Novel energy management system for industry and commerce

Abstract

The application provides a novel industrial and commercial energy storage management system, and belongs to the technical field of energy management, which comprises: a gateway EMU, which is used for collecting working state data of each outdoor cabinet, performing a cooperative control strategy on each outdoor cabinet based on the working state data, and uploading data related to the working state data and the cooperative control strategy; a cloud platform, which is in communication connection with the gateway EMU, and is used for receiving, storing and analyzing the data related to the working state data and the cooperative control strategy; and a terminal, which is used for responding to user operations and sending operation instructions to the cloud platform, so that the operation instructions are forwarded to the gateway EMU through the cloud platform to control the gateway EMU; wherein the working state data comprises battery SOC, rated power and health status. The application can solve the technical problems of the existing industrial and commercial energy storage management system, such as low cooperative efficiency of multiple cabinets, poor data collection reliability, weak remote management and control capability, and unexplored data value.

Description

Technical Field

[0001] This invention relates to the field of energy management technology, specifically to a novel industrial and commercial energy storage management system. Background Technology

[0002] Traditional industrial and commercial energy storage EMUs are mostly single-cabinet local controllers without a gateway-level central control architecture. They can only realize single-cabinet charging and discharging protection and basic operation control, and cannot realize global power distribution across multiple cabinets. When multiple cabinets are running, the load balance is poor and the overall system efficiency is low.

[0003] In addition, core dispatch data such as peak-valley flat electricity pricing and time calibration rely on manual input and regular updates, which can easily lead to problems such as data entry errors and synchronization delays after electricity price policy adjustments. This results in a disconnect between charging and discharging strategies and actual demand, leading to significant losses in peak-valley arbitrage profits.

[0004] A few solutions support remote operation, but they are limited to basic functions such as single cabinet start-up and shutdown and power fine-tuning. They lack core capabilities such as multi-cabinet collaborative control, global status monitoring, and remote policy configuration. Furthermore, the reliability of command transmission is poor and they are easily affected by network fluctuations.

[0005] Operational data is scattered and stored in local storage in each cabinet. There is no unified data cloud upload mechanism, which makes it impossible to achieve global data integration and analysis, fault tracing and policy iteration. Operation and maintenance require on-site data inspection, resulting in high maintenance costs.

[0006] It adopts a fixed "peak charging and valley discharging" rule with no dynamic adaptation capability, and cannot adjust the operation strategy according to real-time electricity price, grid load and battery status, resulting in insufficient dispatch flexibility and economy.

[0007] In summary, existing technologies have the following core pain points, failing to meet the demands for intelligent and efficient operation of large-scale industrial and commercial storage clusters: Low efficiency of multi-cabinet collaboration: Without a gateway central control hub, the independent operation of multiple cabinets leads to uneven load distribution, frequent overload of single cabinets, no fast redundancy switching mechanism in case of failure, poor power supply continuity, and affects the production and operation of industrial and commercial users.

[0008] Poor data collection reliability: Manual data entry is prone to errors and updates are delayed.

[0009] Weak remote management capabilities: It only supports simple remote operations and lacks functions such as global monitoring, multi-cabinet collaborative control, and remote operation and maintenance upgrades. Operation and maintenance personnel need to be on-site to handle the issues, resulting in long response cycles (24-72 hours) and high costs.

[0010] Untapped data value: Data is stored in a scattered manner, without a unified cloud platform for integration and analysis, making it impossible to optimize operating strategies or predict equipment failures based on massive amounts of data, and the system lacks continuous optimization capabilities. Summary of the Invention

[0011] In view of this, it is necessary to provide a new type of industrial and commercial energy storage management system to solve the technical problems of low efficiency of multi-cabinet collaboration, poor reliability of data acquisition, weak remote control capabilities, and lack of data value mining in the existing industrial and commercial energy storage management system.

[0012] To address the above problems, this invention provides a novel industrial and commercial energy storage management system, comprising: The gateway EMU is used to collect the working status data of each outdoor cabinet, and based on the working status data, execute collaborative control strategies for each outdoor cabinet, and upload the working status data and data related to the collaborative control strategies. The cloud platform, which is communicatively connected to the gateway EMU, is used to receive, store, and analyze the working status data and data related to the collaborative control strategy. The terminal is used to respond to user operations and send operation instructions to the cloud platform, so that the cloud platform can forward the operation instructions to the gateway EMU for control of the gateway EMU; The operating status data includes: battery SOC, rated power, and health status; The collaborative control strategy includes: Based on the working status data, the charging and discharging power is allocated to each outdoor cabinet in proportion to ensure that the load balancing rate of each outdoor cabinet is greater than the preset balancing rate threshold. If, based on the aforementioned operating status data, it is determined that an outdoor cabinet has malfunctioned, the load connected to the malfunctioning outdoor cabinet will be switched to a normally functioning outdoor cabinet. Based on the collected electricity price period and real-time electricity price, the charging and discharging mode of the outdoor cabinet is determined.

