At LF Energy Summit 2024 in Brussels, Suyash Joshi, a Developer Advocate at InfluxData, presented a session titled “ju:niz Energy Storage: A Case Study.” The session explored how ju:niz, a German pioneer in decentralized energy storage, leveraged InfluxDB to overcome critical challenges in managing large-scale energy systems (full video follows at the end).
1. Introduction to ju:niz and Energy Management Challenges
ju:niz is a German-based company focusing on decentralized energy storage systems. Their clientele includes energy suppliers serving residential areas, and they employ an intelligent energy management system (EMS) to optimize large-scale storage plants. The EMS needs to manage various metrics, including power, capacity, and battery performance, which are critical for decision-making in energy trading and system maintenance.
However, ju:niz was grappling with several technical challenges. These included outdated legacy infrastructure that couldn’t scale to handle the influx of data, synchronization issues between data collected at energy plants and stored in the cloud, and the need for real-time insights for more effective energy management.
2. The Role of InfluxDB in Overcoming Challenges
To tackle these problems, ju:niz restructured its architecture by integrating InfluxDB, a time-series database specialized in handling large volumes of real-time, time-stamped data. InfluxDB’s ability to ingest, compress, and analyze massive amounts of streaming data from industrial IoT sensors made it an ideal fit for ju:niz ’s needs.
InfluxDB enabled ju:niz to process data from sensors at wind turbines, batteries, and other critical modules in real time. This enhanced system visibility and allowed for the faster and more reliable reporting necessary to make timely decisions.
3. Real-time Data and Scalability with InfluxDB
The core benefit of InfluxDB was its ability to scale effectively while maintaining performance. ju:niz initially faced challenges with 50,000 data points from their PLC controllers, which strained the legacy system. With InfluxDB’s edge data replication and its cloud offerings, ju:niz achieved higher compression rates and improved data storage efficiency, reducing storage costs while increasing reliability.
InfluxDB’s cloud-based architecture also allowed ju:niz to seamlessly integrate both its open-source version and cloud-dedicated version, providing high availability and stability without the burden of managing legacy hardware.
4. Open Source Integration: Telegraf and Data Ingestion
ju:niz also leveraged Telegraf, an open source tool provided by InfluxData, to facilitate seamless data ingestion from various sensors and industrial protocols. Telegraf’s integration with protocols like MQTT and Modbus enabled ju:niz to easily collect data from its plants, whether related to temperature, voltage, or battery metrics. This real-time data ingestion was essential for optimizing plant operations.
5. Improved Decision-making with Edge Data Replication
One of the standout features ju:niz implemented was edge data replication, which ensures that data captured locally at energy plants is synchronized with the cloud in real-time. This approach enhanced the reliability and accuracy of the data used for reports and decision-making. ju:niz’s ability to monitor specific metrics, such as battery temperatures and power fluctuations, in detail allowed for granular insights into plant health, helping to prevent system failures before they occur.
6. Cost and Storage Efficiency Gains
InfluxDB also brought significant improvements in terms of data compression and cost-efficiency. In the presentation, a key example was shared: over a span of four weeks, ju:niz collected 400 GB of battery data using InfluxDB Version 2, which was reduced to just 40 GB in InfluxDB Version 3, a tenfold improvement in compression efficiency. This compression capability not only improved performance but also reduced financial strain related to server and storage costs.
7. Looking Ahead: The Future with InfluxDB
As ju:niz continues to grow and expand its operations, InfluxDB remains at the heart of its data management system. Suyash highlighted how InfluxDB’s continued development – especially with the upcoming InfluxDB Version 3 – will further optimize the handling of complex, high-volume data. This is crucial for companies like ju:niz as they scale their operations to meet the growing demands of the energy storage sector.
