Energy storage grid-connected cabinet control management system

Abstract

The invention discloses an energy storage grid-connected cabinet control management system, and particularly relates to the technical field of energy storage grid-connected cabinets. The intelligent power dispatching module is used for optimizing a charging and discharging strategy of the energy storage system and dynamically adjusting power output; the fault protection management module is used for detecting, preventing and processing a fault intelligent protection mechanism in real time to guarantee the safety of the system; and the intelligent monitoring communication module is used for collecting operation data of the grid-connected cabinet in real time and providing remote monitoring and communication support. By introducing the intelligent power dispatching module, the fault protection management module, the intelligent monitoring communication module and the energy optimization integration module, intelligent management and efficient dispatching of the energy storage system are achieved, the system can automatically adjust the charging and discharging strategy of the energy storage system by predicting the future power grid load, and the energy efficiency is improved. The power resource of the energy storage unit is reasonably distributed when the power grid demand changes, and the resource waste is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage grid-connected cabinets, and in particular to a control and management system for energy storage grid-connected cabinets. Background Art

[0002] With the widespread application of renewable energy, the problems of energy management and grid stability have become increasingly prominent. Energy storage technology, as an important means to solve grid load fluctuations and regulate power supply, has gradually become one of the core technologies in the energy field. As the core connection device between the energy storage system and the grid, the energy storage grid cabinet can realize the grid-connected control and management of the energy storage unit, and optimize the allocation of power resources through reasonable scheduling strategies when the grid load fluctuates or the electricity price changes. The current energy storage grid-connected technology has made some progress in intelligent management and efficient scheduling, but it still faces some technical challenges.

[0003] Although the existing energy storage grid-connected cabinet control system has basic power dispatching functions, it has limitations in grid load forecasting, intelligent power distribution and fault protection. Traditional systems often find it difficult to quickly respond to grid frequency and voltage fluctuations, resulting in unstable grid operation. At the same time, the energy storage unit management of the existing system is relatively decentralized, lacking comprehensive health monitoring and intelligent power dispatching mechanisms, which makes it easy for energy storage units to be overcharged and discharged, resulting in waste of power resources. In addition, the fault management function is relatively passive. When a system failure occurs, it is difficult to predict and quickly restore power supply in a timely manner, affecting the safety and stability of the power system. Therefore, we provide a control and management system for energy storage grid-connected cabinets. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an energy storage grid-connected cabinet control and management system.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An energy storage grid-connected cabinet control and management system, including an intelligent power dispatching module for optimizing the charging and discharging strategy of the energy storage system to dynamically adjust the power output, a fault protection management module for real-time detection, prevention and processing of faults and intelligent protection mechanisms to ensure system safety, an intelligent monitoring and communication module for real-time collection of grid-connected cabinet operation data and providing remote monitoring and communication support, and an energy optimization integration module for realizing efficient integration of energy storage systems and renewable energy and power factor regulation through intelligent dispatching and optimization control;

[0007] The intelligent power dispatching module includes a dynamic load prediction module for automatically adjusting the charging and discharging strategy of the energy storage system based on historical data and real-time monitoring and prediction of future grid loads, a multi-source power regulation module for integrating power resources from different energy storage units and intelligently distributing power output, an adaptive frequency conversion regulation module for real-time monitoring of grid frequency and adjusting frequency control parameters through a self-learning algorithm, and a fast response control module for monitoring grid voltage and power fluctuation abnormalities and responding instantaneously to power adjustment or disconnection;

[0008] The fault protection management module includes an intelligent fault prediction module for analyzing historical operating data through a machine learning algorithm to predict possible faults and issue an early alarm, a fast restart protection module for quickly restoring power supply after a circuit breaker trip or other fault occurs, an automatic isolation module for automatically isolating the fault area upon detecting a short circuit or overload, and a health status monitoring module for real-time monitoring of the health status of key components, predicting lifespan and making maintenance recommendations.

