Distributed energy storage system based on modular design

Abstract

The invention relates to a distributed energy storage system based on modular design, the system comprises a remote management module, a main control module, a dynamic load distribution module, an energy storage module, a fault early warning module, a communication module and a temperature control module, the remote management module realizes remote monitoring and control through an Internet of Things platform; the main control module monitors the electric quantity state of the energy storage module and distributes charging and discharging tasks; the dynamic load distribution module predicts and adjusts the output power according to the power demand; the energy storage module is composed of a basic energy storage unit, a high-density energy storage unit and a long-life energy storage unit, and the energy storage units are dynamically switched according to load requirements to adapt to peak, stable and low-load scenes. According to the system, flexible switching of the energy storage units is realized through modular design, the service life of the system is effectively prolonged, and the operation efficiency and management convenience of the system are improved.

Description

Technical Field

[0001] The invention relates to a distributed energy storage system based on modular design. Background Art

[0002] With the widespread application of renewable energy and the development of smart grids, distributed energy storage systems have gradually become an indispensable part of the power system. Traditional centralized energy storage systems are difficult to adapt to complex and changing load demands due to their large size and poor flexibility.

[0003] Traditional energy storage systems are often centralized structures with single energy storage devices, which are difficult to switch flexibly according to changes in real-time load demand. This lack of adaptability in the design results in the system being unable to fully utilize the efficiency of the power unit when the load demand is high, and may lead to resource waste when the load demand is low, resulting in resource waste, inefficient equipment use and reduced service life.

[0004] Therefore, those skilled in the art need a distributed energy storage system based on modular design to solve the above problems through flexible energy storage unit switching and control methods. Summary of the invention

[0005] The purpose of the present invention is to solve the above deficiencies in the prior art and provide a distributed energy storage system based on modular design. The modular structural design solves the problems of resource waste, low efficiency and low life of the integrated energy storage unit in the prior art. The following is a specific solution:

[0006] A distributed energy storage system based on modular design includes a remote management module, a main control module, a dynamic load distribution module, an energy storage module, a fault warning module, a communication module and a temperature control module; the remote management module is used to realize remote monitoring and control of the system through an Internet of Things platform; the main control module is used to monitor the power status of the energy storage module, distribute the charging and discharging tasks of the energy storage module, and exchange data with the fault warning module and the communication module; the dynamic load distribution module is used to adjust the output power of each energy storage module according to the power demand forecast; the energy storage module includes a basic energy storage unit, a high-density energy storage unit and a long-life energy storage unit, which are used to adjust the output mode according to different output scenarios; the fault detection module is used to monitor the operating status of the energy storage module and send an alarm to the main control module when an abnormality occurs; the communication module is used to transmit data between the energy storage module and the main control module; the temperature control module is used to dynamically adjust the cooling system according to the temperature of the energy storage module.

[0007] The energy storage modules in the present invention are dynamically allocated according to different power demands. The basic energy storage unit provides a quick response at peak load to ensure the stability of power supply; the high-density energy storage unit provides continuous power supply during the load stability period to maintain the efficient operation of the system; the long-life energy storage unit plays a role during the low-load period, reducing the load of other energy storage units and extending the overall life of the system.

[0008] Furthermore, the basic energy storage unit is used to provide power output during peak system load demand, the high-density energy storage unit is used to provide power output during long-term stable system load demand, and the long-life energy storage unit is used to provide power output during low system load.

[0009] Furthermore, the main control module is used to complete the switching between the basic energy storage unit, the high-density energy storage unit and the long-life energy storage unit through an iterative optimization algorithm according to the prediction results of the dynamic load distribution module.

[0010] Furthermore, the iterative optimization algorithm performs real-time dynamic allocation based on the system load demand and energy storage module status data, and is calculated based on the following formula: Among them, η is the learning rate, which is used to control the update step size, and k is the iteration step.

[0011] Furthermore, the temperature control module adjusts the temperatures of the basic energy storage unit, the high-density energy storage unit and the long-life energy storage unit respectively according to the temperature distribution of the energy storage module. The temperature control module triggers the air cooling or liquid cooling circulation system by setting different temperature thresholds, and can remotely adjust the temperature control strategy through the main control module to adapt to changes in the external environment.

[0012] Furthermore, the temperature control module also includes a temperature adjustment unit based on adaptive fuzzy algorithm control, which can analyze the operating status of each energy storage unit and its temperature rising trend in real time, and dynamically adjust the operating rate of the cooling system through the adaptive fuzzy algorithm.

[0013] Furthermore, the fault warning module can monitor the voltage, temperature, internal resistance and charge and discharge rate of the basic energy storage unit, high-density energy storage unit and long-life energy storage unit in real time, analyze the severity of the abnormal signal, and determine whether to send an emergency shutdown command to the main control module.

[0014] Furthermore, the remote management module can autonomously optimize load distribution, temperature regulation and fault warning strategies through historical operation data and system fault records, and store the optimized control parameters in the main control module.

