Step 41: Visualizing the real-time energy storage structure to obtain an energy flow chart corresponding to each energy storage device, obtaining multiple pieces of dynamic information presented in the energy flow chart, extracting the dynamic core corresponding to each piece of dynamic information, and generating a dynamic power consumption corresponding to each energy storage device;

[0139] Step 42: Obtain the original power supply ratio of the solar-storage-direct-flexible smart microgrid, estimate the remaining power supply time corresponding to each energy storage device based on the original power supply ratio and dynamic power consumption, and select high-energy-consuming 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: by visualizing the real-time energy storage structure to determine the dynamic power consumption of the energy storage equipment, and then screening high-consumption energy storage equipment with insufficient remaining power, and increasing the power supply to high-consumption energy storage equipment 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] Based on Example 6, the method for distributing electric energy in a virtual power plant-based solar-storage-direct-flexible smart microgrid may further include:

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

[0146] The unit power supply is distributed to the 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 electrical energy of each energy storage device.

[0148] Example 8

[0149] Based on Example 1, the solar-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 period;

[0151] Calculate and display the profit and loss statement of the solar-storage-direct-flexible smart microgrid during the period.

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

[0153] Example 9

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

[0155] A power generation monitoring module is used to determine the remaining capacity information of the photovoltaic storage direct flexible smart microgrid based on 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 solar-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 is used to transmit corresponding power supply energy to each of the energy storage devices, 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 power in the PV-storage-direct-flexible smart microgrid is first supplied to its own devices, and the excess power is supplied to the energy storage device. Generally speaking, the excess power is much greater than the self-supplied power.

[0160] In this example, the real-time energy production information represents the real-time energy generated by the PV-storage-direct-flexible smart microgrid. The PV-storage-direct-flexible smart microgrid generates energy in various ways, including 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 refers to the electric energy temporarily stored in the solar-storage-direct-flexible smart microgrid and not distributed;

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

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

[0166] In this example, simulated power 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 operation when the energy storage device is powered;

[0168] In this example, the dynamic power consumption represents the amount of electric energy 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 and flexible smart microgrid and improve profitability, when the photovoltaic, storage, direct and 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 electricity 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, energy supply and energy 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 electricity procurement costs.

[0170] Example 10

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

[0172] A first allocation execution unit is used to perform multi-rule processing on the grid data of the photovoltaic, storage, direct and flexible smart microgrid to obtain a plurality of power plant power supply business flows of the photovoltaic, storage, direct and 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 different working modes, map the business flows into the model framework, perform business decisions, and generate a virtual power supply model of the photovoltaic, storage, direct and flexible smart microgrid;

[0173] a second allocation execution unit, configured to respectively obtain 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 based on the accumulated remaining power amount, and simulate a power transmission buffer duration corresponding to each of the energy storage devices in the virtual power supply model;

[0174] a third allocation execution unit, configured to iteratively reduce the energy consumption of target energy storage devices whose power transmission buffer time is unqualified, 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, use the current power supply allocation ratio and the accumulated residual 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.

[0176] In this example, multi-rule processing represents a service flow separation method based on the logical conditions between different services in the PV-storage-direct-flexible smart microgrid. Because different services may overlap, each service corresponds to a rule, resulting in multi-rule processing.

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

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

[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 in an energy storage device;

[0181] In this example, the first allocation amount represents the electric energy that the energy storage device needs to store, determined based on 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 quantities;

[0184] In this example, the power supply energy range indicates that the amount of power received by the energy storage device varies due to changes in 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 plant power supply business flows are constructed. The power plant power supply business flows 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 income of the photovoltaic, storage, direct and flexible smart microgrid.

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

Claims

1. A method for distributing electric energy in a smart microgrid with solar-storage and direct-flexible power plants based on a virtual power plant, characterized in that: include: Step 1: Determine the remaining capacity information of the PV-storage direct-flexible smart microgrid based on the real-time capacity information and real-time load information of the PV-storage direct-flexible smart microgrid, and determine the accumulated remaining electric energy corresponding to the PV-storage direct-flexible smart microgrid at different times, wherein the remaining capacity information represents the real-time excess electric energy generated by the PV-storage direct-flexible smart microgrid, and the accumulated remaining electric energy represents the electric energy temporarily stored in the PV-storage direct-flexible smart microgrid and not distributed; Step 2: Establish a virtual power supply model for the solar-storage-direct-flexible smart microgrid, simulate power supply distribution in the virtual power supply model based on the power demand information corresponding to each energy storage device, 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 solar-storage-direct-flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio; The step 2 comprises: Step 21: Perform multi-rule processing on the grid data of the PV-storage-direct-flexible smart microgrid to obtain several power plant power supply business flows of the PV-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 different working modes, map the business flows into the model framework, perform business decision-making, and generate a virtual power supply model of the PV-storage-direct-flexible smart microgrid; Step 22: Obtain power demand information corresponding to each energy storage device, 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 based on 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 target energy storage devices with unqualified power transmission buffer time, and determining a second allocation amount corresponding to each target energy storage device; 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 residual 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.

