EMQX Enables Smart Energy Storage with Real-Time Data Collection and Cloud-Edge Collaboration
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While the societal trend leans towards substituting traditional energy sources with more renewable options, challenges arise from the intermittent and variable nature of outputs from sources like solar and wind energy. The unpredictable highs and lows of renewable energy make it challenging to maintain a stable and consistent power supply on the electrical grid. Consequently, many power suppliers are considering constructing large-scale energy storage systems to optimize the management and utilization of these smart energy sources.
EMQ offers a unified MQTT platform for power suppliers by facilitating intelligent smart energy battery storage systems. It addresses critical issues such as data collection, analysis, transmission, and storage, ensuring the stable and efficient operation of energy systems.
Challenges of Building an Smart Energy Storage System
Power suppliers typically employ a containerized storage approach to establish an intelligent operational system for large-scale battery energy storage. This is more than just a straightforward energy storage device; it's a sophisticated system encompassing various functional modules, such as battery module management, energy management, air conditioning control, fire safety management, and energy resource management. The complexity of such a system demands efficient, reliable, and intelligent management methods to ensure its stable operation.
MQTT Platform for Large-Scale Centralized Energy Storage
EMQ empowers the construction of an smart energy storage system through the following aspects:
- Efficient Data Collection: NeuronEX gateway collects data from diverse devices at high frequency. It rapidly gathers data from over 10,000 container storage points in just 100ms for safe energy storage system operations.
- Low-Latency Edge Computing: NeuronEX offers an edge computing framework for battery energy storage systems, reducing latency to the millisecond level. This is achieved through SQL statements and function extensions, enabling features such as modeling analysis of State of Charge (SoC) / State of Health (SoH), battery module consistency calculation, predictive warning, data encoding compression, and real-time database storage at the edge.
- System Interconnection: The interconnection of power systems requires bidirectional communication based on higher-level secure communication technology. EMQ provides communication solutions for both forward and reverse gateways, helping battery energy storage enterprises achieve energy system interconnection in compliance with power safety standards.
- Decoupling of Multi-System: In energy storage backend systems, various subsystems have different requirements for throughput and latency. With streaming data persistence and processing capabilities, HStream platforms can help decouple different backend systems. This means that streaming data producers and consumers of data can operate independently, enhancing the overall flexibility and maintainability of the system.
The Advantages of EMQX MQTT Platform
- Massive Device Secure Interconnection: Achieve real-time collection of high-frequency massive data from large-scale smart energy storage devices, and establish bidirectional communication by the safety specifications required by the power system, ensuring the secure interconnection of system devices.
- Rapid Response and Stable Maintenance: Real-time stream computing at the edge reduces latency, enables fault warnings, and ensures stable operation. Besides, smart energy management based on data and algorithms also reduces operational costs.
- Low-Cost Scalable Construction: With high scalability and robust integration capabilities, the system can achieve rapid and flexible scaling, seamlessly integrating multiple systems to meet the requirements of large-scale construction.
EMQX Enterprise is a powerful enterprise MQTT platform designed for large-scale deployments and high reliability in IoT applications. The following capabilities of EMQX Enterprise can benefit the industry:
- High Reliability and Scalability: EMQX Enterprise adopts a distributed architecture with high availability and scalability to handle large-scale concurrent message transmission. It supports horizontal scaling to accommodate the growing number of IoT devices and data traffic, ensuring system stability.
- Rich Protocol Support: EMQX Enterprise supports multiple messaging protocols besides the MQTT protocol. It allows developers to extend to support all kinds of private protocols for their application needs.
- Data Integration: EMQX Enterprise seamlessly integrates with various data storage services, message queues, cloud platforms, and applications. It can connect with cloud services, enabling remote data transmission and cloud-based analysis.
- Security and Authentication: EMQX Enterprise provides robust security features, including TLS/SSL encrypted transmission, client authentication, and access control. It supports various authentication methods such as username/password, X.509 certificates, and OAuth, ensuring the security of IoT communication.
- Rule Engine and Data Processing: EMQX Enterprise has a flexible rule engine for real-time data processing and forwarding based on device data. It supports operations such as data filtering, transformation, aggregation, and persistence, helping users analyze and make decisions based on their business needs.
- Visual Monitoring and Management: EMQX Enterprise provides an intuitive visual monitoring and management interface, allowing users to monitor IoT devices and message transmission in real-time. Users can view connection status, message traffic, and other metrics and perform device management, troubleshooting, and system configuration operations.
NeuronEX is software tailored for the industrial sector, focusing on equipment data collection and edge intelligent analysis. It is primarily deployed in industrial settings, facilitating industrial equipment communication, industrial bus protocol acquisition, industrial system data integration, edge-level data filtering and analysis, AI algorithm integration, and integration with IIoT platforms. It offers the following features:
- Diverse Connectivity: NeuronEX provides multi-protocol access capability, supporting simultaneous access to dozens of industrial protocols such as Modbus, OPC UA, Ethernet/IP, BACnet, Siemens, Mitsubishi, and more. It enables integration with multiple data sources from systems like MES and WMS within the enterprise. NeuronEX also supports bidirectional data flow, allowing both data acquisition and control command issuance to devices.
- Deploy Anywhere: NeuronEX has very low memory footprints and is suitable for running on low-profile architecture devices like x86, ARM, RISC-V, etc. It also supports docker-like containerized deployment, running with other co-located containers in Kubernetes environments.
- Data Processing: NeuronEX incorporates 100+ built-in functions, supporting data filtering, data manipulation, device control, and data persistence, storing data in a time-series database.
- Algorithm Integration: NeuronEX supports the integration of algorithms written in languages such as C, Python, and Go. It facilitates real-time inference of industrial mechanism models, machine learning, and deep learning models at the edge, enabling alerts and intelligent decision-making.
- Edge to Cloud: Through protocols like MQTT and SparkplugB, NeuronEX aggregates and pushes industrial data to cloud platforms. The bidirectional data flow between NeuronEX and the cloud platform establishes cloud-edge data coordination and control synergy, leveraging the platform's big data storage and analysis capabilities to amplify the value of NeuronEX usage.
HStream Platform is a unified streaming data platform that provides the easiest way to ingest, store, process, and distribute your massive data streams. HStream Platform provides the following key features:
- Effortless Ingestion and Scalable Data Storage: Seamlessly ingest vast volumes of data continually generated from diverse sources, such as IoT device sensors. Store millions of data streams securely within a specifically engineered distributed streaming data storage cluster.
- Instantaneous Data Replay and Consumption: Experience real-time data consumption as rapidly as that facilitated by Kafka. By subscribing to topics within HStream, you can consume data streams in real-time. Furthermore, permanently storing data streams enables playback and consumption at any moment.
- Stream Processing with Familiar SQL: Process data streams rooted in event-time leveraging the same SQL syntax familiar to querying data within a relational database. Employ SQL for filtering, transforming, aggregating, and even combining multiple data streams.
- Real-Time Analytics Enhanced by Materialized Views: Through materialized views derived from persistently updated data streams, HStream empowers you to achieve real-time data insights through uncomplicated query operations employing standard SQL statements.
- Seamless Integration with Multiple External Systems: Built-in source and sink connectors for many popular systems, such as Kafka, MySQL, PostgreSQL, MongoDB, etc.