Energy monitoring system of all-vanadium redox flow battery energy storage power station

Abstract

An energy monitoring system for an all-vanadium redox flow battery energy storage power station belongs to the technical field of all-vanadium redox flow battery energy storage monitoring, and comprises a user interface layer which provides a visual operation interface and supports real-time monitoring, parameter setting and fault alarm; the central control layer comprises a data processing module, an energy management module and a fault diagnosis module; the data acquisition and execution layer comprises a sensor network, a data acquisition module and an execution mechanism; and the communication interface layer is used for realizing data interaction inside and outside the system. According to the system disclosed by the invention, by integrating an advanced sensor network, an intelligent energy management algorithm and a modular design, efficient monitoring and management of the all-vanadium redox flow battery energy storage power station are realized.

Description

Technical Field

[0001] This invention belongs to the field of vanadium redox flow battery energy storage monitoring technology, specifically relating to an energy monitoring system for a vanadium redox flow battery energy storage power station. Background Technology

[0002] Analysis of relevant patents: Patent 1: A vanadium redox flow battery energy storage system (CN112736123A).

[0003] Technical features: Involves the structural design and energy management methods of all-vanadium redox flow batteries.

[0004] Comparative analysis: Energy monitoring systems based on model predictive control and machine learning were not included.

[0005] Patent 2: An energy monitoring system for an energy storage power station (US20210066989A1).

[0006] Technical features: Involves monitoring and fault diagnosis methods for energy storage systems.

[0007] Comparative analysis: It was not designed for all-vanadium redox flow batteries and did not employ intelligent algorithms.

[0008] Patent 3: A battery fault diagnosis method based on machine learning (EP3564884A1).

[0009] Technical features: Utilizing machine learning for battery fault diagnosis.

[0010] Comparative analysis: It does not incorporate a full vanadium redox flow battery and an energy monitoring system.

[0011] Technical literature analysis: Reference 1: Research on energy management of vanadium redox flow batteries (Journal of Power Sources, 2020).

[0012] Technical features: Energy management strategies are discussed, but intelligent monitoring systems are not covered.

[0013] Reference 2: Energy storage system optimization based on model predictive control (IEEE Transactions on Smart Grid, 2019).

[0014] Technical features: The application of MPC in energy storage systems is proposed, but not specifically for all-vanadium redox flow batteries.

[0015] Analysis of existing technologies: 1. Monitoring technology for traditional battery energy storage systems Technical features: Data acquisition: Real-time battery status data is collected through sensors such as voltage, current, and temperature.

[0016] Energy management: based on simple charge and discharge control strategies, such as constant current charging and constant voltage charging.

[0017] Fault detection: Detects abnormal conditions such as overvoltage, overcurrent, and overtemperature using threshold judgment method.

[0018] Communication interface: Communication between devices is usually achieved using protocols such as CAN bus and Modbus.

[0019] 2. Flow Battery Management System (BMS) Technical features: Electrolyte management: Monitor electrolyte flow, concentration, and temperature to ensure efficient battery operation.

[0020] Battery State Estimation: Estimate the battery's state of charge (SOC) and state of health (SOH) using data such as voltage and current.

[0021] Charge and discharge control: Adjust the charge and discharge strategy according to grid demand or load conditions.

[0022] Safety protection: It has overvoltage, overcurrent, and overtemperature protection functions.

[0023] 3. Power Grid Energy Storage Monitoring System Technical features: Grid interaction: Communicates with the grid dispatching system to realize functions such as peak shaving and valley filling, frequency regulation, etc.

[0024] Energy optimization: Based on grid load forecasting and electricity price information, optimize the charging and discharging strategies of energy storage systems.

[0025] Multi-system integration: Supports coordinated operation with renewable energy systems such as wind and solar power.

[0026] Remote monitoring: Remote monitoring and management are achieved through the SCADA system.

[0027] Defects or problems existing in the current technology: 1. Limited energy management strategies: Existing technologies mostly adopt fixed strategies, which are difficult to adapt to complex and ever-changing operating environments.

[0028] 2. Low level of intelligence: lacks the ability to diagnose and predict faults based on artificial intelligence.

[0029] 3. Insufficient scalability: It is difficult to adapt to the needs of large-scale energy storage power stations.

[0030] 4. Insufficient support for flow battery characteristics: Existing technologies are mostly designed for traditional batteries such as lithium-ion batteries, and do not fully consider the special characteristics of flow batteries (such as electrolyte management, long life characteristics, etc.). Summary of the Invention

[0031] To address the aforementioned problems, this invention proposes an energy monitoring system for a vanadium redox flow battery energy storage power station, comprising: User interface layer: Provides a visual operation interface, supporting real-time monitoring, parameter setting, and fault alarms; Central control layer: includes data processing, energy management, and fault diagnosis modules; Data acquisition and execution layer: includes sensor network, data acquisition module and actuator; Communication interface layer: Enables data interaction between the system and external systems.