[0009] The present invention is further configured as follows: the intelligent monitoring communication module includes a real-time grid perception module for collecting voltage, current and frequency parameters of the grid cabinet and the grid in real time using high-precision sensors, a multi-protocol communication module for supporting multiple communication protocols to achieve seamless connection between the energy storage system and the grid management system, a data decentralization calculation module for decentralizing the data processing part to the cabinet to reduce delays, quickly process and make control decisions, and a remote control diagnosis module for remotely monitoring the status of the grid cabinet through a cloud platform and supporting online remote fault diagnosis;

[0010] The energy optimization integrated module includes an energy storage optimization management module for dynamically optimizing energy storage charging and discharging plans by analyzing the supply and demand conditions of the power grid, a new energy integrated control module for allowing the grid-connected cabinet to access solar energy and wind energy renewable energy systems and intelligently allocate the usage ratio of these energies, a dynamic power factor compensation module for adjusting reactive power in real time according to the power grid and load conditions to optimize the power factor, and a carbon footprint analysis optimization module for monitoring and recording the carbon emissions generated during the operation of the energy storage system.

[0011] The present invention is further configured as follows: the multi-source power regulation module includes a power source determination module for real-time monitoring and evaluating the state of each energy storage unit to determine the priority power supply or energy storage power supply, a power distribution module for intelligently distributing the output power of each energy storage unit according to the result of the determination module, a grid connection coordination module for coordinating the connection mode of each energy storage unit with the power grid, a power smoothing module for adjusting the output of each power source to smooth power fluctuations, an energy storage switching module for dynamically switching the operating states of different energy storage units according to system requirements, and an energy feedback module for monitoring the energy utilization of each energy storage unit to provide data support for the determination module;

[0012] The power source determination module includes a battery health monitoring module for real-time monitoring of the health status of each energy storage unit, a remaining power calculation module for calculating and tracking the remaining power of each energy storage unit, a load demand evaluation module for real-time monitoring the load demand of the current system to determine the priority of the current power demand, an electricity price scheduling optimization module for analyzing the economic benefits of using the energy storage system in different time periods according to the current electricity price and scheduling strategy, and a power priority determination module for summarizing two branch data and comprehensively determining which energy storage unit has priority in power supply or energy storage based on the health status of the energy storage unit, the remaining power, the load demand and the economic benefits.

[0013] The present invention is further configured as follows: the power allocation module allocates power according to the result of the determination module and adjusts the connection mode between each energy storage unit and the power grid through the grid-connected coordination module to ensure stable power supply; after connecting each energy storage unit, the grid-connected coordination module adjusts the output of each power source through the power smoothing module to smooth power fluctuations.

[0014] The present invention is further configured as follows: after the power smoothing module completes the power output adjustment, the operating status of different energy storage units is dynamically switched through the energy storage switching module according to system requirements; while adjusting the operating status of the energy storage unit, the energy storage switching module monitors the energy utilization of each energy storage unit through the energy feedback module and feeds back the data to the power source determination module.

[0015] The present invention is further configured as follows: the dynamic load prediction module predicts future grid load conditions by analyzing historical data and real-time monitoring and provides a basis for the multi-source power regulation module; the multi-source power regulation module integrates the power resources of each energy storage unit and intelligently distributes power output, monitors the grid frequency in real time and dynamically adjusts control parameters through the adaptive frequency conversion regulation module; the adaptive frequency conversion regulation module dynamically adjusts the frequency control parameters through a self-learning algorithm and links the rapid response control module to perform instantaneous power adjustment or disconnection when power fluctuations occur in the grid; the intelligent fault prediction module analyzes historical data through a machine learning algorithm to predict possible faults in advance and works in conjunction with the rapid restart protection module to quickly restore power supply after a fault occurs.

[0016] The present invention is further configured as follows: the fast restart protection module responds quickly and restores power supply after a fault occurs, and if a more serious short circuit or overload is detected, the fault area is automatically isolated through the automatic isolation module; the automatic isolation module quickly isolates the fault area after detecting a short circuit or overload and monitors the health status of key components in real time through the health status monitoring module.

[0017] The present invention is further configured as follows: the real-time power grid perception module collects voltage, current and frequency parameters in real time through high-precision sensors and transmits the data to the multi-protocol communication module; the multi-protocol communication module ensures efficient communication between the energy storage system and the power grid management system by supporting multiple communication protocols and delegates part of the data processing tasks to the data delegation calculation module.

