Microgrid group control method and device, computer equipment and computer program product

Abstract

The invention discloses a micro-grid group control method and device, computer equipment and a computer program product. The method comprises the following steps: selecting a distributed power supply meeting a preset condition from a target microgrid group as a fixed distributed power supply corresponding to each of a plurality of microgrids; constructing a sparse communication network based on the fixed distributed power supplies corresponding to the plurality of micro-grids; based on a preset droop control algorithm, controlling a plurality of distributed power supplies corresponding to the plurality of micro-grids, and based on the sparse communication network, collecting distributed power supply control data; setting a distributed secondary frequency device and a distributed secondary voltage controller based on a preset time consistency algorithm and distributed power supply control data; and controlling the target microgrid group based on the distributed secondary frequency device and the distributed secondary voltage controller. According to the method, the technical problem that the real-time requirement of the micro-grid group on rapid coordination control cannot be met due to slow convergence speed of coordination control of the micro-grid group at present is solved.

Description

Technical Field

[0001] This invention relates to the field of power system control technology, and more specifically, to a microgrid group control method, device, computer equipment, and computer program product. Background Technology

[0002] While traditional distributed coordination control technology for microgrid groups can achieve efficient energy utilization and reliable power supply to a certain extent, it has revealed inherent defects and shortcomings in practical applications, especially in scenarios requiring high reliability and real-time performance.

[0003] Currently, distributed coordination control mostly employs asymptotic consensus protocols. While these can theoretically achieve state consistency among distributed units, their convergence speed is slow, and theoretically, it requires an infinite amount of time to achieve precise consistency, failing to meet the requirements of microgrid clusters for rapid response and real-time control. Finite-time control methods, although guaranteeing system convergence within a finite time, are affected by the system's initial state and topology, making it impossible to provide stable and reliable convergence time predictions in practical applications, thus limiting their effectiveness in time-sensitive control tasks. Fixed-time control, while having a fixed convergence time, lacks flexibility and cannot adjust the convergence speed according to actual needs or system state, limiting its application scenarios and making it difficult to adapt to the dynamic characteristics of microgrid clusters.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a microgrid group control method, apparatus, computer equipment, and computer program product to at least solve the technical problem that the current coordinated control of microgrid groups has a slow convergence speed and cannot meet the real-time requirements of microgrid groups for fast coordinated control.

[0006] According to one aspect of the present invention, a microgrid group control method is provided, comprising: selecting distributed power sources that meet preset conditions from multiple distributed power sources corresponding to multiple microgrids in a target microgrid group as fixed distributed power sources corresponding to each of the multiple microgrids; constructing a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids; controlling the multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and collecting distributed power source control data based on the sparse communication network, wherein the distributed power source control data includes at least: output frequency, output voltage, and output power; setting a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and controlling the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0007] Optionally, a sparse communication network is constructed based on the fixed distributed power sources corresponding to each of the multiple microgrids, including: using the minimum spanning tree algorithm to determine the topology corresponding to the fixed distributed power sources of each of the multiple microgrids; determining the communication link parameters based on the distance between the multiple microgrids; and constructing the sparse communication network based on the topology and communication link parameters.

[0008] Optionally, based on a preset droop control algorithm, multiple distributed power sources corresponding to each of the multiple microgrids are controlled, including: initializing initial control parameters for the multiple distributed power sources corresponding to each of the multiple microgrids, wherein the control parameters include a first droop coefficient corresponding to active power and frequency, and a second droop coefficient corresponding to reactive power and voltage; adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids; obtaining the power demand of the target microgrid group; adjusting the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids based on the power demand to obtain adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids; repeating the steps of adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm based on the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids to control the multiple distributed power sources corresponding to each of the multiple microgrids.

[0009] Optionally, based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, the active and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted using the target formula in the preset droop control algorithm, wherein the target formula is as follows:

[0010] ,

[0011] in, For the first The first microgrid The actual output frequency of a distributed power source. The rated frequency of the distributed power source. For the first The first microgrid The first droop coefficient of a distributed power source. For the first The first microgrid Active power of a distributed power source For the first The first microgrid The actual output voltage amplitude of a distributed power source The rated voltage of the distributed power source. For the first The first microgrid The second droop coefficient of a distributed power source For the first The first microgrid The reactive power of a distributed power source.

[0012] Optionally, based on a preset time consistency algorithm and distributed power supply control data, a distributed secondary frequency controller and a distributed secondary voltage controller are set up, including: determining a convergence time function according to the preset time consistency algorithm; and setting up the distributed secondary frequency controller and the distributed secondary voltage controller based on the convergence time function.

[0013] Optionally, the target microgrid group is controlled based on a distributed secondary frequency controller and a distributed secondary voltage controller, including: acquiring the structure corresponding to multiple microgrids; determining the adjacent microgrids corresponding to each of the multiple microgrids based on the structure corresponding to the multiple microgrids; adjusting the output frequency corresponding to each of the multiple microgrids based on the frequency and active power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary frequency controller; and adjusting the output voltage corresponding to each of the multiple microgrids based on the voltage and reactive power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary voltage controller.

[0014] According to another aspect of the present invention, a microgrid group control device is also provided, comprising: a selection module, configured to select distributed power sources that meet preset conditions from multiple distributed power sources corresponding to multiple microgrids in a target microgrid group as fixed distributed power sources corresponding to each of the multiple microgrids; a construction module, configured to construct a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids; a first control module, configured to control the multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and to collect distributed power source control data based on the sparse communication network, wherein the distributed power source control data includes at least: output frequency, output voltage, and output power; a setting module, configured to set a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and a second control module, configured to control the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0015] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein, when the program is running, the device where the non-volatile storage medium is located is controlled to execute any of the above-described microgrid group control methods.

[0016] According to another aspect of the present invention, a computer device is also provided, the computer device including a processor, the processor being configured to run a program, wherein the program executes any of the microgrid group control methods described above when it runs.

[0017] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements any of the microgrid group control methods described above.