[0015] Beneficial effects: By dividing the energy storage units into basic energy storage units, high-density energy storage units and long-life energy storage units, each unit can be dynamically switched according to power demand. At the same time, the dynamic load distribution module intelligently adjusts the output mode of each energy storage unit according to the real-time load conditions, reducing the excessive use of high-density and high-power units, thereby extending the service life of each energy storage unit and reducing maintenance frequency and cost;

[0016] Through modular design, the management, monitoring and fault warning functions of the energy storage unit are integrated into the main control module and the communication module, which significantly simplifies the system's operation and maintenance process. The fault warning module can promptly alarm the main control module when the unit is abnormal, making it easier for operation and maintenance personnel to quickly locate and handle faults, further improving the reliability and safety of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural installation diagram of a distributed energy storage system based on modular design;

[0018] In the figure: 100, remote management module, 200, main control module, 300, dynamic load distribution module, 400, energy storage module, 410, basic energy storage unit, 420, high-density energy storage unit, 430, long-life energy storage unit, 500, fault warning module, 600, communication module, 700, temperature control module. DETAILED DESCRIPTION

[0019] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with embodiments and drawings. The embodiments are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0020] Please see Figure 1A distributed energy storage system based on modular design includes a remote management module 100, a main control module 200, a dynamic load distribution module 300, an energy storage module 400, a fault warning module 500, a communication module 600 and a temperature control module 700; the remote management module 100 is used to realize remote monitoring and control of the system through an Internet of Things platform; the main control module 200 is used to monitor the power status of the energy storage module 400, allocate the charging and discharging tasks of the energy storage module 400, and exchange data with the fault warning module 500 and the communication module 600; the dynamic load distribution module 300 0 is used to adjust the output power of each energy storage module 400 according to the power demand forecast; the energy storage module 400 includes a basic energy storage unit 410, a high-density energy storage unit 420 and a long-life energy storage unit 430, which are used to adjust the output mode according to different output scenarios; the fault detection module is used to monitor the operating status of the energy storage module 400 and send an alarm to the main control module 200 when an abnormality occurs; the communication module 600 is used to transmit data between the energy storage module 400 and the main control module 200; the temperature control module 700 is used to dynamically adjust the cooling system according to the temperature of the energy storage module 400.

[0021] The basic energy storage unit 410 is used to provide power output during the peak period of system load demand, the high-density energy storage unit 420 is used to provide power output during the long-term stability of the system load demand, and the long-life energy storage unit 430 is used to provide power output during the low-load period of the system; the main control module 200 is used to complete the switching between the basic energy storage unit 410, the high-density energy storage unit 420 and the long-life energy storage unit 430 through an iterative optimization algorithm according to the prediction results of the dynamic load distribution module 300; the iterative optimization algorithm performs real-time dynamic distribution according to the system load demand and the state data of the energy storage module 400, and is calculated based on the following formula:

[0022] Where η is the learning rate, which is used to control the update step size, and k is the iteration step. The specific calculation steps are as follows: At each iteration step k, calculate the objective function J with respect to each power output P i The gradient of Update the power allocation of each unit according to the gradient descent method, In each iteration step, if the power output of a certain energy storage unit is close to its capacity limit or the load demand changes significantly, the switch is triggered to activate or shut down the corresponding energy storage unit; repeat the above steps until the power allocation meets the convergence conditions, that is, the objective function J reaches the minimum value or meets the preset threshold; during the iteration process, the algorithm selects the appropriate energy storage unit according to the load demand status.

[0023] The temperature control module 700 adjusts the temperature of the basic energy storage unit 410, the high-density energy storage unit 420 and the long-life energy storage unit 430 according to the temperature distribution of the energy storage module 400. The temperature control module 700 triggers the air cooling or liquid cooling circulation system by setting different temperature thresholds, and can remotely adjust the temperature control strategy through the main control module 200 to adapt to changes in the external environment; the temperature control module 700 also includes a temperature adjustment unit based on adaptive fuzzy algorithm control, which can analyze the operating status of each energy storage unit and its temperature rising trend in real time, and dynamically adjust the operating rate of the cooling system through the adaptive fuzzy algorithm; the fault warning module 500 can monitor the voltage, temperature, internal resistance and charge and discharge rate of the basic energy storage unit 410, the high-density energy storage unit 420 and the long-life energy storage unit 430 in real time, analyze the severity of the abnormal signal, and determine whether to send an emergency shutdown command to the main control module 200; the remote management module 100 can autonomously optimize the load distribution, temperature adjustment and fault warning strategy through historical operation data and system fault records, and store the optimized control parameters in the main control module 200.

[0024] In a specific embodiment, the remote management module 100 is configured with a communication interface to connect to the Internet of Things platform, and realizes remote data transmission through a 4G / 5G module or an optical fiber interface; the main control module 200 adopts an STM32F407 processor, has built-in 512KB flash memory and 192KB SRAM, runs the main control program, has a CAN bus interface to communicate with each energy storage unit, and controls the charging and discharging tasks of each energy storage unit; the dynamic load distribution module 300 includes a multi-channel power regulator and a DSP control chip, which are used to adjust the power output of the energy storage module 400, and is equipped with an output adjustment capability of a rated power of 50kW, an accuracy of ±1kW, and can automatically adjust the output according to the system load conditions in real time.

