Micro-grid cluster system based on database type sentry mode

Abstract

The invention relates to a micro-grid cluster system based on a database type sentry mode, and the system integrates a plurality of dispersed micro-grid systems, and forms an overall operation system through the network connection and networking technology. The system architecture comprises a station control layer, a spacing layer and a process layer, each layer collects data through a monitoring slave station, and real-time transmission and storage of the data are achieved. The monitoring master station is responsible for receiving and processing data information from each distributed micro-grid, and centralized management is realized by sending a remote control and remote regulation instruction to the monitoring slave station. Compared with the prior art, the method has the advantages of high availability, high fault-tolerant capability, high response speed and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrids, and in particular to a microgrid cluster system based on a database-like sentinel mode. Background Art

[0002] As the number of servers in microgrids increases year by year, managers need to keep abreast of the cluster situation and monitor the cluster in real time. Cluster monitoring is generally divided into single cluster monitoring for LAN and multi-cluster distributed monitoring for WAN. Single cluster monitoring for LAN and multi-cluster distributed monitoring for WAN are suitable for different network environments and requirements. The former focuses on efficient and fast local monitoring, while the latter emphasizes distributed and reliable wide-area monitoring.

[0003] Microgrid cluster technology involves energy mutual assistance and coordinated control between multiple microgrids. The main challenges include how to achieve effective coordination between microgrids, how to deal with the intermittent and random nature of distributed power sources, and how to ensure the reliability and stability of microgrid clusters. Since data needs to be transmitted across a wide area network, data failures may occur but there is no fast switching, resulting in data delays, network delays, bandwidth limitations, and data transmission reliability issues, ultimately reducing the stability and resource utilization of microgrids. Therefore, a system based on database clusters is needed to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a microgrid cluster system based on a database sentinel mode, including a station control layer, an interval layer and a process layer. The sentinel mode of the real-time database Redis and the replica set mode of the historical database MongoDB constitute the sentinel mode, which effectively ensures the stable power supply of the microgrid and its cluster system, and realizes dynamic power support and the balance of power supply, energy storage and load power.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] The present invention provides a microgrid cluster system based on a database sentinel mode, a microgrid cluster system based on a database sentinel mode, composed of decentralized microgrid systems, which form an overall operation through network connection and networking, including a station control layer, an interval layer and a process layer. The station control layer collects and monitors the operation data of the local microgrid, the interval layer is used for data transmission and communication, and the process layer includes a monitoring master station for processing and analyzing data from each microgrid system to achieve centralized management and control. The sentinel mode is composed of the sentinel mode of the real-time database Redis and the replica set mode of the historical database MongoDB.

[0007] Furthermore, the monitoring master station is the central management and control node of the microgrid cluster system, which receives and integrates data from multiple distributed microgrids, and manages and optimizes the cluster system through real-time monitoring and remote control functions. The master station can send remote control and remote adjustment instructions to each monitoring slave station to achieve dynamic regulation and response of the microgrid system. The system also includes a monitoring slave station, which is used to collect data from each layer of distributed microgrid systems and push the return results of data and operation instructions to the monitoring master station. The monitoring station includes a real-time database Redis and a historical database MongoDB. The real-time database is used to store and quickly retrieve real-time data, and the historical database is used to store and manage long-term historical data.

[0008] Each monitoring station includes a data acquisition module, a data monitoring module, an integrated control module, a human-machine interface module, a real-time event module, an event processing module and an automatic control module.

[0009] The data acquisition module is used to obtain the operating data of each device in the microgrid system in real time, store it in a real-time database and form a historical data record, and then transmit the collected data to the central control system or data processing center through the communication network for data preprocessing and status monitoring. If an abnormal situation occurs, it can assist the alarm system to form an event report. In addition, this module can be integrated with other energy management systems to achieve data sharing and collaborative management, and improve overall operational efficiency.

[0010] The data monitoring module is used to monitor the operating status of each device and node in the microgrid system in real time, helping operation and maintenance personnel to understand the working status of the system in a timely manner, assisting event alarms, and recording and analyzing the historical operating data of the system, generating trend charts and statistical reports. The monitoring module can monitor and record safety-related data, assist operation and maintenance personnel in analyzing data change trends, and then predict potential problems and perform preventive maintenance.

