Case Study: BC Hydro

How Awesense helped BC Hydro gain situational awareness with real-time asset monitoring using IoT grid sensors and data model synchronization.

BC Hydro
Scope Snapshot
Goal

Ingest and synchronize data to build a digital twin in support of grid reliability, revenue protection and grid planning use cases.

The Data
  • GIS (including connectivity)
  • AMI metering
  • SCADA
  • Awesense Raptor line sensors
Awesense Tools Used
  • Energy Data Model (EDM)
  • Awesense Data Engine (grid and time series VEE)
  • EDM data ingestion APIs
  • EDM data retrieval APIs
  • True Grid Intelligence (TGI) web app
  • Awesense Raptor line sensors
  • TGI mobile app

The Challenge

BC Hydro sought new methods of situational awareness of their electric grid to improve reliability, revenue protection, and future grid planning decision making. To accomplish this, the BC Hydro team needed more data from more places on their grid, such as feeder level energy capacity data, power quality data, and other data that supports energy balancing. This further required that they bring all of the grid data into a single dashboard to streamline analysis and decision making processes.

The Solution & Results

Awesense worked with BC Hydro to install the Awesense Raptor sensors, enabling the utility to collect feeder-level power data. This data, along with other data from grid-connected resources, was ingested into the Awesense Platform and structured into a digital twin. Working as a dashboard that visualized the grid data, Awesense’s TGI viewer enabled near real-time data analytics and insight into BC Hydro’s assets and grid performance.

Using TGI, the BC Hydro team could zero in on specific assets or segments of the grid to draw further insight. In use at BC Hydro for over ten years, the TGI also has built-in use cases such as alerts for outage detection and feeder balancing, which enables the team to optimize revenue and increase consumer satisfaction. Furthermore, the BC Hydro team can build more use cases and analytics by pulling data from the digital twin via APIs, allowing them to create and expand their insights into their grid and planning efforts.

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