Power supply and distribution and management and control method, system and equipment of micro-grid, medium and product

Abstract

The invention discloses a micro-grid power supply and distribution and management and control method, system, device, medium and product, and relates to the technical field of micro-grid power distribution. The method comprises the following steps: collecting current operation data and external influence factor data of each distributed power supply in a micro-grid power supply layer; performing feature extraction on the current operation data and the external influence factor data to obtain corresponding feature data; inputting the corresponding feature data into a micro-grid power demand prediction model to obtain a power demand prediction value of the micro-grid; according to the power demand prediction value of the micro-grid, the operation states of renewable energy power generation equipment and fossil fuel power generation equipment are adjusted; and dynamically monitoring the power load demand of the micro-grid load layer, and adjusting a power supply scheme according to the power load demand. According to the invention, the requirement of long-time stable power supply is met, and the reliability and continuity of energy supply are improved.

Description

Technical Field

[0001] This application relates to the technical field of microgrid power distribution, and particularly to a power supply, distribution, control method, system, device, medium and product for a microgrid. Background Art

[0002] The continuous increase in electromechanical equipment on highways and its high-precision integration characteristics have led to an increasing demand for power quality. Power parameter fluctuations, harmonic disturbances, etc. affect the working state and lifespan of equipment, and complex grid load changes, day-night changes, etc. also result in frequent voltage anomalies. To ensure the stable operation of equipment, it is imperative to improve the power supply quality to reduce the negative impact of unstable voltage on equipment.

[0003] The traditional highway power supply mode adopts an island power supply method, with single-direction power supply + UPS assistance, resulting in isolation between power supply nodes and unable to form a ring network structure. This decentralized power supply mode cannot rely on adjacent nodes to provide backup power during power supply failures, causing unstable power supply. In particular, the lead-acid batteries used in UPS have a short lifespan and are difficult to meet the long-term power supply requirements, hindering the reliability and stability of the system.

[0004] Therefore, it is necessary to provide a power supply, distribution, and control method for a microgrid to solve the above problems. Summary of the Invention

[0005] The purpose of this application is to provide a power supply, distribution, and control method, system, device, medium and product for a microgrid to solve the problems that the decentralized power supply mode cannot rely on adjacent nodes to provide backup power during power supply failures, resulting in unstable power supply and difficulty in meeting the long-term power supply requirements.

[0006] To achieve the above purpose, this application provides the following solutions:

[0007] In the first aspect, this application provides a power supply, distribution, and control method for a microgrid. The microgrid includes: a power supply layer, an energy storage device, a load layer, a control system, and a connection device; the power supply layer includes renewable energy power generation equipment and fossil fuel power generation equipment, and the power supply layer is used to provide a power source for the microgrid; the energy storage device is used to store power and balance the supply-demand relationship of the microgrid; the load layer includes various electrical equipment and power users; the control system is used to control the energy flow between the power supply layer, the energy storage device, and the load layer, and coordinate the operation of the microgrid; the connection device is used to connect the microgrid to an external grid to ensure the interconnection and interoperability between the microgrid and the external grid; the power supply, distribution, and control method for the microgrid includes:

[0008] Collect the current operation data of each distributed power source within the microgrid power supply layer and the data of external influencing factors; the current operation data includes: power load, power generation, and equipment status, and the data of external influencing factors includes: weather information, holiday arrangements, and economic activity indicators;

[0009] Using the principal component analysis method, extract the power demand-related characteristics from the current operation data and the data of external influencing factors respectively, to obtain the characteristic data of the current operation data and the characteristic data of the data of external influencing factors;

[0010] Input the characteristic data of the current operation data and the characteristic data of the data of external influencing factors into the microgrid power demand prediction model to obtain the power demand prediction value of the microgrid; the microgrid power demand prediction model is obtained by training a neural network model with a training set; the training set includes: the characteristic data of the historical operation data of each distributed power source within the microgrid power supply layer, the sample characteristic data of the data of external influencing factors, and the corresponding power demand sample values of the microgrid;

[0011] According to the power demand prediction value of the microgrid, adjust the operation status of the renewable energy power generation equipment and the fossil fuel power generation equipment;

[0012] Dynamically monitor the power load demand of the microgrid load layer, and adjust the power supply plan according to the power load demand; wherein, adjusting the power supply plan includes: optimizing the power consumption period, hierarchical management of the load, and using the external power grid for power supply.