[0013] In one possible implementation, the gateway ECU is used to convert the instructions required by the collaborative control strategy into standardized control instructions when executing the collaborative control strategy, and to send the standardized control instructions to each outdoor cabinet through an Ethernet interface.

[0014] In one possible implementation, the gateway EMU is also used to collect peak-valley-flat electricity price data for future times and upload the peak-valley-flat electricity price data to the cloud platform for backup in a standardized format.

[0015] In one possible implementation, the gateway EMU is also used to cache the collected peak-valley-flat electricity price data locally, and after the failure to collect peak-valley-flat electricity price data, execute the scheduling strategy based on the cached peak-valley-flat electricity price data or the peak-valley-flat electricity price data backed up by the cloud platform.

[0016] In one possible implementation, the gateway EMU is further configured to trigger an alarm and send the alarm information to the terminal and the cloud platform when it is determined that the peak-valley-flat electricity price data is abnormal based on preset data verification rules.

[0017] In one possible implementation, the data verification rules include: electricity price range and reasonable time period.

[0018] In one possible implementation, the gateway EMU is also used to synchronize the gateway system time in real time by connecting to an NTP time server, and to perform time synchronization based on the gateway's local real-time clock when the network is interrupted.

[0019] In one possible implementation, the gateway EMU is also used to perform time calibration with an NTP time server based on the gateway's local real-time clock when the network is restored after an interruption.

[0020] In one possible implementation, the charging and discharging modes include: peak discharge, off-peak charging, or normal standby.

[0021] In one possible implementation, the gateway EMU communicates with the cloud platform using the MQTT lightweight protocol, HTTP / 2 protocol, or CoAP protocol.

[0022] The beneficial effects of adopting the above implementation method are as follows: The novel industrial and commercial energy storage management system provided by the present invention includes a gateway EMU, which is used to collect the working status data of each outdoor cabinet, and execute a collaborative control strategy for each outdoor cabinet based on the working status data, as well as upload the working status data and data related to the collaborative control strategy; a cloud platform, which is communicatively connected to the gateway EMU, is used to receive, store and analyze the working status data and data related to the collaborative control strategy; and a terminal, which is used to respond to user operations and send operation instructions to the cloud platform, so that the cloud platform can forward the operation instructions to the gateway EMU for control of the gateway EMU.

[0023] This invention is based on a three-layer cloud-edge collaborative architecture of "gateway EMU - cloud platform - terminal". Based on the working status data, it allocates charging and discharging power to each outdoor cabinet according to a ratio to ensure that the load balancing rate of each outdoor cabinet is greater than a preset balancing rate threshold. If a faulty outdoor cabinet is identified based on the working status data, the load connected to the faulty outdoor cabinet is switched to the normally functioning outdoor cabinet. Based on the collected electricity price period and real-time electricity price, the charging and discharging mode of the outdoor cabinet is determined. Thus, it realizes an integrated design of multi-outdoor cabinet central control coordination, full data upload to the cloud, and remote management and control.

[0024] Furthermore, this invention achieves data collection through a gateway EMU and automatically uploads the data to the cloud platform, eliminating the need for manual data entry and improving the reliability of data collection.

[0025] Furthermore, users can input operation commands through the terminal, which are then forwarded by the cloud platform to the gateway EMU for execution, enhancing remote management capabilities.

[0026] Furthermore, the cloud platform can receive, store, and analyze the aforementioned work status data and data related to collaborative control strategies, thereby enabling data value mining.

[0027] Therefore, the solution provided by this invention solves the technical problems of low multi-cabinet collaboration efficiency, poor data acquisition reliability, weak remote control capabilities, and untapped data value in existing industrial and commercial energy storage management systems. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 A schematic block diagram of an embodiment of the novel industrial and commercial energy storage management system provided by the present invention; Figure 2 A schematic diagram of the three-layer architecture of another embodiment of the novel industrial and commercial energy storage management system provided by the present invention; Figure 3 The Python data acquisition and synchronization flowchart provided by this invention; Figure 4 The flowchart for multi-cabinet collaborative control and remote control provided by this invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] In the description of the embodiments of this application, unless otherwise stated, "a plurality of" means two or more.