[0018] The present invention is further configured as follows: the data decentralization calculation module decentralizes the data processing part to the cabinet to reduce delays and make rapid control decisions and provide remote monitoring and fault diagnosis functions on the cloud platform through the remote control diagnosis module; the energy storage optimization management module dynamically optimizes the energy storage charging and discharging plan by analyzing the supply and demand conditions of the power grid and works in coordination with the new energy integrated control module to intelligently allocate the proportion of renewable energy use.

[0019] The present invention is further configured as follows: the new energy integrated control module is responsible for integrating the energy storage grid-connected cabinet with the solar energy and wind energy renewable energy systems and adjusting the reactive power in real time according to the grid load conditions through the dynamic power factor compensation module; the dynamic power factor compensation module adjusts the reactive power in real time to optimize the power factor of the grid and the energy storage system and the carbon footprint analysis optimization module monitors and records the carbon emissions of the energy storage system.

[0020] The beneficial effects of the present invention are:

[0021] 1. The present invention realizes intelligent management and efficient scheduling of energy storage systems by introducing intelligent power scheduling, fault protection management, intelligent monitoring communication and energy optimization integrated modules. The system can automatically adjust the charging and discharging strategy of the energy storage system by predicting future grid loads, ensuring that the power resources of the energy storage unit are reasonably allocated when grid demand changes to avoid waste of resources. At the same time, through the adaptive frequency conversion adjustment module and the rapid response control module, the system can monitor the fluctuations of grid frequency and voltage in real time, and quickly make power adjustments to ensure the stable operation of the grid. The fault protection management module also improves the safety and reliability of the system through intelligent fault prediction and rapid restart mechanism, so that the system can be warned before potential faults occur and can quickly restore power supply to ensure long-term stable and safe operation of the system.

[0022] 2. The present invention realizes intelligent distribution of power output by integrating the power resources of different energy storage units. The module can monitor the health status and remaining power of each energy storage unit in real time through the power source determination mechanism, and intelligently determine the unit with priority power supply or energy storage in combination with the load demand and electricity price information of the power grid. This distribution method can ensure that the energy storage system performs optimal power output scheduling under different time periods and different demand conditions, thereby improving the utilization efficiency of power resources. At the same time, through the power smoothing and energy storage switching modules, the system can smooth the power output, dynamically adjust the operating status of each energy storage unit, reduce the impact of power fluctuations, ensure the connection stability between the energy storage unit and the power grid, and improve the stability and reliability of the overall power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the system modules in the present invention.

[0024] Figure 2 It is a partial system diagram of the multi-source power regulation module in the present invention.

[0025] Figure 3 It is a schematic diagram of the secondary principle of the energy storage grid-connected metering cabinet in the present invention.

[0026] Figure 4 It is a schematic diagram of the secondary wiring 1 of the energy storage grid-connected metering cabinet in the present invention.

[0027] Figure 5 It is a schematic diagram of the secondary wiring 2 of the energy storage grid-connected metering cabinet in the present invention.

[0028] Figure 6 It is a schematic diagram of the secondary wiring 1 of the metering part of the energy storage grid-connected metering cabinet in the present invention.

[0029] Figure 7 It is a schematic diagram of the secondary wiring 2 of the metering part of the energy storage grid-connected metering cabinet in the present invention. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0031] Example 1

[0032] like Figure 1-7As shown, a control and management system for energy storage grid-connected cabinets includes an intelligent power dispatching module for optimizing the charging and discharging strategy of the energy storage system to dynamically adjust the power output, a fault protection management module for real-time detection, prevention and processing of faults and intelligent protection mechanisms to ensure system safety, an intelligent monitoring and communication module for real-time collection of grid-connected cabinet operation data and providing remote monitoring and communication support, and an energy optimization integration module for realizing efficient integration of energy storage systems and renewable energy and power factor regulation through intelligent dispatching and optimization control;