[0011] The integrated control module is used to adjust the output of power generation equipment, load distribution and the charging and discharging status of energy storage equipment in real time, dynamically adjust the power distribution of microgrids according to demand changes, and optimize energy efficiency. It supports automatic control and can automatically perform control operations according to preset strategies and rules. It has emergency management functions and can respond quickly and take emergency measures in the event of emergencies (such as equipment failure, power outage, etc.).

[0012] The human-machine interface module provides a friendly user interface through which users can view system status, adjust control parameters and view historical records. It allows users to customize monitoring parameters, alarm thresholds and visual interfaces according to specific needs. The human-machine interface has built-in real-time curves, historical curves, real-time reports, historical reports and historical event interfaces. Users can determine whether to manually intervene and adjust control strategies based on curve and report data.

[0013] The real-time event module is used to monitor, record and process various events that occur during the operation of the system. It continuously monitors all parts of the microgrid system, captures all important events and changes, and records all captured events in real time to generate a detailed event log. When an abnormal event is detected, the real-time event module will immediately trigger an alarm and notify relevant personnel in a variety of ways so that they can respond and handle it in a timely manner.

[0014] The event processing module is used to handle various real-time events and abnormal situations, execute preset response measures, and record the processing process. When the system detects an event, the event processing module will respond immediately and perform corresponding operations according to the preset processing strategy.

[0015] The automatic control module is used to automatically monitor and control equipment and processes. It can automatically adjust the operating status of the equipment according to the preset control logic and parameters, thereby improving the efficiency, safety and stability of the system. This automatic control reduces human intervention, optimizes the production process, reduces operating costs, and responds to abnormal situations in a timely manner to ensure the reliable operation of the system.

[0016] Furthermore, the information transmitted between the monitoring master station and the monitoring slave station includes real-time operation data, alarm information, event information, historical data information, control command issuance records, operation records, system status information, user login and logout records, user authority information, and report information. The communication between the monitoring master station and the monitoring slave station adopts the standard interface specification of cluster monitoring to ensure data consistency and system compatibility.

[0017] The Sentinel-like mode monitors the status of the database through Sentinel and automatically performs failover when the primary node fails, ensuring the continuous availability of the system and the consistency of data.

[0018] The Sentinel will regularly monitor the database master and slave instances in the system, and when a master node failure is detected, it will select a suitable slave node to be promoted to the new master node, and notify other slave nodes and applications to update. The database Sentinel is also configured with an alarm mechanism. When a problem occurs in an instance, the Sentinel will notify the operation and maintenance personnel to deal with the problem in a timely manner.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] (1) Improve availability and fault tolerance: The sentinel mode of the real-time database Redis and the replica set mode of the historical database MongoDB are used to form a class of sentinels, which achieves high availability and automatic failover functions at the database level. When the primary database node fails, the system can automatically elect and switch to the backup node to ensure the continuity and real-time performance of data services, and improve the fault tolerance and reliability of the system.

[0021] (2) Improve data response speed and data synchronization: The introduction of the real-time database Redis enables the system to efficiently store and quickly retrieve real-time data and supports high concurrent access, which improves the system's data processing speed and response capability and improves data synchronization, which is particularly important for microgrid systems that require fast response.

[0022] (3) Enhance grid stability and resource utilization: Microgrid clusters can provide support to the grid, especially when the main grid is unstable or fails. The cluster can operate as an independent power system to ensure the power supply of important loads. At the same time, it can optimize and share resources between microgrids, such as electricity, heat, storage devices, etc., to improve resource utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of a microgrid cluster system based on a database-like sentinel mode;

[0024] Figure 2 is a flow chart of a sentinel-like cluster control method;

[0025] Figure 3 It is a failover flow chart;