[0032] In this embodiment of the invention, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, apparatus, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such process, method, product or device.

[0033] The naming or numbering of steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed in the time / logical order indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effect can be achieved.

[0034] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0035] This invention provides a novel industrial and commercial energy storage management system that integrates gateway central control, Python automatic data acquisition, cloud platform remote control, and full data upload to the cloud, thus overcoming the shortcomings of existing technologies.

[0036] like Figure 1 As shown, the present invention provides a novel industrial and commercial energy storage management system, which includes: The gateway EMU is used to collect the working status data of each outdoor cabinet, and based on the working status data, execute collaborative control strategies for each outdoor cabinet, and upload the working status data and data related to the collaborative control strategies. The cloud platform, which is communicatively connected to the gateway EMU, is used to receive, store, and analyze the working status data and data related to the collaborative control strategy. The terminal is used to respond to user operations and send operation instructions to the cloud platform, so that the cloud platform can forward the operation instructions to the gateway EMU for control of the gateway EMU; The operating status data includes: battery SOC, rated power, and health status; The collaborative control strategy includes: Based on the working status data, the charging and discharging power is allocated to each outdoor cabinet in proportion to ensure that the load balancing rate of each outdoor cabinet is greater than the preset balancing rate threshold. If, based on the aforementioned operating status data, it is determined that an outdoor cabinet has malfunctioned, the load connected to the malfunctioning outdoor cabinet will be switched to a normally functioning outdoor cabinet. Based on the collected electricity price periods and real-time electricity prices, the charging and discharging modes of the outdoor cabinet are determined; the charging and discharging modes include: peak discharge, off-peak charging, or standby during normal times.

[0037] Understandably, gateway hardware can be either industrial-grade edge gateways or embedded gateways with equivalent computing power and interface expansion capabilities (such as Huawei AR series and Siemens SIMATIC IPC series). As long as they support Python script execution, multi-protocol data acquisition, and dual-link communication, they are all equivalent alternatives.

[0038] This invention belongs to the field of distributed energy storage system energy management technology, specifically involving the development of an industrial and commercial energy storage energy management unit (EMU) based on an industrial gateway. It focuses on the coordinated control of multiple outdoor cabinet clusters, 24-hour automated collection of electricity price / time data, and automatic optimization and scheduling technology at the edge. It is suitable for the operation and management of industrial and commercial energy storage systems that require high real-time performance and high economy.

[0039] In some embodiments, the gateway ECU is used to convert the instructions required by the collaborative control strategy into standardized control instructions when executing the collaborative control strategy, and to send the standardized control instructions to each outdoor cabinet through an Ethernet interface.

[0040] Understandably, the collaborative strategy is transformed into standardized control commands, which are then distributed in batches to each cabinet's PCS (energy storage converter) via Ethernet interface, supporting both batch control and precise single-cabinet regulation.

[0041] In some embodiments, the gateway EMU is also used to collect peak-valley-flat electricity price data for future times and upload the peak-valley-flat electricity price data to the cloud platform for backup in a standardized format.

[0042] As is understandable, peak-valley-flat electricity pricing data refers to the billing data whereby the power sector divides a day into peak, flat, and off-peak periods (sometimes including extreme peaks) based on changes in grid load, and sets different electricity price levels for each period. Its core purpose is to guide users to use electricity during off-peak hours through price levers, thereby improving grid operating efficiency.

[0043] In some embodiments, the gateway EMU is further configured to cache the collected peak-valley-flat electricity price data locally, and execute a scheduling strategy based on the cached peak-valley-flat electricity price data or the peak-valley-flat electricity price data backed up by the cloud platform after the collection of peak-valley-flat electricity price data fails.

[0044] Understandably, when data collection fails, the system automatically retrieves locally cached historical electricity price data and cloud platform backup data to ensure that the scheduling strategy is not interrupted.

[0045] The scheduling strategy involves controlling the charging and discharging power of each outdoor cabinet to allocate power proportionally, thereby achieving power dispatching.

[0046] In some embodiments, the gateway EMU is further configured to trigger an alarm and send the alarm information to the terminal and the cloud platform when it is determined that the peak-valley-flat electricity price data is abnormal based on preset data verification rules.

[0047] The data verification rules include: electricity price range and reasonable time period.

