Microgrid-based control method, device, medium and equipment

Abstract

The present application provides a microgrid-based control method, apparatus, medium, and device, including: obtaining a distributed energy resource set within a preset time period, selecting a target distributed energy resource from the distributed energy resource set, and optimizing the droop control parameters of the target distributed energy resource based on the preset output power of each distributed energy resource in the distributed energy resource set to obtain optimized data corresponding to the microgrid's stability meeting preset conditions, wherein the droop control parameters represent the frequency and amplitude of the voltage, and adjusting the droop control parameters of each distributed energy resource based on the optimized data and the channel utilization corresponding to the distributed energy resource set within the preset time period. By adjusting the droop control parameters of each distributed energy resource through the optimized data and the channel utilization corresponding to the distributed energy resource set, power regulation through optical fiber communication is eliminated, thereby improving the efficiency of data transmission.

Description

Technical Field

[0001] The present application relates to the field of microgrid-based control technology, and specifically to microgrid-based control methods, devices, media, and equipment. Background Art

[0002] Smart microgrid is a combination of "smart grid" and "microgrid". Smart microgrid can fully utilize clean energy while solving the problem of unstable distributed energy. It can also play an auxiliary role of "peak shaving and valley filling" for the large power grid. Among them, "smart grid" is an automated power supply network that can use sensors to monitor and collect information for power supply and power-consuming equipment in real time, and use the control system to optimize the management of the power system; "microgrid" refers to a small power generation and distribution system composed of distributed energy, energy storage devices, energy conversion devices, related loads and monitoring. The operation and control of the "microgrid" should be able to respond quickly and independently to accidents in the power grid based on local information, without having to accept the unified dispatch of the traditional power grid.

[0003] Traditional microgrid control uses droop control to achieve power balancing and maintain stable system operation. This droop control mimics the power synchronization mechanism of traditional generator systems to achieve communication-free power distribution. However, since droop control eliminates communication between distributed energy resources (DERs), this control method can lead to poor overall grid stability. Another control method uses fiber-optic communication between the control center and DERs for power regulation, but this method is costly and has slow data transmission efficiency. Summary of the Invention

[0004] In order to solve the above technical problems, the present application is proposed. The embodiments of the present application provide a control method, device, medium and equipment based on a microgrid, which solves the problems of high cost and low data transmission efficiency.

[0005] According to one aspect of the present application, a control method based on a microgrid is provided, including: obtaining a set of distributed energy resources within a preset time period; selecting a target distributed energy resource from the set of distributed energy resources; obtaining the actual output power of each distributed energy resource at a first moment; and predicting the actual output power of each distributed energy resource at a second moment based on the actual output power and the droop control parameter of the target distributed energy resource, wherein the first moment is earlier than the second moment; optimizing the droop control parameter of the target distributed energy resource based on the predicted actual output power of each distributed energy resource at the second moment, so as to obtain optimization data corresponding to the degree of stability of the microgrid meeting preset conditions; wherein the droop control parameter represents the frequency and amplitude of the voltage; and adjusting the droop control parameter of each distributed energy resource based on the optimization data and the channel utilization corresponding to the set of distributed energy resources within the preset time period.

[0006] In one embodiment, predicting the actual output power of each distributed energy at the second moment based on the actual output power and the droop control parameters of the target distributed energy includes: performing droop control on the microgrid based on the actual output power of each distributed energy at the first moment to obtain the voltage amplitude and voltage frequency corresponding to each distributed energy; constructing a parameter control matrix based on the voltage amplitude and voltage frequency of each distributed energy; and predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix and the droop control parameters of the target distributed energy.

[0007] In one embodiment, predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the droop control parameter of the target distributed energy includes: predicting the actual output power of the target distributed energy at the second moment based on the output power of each distributed energy at the first moment and the preset output power of the target distributed energy at the second moment; and predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the actual output power of the target distributed energy at the second moment.

[0008] In one embodiment, predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the actual output power of the target distributed energy at the second moment includes: predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, the actual output power of the target distributed energy at the second moment, and a neural network algorithm.