[0033] The intelligent power dispatching module includes a dynamic load prediction module for automatically adjusting the charging and discharging strategy of the energy storage system based on historical data and real-time monitoring and prediction of future grid loads, a multi-source power regulation module for integrating power resources from different energy storage units and intelligently distributing power output, an adaptive frequency conversion regulation module for real-time monitoring of grid frequency and adjusting frequency control parameters through a self-learning algorithm, and a fast response control module for monitoring grid voltage and power fluctuation abnormalities and responding instantaneously to power adjustment or disconnection;

[0034] The fault protection management module includes an intelligent fault prediction module for analyzing historical operation data through machine learning algorithms to predict possible faults and issue early warnings, a fast restart protection module for quickly restoring power supply after a circuit breaker trip or other fault occurs, an automatic isolation module for automatically isolating the fault area upon detection of a short circuit or overload, and a health status monitoring module for real-time monitoring of the health status of key components, predicting lifespan and making maintenance recommendations;

[0035] The intelligent monitoring communication module includes a real-time grid perception module for collecting voltage, current and frequency parameters of the grid cabinet and the grid in real time using high-precision sensors, a multi-protocol communication module for supporting multiple communication protocols to achieve seamless connection between the energy storage system and the grid management system, a data decentralization calculation module for decentralizing the data processing part to the cabinet to reduce delays, quickly process and make control decisions, and a remote control diagnosis module for remotely monitoring the status of the grid cabinet through a cloud platform and supporting online remote fault diagnosis;

[0036] The energy optimization integrated module includes an energy storage optimization management module for dynamically optimizing energy storage charging and discharging plans by analyzing the supply and demand conditions of the power grid, a new energy integrated control module for allowing the grid-connected cabinet to access solar energy and wind energy renewable energy systems to intelligently allocate the proportion of these energy uses, a dynamic power factor compensation module for real-time adjustment of reactive power to optimize power factor according to the power grid and load conditions, and a carbon footprint analysis optimization module for monitoring and recording carbon emissions generated during the operation of the energy storage system;

[0037] The dynamic load prediction module predicts the future grid load by analyzing historical data and real-time monitoring and provides a basis for the multi-source power regulation module; the multi-source power regulation module integrates the power resources of each energy storage unit and intelligently distributes power output, monitors the grid frequency in real time and dynamically adjusts the control parameters through the adaptive frequency conversion regulation module; the adaptive frequency conversion regulation module dynamically adjusts the frequency control parameters through a self-learning algorithm and links the rapid response control module to perform instantaneous power adjustment or disconnection when power fluctuations occur in the grid; the intelligent fault prediction module analyzes historical data through a machine learning algorithm to predict possible faults in advance and works in conjunction with the rapid restart protection module to quickly restore power supply after a fault occurs;

[0038] The fast restart protection module responds quickly and restores power supply after a fault occurs. If a more serious short circuit or overload is detected, the fault area is automatically isolated through the automatic isolation module. The automatic isolation module quickly isolates the fault area after detecting a short circuit or overload and monitors the health status of key components in real time through the health status monitoring module.

[0039] The real-time grid perception module collects voltage, current and frequency parameters in real time through high-precision sensors and transmits the data to the multi-protocol communication module; the multi-protocol communication module ensures efficient communication between the energy storage system and the grid management system by supporting multiple communication protocols and delegates part of the data processing tasks to the data decentralization calculation module;

[0040] The data decentralization calculation module decentralizes the data processing part to the cabinet to reduce delays and make rapid control decisions, and provides remote monitoring and fault diagnosis functions on the cloud platform through the remote control diagnosis module; the energy storage optimization management module dynamically optimizes the energy storage charging and discharging plan by analyzing the supply and demand conditions of the power grid and works with the new energy integrated control module to intelligently allocate the proportion of renewable energy use;

[0041] The new energy integration control module is responsible for integrating the energy storage grid-connected cabinet with the solar energy and wind energy renewable energy systems and adjusting the reactive power in real time according to the grid load conditions through the dynamic power factor compensation module; the dynamic power factor compensation module adjusts the reactive power in real time to optimize the power factor of the grid and energy storage system, and the carbon footprint analysis optimization module monitors and records the carbon emissions of the energy storage system.