[0018] In this embodiment of the invention, a microgrid group control method is adopted. This involves selecting distributed power sources that meet preset conditions from the multiple distributed power sources corresponding to each microgrid in the target microgrid group as fixed distributed power sources for each microgrid; constructing a sparse communication network based on these fixed distributed power sources; controlling the multiple distributed power sources corresponding to each microgrid based on a preset droop control algorithm; and collecting distributed power source control data based on the sparse communication network. This distributed power source control data includes at least: output frequency, output voltage, and output power; setting up a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and controlling the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller. This achieves the goal of hierarchical control of distributed power sources and microgrids based on a time consistency algorithm, thereby improving the convergence speed of the microgrid group to achieve rapid coordinated control. This solves the technical problem that the current coordinated control convergence speed of microgrid groups is slow and cannot meet the real-time requirements of rapid coordinated control in microgrid groups. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0020] Figure 1 A hardware block diagram of a computer terminal for implementing a microgrid group control method is shown.

[0021] Figure 2 This is a schematic flowchart of a microgrid group control method provided according to an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of a microgrid group control method provided according to an optional embodiment of the present invention;

[0023] Figure 4 This is a structural block diagram of a microgrid group control device provided according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to an embodiment of the present invention, a method embodiment of a microgrid group control method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a microgrid group control method is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0028] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0029] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the microgrid group control method in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the microgrid group control method of the aforementioned application. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0030] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0031] Figure 2 This is a flowchart illustrating the microgrid group control method provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes the following steps:

[0032] Step S202: Select a distributed power source that meets the preset conditions from the multiple distributed power sources corresponding to the multiple microgrids in the target microgrid group as the fixed distributed power source corresponding to each of the multiple microgrids.

[0033] In this step, a microgrid cluster refers to a power system network composed of multiple interconnected microgrids. A microgrid itself is a small power system capable of operating independently or connected to the main grid. It includes distributed power sources (such as solar, wind, and small generators), loads, energy storage devices, and necessary control and protection devices, enabling self-balancing and management of power within a local area. When multiple microgrids are connected through appropriate communication and control strategies, they form a microgrid cluster. The construction of microgrid clusters aims to achieve greater power system flexibility, reliability, and economy through coordinated control and resource sharing among the microgrids. Microgrid clusters can perform internal power dispatch to address the volatility of renewable energy, improve load response speed, and provide emergency power support or achieve self-sufficient islanded operation during main grid failures.

[0034] Pinned-DG (Pinned-Generates) are selected from multiple microgrids within the target microgrid cluster. Pinned-DGs play a crucial role in the multi-layered control architecture of the microgrid cluster, acting as information relays and control anchors to ensure effective communication and coordinated control between the microgrid layer and the microgrid cluster layer. The selection criteria for Pinned-DGs should comprehensively consider the following factors:

[0035] 1. Power supply capacity and reliability: Prioritize distributed power supplies with larger capacity and high historical stability to ensure they can handle additional control tasks and execute group-level commands more reliably.

[0036] 2. Communication Capabilities and Network Location: Considering the power supply's communication infrastructure and network topology location, the Pinned-DG should have good communication capabilities and occupy a key position in the network to facilitate rapid information dissemination and real-time execution of coordinated control.

[0037] 3. Response speed and control compatibility: Pinned-DG should have a fast response speed, be able to quickly adjust its control parameters to cope with system changes, and its control strategy should be compatible with the preset time consistency algorithm to ensure the optimization of control effect.

[0038] Specifically, at the microgrid level, the criteria for selecting Pinned-Government (Pinned-Government) sources can be clearly defined, including but not limited to power source capacity, operational stability, communication latency and reliability, geographical location, and evaluation standards for their overall contribution to the microgrid cluster. A comprehensive evaluation of all distributed power sources within each microgrid should be conducted, collecting necessary operational data such as maximum output power, historical failure rate, communication link status, and geographical location information. Based on the evaluation results, one or more of the most suitable distributed power sources should be selected as Pinned-Government sources for each microgrid.

[0039] At coordinate S204, a sparse communication network is constructed based on the fixed distributed power sources corresponding to each of the multiple microgrids.

[0040] In this step, constructing a sparse communication network based on the corresponding fixed distributed generation sources (Pinned-DGs) of multiple microgrids enables efficient and reliable distributed coordinated control of the microgrid group. First, the topology of the sparse communication network can be constructed, connecting only the fixed distributed generation sources, rather than all distributed generation sources. Using graph theory principles, an undirected connected graph is designed, where edges represent communication links and nodes are fixed distributed generation sources, ensuring that each fixed distributed generation source communicates only with its nearest or most important neighbor node. Adjacency matrices and Laplace matrices can be used to ensure network connectivity and stability while reducing the number of communication links. A pre-defined time-consistency algorithm can be implemented between the Pinned-DGs to ensure that information reaches all target nodes from the source node within a fixed time, regardless of the initial state and topology of the network. This protocol, through time-varying gain functions and special scaling functions, can accelerate information propagation and achieve fast consensus convergence. Appropriate communication technologies, such as Wi-Fi, Bluetooth, ZigBee, or Dedicated Short Range Communication (DSRC), are selected for the communication links between the fixed distributed generation sources. Communication parameters, such as transmission rate, frequency, encryption standard, and error detection mechanism, are configured to improve the reliability and security of data transmission. Based on these parameters, a sparse communication network is constructed. Sparse communication networks can reduce information propagation delays and accelerate control response speeds. Furthermore, because information flows only between selected fixed distributed power sources, the exposure of sensitive data is reduced, enhancing network communication security. Even if individual fixed distributed power sources or communication links fail, the network can maintain connectivity through a designed backup mechanism, supporting the "plug-and-play" capability of the microgrid and facilitating system expansion and maintenance.

[0041] Constructing a sparse communication network based on fixed distributed power sources provides an innovative and effective communication architecture for the distributed coordinated control of microgrid clusters. This greatly promotes the rapid frequency recovery, voltage stability, and rational power allocation of microgrid clusters in complex environments, thereby improving the operating efficiency and reliability of the entire power system.

[0042] Step S206: Based on a preset droop control algorithm, control multiple distributed power sources corresponding to each of the multiple microgrids, and collect distributed power source control data based on a sparse communication network. The distributed power source control data includes at least: output frequency, output voltage, and output power.

