i1 Edge-Compute Node (ECN) - Ecosuite Inside (open source) by Ecosuite

Description

The Industrial 1 (i1) Edge Compute Node (ECN) is a versatile, high quality 3-phase Data Acquisition System designed to empower heterogeneous Distributed Energy Resources (DERs) with data acquisition, normalization and command and control capabilities.

The i1 supports the collection and standardization of data from sources such as DERs like building loads, solar inverters, battery energy storage systems (BESS),EV charging stations and building management systems (BMS). With a native integration to Ecosuite, customers can seamlessly leverage a variety of asset management applications and grid services to accelerate deployment and monetization of DERs.

The included revenue-grade kWh meter comes with rogowski coil current transformers (CTs) that can measure up to 3000A along with phase voltages, powerFactor, frequency, and bidirectional accumulating energy totals. Using Modbus TCP and Modbus RTU connections, the ECN can persist data directly from a wide variety of equipment such as solar inverters, pyranometers, thermistors and more. USB devices, IP cameras, weatherstations can also be added as data sources timestamped consistently and made available via Ecosuite and data science toolsets.  All inputs to the i1 ECN are protected from voltage surges - AC, Ethernet, and RS485 for robust operation and durability.

Supporting 4G LTE, 4G and WiFi connectivity, this ECN is easy to deploy regardless of the existing topology where it is deployed. Flexible networking options allows the ECN to be positioned anywhere in range of your weather station, solar + storage plant and building load center. Additionally, secure remote access to the ECN via web interface and command line is built in: fleet managers can now securely communicate with their devices from wherever they are. Stay tuned: A new Ecosuite mobile app is coming soon to add further flexibility and power.

Due to the ECN’s powerful CPU, many more applications can be added such as motion detection triggers, custom expressions for thresholds and hardware control plus edge machine learning (ML).  Check out SolarQuant and some of the first pre-trained models emerging from research work.