[0048] It is understandable that the reasonable time period division varies across different regions and user types (residential / commercial). The following are common division methods: Residential users (most areas): Peak hours: 08:00–22:00 (14 hours); Valley period: 22:00 – 08:00 the next day (10 hours); Flat section: Some provinces do not have a flat section, but only peak and valley sections.

[0049] Industrial and commercial users: Peak hours: 10:00–14:00, 17:00–21:00 (8 hours in total); Low point: 23:00 – 07:00 the next day (8 hours in total); Plain section: The remaining 8 hours.

[0050] Determine whether the peak-valley-flat electricity price data falls within the reasonable time period and corresponding price range mentioned above. If it does, the data is considered normal.

[0051] In some embodiments, the gateway EMU is also used to synchronize the gateway system time in real time by connecting to an NTP time server, and to perform time synchronization based on the gateway's local real-time clock when the network is interrupted.

[0052] Furthermore, the gateway EMU is also used to perform time calibration with the NTP time server based on the gateway's local real-time clock when the network is restored after an interruption.

[0053] Understandably, an NTP time server is a hardware or software system based on the Network Time Protocol (NTP) used to provide high-precision time synchronization services for devices in a computer network, ensuring that the time of all devices is consistent with Coordinated Universal Time (UTC).

[0054] In some embodiments, the gateway EMU communicates with the cloud platform using the MQTT lightweight protocol, HTTP / 2 protocol, or CoAP protocol.

[0055] It is understood that the dual-link transmission protocol between the gateway EMU and the cloud platform can adopt the MQTT protocol, or the MQTT protocol can be replaced by industrial IoT protocols such as HTTP / 2 and CoAP, as long as the transmission latency is ≤100ms and the reliability requirements are met.

[0056] In summary, this invention achieves an innovative breakthrough through an integrated design of "gateway core + Python automatic data collection + cloud-edge collaboration + remote management and control," the specific solution of which is as follows: 1. Overall Architecture Design Construct a three-tier collaborative architecture of "EMU - Cloud Platform - Terminal", such as Figure 2 As shown, this achieves end-to-end data connectivity and closed-loop control: EMU: An industrial-grade edge gateway is selected as the hardware carrier, integrating a multi-cabinet coordination and control module, a data acquisition module, and a dual-link communication module, undertaking the functions of data acquisition, local collaborative decision-making, command execution, and data uploading.

[0057] Cloud platform: Deploys a global data management center, remote control engine, fault diagnosis system and report analysis module, receives all data uploaded by the gateway EMU, stores, analyzes and visualizes it, and responds to remote terminal commands and sends them to the gateway EMU.

[0058] Terminals include web management terminals, mobile apps, and industrial control panels, which support users in remotely viewing operating status, issuing control commands, configuring policy parameters, and receiving fault alarms.

[0059] 2. For example Figure 3 As shown, a Python script automates the collection of electricity price and time data. Electricity price collection logic: A lightweight Python script is developed and deployed locally on the gateway EMU. Every day at 0:00, it automatically calls the open API interface (application programming interface) of the power grid sales platform to collect the peak-valley-flat electricity price data (including time period division and electricity price standard) for the next day. It supports redundant adaptation of multiple API interfaces (such as the official interface of the power grid + the interface of third-party sales platforms). After successful collection, the script automatically parses it into a standardized format (JSON) and stores it synchronously in the local database of the gateway and the distributed database of the cloud platform. If the collection fails, it automatically calls the locally cached historical electricity price data and the backup data of the cloud platform to ensure that the scheduling strategy is not interrupted.

[0060] Time synchronization mechanism: The Python script connects to an NTP (Network Time Protocol) time server (such as pool.ntp.org) to synchronize the gateway system time in real time with a time error of ≤1s; when the network is interrupted, the gateway’s local high-precision real-time clock (RTC) is enabled to maintain time accuracy, and the clock is automatically calibrated after the network is restored to avoid errors in time period judgment.

[0061] Anomaly handling function: The script has built-in data verification rules (such as electricity price range and time period reasonableness verification). When abnormal data is detected, an alarm is immediately triggered and pushed to the cloud platform and remote terminal, while automatically switching to the backup data source.

[0062] It should be noted that the Python script can be replaced with scripts developed in lightweight programming languages ​​such as Go and Lua. The core protection logic is "automatic collection - multi-source backup - cloud synchronization". The choice of language does not affect the scope of protection.