[0013] Optionally, the training process of the microgrid power demand prediction model specifically includes:

[0014] Construct a training set;

[0015] Input the characteristic data of the historical operation data of each distributed power source within the microgrid power supply layer and the sample characteristic data of the data of external influencing factors into the neural network model, and output the power demand prediction value of the microgrid;

[0016] Construct a loss function according to the power demand prediction value of the microgrid and the power demand sample value of the microgrid, and iteratively optimize the network parameters of the neural network model according to the loss function until the number of iterative optimizations reaches the maximum value or the loss function reaches the minimum value, and stop the iterative optimization to obtain the microgrid power demand prediction model.

[0017] Optionally, constructing a training set specifically includes:

[0018] Obtain the historical operation data and the sample data of external influencing factors;

[0019] Clean the historical operation data and the sample data of external influencing factors respectively to obtain the cleaned historical operation data and the cleaned sample data of external influencing factors; wherein, the data cleaning includes eliminating outliers and noise.

[0020] Optionally, dynamically monitor the power load demand of the microgrid load layer, and adjust the power supply plan according to the power load demand, specifically including:

[0021] When the power load demand of the load layer is lower than the power supply capacity of each distributed power source, store the excess electric energy in the energy storage device;

[0022] When the power load demand is higher than the power supply capacity of each distributed power source, preferentially use the electric energy provided by the energy storage device to balance the power supply and demand of the microgrid.

[0023] Optionally, the power supply, distribution and control method of the microgrid further includes:

[0024] Use the DC ring network power supply method to connect each renewable energy power generation device, fossil fuel power generation device and load layer in the microgrid.

[0025] Optionally, the power supply, distribution and control method of the microgrid further includes:

[0026] Collect the operation state parameters of the microgrid in real time, and monitor the operation state of the microgrid in real time according to the operation state parameters; the operation state parameters include at least one of the parameters of voltage, current and frequency;

[0027] When any one of the operation state parameters of the microgrid is monitored to be abnormal, automatically adjust the operation states of each distributed power source in the microgrid to ensure the stable operation of the microgrid.

[0028] In a second aspect, the present application provides a power supply, distribution and control system of a microgrid. The power supply, distribution and control system of the microgrid is connected to the microgrid. The microgrid includes: a power supply layer, an energy storage device, a load layer, a control system and a connection device; the power supply layer includes renewable energy power generation devices and fossil fuel power generation devices, and the power supply layer is used to provide a power source for the microgrid; the energy storage device is used to store electric power and balance the supply and demand relationship of the microgrid; the load layer includes various electrical equipment and power users; the control system is used to control the energy flow between the power supply layer, the energy storage device and the load layer, and coordinate the operation of the microgrid; the connection device is used to connect the microgrid to an external power grid to ensure the interconnection and interoperability between the microgrid and the external power grid; the power supply, distribution and control system of the microgrid is used to implement the power supply, distribution and control method of the microgrid, and the power supply, distribution and control system of the microgrid includes:

[0029] A data acquisition unit for collecting the current operation data of each distributed power source within the microgrid power supply layer and the data of external influencing factors; the current operation data includes: power load, power generation, and equipment status, and the data of external influencing factors includes: weather information, holiday arrangements, and economic activity indicators;

[0030] A feature extraction unit for respectively extracting power demand-related features from the current operation data and the data of external influencing factors by using the principal component analysis method to obtain the feature data of the current operation data and the feature data of the data of external influencing factors;

[0031] A unit for determining the power demand prediction value of the microgrid, which inputs the feature data of the current operation data and the feature data of the data of external influencing factors into the microgrid power demand prediction model to obtain the power demand prediction value of the microgrid; the microgrid power demand prediction model is obtained by training a neural network model with a training set; the training set includes: the feature data of the historical operation data of each distributed power source within the microgrid power supply layer, the sample feature data of the data of external influencing factors, and the corresponding power demand sample values of the microgrid;

[0032] An operation state adjustment unit for adjusting the operation states of renewable energy power generation equipment and fossil fuel power generation equipment according to the power demand prediction value of the microgrid;

[0033] A monitoring unit for dynamically monitoring the power load demand of the microgrid load layer and adjusting the power supply plan according to the power load demand; wherein, adjusting the power supply plan includes: optimizing the power consumption period, hierarchical management of the load, and using the external power grid for power supply.

[0034] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the power supply, distribution, and control method of the microgrid described in any one of the above.