[0009] In one embodiment, selecting a target distributed energy source from the distributed energy source set includes: selecting a distributed energy source with an air pollution level less than or equal to a preset pollution level threshold from the distributed energy source set as the target distributed energy source.

[0010] According to another aspect of the present application, a control device based on a microgrid is provided, including: an acquisition module for acquiring a set of distributed energy resources within a preset time period; a selection module for selecting a target distributed energy resource from the set of distributed energy resources; an output power acquisition unit for acquiring the actual output power of each distributed energy resource at a first moment; and predicting the actual output power of each distributed energy resource at a second moment based on the actual output power and the droop control parameter of the target distributed energy resource, wherein the first moment is earlier than the second moment; an optimization module for optimizing the droop control parameter of the target distributed energy resource based on the predicted actual output power of each distributed energy resource at the second moment, so as to obtain optimization data corresponding to the degree of stability of the microgrid meeting preset conditions; wherein the droop control parameter represents the frequency and amplitude of the voltage; and an adjustment module for adjusting the droop control parameter of each distributed energy resource based on the optimization data and the channel utilization corresponding to the set of distributed energy resources within the preset time period.

[0011] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute any of the above-mentioned microgrid-based control methods.

[0012] According to another aspect of the present application, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; and the processor for executing any of the above-mentioned microgrid-based control methods.

[0013] The present application provides a microgrid-based control method, device, medium, and device, including: obtaining a distributed energy set within a preset time period, selecting a target distributed energy from the distributed energy set, and optimizing the droop control parameters of the target distributed energy based on the preset output power of each distributed energy in the distributed energy set to obtain optimized data corresponding to the microgrid's stability meeting preset conditions, wherein the droop control parameters represent the frequency and amplitude of the voltage, and adjusting the droop control parameters of each distributed energy based on the optimized data and the channel utilization corresponding to the distributed energy set within the preset time period. By adjusting the droop control parameters of each distributed energy by optimizing the data and the channel utilization corresponding to the distributed energy set, the droop control parameters of each distributed energy can be adjusted without power regulation through optical fiber communication, thereby improving the efficiency of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other purposes, features, and advantages of the present application will become more apparent through a more detailed description of the embodiments of the present application in conjunction with the accompanying drawings. The accompanying drawings are intended to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0015] Figure 1 It is a flowchart of a control method for a communication terminal provided by an exemplary embodiment of the present application.

[0016] Figure 2 It is a flowchart of a microgrid-based control method provided by another exemplary embodiment of the present application.

[0017] Figure 3 It is a flowchart of a method for predicting output power provided by an exemplary embodiment of the present application.

[0018] Figure 4 It is a flowchart of a method for predicting output power provided by another exemplary embodiment of the present application.

[0019] Figure 5 It is a flowchart of a microgrid-based control method provided by another exemplary embodiment of the present application.

[0020] Figure 6 It is a structural diagram of a microgrid-based control device provided by an exemplary embodiment of the present application.

[0021] Figure 7 It is a structural diagram of a microgrid-based control device provided by another exemplary embodiment of the present application.

[0022] Figure 8 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0023] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described herein.

[0024] Figure 1 FIG. 1 is a flow chart of a microgrid-based control method provided by an exemplary embodiment of the present application. Figure 1 As shown, the control method based on microgrid includes:

[0025] Step 110: Obtain a set of distributed energy resources within a preset time period.

[0026] Obtain a distributed energy set within a preset time period, where the distributed energy set includes electric energy, carbon energy, wind energy, water energy, solar energy, etc.

[0027] Step 120: Select a target distributed energy from the distributed energy set.

[0028] The target distributed energy is clean energy, such as wind energy, water energy, solar energy, etc. The target distributed energy with the least environmental pollution is selected from the distributed energy set.

[0029] Step 130: Optimize the droop control parameters of the target distributed energy based on the predicted actual output power of each distributed energy at the second moment to obtain optimized data corresponding to the stability of the microgrid meeting the preset conditions, wherein the droop control parameters represent the frequency and amplitude of the voltage.