[0063] 3. For example Figure 4 As shown, the multi-outdoor cabinet central control coordination logic The gateway EMU acts as the central control hub, enabling global collaborative control. Data Acquisition: Real-time acquisition of core data from each outdoor cabinet via Modbus / TCP and RTU industrial protocols, including battery SOC (State of Charge) / SOH (State of Health), charging and discharging power, temperature, grid voltage / frequency, fault status, etc.

[0064] Collaborative control strategy: Load balancing: Based on the SOC, rated power and health status of each cabinet, the charging and discharging power is allocated proportionally to ensure a multi-cabinet load balancing rate of ≥95% and avoid single cabinet overload; Fault redundancy: Real-time monitoring of the operating status of each cabinet. When a cabinet fails, a load transfer command is triggered within 50ms to quickly distribute the load of the faulty cabinet to other normal cabinets, ensuring power supply continuity. Time-of-use adaptation: Based on the electricity price time period and real-time electricity price collected by Python, automatically switch the charging and discharging mode (peak discharge, off-peak charging, and standby during normal times) to maximize peak-valley arbitrage profits.

[0065] Command issuance: The collaborative strategy is converted into standardized control commands and distributed in batches to each cabinet PCS (energy storage converter) via Ethernet interface, supporting batch control and precise single-cabinet regulation.

[0066] 4. Full data migration to the cloud Data transmission scheme: The gateway EMU transmits data through dual-link redundancy of "4G + Ethernet" and uses the MQTT lightweight protocol to ensure real-time transmission.

[0067] Cloud storage and analysis: The cloud platform uses a distributed database to store all data, supporting long-term data storage and fast retrieval; it integrates a data visualization module to generate global revenue / single cabinet operation curves, fault traceability logs, etc.

[0068] 5. Cloud platform remote control and operation and maintenance Remote monitoring: Users can view the overall operating status (total power, total SOC, cumulative revenue), single cabinet details (real-time parameter data, historical curves), electricity price data, and fault alarm information in real time through a remote terminal.

[0069] Remote control: Supports remote issuance of commands such as cluster start / stop, adjustment of charging / discharging power limit, switching of operating mode (peak shaving / valley filling / emergency power supply), manual update of electricity price data, and configuration of collaborative strategy parameters.

[0070] Remote operation and maintenance: Supports remote maintenance. When the gateway control policy is updated, no local operation is required, and maintenance and upgrades can be performed directly remotely.

[0071] The implementation process of this invention is as follows: 1. Implementation of EMU Hardware selection: Edge computing gateway, Kunlun Tongtai human-machine interface; Data Acquisition Logic: Millisecond-level real-time data acquisition is achieved through an EMU developed based on the gateway, and data preprocessing is completed. Edge functionality: The touchscreen can store quantitative data and work with an edge computing gateway to implement local emergency logic; Command reception: The edge computing gateway includes a 4G communication module to receive control commands issued by the cloud platform and drive the outdoor cabinet to perform charging and discharging commands.

[0072] 2. Data transmission link Redundant transmission link setup: A dual-link architecture of "4G wireless communication + Ethernet wired communication" is adopted; Communication Protocol and Security: MQTT / HTTP protocol is used to transmit collected data / commands, and CRC check is added to critical data (such as control commands).

[0073] 3. Implementation of the cloud platform (a) Data storage Building a combination of "time-series database + relational database": The time-series library is used to store time-series data of the real-time operation of outdoor cabinets; The relational database is used to store structured data such as basic device information, policy configuration, and fault logs; (II) Global Optimization Load forecasting: Based on time series models, combined with historical operating data and peak and valley periods of the power grid, the load demand for the next 1-24 hours is predicted; Power grid status analysis: Real-time monitoring of power grid voltage, frequency, and load factor to identify heavy / light load conditions of the power grid; Optimized calculation: Using Python algorithms, the system continuously collects official electricity prices and times from the power grid 24 hours a day, updates electricity price and time data in real time, and generates multi-outdoor power allocation instructions with the goals of "SOC balance, grid load smoothing, and minimum operating costs". (iii) Power distribution; The platform converts the optimized strategy into standardized control commands, which are then sent to the edge computing gateway of the corresponding outdoor cabinet via the transmission link.

[0074] 4. Terminal Implementation Multi-application development Web-based: A visualization page can be built using the Vue / React framework, and real-time curves of SOC, power, and grid parameters can be displayed using ECharts; APP side: A mobile APP platform can be built using the Uni-A framework to display real-time data such as SOC, power, voltage, and grid parameters; Industrial control screen: Develop an embedded UI (interactive interface) using QT to adapt to large screens in industrial scenarios; 5. Permissions and Operations Define roles and permissions (administrator / operation engineer / viewer) and restrict the command and operation permissions of different roles; Built-in operation and maintenance functions: equipment ledger management, fault alarm record, and export of historical operation reports.