[0035] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the power supply, distribution, and control method of the microgrid described in any one of the above.

[0036] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the power supply, distribution, and control method of the microgrid described in any one of the above.

[0037] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0038] The present application discloses a method, system, equipment, medium and product for power supply and distribution and control of a microgrid, the method comprising: collecting the current operation data and external influencing factor data of each distributed power source within the microgrid power layer, using the principal component analysis method to extract features of the current operation data and external influencing factor data to obtain corresponding feature data; inputting the corresponding feature data into the microgrid power demand prediction model to obtain the power demand prediction value of the microgrid; adjusting the operating status of renewable energy power generation equipment and fossil fuel power generation equipment according to the power demand prediction value of the microgrid; dynamically monitoring the power load demand of the microgrid load layer, and adjusting the power supply plan according to the power load demand. Among them, the energy link between adjacent sites is opened up through the intelligent microgrid, and the energy on-demand mutual assistance between adjacent sites is realized through the power distribution and power control, which meets the long-term stable power supply demand and improves the reliability and continuity of energy supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A schematic diagram of a power supply, distribution and control method of a microgrid provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of functional modules of a power supply, distribution and control system of a microgrid provided in one embodiment of the present application;

[0042] Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application.

[0043] Reference numerals:

[0044] Data collection unit 1, feature extraction unit 2, microgrid power demand forecast value determination unit 3, operation status adjustment unit 4, monitoring unit 5. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] The linear energy consumption characteristics of expressways increase the difficulty of achieving full coverage of high-quality energy. The geographical and environmental factors on which their construction depends determine the uneven distribution of new energy construction conditions. In response to the energy consumption needs of smart expressways, research on key technologies for collaborative design and intelligent evaluation of green energy under different conditions; research on microgrid modeling and multi-mode control technologies that comprehensively consider demand response; optimize the capacity configuration of green energy power generation and energy storage facilities, and construct an expressway microgrid to effectively ensure the self-consistency rate of expressway energy consumption.

[0047] Therefore, in response to the linear and distributed energy consumption characteristics of smart expressways, as well as problems such as uneven and mismatched renewable energy construction and power supply, research on microgrid architecture design under different scales and application scenarios, including the cases of single microgrids and interconnection of multiple microgrids, and microgrid architectures applicable to various energy sources such as photovoltaic power generation and energy storage systems, and ensure the stability and reliability of the microgrid.

[0048] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] In an exemplary embodiment, as Figure 1 shown, a power supply, distribution, and control method for a microgrid is provided, including the following steps. Among them:

[0050] The microgrid includes: a power supply layer, an energy storage device, a load layer, a control system, and a connection device; the power supply layer includes renewable energy power generation equipment and fossil fuel power generation equipment, and the power supply layer is used to provide a power source for the microgrid; the energy storage device is used to store electricity and balance the supply and demand relationship of the microgrid; the load layer includes various electrical equipment and power users; the control system is used to control the energy flow between the power supply layer, the energy storage device, and the load layer, and coordinate the operation of the microgrid; the connection device is used to connect the microgrid to the external power grid to ensure the interconnection and interoperability between the microgrid and the external power grid; the power supply, distribution, and control method of the microgrid includes:

[0051] Step S1, collect the current operation data of each distributed power source inside the power supply layer of the microgrid and external influencing factor data; the current operation data includes: power load, power generation, and equipment status, and the external influencing factor data includes: weather information, holiday arrangements, and economic activity indicators.

[0052] Step S2, using the principal component analysis method, respectively extract the power demand-related characteristics from the current operation data and the external influencing factor data to obtain the characteristic data of the current operation data and the characteristic data of the external influencing factor data.

[0053] Step S3: Input the feature data of the current operation data and the feature data of the external influencing factor data into the microgrid power demand prediction model to obtain the power demand prediction value of the microgrid. The microgrid power demand prediction model is obtained by training a neural network model with a training set. The training set includes: the feature data of the historical operation data of each distributed power source within the microgrid power source layer, the sample feature data of the external influencing factor data, and the corresponding power demand sample values of the microgrid.

[0054] Step S4: Adjust the operation states of the renewable energy power generation equipment and the fossil fuel power generation equipment according to the power demand prediction value of the microgrid.

[0055] Step S5: Dynamically monitor the power load demand of the microgrid load layer, and adjust the power supply plan according to the power load demand. Among them, adjusting the power supply plan includes: optimizing the power consumption period, hierarchical management of the load, and using the external power grid for power supply.