[0032] Furthermore, the user interface layer includes: Monitoring interface: Displays battery status: voltage, current, temperature, and SOC; Control panel: Supports manual / automatic mode switching and charging / discharging strategy settings; Alarm system: Displays fault information in real time and provides early warnings.

[0033] Furthermore, the user interface layer: It provides a visual interface, making it easy for operators to monitor system status and parameters; It supports manual control and automatic mode switching.

[0034] Furthermore, the central control layer includes: Data processing module: filters, stores, and analyzes sensor data; Energy Management Module: Implements MPC-based charging and discharging strategy optimization; Fault diagnosis module: Uses machine learning algorithms for fault detection and diagnosis.

[0035] Furthermore, the data acquisition and execution layer includes: Sensor networks include voltage sensors, current sensors, temperature sensors, and flow sensors. Data acquisition module: converts sensor signals into digital signals and transmits them to the central control layer; Actuators: including pumps, valves, and power converters, are used to control the flow of electrolyte and the charging and discharging process.

[0036] Furthermore, the data acquisition and execution layer includes: Sensor network: Real-time acquisition of battery status data.

[0037] Data acquisition module: converts sensor signals into digital signals.

[0038] Actuator: Controls the flow of electrolyte and the charging and discharging process.

[0039] Furthermore, the communication interface layer includes: Internal communication: Communication between sensors, data acquisition modules and central control unit is achieved through CAN bus and Modbus protocol.

[0040] Furthermore, the internal communication enables data interaction between various modules within the system.

[0041] Furthermore, the communication interface layer also includes: External communication: Data interaction with the power grid dispatch system and renewable energy system is achieved through Ethernet and 4G / 5G wireless communication.

[0042] Furthermore, the external communication enables data interaction with the power grid dispatch system and the renewable energy system.

[0043] The beneficial effects of this invention are as follows: By integrating advanced sensor networks, intelligent energy management algorithms, and modular design, this system achieves efficient monitoring and management of vanadium redox flow battery energy storage power stations. Specifically: 1. Advanced Fault Diagnosis: Utilizing big data analytics and artificial intelligence technologies, it enables early fault warnings and accurate diagnosis.

[0044] 2. Designed specifically for flow batteries: Electrolyte management and battery state estimation are optimized to suit the characteristics of flow batteries.

[0045] 3. Modularity and scalability: The modular design facilitates system expansion and maintenance.

[0046] 4. High-efficiency communication and integration: Designed based on advanced networked communication technology, it features an open, layered, distributed structure that facilitates software function expansion and supports access via multiple protocols such as 61850 and 104.

[0047] 5. Supports domestically developed secure operating systems such as NingSi and Kylin; supports various commercial relational databases such as Oracle and SQL. 6. Passing multiple tests by the State Electric Power Research Institute and other institutions, it provides a reliable guarantee for the safe and economical operation of energy storage power stations. Attached Figure Description

[0048] Figure 1 This is a system architecture diagram of the present invention; Figure 2 This is a system functional block diagram of the present invention. Detailed Implementation

[0049] To make the technical means and objectives of this invention easier to understand, the invention is further described below in conjunction with specific embodiments. A vanadium redox flow battery energy storage power station energy monitoring system includes: User interface layer: Provides a visual operation interface, supporting real-time monitoring, parameter setting, and fault alarms.

[0050] Central control layer: includes data processing, energy management and fault diagnosis modules.

[0051] Data acquisition and execution layer: includes sensor network, data acquisition module and actuator.

[0052] Communication interface layer: Enables data interaction between the system and external systems.

[0053] User interface layer: Monitoring interface: Displays battery status (voltage, current, temperature, SOC, etc.).

[0054] Control panel: Supports manual / automatic mode switching and charging / discharging strategy settings.

[0055] Alarm system: Displays fault information in real time and provides early warnings.

[0056] • Central control layer: Data processing module: Filters, stores, and analyzes sensor data.

[0057] Energy Management Module: Implements MPC-based charging and discharging strategy optimization.

[0058] Fault diagnosis module: Uses machine learning algorithms for fault detection and diagnosis.

[0059] • Data Acquisition and Execution Layer: Sensor networks include voltage sensors, current sensors, temperature sensors, and flow sensors.

[0060] Data acquisition module: converts sensor signals into digital signals and transmits them to the central control layer.

[0061] Actuators: These include pumps, valves, power converters, etc., used to control the flow of electrolyte and the charging and discharging process.

[0062] • Communication interface layer: Internal communication: Communication between sensors, data acquisition modules and central control unit is achieved through protocols such as CAN bus and Modbus.

[0063] External communication: Data interaction with the power grid dispatch system and renewable energy system is achieved through Ethernet and 4G / 5G wireless communication.