[0026] Figure 4 Schematic diagram of the working principle of the sentinel mode of the class database in the microgrid cluster system. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] like Figure 1As shown in the figure, a microgrid cluster system based on a database-type sentinel mode is composed of decentralized microgrid systems, which are connected and networked to form an overall operation. The system includes a station control layer, an interval layer, and a process layer. Among them, the station control layer is a control and monitoring unit inside each microgrid system, which is used to collect and monitor the operation data of the local microgrid, and obtain the status and performance data of various power equipment in real time through sensors and monitoring equipment. The interval layer connects the transmission and communication layers of each microgrid system for data transmission and communication, ensuring that each microgrid system can be interconnected and realize centralized management and control of data. The process layer includes a data processing and decision-making layer, which is usually composed of a monitoring master station or a centralized control center. The process layer processes, analyzes, and makes decisions on the data collected from each microgrid system, such as optimizing the scheduling strategy of power generation, energy storage, and load to achieve efficient operation of the microgrid as a whole.

[0029] Microgrid cluster technology involves energy mutual assistance and coordinated control between multiple microgrids. The main challenges include how to achieve effective coordination between microgrids, how to deal with the intermittent and random nature of distributed power sources, and how to ensure the reliability and stability of microgrid clusters. The sentinel-like mode consists of the sentinel mode of the real-time database Redis and the replica set mode of the historical database MongoDB. Through the sentinel-like mode, the high availability and fault tolerance of data storage can be guaranteed to meet the requirements of the microgrid cluster system for data security and real-time performance. The system can effectively ensure the stable power supply of microgrids and their cluster systems, especially when multiple microgrid systems are connected to form a cluster, to achieve dynamic power support and the balance of power supply, energy storage and load power, and promote the application and development of distributed renewable energy.

[0030] The monitoring master station in the system process layer is the central management and control node of the microgrid cluster system. It receives and integrates data from multiple distributed microgrids, and manages and optimizes the cluster system through real-time monitoring and remote control functions. The master station can send remote control and remote adjustment instructions to each monitoring slave station to dynamically control and respond to the microgrid system. Among them, the cluster system includes but is not limited to the following information: real-time alarm information, real-time event push information, historical event query information, message monitoring information, system log information, event processing information, CPU utilization and memory space occupied, etc.

[0031] The system also includes a monitoring slave station, which is used to collect data from each layer of the distributed microgrid system and push the return results of the data and operation instructions to the monitoring master station. Each monitoring station includes a real-time database Redis and a historical database MongoDB. The real-time database Redis is used to store and quickly retrieve real-time data, cache important information, and manage temporary data to ensure efficient data processing and rapid response to monitoring needs. The historical database MongoDB is used to store and manage long-term historical data. The information transmission process between the monitoring master station and the monitoring slave station is as follows: after each monitoring slave station collects the information inside each system, it pushes the information to the monitoring master station; the monitoring master station receives the information from the monitoring slave station and uniformly configures all monitoring slave stations according to the information; and the monitoring slave station receives the unified configuration results from the monitoring master station and monitors and manages the microgrid according to the configuration results. The communication between the monitoring master station and the monitoring slave station adopts the standard interface specification of cluster monitoring to ensure data consistency and system compatibility.

[0032] Each monitoring station includes a data acquisition module, a data monitoring module, an integrated control module, a human-machine interface module, a real-time event module, an event processing module and an automatic control module.

[0033] Among them, the data acquisition module is used to obtain the operating data of each device in the microgrid system in real time, store it in the real-time database and form a historical data record, and then transmit the collected data to the central control system or data processing center through the communication network for data preprocessing and status monitoring. If an abnormal situation occurs, it can assist the alarm system to form an event report. In addition, this module can be integrated with other energy management systems to achieve data sharing and collaborative management, and improve overall operational efficiency. The relationship between this module and the real-time database Redis is: the real-time data obtained from sensors and devices is stored in the Redis database, which is convenient for other modules to quickly access and process. The relationship between this module and the historical database MongoDB is: after the data acquisition module collects data from various devices on the industrial site, it usually transfers the data to the historical database in batches at certain time intervals.