[0056] Specifically, combine the Internet of Things and intelligent sensors to dynamically monitor the microgrid load, and by mastering the power load demand in real time, enable the control system to adjust the power supply plan.

[0057] As an optional implementation manner, in step S3, the training process of the microgrid power demand prediction model specifically includes:

[0058] Step S31: Construct a training set.

[0059] Step S32: Input the feature data of the historical operation data of each distributed power source within the microgrid power source layer and the sample feature data of the external influencing factor data into the neural network model, and output the power demand prediction value of the microgrid.

[0060] Step S33: Construct a loss function according to the power demand prediction value of the microgrid and the power demand sample value of the microgrid, and iteratively optimize the network parameters of the neural network model according to the loss function until the number of iterative optimizations reaches the maximum value or the loss function reaches the minimum value, then stop the iterative optimization to obtain the microgrid power demand prediction model. In addition, cross-validation is used to optimize the microgrid power demand prediction model.

[0061] As an optional implementation manner, in step S31, constructing a training set specifically includes:

[0062] Step S311: Obtain the historical operation data and the external influencing factor sample data.

[0063] Step S312, perform data cleaning on the historical operation data and the external influencing factor sample data respectively to obtain the cleaned historical operation data and the cleaned external influencing factor sample data; wherein, the data cleaning includes eliminating outliers and noise.

[0064] As an alternative implementation manner, step S5 specifically includes:

[0065] Step S51, when the power load demand of the load layer is lower than the power supply capacity of each distributed power source, store the excess electric energy in the energy storage device;

[0066] Step S52, when the power load demand is higher than the power supply capacity of each distributed power source, preferentially use the electric energy provided by the energy storage device to balance the power supply and demand of the microgrid.

[0067] As an alternative implementation manner, the power supply, distribution and control method of the microgrid further includes:

[0068] Step S6, utilize the DC ring network power supply technology to directly connect each renewable energy power generation device, fossil fuel power generation device and the load layer in the microgrid to reduce the energy loss during the energy conversion process. Through the application of the DC ring network power supply technology, the energy transmission inside the microgrid is more efficient and stable, improving the reliability of the energy supply of the microgrid and reducing the loss during the energy supply process.

[0069] As an alternative implementation manner, the power supply, distribution and control method of the microgrid further includes:

[0070] Step S7, collect the operation state parameters of the microgrid in real time and monitor the operation state of the microgrid according to the operation state parameters; the operation state parameters include at least one of the parameters of voltage, current and frequency.

[0071] Step S8, when any one of the operation state parameters of the microgrid is monitored to be abnormal, automatically adjust the operation states of the distributed power sources in the microgrid to ensure the stable operation of the microgrid.

[0072] As an alternative implementation manner, the power supply, distribution and control method of the microgrid further includes:

[0073] Step S9, when a failure of the renewable energy power generation device and the fossil fuel power generation device inside the microgrid is detected, automatically locate the fault source and generate a fault report.

[0074] Step S10, through wireless communication, transmit the operation data, energy usage situation and fault report of the microgrid to the remote monitoring center in real time so that the remote monitoring center can perform remote monitoring and fault warning.

[0075] Advantages of this application:

[0076] Through smart microgrids, energy links between adjacent sites are opened up, and energy on-demand mutual assistance between adjacent sites is achieved, which meets the long-term stable power supply needs, improves the reliability and continuity of energy supply, and achieves efficient coverage of all energy scenarios and road areas such as roadsides, toll stations, tunnels, and service areas.

[0077] Based on the same inventive concept, the embodiment of the present application also provides a microgrid power distribution and control system for implementing the above-mentioned microgrid power distribution and control method. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more microgrid power distribution and control system embodiments provided below can refer to the limitations of the microgrid power distribution and control method above, and will not be repeated here.