[0042] In the above embodiment, the energy storage grid cabinet control and management system predicts the grid load and dynamically adjusts the charging and discharging strategy of the energy storage system through the intelligent power dispatching module, integrates the power resources of each energy storage unit and intelligently distributes the power output through the multi-source power regulation module, and at the same time, the adaptive frequency conversion regulation module monitors the grid frequency in real time, dynamically adjusts the control parameters through the self-learning algorithm, and quickly responds to power fluctuations. This part of the circuit allows multiple energy storage units to integrate power in the same system and reasonably distributes the output power through the power regulation module. The fault protection management module warns of potential faults in advance through the intelligent fault prediction module. If a fault occurs, the fast restart protection module quickly restores power supply. The automatic isolation module isolates the fault area when a short circuit or overload is detected. The health status monitoring module monitors the status of key components, predicts life and provides maintenance suggestions;

[0043] The specific secondary wiring diagram of the energy storage grid-connected metering cabinet is as follows: Figure 4 and Figure 5 As shown in the figure, the intelligent fault prediction module will warn of potential faults in advance. When an abnormality is detected, the protection circuit will start quickly to isolate the fault area and optimize the response mechanism for the next fault through the self-learning algorithm. The automatic isolation device in the circuit diagram isolates the fault area through the rapid action of the circuit breaker. The circuit diagram uses a variety of sensors and detection equipment to monitor the status of key components (such as capacitors and transformers). Through these sensors, the health monitoring module can predict the life of the equipment in real time and provide maintenance suggestions, thereby extending the service life of the system and ensuring its long-term reliable operation.

[0044] The intelligent monitoring communication module collects the operation data of the grid-connected cabinet in real time through high-precision sensors, and uses the multi-protocol communication module to achieve seamless connection with the power grid management system. It also transfers some data to the cabinet for processing, reducing delays and making control decisions quickly. The remote control diagnosis module provides remote monitoring and fault diagnosis functions on the cloud platform;

[0045] The specific secondary wiring diagram of the energy storage grid-connected metering cabinet is as follows: Figure 5 and Figure 6 As shown in the figure, the part related to the energy storage system in the circuit diagram demonstrates the ability to dynamically optimize the energy storage plan. Through the energy storage optimization management module, this part of the circuit can dynamically adjust the charging and discharging plan of the energy storage system according to the load conditions of the power grid to ensure the stability of the power grid. Through the reactive power compensation part in the circuit, the reactive power can be adjusted in real time, the power factor can be optimized, and the energy loss of the system can be reduced.

[0046] The energy optimization integration module dynamically optimizes the charging and discharging plan of the energy storage system through the energy storage optimization management module, and works in conjunction with the new energy integration control module to intelligently allocate the proportion of renewable energy use. The dynamic power factor compensation module adjusts the reactive power in real time to optimize the power factor. At the same time, the carbon footprint analysis optimization module monitors and reduces the system's carbon emissions to ensure that the system operates efficiently, stably and environmentally friendly.

[0047] Example 2

[0048] like Figure 1-7 As shown, a control and management system for energy storage grid-connected cabinets, wherein the multi-source power regulation module includes a power source determination module for real-time monitoring and evaluating the status of each energy storage unit to determine the priority power supply or energy storage power supply, a power distribution module for intelligently distributing the output power of each energy storage unit according to the result of the determination module, a grid-connected coordination module for coordinating the connection mode of each energy storage unit with the power grid, a power smoothing module for adjusting the output of each power source to smooth power fluctuations, an energy storage switching module for dynamically switching the operating states of different energy storage units according to system requirements, and an energy feedback module for monitoring the energy utilization of each energy storage unit to provide data support for the determination module;

[0049] The power source determination module includes a battery health monitoring module for real-time monitoring of the health status of each energy storage unit, a remaining power calculation module for calculating and tracking the remaining power of each energy storage unit, a load demand evaluation module for real-time monitoring of the load demand of the current system to determine the priority of the current power demand, an electricity price scheduling optimization module for analyzing the economic benefits of using the energy storage system in different time periods according to the current electricity price and scheduling strategy, and a power priority determination module for summarizing two branch data based on the health status of the energy storage unit, the remaining power, the load demand and the economic benefits to comprehensively determine which energy storage unit has priority in power supply or energy storage;