2. The method for distributing electric energy of a photovoltaic, storage, direct-current and flexible smart microgrid based on a virtual power plant according to claim 1, characterized in that: The step 1 comprises: Step 11: Collecting power generation environment information of the PV-storage-direct-flexible smart microgrid, performing capacity analysis on each power generation mode in the PV-storage-direct-flexible smart microgrid based on the power generation environment information, constructing a real-time power chart corresponding to each power generation mode, and analyzing the real-time capacity information of the PV-storage-direct-flexible smart microgrid using the basic data corresponding to each power generation mode and the real-time power chart; Step 12: Obtain device data of the solar-storage-direct-flexible smart microgrid, calculate the average load value, peak load value, and base load of the solar-storage-direct-flexible smart microgrid based on the device data, determine the load factor of the solar-storage-direct-flexible smart microgrid using the average load value and the peak load value, and correct the base load using the load factor to obtain real-time load information of the solar-storage-direct-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 in a photovoltaic, direct-current and flexible smart microgrid based on a virtual power plant according to claim 1, wherein: The step 23 includes: 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 corresponding level classes, screening out unqualified level classes to be processed, and locating the target energy storage device corresponding to each unqualified power transmission buffer duration in the level classes 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 to the corresponding buffer time axis to obtain a power buffer process axis; Step 233: extracting a number of pause moments in each of the electric energy buffering process axes where the buffer amount is lower than the corresponding average buffer amount, counting the amount to be buffered at each of the pause moments, and cyclically degrading the amount to be buffered using a preset iterative step size 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 for 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.

4. The method for distributing electric energy in a photovoltaic, direct-current and flexible smart microgrid based on a virtual power plant according to claim 1, wherein: The step 3 comprises: Step 31: supplying energy to each of the energy storage devices respectively, obtaining real-time energy storage feedback information corresponding to each of the energy storage devices respectively, and determining the external energy supply amount 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 storage 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.

5. The method for distributing electric energy of a photovoltaic, storage, direct-current and flexible smart microgrid based on a virtual power plant according to claim 1, wherein: The step 4 comprises: Step 41: Visualizing the real-time energy storage structure to obtain an energy flow chart corresponding to each energy storage device, obtaining multiple pieces of dynamic information presented in the energy flow chart, extracting the dynamic core corresponding to each piece of dynamic information, and generating a dynamic power consumption corresponding to each energy storage device; Step 42: Obtain the original power supply ratio of the solar-storage-direct-flexible smart microgrid, estimate the remaining power supply time corresponding to each energy storage device based on the original power supply ratio and dynamic power consumption, and select high-energy-consuming 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.

6. The method for distributing electric energy in a photovoltaic, energy storage, direct-current and flexible smart microgrid based on a virtual power plant according to claim 5, characterized in that: The step 4 further includes: Screening low-energy storage devices whose dynamic power consumption is within the low-energy consumption range, and determining the unit power supply corresponding to each low-energy storage device by the solar-storage-direct-flexible smart microgrid according to the original power supply ratio; The unit power supply is distributed to the corresponding high-energy-consuming energy storage devices to generate a new power supply ratio.

7. The method for distributing electric energy in a photovoltaic, direct-current and flexible smart microgrid based on a virtual power plant according to claim 1, wherein: 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 period; Calculate and display the profit and loss statement of the solar-storage-direct-flexible smart microgrid during the period.

8. The solar-storage-direct-flexible smart 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 and flexible smart microgrid based on the real-time capacity information and real-time load information of the photovoltaic, storage, direct and flexible smart microgrid, and determine the corresponding accumulated remaining electric energy of the photovoltaic, storage, direct and flexible smart microgrid at different times, wherein the remaining capacity information represents the real-time excess electric energy generated by the photovoltaic, storage, direct and flexible smart microgrid, and the accumulated remaining electric energy represents the electric energy temporarily stored in the photovoltaic, storage, direct and flexible smart microgrid and not distributed; An electric energy distribution module is used to establish a virtual power supply model of the solar-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 is used to transmit corresponding power supply energy to each of the energy storage devices, 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; A 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 solar-storage-direct-flexible smart microgrid, and supply power to each of the energy storage devices according to the new power supply ratio; The electric energy distribution module comprises: A first allocation execution unit is used to perform multi-rule processing on the grid data of the photovoltaic, storage, direct and flexible smart microgrid to obtain a plurality of power plant power supply business flows of the photovoltaic, storage, direct and 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 different working modes, map the business flows into the model framework, perform business decisions, and generate a virtual power supply model of the photovoltaic, storage, direct and flexible smart microgrid; a second allocation execution unit, configured to respectively obtain 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 based on the accumulated remaining power amount, and simulate a power transmission buffer duration corresponding to each of the energy storage devices in the virtual power supply model; a third allocation execution unit, configured to iteratively reduce the energy consumption of target energy storage devices whose power transmission buffer time is unqualified, 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, use the current power supply allocation ratio and the accumulated residual 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.

Images