[0078] In an exemplary embodiment, Figure 2 As shown, a power supply and distribution and control system of a microgrid is provided, and the power supply and distribution and control system of the microgrid is connected to the microgrid, and the microgrid includes: a power supply layer, an energy storage device, a load layer, a control system and a connection device; the power supply layer includes renewable energy power generation equipment and fossil fuel power generation equipment, and the power supply layer is used to provide a power source for the microgrid; the energy storage device is used to store electricity and balance the supply and demand relationship of the microgrid; the load layer includes various power-consuming equipment and power users; the control system is used to control the energy flow between the power supply layer, the energy storage device and the load layer, and coordinate the operation of the microgrid; the connection device is used to connect the microgrid to an external power grid to ensure the interconnection between the microgrid and the external power grid; the power supply and distribution and control system of the microgrid is used to implement the power supply and distribution and control method of the microgrid, and the power supply and distribution and control system of the microgrid includes:

[0079] Data acquisition unit 1, used to collect current operation data and external influencing factor data of each distributed power source in the microgrid power layer; the current operation data includes: power load, power generation and equipment status, and the external influencing factor data includes: weather information, holiday arrangements and economic activity indicators;

[0080] The feature extraction unit 2 is used to extract the power demand related features of the current operation data and the external influencing factor data respectively by using the principal component analysis method, so as to obtain the feature data of the current operation data and the feature data of the external influencing factor data;

[0081] The power demand prediction value determination unit 3 of the microgrid is configured to input the characteristic data of the current operation data and the characteristic data of the external influence factor data into the microgrid power demand prediction model to obtain the power demand prediction value of the microgrid; the microgrid power demand prediction model is obtained by training a neural network model using a training set; the training set includes: the characteristic data of the historical operation data of each distributed power source inside the microgrid power source layer, the sample characteristic data of the external influence factor data, and the corresponding power demand sample value of the microgrid.

[0082] The operation state adjustment unit 4 is configured to adjust the operation states of the renewable energy power generation equipment and the fossil fuel power generation equipment according to the power demand prediction value of the microgrid.

[0083] The monitoring unit 5 is configured to dynamically monitor the power load demand of the microgrid load layer and adjust the power supply plan according to the power load demand; wherein, adjusting the power supply plan includes: optimizing the power consumption period, hierarchically managing the load, and using the external power grid for power supply.

[0084] In an exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the power supply, distribution, and control method of the microgrid.

[0085] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the power supply, distribution, and control method of the microgrid is implemented.

[0086] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the power supply, distribution, and control method of the microgrid is implemented.

[0087] In an exemplary embodiment, a computer device is provided, and the computer device can be a server or a terminal, and its internal structure diagram can be as Figure 3As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes a power supply, distribution, and management and control method for a microgrid.

[0088] Those skilled in the art can understand that Figure 3 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0089] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0090] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0091] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0092] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0093] In this article, specific examples are used to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A power supply, distribution and control method for a microgrid, characterized in that: The microgrid comprises: a power supply layer, an energy storage device, a load layer, a control system and a connection device; the power supply layer comprises renewable energy power generation equipment and fossil fuel power generation equipment, and the power supply layer is used to provide a power source for the microgrid; the energy storage device is used to store power and balance the supply and demand relationship of the microgrid; the load layer comprises various power-consuming equipment and power users; the control system is used to control the energy flow between the power supply layer, the energy storage device and the load layer, and coordinate the operation of the microgrid; the connection device is used to connect the microgrid to an external power grid to ensure the interconnection between the microgrid and the external power grid; the power supply, distribution and control method of the microgrid comprises: Collect the current operation data and external influencing factor data of each distributed power source within the microgrid power layer; the current operation data includes: power load, power generation and equipment status, and the external influencing factor data includes: weather information, holiday arrangements and economic activity indicators; The principal component analysis method is used to extract the power demand-related features of the current operation data and the external influencing factor data, respectively, to obtain the feature data of the current operation data and the feature data of the external influencing factor data; Input the characteristic data of the current operation data and the characteristic data of the external influencing factor data into the microgrid power demand prediction model to obtain the power demand prediction value of the microgrid; the microgrid power demand prediction model is obtained by training the neural network model with a training set; the training set includes: the characteristic data of the historical operation data of each distributed power source within the microgrid power layer, the sample characteristic data of the external influencing factor data and the corresponding microgrid power demand sample value; Adjust the operating status of renewable energy power generation equipment and fossil fuel power generation equipment according to the power demand forecast value of the microgrid; Dynamically monitor the power load demand of the microgrid load layer, and adjust the power supply plan according to the power load demand; wherein the adjustment of the power supply plan includes: optimizing power consumption time periods, hierarchical load management, and using external power grids for power supply.