[0043] In this step, within the distributed coordinated control framework of a microgrid cluster, droop control algorithm is a fundamental and crucial control strategy used to achieve automatic frequency and voltage regulation of the power supply. By combining a preset time-based droop control algorithm with a sparse communication network, this invention aims to optimize the control performance of multiple distributed generators (DGs) corresponding to multiple microgrids, ensuring fast and accurate frequency recovery, voltage stabilization, and power distribution at the microgrid cluster level. This method not only improves the system's response speed and stability but also reduces communication burden and system complexity through the design of the sparse communication network. In the DG controller within each microgrid, active power-frequency and reactive power-voltage droop coefficients can be preset based on device characteristics and expected performance. These coefficients determine the response characteristics of the DGs when frequency and voltage change. Each DG continuously monitors its local output frequency, output voltage, and output power. When a frequency or voltage deviation is detected, the DG automatically adjusts its output power according to the preset droop control algorithm to restore the frequency and voltage to normal levels. This process is independent and autonomous, requiring no central command. Pinned-Generators (PGs) periodically collect control data from their connected distributed generators (DGs) and report it to the coordinating controller at the microgrid cluster level via a sparse communication network. The collected data undergoes preliminary processing to ensure its accuracy and completeness. At the microgrid cluster level, the coordinating controller, based on the collected distributed generation control data and a pre-defined time consistency algorithm, performs global state estimation and command allocation, guiding each microgrid and DG to achieve accurate frequency and voltage recovery and rational power allocation within a preset timeframe.

[0044] In summary, by combining a preset time droop control algorithm with a sparse communication network, it is possible to effectively control and coordinate multiple distributed power sources in multiple microgrids within a microgrid cluster, achieving the goals of rapid frequency recovery, voltage stability, and reasonable power allocation. At the same time, it reduces communication costs and enhances the system's flexibility, security, and robustness.

[0045] Step S208: Based on the preset time consistency algorithm and distributed power supply control data, set up the distributed secondary frequency converter and the distributed secondary voltage controller.

[0046] In this step, while primary control (such as droop control) can achieve basic frequency and voltage stability in the distributed coordinated control of microgrid clusters, its limited adjustment response speed and accuracy make it difficult to meet the stringent requirements of modern power systems for rapid response and high-precision control. Therefore, a secondary control strategy based on a preset time consistency algorithm is proposed. By utilizing distributed power source control data collected from multiple microgrids, a distributed secondary frequency controller and a distributed secondary voltage controller are set up to achieve faster and more accurate frequency and voltage recovery. A preset time consistency algorithm, including time-varying gain functions and scaling functions, can be designed according to system requirements and control objectives to ensure that the algorithm can achieve frequency consistency across all microgrids and distributed power sources within a fixed time. A distributed secondary frequency controller can be set up by combining the preset time consistency algorithm and distributed power source control data. This controller can generate frequency adjustment signals based on frequency data through rapid calculation and coordination. The controller design must consider factors such as frequency deviation, active power allocation, and communication delay to ensure that all microgrids and distributed power sources achieve frequency synchronization within a preset time. Specific control strategies may include frequency consistency terms sent to neighboring units and the system reference frequency, as well as power allocation terms. Adjusting these terms enables rapid frequency recovery and proportional power allocation. Distributed power source control data collected from Pinned-DGs can be analyzed to assess reactive power demand and voltage consistency. Based on voltage control and reactive power regulation requirements, the parameters of the preset time consistency algorithm, including the scaling function and control gain, are optimized to ensure the system achieves voltage consistency within a preset time without over-reliance on network topology and initial states. A distributed secondary voltage controller is designed and implemented, generating voltage adjustment signals based on the preset time consistency algorithm and collected voltage and reactive power data. Control strategies may include voltage consistency terms, reactive power allocation terms, and neighbor node state coordination terms. Through the coordination of these terms, the voltage of all microgrids and distributed power sources is ensured to recover to the target value within a preset time, and proportional reactive power allocation is achieved. Through the distributed secondary frequency controller and distributed secondary voltage controller, the microgrid group can achieve rapid global frequency and voltage recovery, as well as reasonable allocation of active and reactive power, within a preset time. This integrated and coordinated control strategy can significantly improve the dynamic response capability and robustness of the system, reduce frequency and voltage fluctuations during transient processes, thereby enhancing the stability and power supply quality of the entire microgrid group.

[0047] Step S210: Control the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0048] In this step, a frequency regulation signal can be generated based on a distributed secondary frequency converter (DG) algorithm. This signal includes a weighted sum of frequency deviations and a power allocation term to compensate for the frequency deviation caused by droop control. The control signal is distributed to the DGs within their respective microgrids via the Pinned-DG, guiding them to adjust their output active power until the frequency of the entire microgrid group recovers to the preset value. The distributed secondary frequency converter can adjust the control signal in real time according to dynamic changes in the system, ensuring rapid frequency recovery even in the face of sudden load changes or fluctuations in renewable resources. By optimizing the control gain parameters and time-varying gain function, the system can flexibly adjust the convergence time to meet the needs of different operating conditions.

[0049] The distributed secondary voltage controller generates a voltage regulation signal based on a preset time consistency algorithm. This signal includes a voltage deviation term and a reactive power allocation term, used to compensate for voltage deviations and achieve voltage stability. The control signal is broadcast to the distributed generation services (DGs) within the microgrid via the Pinned-DG, adjusting their reactive power output to restore the voltage to its rated value. The distributed secondary voltage controller coordinates voltage recovery and reactive power allocation among microgrids, ensuring that the entire microgrid group reaches a voltage consistency state within a fixed time frame through the preset time consistency algorithm. This control strategy enhances the power quality of the microgrid group, reduces voltage fluctuations, and improves the overall stability of the system.

[0050] A control method based on distributed secondary frequency controllers and distributed secondary voltage controllers provides a complete and efficient solution for distributed coordinated control of microgrid clusters. By utilizing a preset time consistency algorithm, it can not only quickly restore frequency and voltage and achieve rational power allocation, but also simplify the communication network, reduce costs, and enhance system stability and flexibility. This technical solution has significant practical implications and broad application value for promoting the optimized operation of microgrid clusters, especially under conditions of high-proportion renewable energy integration and complex environmental changes.