[0050] The power distribution module distributes power according to the result of the determination module and adjusts the connection mode of each energy storage unit with the power grid through the grid coordination module to ensure stable power supply; after connecting each energy storage unit, the grid coordination module adjusts the output of each power source through the power smoothing module to smooth power fluctuations. After the power smoothing module completes the power output adjustment, it dynamically switches the operating status of different energy storage units according to system requirements through the energy storage switching module; while adjusting the operating status of the energy storage unit, the energy storage switching module monitors the energy utilization of each energy storage unit through the energy feedback module and feeds back the data to the power source determination module.

[0051] In the above embodiment, the state of each energy storage unit is monitored in real time through the power source determination module. The module monitors the health status of each energy storage unit in real time through the battery health monitoring module, and tracks the remaining power of each energy storage unit through the remaining power calculation module. At the same time, the load demand assessment module monitors the load demand of the current system in real time, and analyzes the economic benefits of using the energy storage system in different time periods in combination with the electricity price scheduling optimization module, and comprehensively judges which energy storage unit has priority in power supply or energy storage. After determining the priority power supply, the power allocation module intelligently allocates the output power of each energy storage unit according to the result of the power source determination module, and adjusts the connection mode of each energy storage unit with the power grid through the grid coordination module to ensure the stability of power supply. After the connection is stable, the power smoothing module further adjusts the output of the power source, smoothes the power fluctuation, and ensures the stability of power output. The energy feedback module monitors the energy utilization of each energy storage unit, and feeds back the data to the power source determination module to provide data support for the next round of power allocation decisions;

[0052] The specific secondary schematic diagram of the energy storage grid-connected metering cabinet is as follows: Figure 3 As shown, the current transformer and voltage transformer can accurately measure the current and voltage key parameters of the power grid and input these data into the intelligent power dispatching module to predict the grid load and dynamically adjust the charging and discharging strategy of the energy storage system through the control signal interface of the module to balance the grid load.

[0053] Among them, the power source determination module monitors the health status of each energy storage unit in real time through the battery health monitoring module and tracks the remaining power of each energy storage unit through the remaining power calculation module; the power source determination module monitors the load demand of the current system in real time through the load demand evaluation module and analyzes the economic benefits of using the energy storage system in different time periods through the electricity price scheduling optimization module.

[0054] The power priority determination module makes a judgment based on the data provided by the power source determination module and transmits the result to the power allocation module for intelligently allocating the output power of each energy storage unit.

[0055] Working principle: When the present invention is in use, the intelligent power dispatching module monitors the load of the power grid in real time, such as Figure 3 The current transformer, voltage transformer and related sensors shown in FIG. collect the voltage, current and frequency data of the power grid in real time. These data are input into the dynamic load prediction module to predict the future power grid load based on the historical load data and the current power grid status. Subsequently, the multi-source power regulation module integrates the power resources of each energy storage unit, such as Figure 4The energy storage unit grid-connected coordination section shows the grid-connected switching of multiple energy storage units through relays or circuit breakers, which enables the system to intelligently distribute the output power of each energy storage unit. The adaptive frequency conversion regulation module monitors the grid frequency fluctuations and adjusts the frequency control parameters through a self-learning algorithm, responding to power fluctuations in real time to ensure stable system operation.

[0056] During the operation of the system, the fault protection management module continuously analyzes historical data and real-time data through the intelligent fault prediction module to warn of potential faults in advance. The specific secondary wiring diagram is as follows Figure 5 In the layout of protection circuits and circuit breakers, the automatic isolation module can quickly start to isolate the fault area when a fault (such as short circuit or overload) occurs. At the same time, the fast restart protection module will automatically restore power supply after the fault disappears. The health status monitoring module Figure 5 The sensor arrangement shown monitors the health status of energy storage units and key components (such as battery voltage, current and temperature) in real time, predicts component life and provides maintenance recommendations. These functions ensure that the energy storage system can respond quickly and effectively and maintain normal operation when a fault occurs.

