For more than a decade, Ontario has been a pioneer in the installation of smart meters and the implementation of time-of-use rates, which enable residential and Small General Service (>50 kW) customers to actively manage their electricity consumption. More than that, smart meters also produce large volumes of data related to consumption patterns that can be leveraged in ways that stimulate new value creation.
As Ontario’s designated Smart Metering Entity (SME), the IESO is responsible for the implementation and operation of the province’s Meter Data Management/Repository (MDM/R). The MDM/R is a central hub, providing a common platform for storing, processing, validating and managing hourly electricity consumption information to support local distribution companies (LDCs)’ billing processes – all in a highly secure environment.
With nearly five million smart meters sending hourly data to the MDM/R, and more than 65 LDCs integrated into the system, Ontario’s MDM/R is one of the largest shared systems in the world, adding 100 to 120 million records every day.
It’s still fairly early days for the widespread use of analytics related to electricity consumption in North America. In many respects, the electricity sector is in its infancy when it comes to using its own data for the benefit of customers and other third parties. There is significant untapped potential in smart meter data but before this potential can be realized, the data must first be analyzed and interpreted. In this era of big data, this information offers an important opportunity for the IESO and other rigorously screened third parties to take raw consumption data – stripped of all personal identifying information – and leverage it for other purposes.
Analytics and modelling may reveal previously unknown correlations and patterns, turning raw data into usable information. Although the MDM/R has been highly effective for billing purposes, it has the potential to support other uses. For example, a province-wide database of electricity consumption data could be used in a number of ways:
- Conservation and demand management program design
- Load forecasting and modelling
- Pricing analysis
- Transmission and distribution planning
- Development of apps and other energy management tools
- Identification of energy-savings opportunities within specific regions or sectors
The IESO has launched a stakeholder engagement related to third-party access to the MDM/R data. At the core of the implementation plan is a data de-identification methodology that is the gold standard in the disclosure control community. This methodology is aligned with the Information & Privacy Commissioner of Ontario's De-identification Guidelines.
Innovation is about creating new value. By making non-identifiable, non-confidential information available to third parties, this initiative will help them in developing innovative, new products and services that will enhance customer choice and control.