[0051] Through the above steps, the goal of hierarchical control of distributed power sources and microgrids based on time consistency algorithms can be achieved, thereby improving the convergence speed of microgrid groups to achieve rapid coordinated control. This solves the technical problem that the current coordinated control of microgrid groups has a slow convergence speed and cannot meet the real-time requirements of rapid coordinated control for microgrid groups.

[0052] As an optional embodiment, a sparse communication network is constructed based on the fixed distributed power sources corresponding to each of the multiple microgrids, including: using the minimum spanning tree algorithm to determine the topology corresponding to the fixed distributed power sources of each of the multiple microgrids; determining the communication link parameters based on the distance between the multiple microgrids; and constructing the sparse communication network based on the topology and communication link parameters.

[0053] Optionally, when constructing a sparse communication network for the microgrid layer, a minimum spanning tree algorithm is used to determine the fixed distributed power sources corresponding to each of the multiple microgrids. This ensures network connectivity while reducing unnecessary communication links and lowering the communication burden. Based on the physical distance between multiple microgrids, communication link parameters, such as communication delay and data transmission rate, are designed to adapt the network to the actual physical distribution and ensure efficient and accurate data transmission. The sparse communication network constructed through the above steps, based on a preset time consistency algorithm, realizes the rapid exchange and processing of current and voltage information between microgrids. A distributed secondary frequency controller and a secondary voltage controller are then designed to achieve rapid frequency and voltage recovery and precise proportional power allocation, respectively, overcoming the limitations of traditional control methods in terms of convergence speed, time determinism, and system stability. This optimized network architecture and control strategy significantly improves the dynamic response capability and overall reliability of the microgrid cluster, ensuring efficient system operation and power quality.

[0054] As an optional embodiment, based on a preset droop control algorithm, multiple distributed power sources corresponding to each of the multiple microgrids are controlled, including: initializing initial control parameters for the multiple distributed power sources corresponding to each of the multiple microgrids, wherein the control parameters include a first droop coefficient corresponding to active power and frequency, and a second droop coefficient corresponding to reactive power and voltage; adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids; obtaining the power demand of the target microgrid group; adjusting the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids based on the power demand to obtain adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids; repeating the steps of adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm based on the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids to control the multiple distributed power sources corresponding to each of the multiple microgrids.

[0055] Optionally, multiple distributed power sources corresponding to each microgrid initialize control parameters, including a first droop coefficient corresponding to active power and frequency, and a second droop coefficient corresponding to reactive power and voltage, and use a preset droop control algorithm to initially adjust active and reactive power. Subsequently, based on the power demand of the target microgrid group, these initial control parameters are further optimized to obtain adjusted control parameters. This process is achieved through repeated iterations to ensure that the microgrid group can dynamically adjust in the face of changing power demand, maintaining the stability of frequency, voltage, and power. A preset time consistency algorithm constructs a sparse communication network between adjacent distributed power sources, promoting efficient information exchange. At the same time, a distributed secondary frequency controller and voltage controller are designed to overcome the limitations of existing technologies in convergence time and control accuracy, realizing rapid recovery of frequency and voltage and reasonable power allocation within the microgrid group. By selecting a Pinned-DG within each microgrid as the communication and control hub, a hierarchical coordinated control architecture is constructed, effectively reducing the overall network communication burden and improving the overall system response speed and reliability. Ultimately, the microgrid group coordination controller designed based on a preset time consistency algorithm among all Pinned-DGs ensures the accurate proportional distribution of active power among microgrids within a preset time period, significantly improving the operating efficiency and power quality of the microgrid group system, and realizing efficient management of the dynamic characteristics of the microgrid group.

[0056] As an optional embodiment, based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, the active and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted using the target formula in the preset droop control algorithm. The target formula is as follows:

[0057] ,

[0058] in, For the first The first microgrid The actual output frequency of a distributed power source. The rated frequency of the distributed power source. For the first The first microgrid The first droop coefficient of a distributed power source. For the first The first microgrid Active power of a distributed power source For the first The first microgrid The actual output voltage amplitude of a distributed power source The rated voltage of the distributed power source. For the first The first microgrid The second droop coefficient of a distributed power source For the first The first microgrid The reactive power of a distributed power source.

[0059] As an optional embodiment, a distributed secondary frequency controller and a distributed secondary voltage controller are set up based on a preset time consistency algorithm and distributed power supply control data, including: determining a convergence time function according to the preset time consistency algorithm; and setting up a distributed secondary frequency controller and a distributed secondary voltage controller based on the convergence time function.

[0060] Optionally, by deeply integrating time-consistency algorithms with distributed power source control data, distributed secondary frequency controllers and distributed secondary voltage controllers can be configured to optimize the coordinated control performance of the microgrid cluster. Specifically, a convergence time function is determined based on a preset time algorithm. This function serves as a time scale for the system to converge to an equilibrium state, ensuring that all nodes reach a consistent state within a specified time, and that the convergence time is independent of the initial network conditions. Based on the convergence time function, distributed secondary frequency controllers and distributed secondary voltage controllers are configured. These two controllers work synergistically; the former is responsible for the rapid recovery and precise allocation of frequency and active power, while the latter focuses on the stable control of voltage and reactive power. This configuration not only accelerates the system response speed but also enhances the system's robustness and power quality. In practical applications, this design enables the microgrid cluster to exhibit smaller overshoot and faster recovery speed when facing challenges such as load surges and renewable energy fluctuations, effectively suppressing drastic frequency and voltage fluctuations, maintaining system stability, and improving power quality. Furthermore, this embodiment reduces the communication burden by constructing a sparse communication network, supports the "plug-and-play" function of sub-microgrids, enhances the scalability and privacy protection of the system, and meets the development needs of modern microgrid group control technology.

[0061] As an optional embodiment, the target microgrid group is controlled based on a distributed secondary frequency controller and a distributed secondary voltage controller, including: acquiring the structure corresponding to multiple microgrids; determining the adjacent microgrids corresponding to each of the multiple microgrids based on the structure corresponding to the multiple microgrids; adjusting the output frequency of each of the multiple microgrids based on the frequency and active power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary frequency controller; and adjusting the output voltage of each of the multiple microgrids based on the voltage and reactive power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary voltage controller.