[0034] The data monitoring module is used to monitor the operating status of each device and node in the microgrid system in real time, helping operation and maintenance personnel to understand the working status of the system in a timely manner, assisting event alarms, and recording and analyzing the historical operating data of the system, generating trend charts and statistical reports. The monitoring module can monitor and record security-related data, assist operation and maintenance personnel in analyzing the changing trends of data, and then predict potential problems and perform preventive maintenance. The relationship between this module and the real-time database Redis is: read and display real-time data from the Redis database, and provide visual monitoring of data. The relationship between this module and the historical database MongoDB is: MongoDB is responsible for storing, managing and providing long-term access to these monitoring data. In some cases, the data monitoring module may adjust monitoring parameters or trigger alarms based on the historical data analysis results stored in MongoDB to achieve a linkage response of the system.

[0035] The integrated control module is used to adjust the output of power generation equipment, load distribution and the charging and discharging status of energy storage equipment in real time, dynamically adjust the power distribution of microgrids according to changes in demand, and optimize energy efficiency. It supports automatic control and can automatically perform control operations according to preset strategies and rules. It has emergency management functions and can respond quickly and take emergency measures when emergencies (such as equipment failures, power outages, etc.) occur. The relationship between this module and the real-time database Redis is: obtain global system status data from the Redis database, and store control instructions and configuration parameters in Redis to coordinate and manage each subsystem. The relationship between this module and the historical database MongoDB is: the integrated control module may refer to historical data in MongoDB when making control decisions. These data can help predict future system behavior, optimize control strategies, and improve overall system efficiency.

[0036] The human-machine interface module provides a friendly user interface through which users can view system status, adjust control parameters and view historical records. It allows users to customize monitoring parameters, alarm thresholds and visual interfaces according to specific needs. The human-machine interface has built-in real-time curves, historical curves, real-time reports, historical reports, and historical event interfaces. Users can determine whether to manually intervene and adjust control strategies based on curve and report data. The relationship between this module and the real-time database Redis is: interact with the Redis database, read real-time data and system status, provide an interactive interface between users and the system, and display and input control commands. The relationship between this module and the historical database MongoDB is: the human-machine interface can query the historical database to display the system status, process data and alarm information on the interface in the form of historical trend charts and statistical reports.

[0037] The real-time event module is used to monitor, record and process various events that occur during the operation of the system. It continuously monitors all parts of the microgrid system, captures all important events and changes, and records all captured events in real time to generate detailed event logs. When an abnormal event is detected, the real-time event module will immediately trigger an alarm and notify relevant personnel in a variety of ways so that they can respond and handle it in a timely manner. The relationship between this module and the real-time database Redis is: real-time events and state changes in the system are recorded in the Redis database for quick retrieval and processing. The relationship between this module and the historical database MongoDB is: MongoDB provides the ability to persistently store real-time capture and processing events, and provides query and analysis functions for historical data.

[0038] The event processing module is used to handle various real-time events and abnormal situations, execute preset response measures, and record the processing process. When the system detects an event, the event processing module will respond immediately and perform corresponding operations according to the preset processing strategy. The relationship between this module and the real-time database Redis is: obtain event data from the Redis database, analyze and process it, and store the processing results and instructions back to Redis. The relationship between this module and the historical database MongoDB is: MongoDB provides storage, management and query capabilities. The event processing module is responsible for detecting, classifying and processing events.

[0039] The automatic control module is used to automatically monitor and control equipment and processes. It can automatically adjust the operating status of the equipment according to the preset control logic and parameters, thereby improving the efficiency, safety and stability of the system. This automatic control reduces human intervention, optimizes the production process, reduces operating costs, and responds to abnormal situations in a timely manner to ensure the reliable operation of the system. The relationship between this module and the real-time database Redis is: based on the real-time data and predetermined rules obtained from the Redis database, the control operation is automatically performed, and the control results and status are updated to Redis. The relationship between this module and the historical database MongoDB is: the automatic control module is responsible for automatically adjusting and controlling the production process according to the preset logic, and MongoDB provides the ability to store, manage and analyze these control data. Through data interaction, the two jointly ensure the stable operation and continuous improvement of the automatic control system.

[0040] The database sentinel mode is deployed on the monitoring master station, which consists of the sentinel mode of the real-time database Redis and the replica set mode of the historical database MongoDB. Setting n sentinels means monitoring the monitoring master station. If the monitoring master station fails, the election result will be used to determine whether the node can continue to serve as the monitoring master station. If the node is objectively offline, the Leader Sentinel will be responsible for the failover operation and select an optimal slave node from the microgrid as the new master node, that is, the monitoring master station, to continue to maintain the normal operation of the microgrid cluster system. The sentinel-like mode monitors the status of the database through the sentinel and automatically performs failover when the master node fails, ensuring the continuous availability of the system and the consistency of the data.