[0030] The droop control parameters of the target distributed energy are optimized according to the actual output power of each distributed energy in the distributed energy set at the second moment, that is, the frequency and amplitude of the voltage of the target distributed energy are optimized, so as to obtain the optimization data corresponding to the stability of the microgrid meeting the preset conditions, that is, if the stability is greater than or equal to the preset stability threshold, the optimization data is obtained.

[0031] Step 140: Adjust the droop control parameters of each distributed energy source according to the optimization data and the channel utilization rate corresponding to the distributed energy source set within a preset time period.

[0032] The droop control parameters of each distributed energy are adjusted according to the optimization data and the channel utilization corresponding to the distributed energy set within a preset time period.

[0033] The present application provides a microgrid-based control method, device, medium, and device, including: obtaining a distributed energy set within a preset time period, selecting a target distributed energy from the distributed energy set, and optimizing the droop control parameters of the target distributed energy based on the actual output power of each distributed energy in the distributed energy set at the second moment, so as to obtain optimization data corresponding to the stability of the microgrid meeting preset conditions, wherein the droop control parameters represent the frequency and amplitude of the voltage, and adjusting the droop control parameters of each distributed energy based on the optimization data and the channel utilization corresponding to the distributed energy set within the preset time period. By adjusting the droop control parameters of each distributed energy by optimizing the data and the channel utilization corresponding to the distributed energy set, the droop control parameters of each distributed energy can be adjusted without power regulation through optical fiber communication, thereby improving the efficiency of data transmission.

[0034] Figure 2 It is a flowchart of a microgrid-based control method provided by another exemplary embodiment of the present application.

[0035] like Figure 2 As shown, the microgrid-based control method may include:

[0036] Step 150: Obtain the actual output power of each distributed energy source at the first moment.

[0037] The output power of each distributed energy source at a first moment is obtained, where the first moment may be an initial moment.

[0038] Step 160: predicting the actual output power of each distributed energy at a second moment according to the actual output power and the droop control parameter of the target distributed energy, wherein the first moment is earlier than the second moment.

[0039] The actual output power of each distributed energy is predicted according to the actual output power and the voltage amplitude and voltage frequency of the target distributed energy at a second moment, where the second moment is later than the first moment.

[0040] Figure 3 FIG. 1 is a flow chart of a method for predicting output power provided by an exemplary embodiment of the present application. Figure 3 As shown, step 160 may include:

[0041] Step 161: Perform droop control on the microgrid according to the actual output power of each distributed energy at the first moment, and obtain the voltage amplitude and voltage frequency corresponding to each distributed energy.

[0042] The microgrid performs droop control based on the actual output power of each distributed energy resource at the first moment, obtaining the voltage amplitude and voltage frequency corresponding to each distributed energy resource. Each distributed energy resource is input into the microgrid, and the microgrid performs droop control, thereby outputting the voltage amplitude and voltage frequency corresponding to each distributed energy resource.

[0043] Step 162: Construct a parameter control matrix according to the voltage amplitude and voltage frequency of each distributed energy source.

[0044] The voltage amplitude and voltage frequency of each distributed energy source are integrated to form a parameter control matrix. The voltage amplitude can be used as the matrix row, and the voltage frequency as the matrix column, and the matrix can be arranged uniformly.

[0045] Step 163: predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the droop control parameter of the target distributed energy.

[0046] According to the actual output power of each distributed energy at the first moment, the parameter control matrix and the droop control parameter of the target distributed energy, the actual output power of each distributed energy at the second moment is predicted.

[0047] Figure 4 FIG. 1 is a flow chart of a method for predicting output power provided by another exemplary embodiment of the present application. Figure 4 As shown, step 163 may include:

[0048] Step 1631: predicting the actual output power of the target distributed energy at the second moment based on the output power of each distributed energy at the first moment and the preset output power of the target distributed energy at the second moment.

[0049] Step 1632: predict the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the actual output power of the target distributed energy at the second moment.

[0050] In one embodiment, step 1632 is specifically implemented as follows: based on the output power of each distributed energy at the first moment, the parameter control matrix, the actual output power of the target distributed energy at the second moment, and the neural network algorithm, predicting the actual output power of each distributed energy at the second moment.