[0062] Optionally, the control strategy for the target microgrid cluster was optimized and upgraded. By comprehensively utilizing a distributed secondary frequency controller and a distributed secondary voltage controller, efficient coordination among the microgrids within the cluster was achieved. First, through analysis of the microgrid cluster structure, a communication network reflecting the interconnection relationships among the microgrids was constructed, establishing data interaction channels between each microgrid and its directly adjacent microgrids. This construction follows the sparsity principle, reducing unnecessary communication links and improving network operating efficiency and data security. Based on this communication network, the distributed secondary frequency controller adjusts the output frequency of each microgrid according to the frequency and active power information of adjacent microgrids, ensuring frequency consistency and balanced active power distribution. This dynamic adjustment process follows a preset time consistency algorithm, guaranteeing frequency recovery and power distribution within a predetermined time, enhancing the overall stability and reliability of the system. Simultaneously, the distributed secondary voltage controller adjusts the output voltage of each microgrid based on reactive power and voltage information, promoting consistent voltage recovery and rational reactive power distribution. This controller also employs a preset time consistency algorithm, enabling rapid voltage recovery to the target value within a preset time period, reducing voltage fluctuations and improving power quality. At the microgrid cluster level, key distributed generation sources within each microgrid are selected as Pinned-DGs. These Pinned-DGs serve as a bridge between the microgrid-level droop controller and the cluster-level coordinating controller, enabling efficient command transmission and execution. Pinned-DGs exchange information in real time through a sparse communication network and respond quickly to system-level commands based on a pre-defined time consistency algorithm, achieving active power allocation at the microgrid cluster level and significantly improving the real-time performance and effectiveness of the control strategy.

[0063] By applying the aforementioned control strategy, whether at the local control level, microgrid layer control, or microgrid group layer control, precise synchronization and distribution of frequency, voltage, and power can be guaranteed within a preset time. This overcomes the limitations of traditional control methods in terms of convergence speed, time determinism, and system flexibility, improving the overall performance and operating efficiency of the microgrid group and providing strong technical support for the stable operation and energy-efficient utilization of microgrids. This control strategy is not only applicable to current microgrid systems but also lays a solid theoretical and practical foundation for the coordinated control of large-scale, highly complex microgrid groups in the future.

[0064] The following is a specific example. Figure 3 This is a schematic diagram of a microgrid group control method provided by an optional embodiment of the present invention, such as... Figure 3 As shown, it includes:

[0065] Step S1: Primary droop control is one of the most fundamental and core control strategies in microgrids and traditional power systems. It is used to automatically distribute active and reactive power among parallel distributed power sources without communication. Its standard formula is as follows:

[0066] ;

[0067] in, Indicates the first In the first distributed power source, the first The actual output frequency of each unit. This indicates the rated frequency of the distributed power source. Indicates the first In the first distributed power source, the first The active power-frequency droop factor for each unit reflects the degree to which changes in active power affect the frequency. Indicates the first In the first distributed power source, the first The output active power of each unit. Indicates the first In the first distributed power source, the first The actual output voltage amplitude of each unit, and This indicates the rated voltage of the distributed power source. Indicates the first In the first distributed power source, the first The reactive power-voltage droop coefficient of each unit reflects the degree to which changes in reactive power affect voltage. Indicates the first In the first distributed power source, the first The reactive power output of each unit. Droop coefficient. , The formula is as follows:

[0068] ;

[0069] in, The active power frequency droop factor; This represents the maximum allowable frequency deviation of the system. This refers to the reactive power voltage droop factor. For maximum active power, This represents the maximum reactive power.

[0070] Step S2: The preset time-consistency algorithm is an advanced distributed coordination strategy in the field of multi-node system coordination and control. Its core objective is to enable multiple nodes to achieve state consistency within a user-defined fixed time, and the convergence time does not depend on the initial conditions of the system, thereby overcoming the limitations of traditional consensus algorithms in terms of convergence speed and flexibility. The design is as follows:

[0071] ;

[0072] ;

[0073] in, Represents a node The state, that is, the variables that need to be agreed upon. For nodes The neighborhood group, These are adjacency matrix elements. This is a time-varying gain function used to achieve convergence within a predetermined time. Scaling function. It is an important function introduced by the controller in the presupposed time stability theory. Its expression is defined in intervals to describe the system's scale characteristics in different time intervals. Additionally, for... Differentiation yields:

[0074] ;

[0075] This formula defines a time-varying function for preset time control. This function is used to implement the system at a specified time. The key to internal convergence is the pre-defined time consistency algorithm, which generates frequency correction values ​​through frequency information exchange between adjacent nodes to compensate for deviations in primary control and achieve global frequency synchronization. Its core is the pre-defined time consistency protocol, and the pre-defined time consistency observer is designed as follows:

[0076] ;

[0077] The first formula is the state observer dynamics equation, and the latter... For the signal dynamics equations, nodes State estimation node Reference signal. A positive control gain parameter is used to adjust the convergence speed.

[0078] The controller design is a combination of voltage regulator synchronization and tracking synchronization problems, and is based on a distributed secondary frequency controller with a preset time consistency algorithm as follows:

[0079] ;

[0080] ;

[0081] in, To control the output; and To control the gain coefficient; It is a preset time function; and These represent the frequencies of the local and neighboring units, respectively. This is the reference frequency for the k-th sub-microgrid; and For power output; This is the droop coefficient; It is the communication topology weight; Represents a set of neighbors; The connection weights are determined by the reference frequency. The formula, through frequency and power consistency terms, forces all units to achieve frequency synchronization and power allocation within a preset time. In the formula... and Positive control gain, dominant gain Using the weights of the edges connected to the reference connection, the controller achieves frequency recovery and precise power allocation through distributed coordination.