[0041] The functions of the database sentinel mode system cluster include the following aspects: monitoring database instances, automatic failover, configuration management and update, providing high availability and fault tolerance, monitoring and alarm. The specific implementation process of monitoring database instances is: Sentinel will regularly monitor the master and slave instances in the database in the system and check their health status. If an instance fails, Sentinel will detect it and take corresponding measures. The specific implementation process of automatic failover is: When the database master node fails in the system, Sentinel will automatically failover. It will select a suitable slave node to be promoted to the new master node and notify other slave nodes and applications to update. The specific implementation process of configuration management and update is: After failover, the database Sentinel will automatically update the configuration of all related components in the system to point to the new master node. This ensures the high availability and consistency of the system. The specific implementation process of providing high availability and fault tolerance is: Through the monitoring and automatic failover functions of the database Sentinel, the system can continue to run when the database instance fails, avoiding single point failures and providing higher reliability and fault tolerance. The specific implementation process of monitoring and alarm is as follows: Database Sentinel not only monitors the health status of the instance, but also configures the alarm mechanism. When a problem occurs in an instance, Sentinel can notify the operation and maintenance personnel through log records, emails, SMS, etc., so that the problem can be handled in time.

[0042] Distributed microgrids are networked together to form a cluster monitoring system, such as Figure 2 As shown, the sentinel mode cluster control includes the following steps:

[0043] S1. Each module in the monitoring station performs efficient data storage, retrieval and sharing through the database, realizing real-time data collection, monitoring, control, interaction, event management and automatic control functions.

[0044] S2. Sentinel will continuously monitor all master and slave instances and send PING commands to them regularly to ensure their health status. Each Sentinel will save the health information of these instances. If an instance responds abnormally or times out, Sentinel will consider that the instance may have a problem.

[0045] S3. When a Sentinel finds that an instance fails to respond to the PING command normally for multiple consecutive times, it will mark the instance as subjective offline (SDOWN), which means that the Sentinel personally considers the instance to be unavailable.

[0046] S4: When an instance is marked as subjective offline by multiple Sentinels, an election will be held. If the majority of Sentinels agree that the instance is unavailable, it will be marked as objective offline (ODOWN). At this point, the Sentinel group unanimously agrees that the instance is unavailable.

[0047] S5. Once the master node is marked as offline, Sentinel will perform a failover. Figure 3 As shown, the specific steps include:

[0048] S501, electing a new master node: electing a suitable slave node from the slave nodes to become the new master node.

[0049] S502, configure a new master node: notify other slave nodes to point their master nodes to the new master node.

[0050] S503, update configuration: synchronize the new master node information to all Sentinels and clients.

[0051] S6. After the failover is complete, all Sentinels and clients will update their configurations to point to the new master node. These updates are performed automatically to ensure system consistency and high availability.

[0052] Sentinels communicate and coordinate with each other through the Pub / Sub mechanism, exchanging information about the status of Redis instances and negotiating the details of failover. With the help of the above technical solution, the distributed monitoring system can be uniformly controlled and managed by using a database-based clustering method.