[0064] Module Function Description: User interface layer: It provides a visual interface, making it easy for operators to monitor system status and parameters.

[0065] It supports manual control and automatic mode switching.

[0066] • Central control layer: Data processing module: Filters, stores, and analyzes sensor data.

[0067] Energy management module: Optimizes charging and discharging strategies to improve system efficiency.

[0068] Fault diagnosis module: Utilizes machine learning algorithms to achieve fault detection and early warning.

[0069] • Data Acquisition and Execution Layer: Sensor network: Real-time acquisition of battery status data.

[0070] Data acquisition module: converts sensor signals into digital signals.

[0071] Actuator: Controls the flow of electrolyte and the charging and discharging process.

[0072] • Communication interface layer: Internal communication: Enables data interaction between various modules within the system.

[0073] External communication: Enables data interaction with the power grid dispatch system and renewable energy system.

[0074] An energy monitoring system for a vanadium redox flow battery energy storage power station, the system architecture of which is shown in the figure below. Figure 1 As shown: The data control sub-network and ring network mode means that the control network and data network of the energy storage power station adopt separate networks. The bay layer switches are connected in a ring through fiber optic interfaces and aggregation switches. The network architecture diagram is divided into the station control layer and the bay layer from top to bottom.

[0075] The station control layer mainly consists of equipment such as energy storage coordination controller, data server, SCADA server, AGVC server, engineering station, and aggregation switch; The bay layer mainly consists of bay layer switches, PCS, BMS, and transformer substation monitoring and control equipment.

[0076] like Figure 2 As shown, the system achieves efficient monitoring and management of vanadium redox flow battery energy storage power stations by integrating advanced sensor networks, intelligent energy management algorithms, and modular design.

[0077] A hardware implementation of an energy monitoring system for an all-vanadium redox flow battery energy storage power station: Monitoring Host: The monitoring host adopts a primary / backup redundant configuration; it performs calculations and analysis after front-end data acquisition, ensuring sufficient data computing resources and correct processing of real-time and historical data. It is responsible for monitoring the entire system, data analysis, and formulating control strategies such as peak shaving and frequency regulation, AGVC power command issuance, and has functions such as SOC automatic maintenance, anomaly detection triggering adjustment, and interlocking adjustment. The host equipment is arranged in a panel (cabinet) configuration in the central control room. It can also perform monitoring and energy management system maintenance functions.

[0078] AGVC Server: The AGVC server adopts a primary / backup redundant configuration; it can quickly respond to active / reactive power control targets, employing optimized control strategies and allocation algorithms to control each PCS device in real time, thereby quickly and accurately adjusting the active / reactive power at the grid connection point. When the grid frequency is too low or active power is severely insufficient, it can respond to the dispatch emergency control discharge demand.

[0079] The main equipment is arranged in a panel (cabinet) configuration in the central control room.

[0080] AGC: Automatic Generation Control, primarily controls active power and ensures frequency stability. AVC: Automatic Voltage Control, primarily controls reactive power and stabilizes voltage. Database server: The database server adopts a primary and backup redundant configuration; a dedicated database server is configured to improve communication speed and ensure system smoothness, while meeting the needs of large-capacity historical data storage. The host equipment is arranged in a panel (cabinet) manner in the central control room.

[0081] Operator / Engineer Workstation: The operator / engineer workstation is configured according to the project's scope of supply requirements; The operator / engineer workstation is the main human-machine interface for the station's monitoring and energy management system. It is used for graphical and report display, event logging and alarm status display and querying, equipment status and parameter queries, operation guidance, interpretation and issuance of operation control commands, and maintenance and management of the entire monitoring and energy management system. It can perform database definition and modification, system parameter definition and modification, report creation and modification, network maintenance, and system diagnostics. Operating personnel can monitor and control the operation of primary and secondary equipment in the energy storage power station through the operator / engineer workstation. Maintenance of the monitoring and energy management system can only be performed on the operator / engineer workstation, and reliable login protection is provided.

[0082] Printer: Configure one laser printer (A3 or A4 size optional). Used for printing events, alarm signals, reports, etc. The printer should have network printing capabilities. The printer can be installed in a panel on the monitoring host or distributed across monitoring stations.

[0083] Audio alarm device: The audio alarm is driven by the workstation and the volume is adjustable.

[0084] Station control layer switch: The station control layer switch adopts an AB dual-network configuration for network communication of station control layer equipment. The station control layer equipment is connected to the station control layer switch through the electrical port. The communication rate of the station control layer switch is not less than 100Mbit / s.

[0085] Aggregation Switch: The aggregation switch adopts an AB dual-network configuration with separate control and data networks. It is used for the aggregation and communication of control commands and data from the bay-level switch, with a communication rate of not less than 100 Mbit / s.