[0075] V. Key points that need to be protected in this plan (listed in order of importance) 1. Based on the three-layer cloud-edge collaborative architecture of "EMU-cloud platform-terminal", it realizes the integrated design of multi-outdoor cabinet central control coordination, full data cloud uploading and remote management.

[0076] 2. Automated collection of electricity price and time data based on Python scripts, including API interface adaptation and local-cloud dual storage strategy.

[0077] 3. The multi-outdoor cabinet collaborative control logic led by the gateway EMU includes load balancing algorithms, fault redundancy fast switching mechanisms, and dynamic adaptation strategies based on electricity price periods.

[0078] 4. A dual-link redundant transmission and secure storage solution for full data upload to the cloud, including the MQTT protocol transmission mechanism.

[0079] 5. A cloud platform remote operation system that integrates remote monitoring, remote control, and remote operation and maintenance, supporting remote upgrades, remote fault diagnosis, and remote policy configuration.

[0080] The novel industrial and commercial energy storage management system provided by this invention has been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A novel industrial and commercial energy storage management system, characterized in that, include: The gateway EMU is used to collect the working status data of each outdoor cabinet, and based on the working status data, execute collaborative control strategies for each outdoor cabinet, and upload the working status data and data related to the collaborative control strategies. The cloud platform, which is communicatively connected to the gateway EMU, is used to receive, store, and analyze the working status data and data related to the collaborative control strategy. The terminal is used to respond to user operations and send operation instructions to the cloud platform, so that the cloud platform can forward the operation instructions to the gateway EMU for control of the gateway EMU; The operating status data includes: battery SOC, rated power, and health status; The collaborative control strategy includes: Based on the working status data, the charging and discharging power is allocated to each outdoor cabinet in proportion to ensure that the load balancing rate of each outdoor cabinet is greater than the preset balancing rate threshold. If, based on the aforementioned operating status data, it is determined that an outdoor cabinet has malfunctioned, the load connected to the malfunctioning outdoor cabinet will be switched to a normally functioning outdoor cabinet. Based on the collected electricity price period and real-time electricity price, the charging and discharging mode of the outdoor cabinet is determined.

2. The novel industrial and commercial energy storage management system according to claim 1, characterized in that, The gateway ECU is used to convert the instructions required by the collaborative control strategy into standardized control instructions when executing the collaborative control strategy, and to send the standardized control instructions to each outdoor cabinet through the Ethernet interface.

3. The novel industrial and commercial energy storage management system according to claim 1, characterized in that, The gateway EMU is also used to collect peak-valley-flat electricity price data for future times, and upload the peak-valley-flat electricity price data to the cloud platform in a standardized format for backup.

4. The novel industrial and commercial energy storage management system according to claim 1, characterized in that, The gateway EMU is also used to cache the collected peak-valley-flat electricity price data locally. If the collection of peak-valley-flat electricity price data fails, the scheduling strategy is executed based on the cached peak-valley-flat electricity price data or the peak-valley-flat electricity price data backed up by the cloud platform.

5. The novel industrial and commercial energy storage management system according to claim 1, characterized in that, The gateway EMU is also used to trigger an alarm and send the alarm information to the terminal and the cloud platform when it is determined that the peak-valley-flat electricity price data is abnormal based on preset data verification rules.

6. The novel industrial and commercial energy storage management system according to claim 5, characterized in that, The data verification rules include: electricity price range and reasonable time period.

7. The novel industrial and commercial energy storage management system according to claim 1, characterized in that, The gateway EMU is also used to synchronize the gateway system time in real time by connecting to an NTP time server, and to perform time synchronization based on the gateway's local real-time clock when the network is interrupted.

8. The novel industrial and commercial energy storage management system according to claim 7, characterized in that, The gateway EMU is also used to perform time calibration with the NTP time server based on the gateway's local real-time clock when the network is restored after an interruption.

9. The novel industrial and commercial energy storage management system according to claim 1, characterized in that, The charging and discharging modes include: peak discharge, off-peak charging, or standby mode.

10. The novel industrial and commercial energy storage management system according to any one of claims 1-9, characterized in that, The gateway EMU communicates with the cloud platform using the MQTT lightweight protocol, HTTP / 2 protocol, or CoAP protocol.

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