Case Study: Snohomish County PUD

How Awesense helped SNOPUD gain insight into microgrid resilience by structuring their data into a model for real-time analytics and management

Scope Snapshot
Goal

Achieve microgrid situational awareness through real-time data from grid resources and DERs.

The Data
  • SCADA
  • Meters
  • Storage
  • V2G/EVSE data
  • Grid Sensors
Awesense Tools Used
  • Awesense Raptor Sensors
  • AI Data Engine
  • Awesense Energy Data Model APIs
  • True Grid Intelligence (TGI)

The Challenge

Snohomish County Public Utility District (SnoPUD) and Doosan, a Distributed Energy Resource Management System (DERMS) software vendor, lacked visibility into the DERs within a microgrid in SnoPUD territory. The microgrid’s DERs include a battery, solar, and vehicle-to-grid (V2G) EV chargers. Doosan’s DERMS software, DERO, needed real-time data from the DERs and other grid resources, which in turn would provide SnoPUD situational awareness of the full microgrid system.

Without situational awareness of the microgrid and its DERs, as well as those of resources connected to SnoPUD’s electric grid, the teams were unable to make data-backed business and operational decisions, as well as scale the technology.

The Solution & Results

Awesense’s AI Data Engine ingested SnoPUD’s SCADA, Meters, BESS and V2G/EVSE data, which was subsequently structured and synchronized with differing reporting frequencies. The data, which was geo-referenced and provided in real-time, was visualized on TGI and made available to multiple teams via Awesense’s APIs.

With easy access to accurate and granular data from the DER and other grid resources, the Doosan team could better control and dispatch the microgrid’s energy storage system and V2G charging stations. Similarly, SnoPUD gained complete situational awareness of the microgrid and its integration within their territory. The data also supported long term planning such as the potential scaling of microgrids and V2G devices.

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