[0051] Figure 5 It is a flowchart of a microgrid-based control method provided by another exemplary embodiment of the present application.

[0052] like Figure 5As shown, step 120 may include:

[0053] Step 121: Select a distributed energy source with an air pollution level less than or equal to a preset pollution level threshold from the distributed energy source set as a target distributed energy source.

[0054] In one embodiment, step 121 is specifically implemented as follows: marking the actual output power of each distributed energy source at the second moment.

[0055] Figure 6 This is a schematic diagram of the structure of a microgrid-based control device provided by an exemplary embodiment of the present application. Figure 6 As shown, the microgrid-based control device 20 includes: an acquisition module 201 for acquiring a distributed energy set within a preset time period, a selection module 202 for selecting a target distributed energy from the distributed energy set, an optimization module 203 for optimizing the droop control parameters of the target distributed energy according to the preset output power of each distributed energy in the distributed energy set, so as to obtain optimization data corresponding to the stability of the microgrid meeting the preset conditions, wherein the droop control parameters represent the frequency and amplitude of the voltage, and an adjustment module 204 adjusts the droop control parameters of each distributed energy according to the optimization data and the channel utilization corresponding to the distributed energy set within the preset time period.

[0056] Figure 7 This is a schematic diagram of the structure of a microgrid-based control device provided by another exemplary embodiment of the present application. Figure 7 As shown, the microgrid-based control device 20 may include: an output power acquisition unit 205, used to obtain the actual output power of each distributed energy at a first moment; a prediction unit 206, used to predict the actual output power of each distributed energy at a second moment based on the actual output power and the droop control parameter of the target distributed energy; wherein, the first moment is earlier than the second moment.

[0057] In one embodiment, if Figure 7 As shown, the prediction unit 206 may include: an amplitude and frequency acquisition unit 2061, which is used to perform droop control on the microgrid according to the actual output power of each distributed energy at the first moment, and obtain the amplitude of the voltage and the frequency of the voltage corresponding to each distributed energy; a construction unit 2062, which is used to construct a parameter control matrix according to the amplitude of the voltage and the frequency of the voltage of each distributed energy; a power prediction unit 2063, which is used to predict the actual output power of each distributed energy at the second moment according to the actual output power of each distributed energy at the first moment, the parameter control matrix and the droop control parameter of the target distributed energy.

[0058] In one embodiment, the power prediction unit 2063 can be specifically configured as: predicting the actual output power of the target distributed energy at the second moment based on the output power of each distributed energy at the first moment and the preset output power of the target distributed energy at the second moment; predicting the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix and the actual output power of the target distributed energy at the second moment.

[0059] In one embodiment, the power prediction unit 2063 can be specifically configured to predict the actual output power of each distributed energy at the second moment based on the actual output power of each distributed energy at the first moment, the parameter control matrix, the actual output power of the target distributed energy at the second moment, and the neural network algorithm.

[0060] In one embodiment, if Figure 7 As shown, the selection module 202 may include: a selection subunit 2021, configured to select a distributed energy with an air pollution level less than or equal to a preset pollution level threshold from the distributed energy set as a target distributed energy.

[0061] In one embodiment, the microgrid-based control device 20 may be specifically configured to: identify the actual output power of each distributed energy source at the second moment.

[0062] Figure 8 The figure shows a block diagram of an electronic device according to an embodiment of the present application.

[0063] like Figure 8 As shown, the electronic device 10 includes one or more processors 11 and a memory 12 .

[0064] The processor 11 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0065] The memory 12 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may execute the program instructions to implement the microgrid-based control method of each embodiment of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage medium.

[0066] In one example, the electronic device 10 may further include an input device 13 and an output device 14 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0067] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector, configured to receive collected input signals from the first device and the second device.

[0068] In addition, the input device 13 may also include, for example, a keyboard, a mouse, and the like.

[0069] The output device 14 can output various information to the outside, including determined distance information, direction information, etc. The output device 14 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0070] Of course, to simplify, Figure 8 Only some of the components related to the present application in the electronic device 10 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device 10 may further include any other appropriate components according to specific application scenarios.