2. The power supply, distribution and control method of a microgrid according to claim 1, characterized in that: The training process of the microgrid power demand prediction model specifically includes: Construct a training set; Input the characteristic data of the historical operation data of each distributed power source within the microgrid power layer and the sample characteristic data of the external influencing factor data into the neural network model, and output the power demand forecast value of the microgrid; A loss function is constructed according to the power demand prediction value of the microgrid and the power demand sample value of the microgrid, and the network parameters of the neural network model are iteratively optimized according to the loss function until the iterative optimization times reach the maximum value or the loss function reaches the minimum value, and the iterative optimization is stopped to obtain the microgrid power demand prediction model.

3. The power supply, distribution and control method of a microgrid according to claim 2, characterized in that: Construct a training set, including: Obtain historical operation data and sample data of external influencing factors; Data cleaning is performed on the historical operation data and the sample data of external influencing factors respectively to obtain cleaned historical operation data and cleaned sample data of external influencing factors; wherein data cleaning includes eliminating outliers and noise.

4. The power supply, distribution and control method of a microgrid according to claim 1, characterized in that: Dynamically monitor the power load demand of the microgrid load layer and adjust the power supply plan according to the power load demand, including: When the power load demand of the load layer is lower than the power supply capacity of each distributed power source, the excess power is stored in the energy storage device; When the power load demand is higher than the power supply capacity of each distributed power source, the power provided by the energy storage device is used first to balance the power supply and demand of the microgrid.

5. The power supply, distribution and control method of a microgrid according to claim 1, characterized in that: The power supply, distribution and control method of the microgrid further includes: The DC ring network power supply method is used to connect the renewable energy power generation equipment and fossil fuel power generation equipment and the load layer in the microgrid.

6. The power supply, distribution and control method of a microgrid according to claim 1, characterized in that: The power supply, distribution and control method of the microgrid further includes: Collecting the operating state parameters of the microgrid in real time, and monitoring the operating state of the microgrid in real time according to the operating state parameters; the operating state parameters include: at least one parameter of voltage, current and frequency; When any of the operating status parameters of the microgrid is monitored to be abnormal, the operating status of each distributed power source in the microgrid is automatically adjusted to ensure the stable operation of the microgrid.

7. A power supply, distribution and control system for a microgrid, characterized in that: The power supply and distribution and control system of the microgrid is connected to the microgrid, and the microgrid includes: a power supply layer, an energy storage device, a load layer, a control system and a connection device; the power supply layer includes renewable energy power generation equipment and fossil fuel power generation equipment, and the power supply layer is used to provide a power source for the microgrid; the energy storage device is used to store electricity and balance the supply and demand relationship of the microgrid; the load layer includes various power-consuming equipment and power users; the control system is used to control the energy flow between the power supply layer, the energy storage device and the load layer, and coordinate the operation of the microgrid; the connection device is used to connect the microgrid to an external power grid to ensure the interconnection between the microgrid and the external power grid; the power supply and distribution and control system of the microgrid is used to implement the power supply and distribution and control method of the microgrid described in any one of claims 1-6, and the power supply and distribution and control system of the microgrid includes: A data acquisition unit is used to collect current operation data and external influencing factor data of each distributed power source within the microgrid power layer; the current operation data includes: power load, power generation and equipment status, and the external influencing factor data includes: weather information, holiday arrangements and economic activity indicators; A feature extraction unit is used to extract the power demand-related features of the current operation data and the external influencing factor data by using the principal component analysis method, so as to obtain the feature data of the current operation data and the feature data of the external influencing factor data; A power demand forecast value determination unit of a microgrid is used to input characteristic data of current operation data and characteristic data of external influencing factor data into a microgrid power demand forecast model to obtain a power demand forecast value of the microgrid; the microgrid power demand forecast model is obtained by training a neural network model using a training set; the training set includes: characteristic data of historical operation data of each distributed power source within the microgrid power layer, sample characteristic data of external influencing factor data and corresponding sample values ​​of power demand of the microgrid; An operation state adjustment unit, used for adjusting the operation state of the renewable energy power generation equipment and the fossil fuel power generation equipment according to the power demand forecast value of the microgrid; The monitoring unit is used to dynamically monitor the power load demand of the microgrid load layer and adjust the power supply plan according to the power load demand; wherein the adjustment of the power supply plan includes: optimizing the power consumption period, hierarchical load management and using external power grid for power supply.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the power supply, distribution, and control method of the microgrid described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the power supply, distribution and control method of the microgrid described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the power supply, distribution and control method of the microgrid described in any one of claims 1 to 6 is implemented.

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