Energy Innovation Challenge

The Energy Innovation Challenge is a groundbreaking three-year program designed to develop capacity that supports Alberta energy transition and diversifies the energy economy.

We partnered with Decentralised Energy Canada (DEC) to empower small and medium-sized Canadian businesses to overcome commercialization obstacles and bring their innovations to market. The innovations will address focus areas related to:

  • grid reliability
  • grid resiliency
  • energy affordability
  • sustainability

Up to six successful applicants will be invited to demonstrate their innovative solutions with small-scale pilot projects within the City of Medicine Hat franchise territory. The City of Medicine Hat will provide 50% of the capital requirements for each project, up to $850,000 in total for all six projects, funded through reserves. 

Intake 2 now open!

Learn more about the program and how to apply by visiting the Decentralised Energy Canada website.

Energy Innovation Challenge website

Winners of intake 1

The City of Medicine Hat and Decentralised Energy Canada congratulate Arcus Power and Edgecom Energy as the first two winners of the Energy Innovation Challenge. 

Arcus Power

Arcus Power is an Alberta based Smart-Grid power market solutions provider that offers SaaS based software products to generators and utilities, industrial customers and financial users. This project will pilot a distributed energy storage planning functionality that will be integrated with Arcus Power’s existing SaaS platform. The planning software will support the City of Medicine Hat in planning and evaluating the optimal size, location, and investment for distributed energy resources, specifically battery energy storage and solar systems, which are needed to remove congestion on its electrical distribution system.

Edgecom Energy

Edgecom Energy offers a comprehensive Energy Management Solution suite that integrates Artificial Intelligence (AI) and the Internet of Things (IoT). Edgecom will install sensors at eight City of Medicine Hat facilities to monitor energy usage and report data into their building management system. The model will use AI to identify opportunities to reduce energy use based on machine learning of usage patterns in the building without imposing an additional burden on staff.

Additional info