[0082] Step S3: Based on the preset time consistency algorithm, a frequency correction amount is generated through frequency information exchange between adjacent nodes to compensate for the deviation of the primary control and achieve global frequency synchronization. Based on the preset time consistency protocol, a preset time consistency observer is designed as follows:

[0083] ;

[0084] The first formula is the state observer dynamics equation, and the latter... For the signal dynamics equations, nodes State estimation node Reference signal. A positive control gain parameter is used to adjust the convergence speed. It is a time-varying function designed to operate at a preset time. The value decays from its initial value to zero. Represents a node The set of neighbors; These are elements of the adjacency matrix, representing nodes. and The connection weights between them. This is achieved by introducing a time-varying function. The system can be set to a preset time. It achieves consistency internally, without depending on initial conditions or network topology. exist As time approaches infinity, convergence is accelerated, while the reference signal... This indicates that each node has a constant reference value, and the observer's goal is to achieve time... Internally make all Converging to a consistent preset value.

[0085] By adding a distributed secondary voltage controller to the primary Q / V droop controller, the control objectives of proportional reactive power distribution and restoring the average voltage of each microgrid to its rated value can be achieved, as shown in the following formula:

[0086] ;

[0087] in, It controls the output voltage with a droop. Rated voltage, It is the reactive power droop factor. It is the actual reactive power. It is the regulating term of the distributed secondary voltage controller.

[0088] in, These are related voltage variables. Rated voltage, It is the reactive power droop factor. This refers to reactive power. These are entity information related to microgrid voltage control and reactive power regulation, used to realize distributed secondary voltage control functions.

[0089] ;

[0090] This formula describes a preset time consistency algorithm for distributed secondary voltage control and reactive power regulation in microgrid groups. Wherein, Indicates the first Nodes in a sub-microgrid The average voltage uniformity state is determined by the time-varying gain function. (Ensure convergence within the preset time) and the state of neighboring nodes Coordination was carried out.

[0091] ;

[0092] ;

[0093] in, This is the local voltage deviation signal, generated by reactive power. and actual voltage Calculation The droop coefficient is... These are weight parameters; For the output of the voltage regulator, through the integral term Tracking average consistency state With target value including rated voltage The deviation from the reactive power compensation item ultimately enables the entire network voltage to quickly recover to the rated value within a preset time. Nearby, and to achieve a reasonable distribution of reactive power.

[0094] Step S4: Within each sub-microgrid, a dominant distributed generation (DG) is selected as the Pinned-DG based on its capacity, reliability, and communication capabilities. This unit is typically chosen as the DG with the largest capacity, most stable operation, or located in a critical grid position. This Pinned-DG is responsible for communicating with the microgrid group-level coordination controller and receiving group-level reference commands. A microgrid-level droop controller is constructed based on this Pinned-DG, and its controller is as follows:

[0095] ;

[0096] ;

[0097] In the formula, Indicates the first Output frequency of microgrid droop control The rated angular frequency of MG. The rated voltage of the low-voltage network. This serves as the inverter-side voltage reference provided to the internal voltage controller. , The active and reactive power droop coefficients are given by the following formula:

[0098] ;

[0099] ;

[0100] In the formula, and These are the upper and lower limits of the angular frequency, respectively. These are the upper and lower limits of the DG output voltage. This is the lower limit of the DG output voltage; and These represent the maximum active and reactive power outputs of the microgrid MGk, respectively. By fusing group-level reference commands with local measurement information, this controller ensures that the sub-microgrids achieve internal coordination and consistency with group objectives within a preset timeframe, significantly improving the system's dynamic response speed and control accuracy.

[0101] Step S5: All Pinned-DGs are interconnected through a sparse communication network to collect and exchange key operational information of each sub-microgrid in real time, including bus voltage, output current, and active / reactive power. To achieve preset time consistency control of the microgrid group system, one of the core steps of this invention is to construct a Pinned-DG-based distributed controller within each sub-microgrid. The specific implementation is as follows:

[0102] ;

[0103] ;

[0104] in, Indicates the first Output frequency of individual microgrid droop control; The reference frequency for the entire microgrid group. , : Control gain coefficient, used to adjust the strength of the frequency and active power related coordination terms, for different sub-microgrids. It may have different possible values.

[0105] The system-level reference angular frequency is the consistent frequency target that the entire microgrid group is expected to achieve. , : No. , The active power droop factor of a sub-microgrid is used to describe the droop characteristics between active power and frequency. Different sub-microgrids may have different droop factors due to factors such as equipment. It is the first Individual microgrids and the first The communication weights between individual microgrids reflect characteristics such as the strength of their communication relationship. It is the first The rated angular frequency of a sub-microgrid Indicates the first The gain coefficients related to the sub-microgrid frequency and the system reference frequency are used to correlate the sub-microgrid frequency with the system-level reference frequency. Connect them. , Indicates the first , Active power output of individual microgrids.

[0106] The dynamic equation for the adjustment term is obtained by using a preset time function. The driver contains two key coordination items: the first item ensures frequency consistency. Frequency of neighboring microgrids and system reference frequency The weighted sum of the deviations, where For inter-microgrid communication weights, For the connection weights referenced by the system, This represents a set of neighboring microgrids.

[0107] This controller ensures that all sub-microgrids achieve rapid frequency synchronization and rational active power allocation within a user-defined timeframe by introducing a preset time consistency protocol at the microgrid group level. This avoids the complexity and cost of all DG units communicating with external or upper-level systems. A single pinned DG acts as a "gateway" to receive commands and rapidly propagates them within the microgrid via the preset time consistency algorithm, significantly improving communication efficiency and system reliability.

[0108] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0109] Through the above description of the embodiments, those skilled in the art can clearly understand that the microgrid group control method according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0110] According to embodiments of the present invention, a microgrid group control device for implementing the above-described microgrid group control method is also provided. Figure 4 This is a structural block diagram of a microgrid group control device provided according to an embodiment of the present invention, such as... Figure 4 As shown, the microgrid group control device includes: a selection module 402, a construction module 404, a first control module 406, a setting module 408, and a second control module 410. The microgrid group control device will be described below.

[0111] The selection module 402 is used to select, from the multiple distributed power sources corresponding to the multiple microgrids in the target microgrid group, a distributed power source that meets the preset conditions as the fixed distributed power source corresponding to the multiple microgrids.

[0112] The construction module 404, connected to the selection module 402, is used to construct a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids.