[0025] In a specific embodiment, the energy storage module 400 includes three energy storage units: the basic energy storage unit 410 has a capacity of 5kWh and a charge and discharge rate of 2C, which can respond quickly during peak loads; the high-density energy storage unit 420 has a capacity of 20kWh and a charge and discharge rate of 0.5C, which is suitable for long-term stable loads; the long-life energy storage unit 430 has a capacity of 15kWh and adopts a low-rate 0.2C charge and discharge design for maintaining low load cycles.

[0026] In a specific embodiment, the fault warning module 500 adopts an MSP430 chip with built-in temperature sensors, voltage sensors and current sensors to monitor the operating status of the energy storage unit. If the voltage or temperature is abnormal, an alarm signal is automatically issued; the communication module 600 is designed based on the RS485 bus, which can realize multi-module data transmission, and has built-in data encryption and error detection functions to ensure data security and reliability; the temperature control module 700 adopts a closed-loop PID controlled cooling system with two modes of water cooling and air cooling. By real-time monitoring of the temperature of each unit and adjusting the cooling method, the energy storage unit is ensured to operate at the optimal temperature.

[0027] Implementation example: The distributed energy storage system is applied in a commercial building power supply system. During the peak load period during the day, the basic energy storage unit 410 begins to discharge quickly to ensure stable power supply and avoid excessive pressure on the external power grid. From noon to afternoon, when the load is stable, the system switches to the high-density energy storage unit 420 to provide continuous power supply and save resources. At night when the load is low, only the long-life energy storage unit 430 is enabled to maintain the minimum load demand.

[0028] The system monitors power, temperature and operating status around the clock. The remote management module 100 can access the Internet of Things platform at any time to view the operating status. When the fault warning module 500 detects excessive current or abnormal temperature, it will send an alarm to the remote platform to facilitate maintenance personnel to handle it in time.

[0029] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A distributed energy storage system based on modular design, characterized in that: It includes a remote management module, a main control module, a dynamic load distribution module, an energy storage module, a fault warning module, a communication module and a temperature control module; the remote management module is used to realize remote monitoring and control of the system through the Internet of Things platform; the main control module is used to monitor the power status of the energy storage module, allocate the charging and discharging tasks of the energy storage module, and exchange data with the fault warning module and the communication module; the dynamic load distribution module is used to adjust the output power of each energy storage module according to the power demand forecast; the energy storage module includes a basic energy storage unit, a high-density energy storage unit and a long-life energy storage unit, which are used to adjust the output mode according to different output scenarios; the fault detection module is used to monitor the operating status of the energy storage module and issue an alarm to the main control module when an abnormality occurs; the communication module is used to transmit data between the energy storage module and the main control module; the temperature control module is used to dynamically adjust the cooling system according to the temperature of the energy storage module.

2. A distributed energy storage system based on modular design according to claim 1, characterized in that: The basic energy storage unit is used to provide power output during peak system load demand, the high-density energy storage unit is used to provide power output during long-term stable system load demand, and the long-life energy storage unit is used to provide power output during low system load.

3. A distributed energy storage system based on modular design according to claim 1, characterized in that: The main control module is used to complete the switching between the basic energy storage unit, the high-density energy storage unit and the long-life energy storage unit through an iterative optimization algorithm according to the prediction results of the dynamic load distribution module.

4. A distributed energy storage system based on modular design according to claim 3, characterized in that: The iterative optimization algorithm performs real-time dynamic allocation based on the system load demand and energy storage module status data, and is calculated based on the following formula: Among them, η is the learning rate, which is used to control the update step size, and k is the iteration step.

5. A distributed energy storage system based on modular design according to claim 1, characterized in that: The temperature control module adjusts the temperature of the basic energy storage unit, the high-density energy storage unit and the long-life energy storage unit respectively according to the temperature distribution of the energy storage module. The temperature control module triggers the air cooling or liquid cooling circulation system by setting different temperature thresholds, and can remotely adjust the temperature control strategy through the main control module to adapt to changes in the external environment.

6. A distributed energy storage system based on modular design according to claim 1, characterized in that: The temperature control module also includes a temperature adjustment unit based on adaptive fuzzy algorithm control, which can analyze the operating status of each energy storage unit and its temperature rising trend in real time, and dynamically adjust the operating rate of the cooling system through the adaptive fuzzy algorithm.

7. A distributed energy storage system based on modular design according to claim 6, characterized in that: The fault warning module can monitor the voltage, temperature, internal resistance and charge and discharge rate of the basic energy storage unit, high-density energy storage unit and long-life energy storage unit in real time, analyze the severity of abnormal signals, and determine whether to send an emergency shutdown command to the main control module.

8. The distributed energy storage system based on modular design according to claim 1, characterized in that: The remote management module can autonomously optimize load distribution, temperature regulation and fault warning strategies through historical operation data and system fault records, and store the optimized control parameters in the main control module.

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