[0086] Energy Storage Coordination Controller: Two master energy storage coordination controllers are configured. The number of slave controllers needs to be determined based on the number of grid connection assessment points in the project. The energy storage coordination controller controls the energy storage units and communicates with the PCS via GOOSE, MODBUSTCP, or IEC104 protocols to achieve rapid power control of multiple PCSs in a 100MW-level energy storage power station. If the project has a large number of PCSs, a master-slave configuration will be used to expand the PCS access capacity. Simultaneously, the coordination controller can independently collect the voltage and frequency of the grid connection points and actively perform primary frequency regulation, dynamic voltage regulation, inertia support, and damping control functions.

[0087] Spacer layer equipment: (1) Substation monitoring and control device. The substation monitoring and control device should have functions such as status quantity acquisition, AC sampling and measurement, circuit breaker control and digital display.

[0088] (2) PCS (3) BMS A software implementation method for an energy monitoring system of an all-vanadium redox flow battery energy storage power station: • Data acquisition and processing: Develop data acquisition programs based on real-time operating systems (such as FreeRTOS or VxWorks).

[0089] Digital filtering algorithms (such as Kalman filtering) are used to process sensor data to improve data accuracy.

[0090] • Energy management algorithm: Implement a charging and discharging strategy optimization algorithm based on model predictive control (MPC).

[0091] The charging and discharging plan is dynamically adjusted based on grid load forecasts and electricity price information.

[0092] • Fault diagnosis and early warning: Machine learning algorithms (such as support vector machines and random forests) are used to analyze historical data and build fault diagnosis models.

[0093] Implement early fault warning function to notify operators via user interface or SMS.

[0094] User interface development: Develop graphical user interfaces (GUIs) using Qt or Web technologies.

[0095] It provides functions such as real-time data display, historical data query, parameter setting, and fault alarm.

[0096] Operation and maintenance: (1) Before using and operating the energy management system, you should understand and be familiar with the basic structure, composition and operation mode of the system, as well as the safety management system and specific operating procedures to ensure personal safety and system safety.

[0097] (2) Electrochemical energy storage power stations should establish various safety production management systems including equipment and facilities, operation and maintenance, repair and testing, and implement the "two tickets" (work ticket and operation ticket) and "three systems" (shift handover system, patrol inspection system, and equipment periodic switching and testing system). They should also establish and improve the safety production responsibility system for personnel at all levels.

[0098] (3) Electrochemical energy storage power stations should be equipped with personnel capable of ensuring the safe and reliable operation of the power station and should be assigned a safety officer. Personnel should be trained and certified before taking up their posts.

[0099] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An energy monitoring system for a vanadium redox flow battery energy storage power station, characterized in that, include: User interface layer: Provides a visual operation interface, supporting real-time monitoring, parameter setting, and fault alarms; Central control layer: includes data processing, energy management, and fault diagnosis modules; Data acquisition and execution layer: includes sensor network, data acquisition module and actuator; Communication interface layer: Enables data interaction between the system and external systems.

2. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 1, characterized in that, The user interface layer includes: Monitoring interface: Displays battery status: voltage, current, temperature, and SOC; Control panel: Supports manual / automatic mode switching and charging / discharging strategy settings; Alarm system: Displays fault information in real time and provides early warnings.

3. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 2, characterized in that, The user interface layer: It provides a visual interface, making it easy for operators to monitor system status and parameters; It supports manual control and automatic mode switching.

4. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 1, characterized in that, The central control layer includes: Data processing module: filters, stores, and analyzes sensor data; Energy Management Module: Implements MPC-based charging and discharging strategy optimization; Fault diagnosis module: Uses machine learning algorithms for fault detection and diagnosis.

5. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 1, characterized in that, The data acquisition and execution layer includes: Sensor networks include voltage sensors, current sensors, temperature sensors, and flow sensors. Data acquisition module: converts sensor signals into digital signals and transmits them to the central control layer; Actuators: including pumps, valves, and power converters, are used to control the flow of electrolyte and the charging and discharging process.

6. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 5, characterized in that, The data acquisition and execution layer includes: Sensor network: Real-time acquisition of battery status data; Data acquisition module: converts sensor signals into digital signals; Actuator: Controls the flow of electrolyte and the charging and discharging process.

7. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 1, characterized in that, The communication interface layer includes: Internal communication: Communication between sensors, data acquisition modules and central control unit is achieved through CAN bus and Modbus protocol.

8. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 7, characterized in that, The internal communication enables data interaction between various modules within the system.

9. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 8, characterized in that, The communication interface layer also includes: External communication: Data interaction with the power grid dispatch system and renewable energy system is achieved through Ethernet and 4G / 5G wireless communication.

10. The energy monitoring system for a vanadium redox flow battery energy storage power station as described in claim 9, characterized in that, The external communication enables data interaction with the power grid dispatch system and renewable energy system.

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