[0113] The first control module 406, connected to the construction module 404, is used to control multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and to collect distributed power source control data based on a sparse communication network. The distributed power source control data includes at least: output frequency, output voltage and output power.

[0114] Setting module 408, connected to the first control module 406, is used to set up the distributed secondary frequency converter and the distributed secondary voltage controller based on a preset time consistency algorithm and distributed power supply control data.

[0115] The second control module 410, connected to the setting module 408, is used to control the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0116] It should be noted that the selection module 402, construction module 404, first control module 406, setting module 408, and second control module 410 mentioned above correspond to steps S202 to S210 in the embodiments. Multiple modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of the device, can run on the computer terminal 10 provided in the embodiments.

[0117] Embodiments of the present invention may provide a computer device. Optionally, in this embodiment, the computer device may be located in at least one of a plurality of network devices in a computer network. The computer device includes a memory and a processor.

[0118] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the microgrid group control method and device in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned microgrid group control method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0119] The processor can access information and application programs stored in memory via a transmission device to execute the following steps: selecting distributed power sources that meet preset conditions from the multiple distributed power sources corresponding to each of the multiple microgrids in the target microgrid group as fixed distributed power sources corresponding to each of the multiple microgrids; constructing a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids; controlling the multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and collecting distributed power source control data based on the sparse communication network, wherein the distributed power source control data includes at least: output frequency, output voltage, and output power; setting up a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and controlling the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0120] Optionally, the processor may also execute program code for the following steps: constructing a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids, including: using the minimum spanning tree algorithm to determine the topology corresponding to the fixed distributed power sources corresponding to each of the multiple microgrids; determining the communication link parameters based on the distance between the multiple microgrids; and constructing a sparse communication network based on the topology and communication link parameters.

[0121] Optionally, the processor may also execute program code with the following steps: controlling multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, including: initializing the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, wherein the control parameters include a first droop coefficient corresponding to active power and frequency, and a second droop coefficient corresponding to reactive power and voltage; adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm; obtaining the power demand of the target microgrid group; adjusting the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids based on the power demand to obtain the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids; repeating the steps of adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids based on the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm to control the multiple distributed power sources corresponding to each of the multiple microgrids.

[0122] Optionally, the processor may also execute program code that performs the following steps: based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, the active and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted using the target formula in the preset droop control algorithm, wherein the target formula is as follows:

[0123] ,

[0124] in, For the first The first microgrid The actual output frequency of a distributed power source. The rated frequency of the distributed power source. For the first The first microgrid The first droop coefficient of a distributed power source. For the first The first microgrid Active power of a distributed power source For the first The first microgrid The actual output voltage amplitude of a distributed power source The rated voltage of the distributed power source. For the first The first microgrid The second droop coefficient of a distributed power source For the first The first microgrid The reactive power of a distributed power source.

[0125] Optionally, the processor may also execute program code that performs the following steps: setting up a distributed secondary frequency controller and a distributed secondary voltage controller based on a preset time consistency algorithm and distributed power supply control data, including: determining a convergence time function according to the preset time consistency algorithm; and setting up the distributed secondary frequency controller and the distributed secondary voltage controller based on the convergence time function.

[0126] Optionally, the processor may also execute program code for the following steps: controlling the target microgrid group based on a distributed secondary frequency controller and a distributed secondary voltage controller, including: acquiring the structure corresponding to multiple microgrids; determining the adjacent microgrids corresponding to each of the multiple microgrids based on the structure corresponding to the multiple microgrids; adjusting the output frequency corresponding to each of the multiple microgrids based on the frequency and active power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary frequency controller; and adjusting the output voltage corresponding to each of the multiple microgrids based on the voltage and reactive power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary voltage controller.

[0127] This invention provides a microgrid group control method. It involves selecting distributed power sources that meet preset conditions from multiple distributed power sources corresponding to each microgrid in a target microgrid group as fixed distributed power sources for each microgrid; constructing a sparse communication network based on these fixed distributed power sources; controlling the multiple distributed power sources corresponding to each microgrid based on a preset droop control algorithm; and collecting distributed power source control data via the sparse communication network, wherein the distributed power source control data includes at least: output frequency, output voltage, and output power; setting up a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and controlling the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller. This achieves the goal of hierarchical control of distributed power sources and microgrids based on a time consistency algorithm, thereby improving the convergence speed of the microgrid group to achieve rapid coordinated control. This solves the technical problem that the current coordinated control of microgrid groups has a slow convergence speed, failing to meet the real-time requirements of rapid coordinated control in microgrid groups.

[0128] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a non-volatile storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0129] Embodiments of the present invention also provide a non-volatile storage medium. Optionally, in this embodiment, the aforementioned non-volatile storage medium can be used to store the program code executed by the microgrid group control method provided in the above embodiments.

[0130] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0131] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: selecting distributed power sources that meet preset conditions from the multiple distributed power sources corresponding to each of the multiple microgrids in the target microgrid group as fixed distributed power sources corresponding to each of the multiple microgrids; constructing a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids; controlling the multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and collecting distributed power source control data based on the sparse communication network, wherein the distributed power source control data includes at least: output frequency, output voltage, and output power; setting up a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and controlling the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0132] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: constructing a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids, including: using the minimum spanning tree algorithm to determine the topology corresponding to the fixed distributed power sources corresponding to each of the multiple microgrids; determining the communication link parameters based on the distance between the multiple microgrids; and constructing a sparse communication network based on the topology and the communication link parameters.

[0133] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: controlling multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, including: initializing initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, wherein the control parameters include a first droop coefficient corresponding to active power and frequency, and a second droop coefficient corresponding to reactive power and voltage; adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm; obtaining the power demand of the target microgrid group; adjusting the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids based on the power demand to obtain the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids; repeating the step of adjusting the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids based on the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm to control the multiple distributed power sources corresponding to each of the multiple microgrids.