[0053] like Figure 4The figure shows the working principle of the sentinel mode of the class database in the microgrid cluster system. There are multiple monitoring stations in the microgrid cluster system, such as the first monitoring station S1, the i-th monitoring station Si, the k-th monitoring station Sk, and the n-th monitoring station Sn. In the microgrid cluster, each monitoring station S1, Si, Sk, and Sn is connected to the cluster managed by the sentinel mode through the database client, and each monitoring station is connected to the master node in the cluster through the database client to perform data read and write operations. Multiple Sentinel instances are deployed on different monitoring stations or independent servers, and the initial configuration monitors the status of the master and slave instances. The data acquisition module of each monitoring station obtains real-time data from sensors and devices and stores the data to the master node. The data monitoring, integrated control, human-machine interface, event processing and other modules of the monitoring station read data from the database for processing and display. Sentinel continuously sends PING commands to monitor the health status of the master and slave instances. When a sentinel detects that the master node does not respond or the response times out, the master node is marked as subjective offline (SDOWN). If multiple sentinels detect that the master node fails and reach an agreement after negotiation, the master node is marked as objective offline (ODOWN). Sentinel conducts an election to select a new master node from the available slave nodes. After the new master node is selected, Sentinel notifies all slave nodes to point their master nodes to the new master node and synchronizes the new configuration to all Sentinels and clients. The monitoring station updates the connection information through Sentinel's automatic discovery mechanism and points to the new master node to continue data reading and writing operations. After the failover, the new master node synchronizes data with the slave nodes to ensure data consistency. All monitoring stations continue to operate normally, and data collection, monitoring, processing and control operations return to normal.

[0054] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A microgrid cluster system based on a database-type sentinel mode, consisting of dispersed microgrid systems, forming an overall system through network connection and networking, characterized in that: It includes a station control layer, an interval layer and a process layer, each layer is distributed with monitoring slave stations. The station control layer collects and monitors the operation data of the local microgrid. The interval layer is used for data transmission and communication. The process layer includes a monitoring master station for processing and analyzing data from each microgrid system to achieve centralized management and control. The sentinel-like mode is composed of the sentinel mode of the real-time database Redis and the replica set mode of the historical database MongoDB.

2. A microgrid cluster system based on a database sentinel mode according to claim 1, characterized in that: The monitoring master station is the central management and control node of the microgrid cluster system, which receives and integrates data from multiple distributed microgrids and manages and optimizes the cluster system through real-time monitoring and remote control functions.

3. A microgrid cluster system based on a database-type sentinel mode according to claim 1, characterized in that: The monitoring slave station is used to collect data from each layer of the distributed microgrid system and push the return results of the data and operation instructions to the monitoring master station.

4. A microgrid cluster system based on a database sentinel mode according to claim 1, characterized in that: The monitoring station includes a real-time database Redis and a historical database MongoDB. The real-time database is used to store and quickly retrieve real-time data, and the historical database is used to store and manage long-term historical data.

5. A microgrid cluster system based on a database-type sentinel mode according to claim 4, characterized in that: The monitoring station also includes a data acquisition module, a data monitoring module, an integrated control module, a human-machine interface module, a real-time event module, an event processing module and an automatic control module, wherein the data acquisition module is used to obtain real-time data; the data monitoring module is used to monitor and display the collected data in real time; the integrated automatic control module performs global system control and coordinates the operations of various systems; the human-machine interface module provides a graphical interface for users to interact with the system; the real-time event module records and manages real-time events and status changes in the system; the event processing module analyzes and processes events in the system and triggers corresponding response measures; the automatic control module automatically performs control operations based on predetermined rules and real-time data.

6. A microgrid cluster system based on a database-type sentinel mode according to claim 1, characterized in that: The information transmitted between the monitoring master station and the monitoring slave station includes real-time operation data, alarm information, event information, historical data information, control command issuance records, operation records, system status information, user login and logout records, user authority information, and report information.

7. A microgrid cluster system based on a database sentinel mode according to claim 1, characterized in that: The communication between the monitoring master station and the monitoring slave stations adopts the standard interface specification of cluster monitoring to ensure data consistency and system compatibility.

8. A microgrid cluster system based on a database sentinel mode according to claim 1, characterized in that: The Sentinel-like mode monitors the status of the database through Sentinel and automatically performs failover when the primary node fails, ensuring the continuous availability of the system and the consistency of data.

9. A microgrid cluster system based on a database-type sentinel mode according to claim 8, characterized in that: The Sentinel will regularly monitor the database master-slave instances in the system, and when a master node failure is detected, it will select a suitable slave node to be promoted to the new master node, and notify other slave nodes and applications to update.

10. A microgrid cluster system based on a database-type sentinel mode according to claim 8, characterized in that: The database Sentinel is also configured with an alarm mechanism. When a problem occurs with an instance, the Sentinel notifies the operation and maintenance personnel to handle the problem in a timely manner.

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