[0057] In the long-term operation of the energy storage grid-connected system, the energy optimization integration module dynamically optimizes the charging and discharging plan of the energy storage system by analyzing the supply and demand conditions of the power grid. The energy storage optimization management module uses Figure 5 and Figure 6 The energy feedback loop in the system analyzes the status of the energy storage unit in real time and intelligently allocates the proportion of renewable energy (such as solar energy or wind energy) in the entire energy storage system. At the same time, the system also collects operating data through the high-precision sensors (voltage, current, frequency) of the intelligent monitoring communication module, and seamlessly connects with the power grid management system through the multi-protocol communication module to ensure real-time data transmission. The remote control diagnosis module of this module, such as Figure 7 As shown in the , remote monitoring, fault diagnosis and maintenance suggestions are provided through the cloud platform, allowing users to monitor the status of energy storage grid cabinets anytime and anywhere, and optimize the long-term operation and management of the system.

[0058] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A control and management system for energy storage grid-connected cabinets, characterized in that: It includes an intelligent power dispatching module for optimizing the charging and discharging strategy of the energy storage system to dynamically adjust the power output, a fault protection management module for real-time detection, prevention and processing of faults and intelligent protection mechanisms to ensure system safety, an intelligent monitoring and communication module for real-time collection of grid cabinet operation data and providing remote monitoring and communication support, and an energy optimization integration module for achieving efficient integration of energy storage systems and renewable energy and power factor regulation through intelligent dispatching and optimization control; The intelligent power dispatching module includes a dynamic load prediction module for automatically adjusting the charging and discharging strategy of the energy storage system based on historical data and real-time monitoring and prediction of future grid loads, a multi-source power regulation module for integrating power resources from different energy storage units and intelligently distributing power output, an adaptive frequency conversion regulation module for real-time monitoring of grid frequency and adjusting frequency control parameters through a self-learning algorithm, and a fast response control module for monitoring grid voltage and power fluctuation abnormalities and responding instantaneously to power adjustment or disconnection; The fault protection management module includes an intelligent fault prediction module for analyzing historical operating data through a machine learning algorithm to predict possible faults and issue an early alarm, a fast restart protection module for quickly restoring power supply after a circuit breaker trip or other fault occurs, an automatic isolation module for automatically isolating the fault area upon detecting a short circuit or overload, and a health status monitoring module for real-time monitoring of the health status of key components, predicting lifespan and making maintenance recommendations.

2. The energy storage grid-connected cabinet control and management system according to claim 1, characterized in that: The intelligent monitoring communication module includes a real-time grid perception module for collecting voltage, current and frequency parameters of the grid cabinet and the grid in real time using high-precision sensors, a multi-protocol communication module for supporting multiple communication protocols to achieve seamless connection between the energy storage system and the grid management system, a data decentralization calculation module for decentralizing the data processing part to the cabinet to reduce delays, quickly process and make control decisions, and a remote control diagnosis module for remotely monitoring the status of the grid cabinet through a cloud platform and supporting online remote fault diagnosis; The energy optimization integrated module includes an energy storage optimization management module for dynamically optimizing energy storage charging and discharging plans by analyzing the supply and demand conditions of the power grid, a new energy integrated control module for allowing the grid-connected cabinet to access solar energy and wind energy renewable energy systems and intelligently allocate the usage ratio of these energies, a dynamic power factor compensation module for adjusting reactive power in real time according to the power grid and load conditions to optimize the power factor, and a carbon footprint analysis optimization module for monitoring and recording the carbon emissions generated during the operation of the energy storage system.