[0071] The computer program product may be written in any combination of one or more programming languages ​​to implement the program code for performing the operations of the embodiments of the present application, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0072] The above description has been provided for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A control method based on a microgrid, characterized in that: include: Obtaining a set of distributed energy resources within a preset time period; Selecting a target distributed energy source from the distributed energy source set; Obtain the actual output power of each distributed energy at the first moment; as well as predicting the actual output power of each distributed energy at a second moment according to the actual output power and the droop control parameter of the target distributed energy, wherein the first moment is earlier than the second moment; Optimizing the droop control parameters of the target distributed energy source based on the predicted actual output power of each distributed energy source at the second moment to obtain optimized data corresponding to the stability of the microgrid meeting a preset condition; wherein the droop control parameters represent the frequency and amplitude of the voltage; and The droop control parameter of each distributed energy source is adjusted according to the optimization data and the channel utilization rate corresponding to the distributed energy source set within the preset time period.

2. The microgrid-based control method according to claim 1, characterized in that: The predicting, based on the actual output power and the droop control parameter of the target distributed energy, the actual output power of each distributed energy at the second moment includes: Performing droop control on the microgrid according to the actual output power of each distributed energy at the first moment, to obtain the voltage amplitude and voltage frequency corresponding to each distributed energy; Constructing a parameter control matrix according to the voltage amplitude and voltage frequency of each distributed energy source; and The actual output power of each distributed energy at a second moment is predicted according to the actual output power of each distributed energy at a first moment, the parameter control matrix, and the droop control parameter of the target distributed energy.

3. The microgrid-based control method according to claim 2, characterized in that: The predicting, based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the droop control parameter of the target distributed energy, the actual output power of each distributed energy at the second moment includes: Predicting the actual output power of the target distributed energy at the second moment based on the output power of each distributed energy at the first moment and the preset output power of the target distributed energy at the second moment; as well as The actual output power of each distributed energy at the second moment is predicted according to the actual output power of each distributed energy at the first moment, the parameter control matrix, and the actual output power of the target distributed energy at the second moment.

4. The microgrid-based control method according to claim 3, characterized in that: The predicting, based on the actual output power of each distributed energy at the first moment, the parameter control matrix, and the actual output power of the target distributed energy at the second moment, the actual output power of each distributed energy at the second moment includes: The actual output power of each distributed energy at the second moment is predicted based on the actual output power of each distributed energy at the first moment, the parameter control matrix, the actual output power of the target distributed energy at the second moment, and the neural network algorithm.

5. The microgrid-based control method according to claim 1, characterized in that: The selecting a target distributed energy source from the distributed energy source set includes: A distributed energy source with an air pollution level less than or equal to a preset pollution level threshold in the distributed energy source set is selected as the target distributed energy source.

6. A control device based on a microgrid, characterized in that: include: An acquisition module, used to acquire a set of distributed energy resources within a preset time period; A selection module, configured to select a target distributed energy from the distributed energy set; an output power acquisition unit, configured to acquire an actual output power of each distributed energy resource at a first moment; and predict, based on the actual output power and a droop control parameter of the target distributed energy resource, the actual output power of each distributed energy resource at a second moment, wherein the first moment is earlier than the second moment; an optimization module, configured to optimize the droop control parameters of the target distributed energy source based on the predicted actual output power of each distributed energy source at the second moment, so as to obtain optimized data corresponding to the stability of the microgrid satisfying a preset condition; wherein the droop control parameters represent the frequency and amplitude of the voltage; and An adjustment module is configured to adjust a droop control parameter of each distributed energy source according to the optimization data and a channel utilization rate corresponding to the distributed energy source set within the preset time period.

7. A computer-readable storage medium storing a computer program, wherein the computer program is used to execute the microgrid-based control method according to any one of claims 1 to 5.

8. An electronic device, comprising: processor; a memory for storing instructions executable by the processor; The processor is used to execute the microgrid-based control method described in any one of claims 1 to 5.

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