[0134] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted using a target formula in a preset droop control algorithm, wherein the target formula is as follows:

[0135] ,

[0136] in, For the first The first microgrid The actual output frequency of a distributed power source. The rated frequency of the distributed power source. For the first The first microgrid The first droop coefficient of a distributed power source. For the first The first microgrid Active power of a distributed power source For the first The first microgrid The actual output voltage amplitude of a distributed power source The rated voltage of the distributed power source. For the first The first microgrid The second droop coefficient of a distributed power source For the first The first microgrid The reactive power of a distributed power source.

[0137] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: setting up a distributed secondary frequency controller and a distributed secondary voltage controller based on a preset time consistency algorithm and distributed power control data, including: determining a convergence time function according to the preset time consistency algorithm; and setting up the distributed secondary frequency controller and the distributed secondary voltage controller based on the convergence time function.

[0138] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: controlling the target microgrid group based on a distributed secondary frequency controller and a distributed secondary voltage controller, including: acquiring the structure corresponding to multiple microgrids; determining the adjacent microgrids corresponding to each of the multiple microgrids based on the structure corresponding to the multiple microgrids; adjusting the output frequency corresponding to each of the multiple microgrids based on the frequency and active power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary frequency controller; and adjusting the output voltage corresponding to each of the multiple microgrids based on the voltage and reactive power data of the adjacent microgrids corresponding to each of the multiple microgrids based on the distributed secondary voltage controller.

[0139] Embodiments of the present invention also provide a computer program product, including a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, it can: select distributed power sources that meet preset conditions from multiple distributed power sources corresponding to multiple microgrids in a target microgrid group as fixed distributed power sources corresponding to each of the multiple microgrids; construct a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids; control the multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and collect distributed power source control data based on the sparse communication network, wherein the distributed power source control data includes at least: output frequency, output voltage, and output power; set up a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power source control data; and control the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

[0140] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0141] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0143] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0144] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0145] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0146] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A microgrid group control method, characterized in that, include: From the multiple distributed power sources corresponding to each of the multiple microgrids in the target microgrid group, select distributed power sources that meet the preset conditions as the fixed distributed power sources corresponding to each of the multiple microgrids. A sparse communication network is constructed based on the fixed distributed power sources corresponding to each of the multiple microgrids. Based on a preset droop control algorithm, multiple distributed power sources corresponding to each of the multiple microgrids are controlled, and distributed power source control data is collected based on the sparse communication network. The distributed power source control data includes at least: output frequency, output voltage and output power. Based on the preset time consistency algorithm and the distributed power control data, a distributed secondary frequency converter and a distributed secondary voltage controller are set up. The target microgrid group is controlled based on the distributed secondary frequency converter and the distributed secondary voltage controller.

2. The method according to claim 1, characterized in that, The construction of a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids includes: The minimum spanning tree algorithm is used to determine the topology of each of the multiple microgrids corresponding to their respective fixed distributed power sources. Based on the distances between the multiple microgrids, the communication link parameters are determined; Based on the topology and the communication link parameters, the sparse communication network is constructed.

3. The method according to claim 1, characterized in that, The preset droop control algorithm controls multiple distributed power sources corresponding to each of the multiple microgrids, including: Initialize the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, wherein the control parameters include a first droop coefficient corresponding to active power and frequency and a second droop coefficient corresponding to reactive power and voltage; Based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, the active power and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted using the preset droop control algorithm. Obtain the power requirements of the target microgrid group; Based on the power demand, the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted to obtain the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids. The process involves repeatedly adjusting the active and reactive power of the distributed power sources corresponding to each of the multiple microgrids using the preset droop control algorithm based on the adjusted control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, thereby controlling the multiple distributed power sources corresponding to each of the multiple microgrids.

4. The method according to claim 3, characterized in that, Based on the initial control parameters of the multiple distributed power sources corresponding to each of the multiple microgrids, the active and reactive power of the multiple distributed power sources corresponding to each of the multiple microgrids are adjusted using the target formula in the preset droop control algorithm. The target formula is as follows: ， in, For the first The first microgrid The actual output frequency of a distributed power source. The rated frequency of the distributed power source. For the first The first microgrid The first droop coefficient of a distributed power source. For the first The first microgrid Active power of a distributed power source For the first The first microgrid The actual output voltage amplitude of a distributed power source The rated voltage of the distributed power source. For the first The first microgrid The second droop coefficient of a distributed power source For the first The first microgrid The reactive power of a distributed power source.

5. The method according to claim 1, characterized in that, The step of setting up a distributed secondary frequency converter and a distributed secondary voltage controller based on a preset time consistency algorithm and the distributed power supply control data includes: The convergence time function is determined according to the preset time consistency algorithm; Based on the convergence time function, the distributed secondary frequency controller and the distributed secondary voltage controller are configured.

6. The method according to claim 1, characterized in that, The control of the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller includes: Obtain the structure corresponding to the multiple microgrids; Based on the structure of the multiple microgrids, the adjacent microgrids corresponding to each of the multiple microgrids are determined. Based on the distributed secondary frequency controller, the output frequency of each of the multiple microgrids is adjusted according to the frequency and active power data of their respective adjacent microgrids. Based on the distributed secondary voltage controller, the output voltage of each of the multiple microgrids is adjusted according to the voltage and reactive power data of their respective adjacent microgrids.

7. A microgrid group control device, characterized in that, include: The selection module is used to select, from the multiple distributed power sources corresponding to each of the multiple microgrids in the target microgrid group, a distributed power source that meets the preset conditions as the fixed distributed power source corresponding to each of the multiple microgrids. A construction module is used to construct a sparse communication network based on the fixed distributed power sources corresponding to each of the multiple microgrids; The first control module is used to control multiple distributed power sources corresponding to each of the multiple microgrids based on a preset droop control algorithm, and to collect distributed power source control data based on the sparse communication network. The distributed power source control data includes at least: output frequency, output voltage and output power. The setting module is used to set up the distributed secondary frequency converter and the distributed secondary voltage controller based on the preset time consistency algorithm and the distributed power control data. The second control module is used to control the target microgrid group based on the distributed secondary frequency converter and the distributed secondary voltage controller.

8. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the non-volatile storage medium to perform the microgrid group control method according to any one of claims 1 to 6.

9. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the microgrid group control method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the microgrid group control method according to any one of claims 1 to 6.

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