3. The energy storage grid-connected cabinet control and management system according to claim 1, characterized in that: The multi-source power regulation module includes a power source determination module for real-time monitoring and evaluating the status of each energy storage unit to determine the priority power supply or energy storage power supply, a power distribution module for intelligently distributing the output power of each energy storage unit according to the result of the determination module, a grid connection coordination module for coordinating the connection mode of each energy storage unit with the power grid, a power smoothing module for adjusting the output of each power source to smooth power fluctuations, an energy storage switching module for dynamically switching the operating status of different energy storage units according to system requirements, and an energy feedback module for monitoring the energy utilization of each energy storage unit to provide data support for the determination module; The power source determination module includes a battery health monitoring module for real-time monitoring of the health status of each energy storage unit, a remaining power calculation module for calculating and tracking the remaining power of each energy storage unit, a load demand evaluation module for real-time monitoring the load demand of the current system to determine the priority of the current power demand, an electricity price scheduling optimization module for analyzing the economic benefits of using the energy storage system in different time periods according to the current electricity price and scheduling strategy, and a power priority determination module for summarizing two branch data and comprehensively determining which energy storage unit has priority in power supply or energy storage based on the health status of the energy storage unit, the remaining power, the load demand and the economic benefits.

4. The energy storage grid-connected cabinet control and management system according to claim 3, characterized in that: The power allocation module allocates power according to the result of the determination module and adjusts the connection mode between each energy storage unit and the power grid through the grid coordination module to ensure stable power supply; after connecting each energy storage unit, the grid coordination module adjusts the output of each power source through the power smoothing module to smooth power fluctuations.

5. The energy storage grid-connected cabinet control and management system according to claim 4, characterized in that: After the power smoothing module completes the power output adjustment, it dynamically switches the operating status of different energy storage units according to system requirements through the energy storage switching module; while adjusting the operating status of the energy storage unit, the energy storage switching module monitors the energy utilization of each energy storage unit through the energy feedback module and feeds back the data to the power source determination module.

6. The energy storage grid-connected cabinet control and management system according to claim 2, characterized in that: The dynamic load prediction module predicts future grid load conditions by analyzing historical data and real-time monitoring and provides a basis for the multi-source power regulation module; the multi-source power regulation module integrates the power resources of each energy storage unit and intelligently distributes power output, monitors the grid frequency in real time through the adaptive frequency regulation module and dynamically adjusts the control parameters; the adaptive frequency regulation module dynamically adjusts the frequency control parameters through a self-learning algorithm and links the rapid response control module to perform instantaneous power adjustment or disconnection when power fluctuations occur in the grid; the intelligent fault prediction module analyzes historical data through a machine learning algorithm to predict possible faults in advance and works in conjunction with the rapid restart protection module to quickly restore power supply after a fault occurs.

7. The energy storage grid-connected cabinet control and management system according to claim 2, characterized in that: The fast restart protection module responds quickly and restores power supply after a fault occurs. If a more serious short circuit or overload is detected, the fault area is automatically isolated through the automatic isolation module. The automatic isolation module quickly isolates the fault area after detecting a short circuit or overload and monitors the health status of key components in real time through the health status monitoring module.

8. The energy storage grid-connected cabinet control and management system according to claim 2, characterized in that: The real-time grid perception module collects voltage, current and frequency parameters in real time through high-precision sensors and transmits the data to the multi-protocol communication module; the multi-protocol communication module ensures efficient communication between the energy storage system and the grid management system by supporting multiple communication protocols and delegates part of the data processing tasks to the data decentralization calculation module.

9. The energy storage grid-connected cabinet control and management system according to claim 2, characterized in that: The data decentralization computing module decentralizes the data processing part to the cabinet to reduce delays and make rapid regulatory decisions, and provides remote monitoring and fault diagnosis functions on the cloud platform through the remote control diagnosis module; the energy storage optimization management module dynamically optimizes the energy storage charging and discharging plan by analyzing the supply and demand conditions of the power grid and works in conjunction with the new energy integrated control module to intelligently allocate the proportion of renewable energy use.

10. The energy storage grid-connected cabinet control and management system according to claim 2, characterized in that: The new energy integration control module is responsible for integrating the energy storage grid-connected cabinet with the solar energy and wind energy renewable energy systems and adjusting the reactive power in real time according to the grid load conditions through the dynamic power factor compensation module; the dynamic power factor compensation module adjusts the reactive power in real time to optimize the power factor of the grid and energy storage system, and the carbon footprint analysis optimization module monitors and records the carbon emissions of the energy storage system.

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