Note: This is the second part of Copper’s blog series about how an AMx framework can help energy utilities accelerate decarbonization.

 

For electric and gas utilities currently exploring territory-wide decarbonization pathways, there’s a clear and urgent need for better consumption data. Not only can better data help more precisely inform potential grid impacts associated with decarbonization measures at the distribution- or customer-level (helping utilities assure cost-effectiveness and potential reliability impacts), but it can also help ensure a more positive customer experience by allowing utilities to confirm that they will see direct benefits from decarbonization and enabling more effective personalized outreach and communication.

Unfortunately, many electric utilities are currently only able to get fairly latent (e.g. yesterday’s) data even if they have smart meters deployed, and many gas utilities only have access to monthly gas meter data at best since gas smart meter adoption lags well behind electric. But with a technology-enabled AMx approach, gas and electric utilities can quickly access much more frequent (in some cases down to 30 second) data from their existing meters, without having to replace or retrofit the meters themselves.

As one example of how this kind of data could be invaluable, consider potential options for replacing a building’s existing gas space heating equipment. One might consider swapping it out with:

  • An all-electric heat pump system (full fuel switching)
  • A hybrid system that combines an electric heat pump with a gas furnace (partial electrification)
  • A new more-efficient gas heat pump system (increased efficiency).

Each of those decisions can have marked impacts on gas and electric peak demand, overall measure cost-effectiveness, and customers’ overall energy bills. But without high-interval data on customers’ gas and electricity consumption—particularly during very cold days—utilities and other stakeholders could make flawed assumptions about the impacts associated with different options that ultimately lead to decisions that stress the grid by driving unexpectedly high new peaks in demand, unnecessarily inflate gas or electric prices, or exacerbate existing inequities in vulnerable communities.

By combining high-resolution gas data with comparable electric data on a single centralized platform, utilities can also get unprecedented visibility into potential grid- and customer-level impacts of building electrification or other decarbonization strategies—whether through user-friendly graphical portals or through more traditional manual data analysis. That kind of visibility is critical to ensure that decarbonization won’t lead to customer dissatisfaction or to unexpectedly large grid challenges that could reduce reliability or unnecessarily drive-up costs. Additionally, for electric and dual-fuel utilities, an AMx approach can enable improved visibility and modeling of EV adoption, allowing for better proactive management of distribution transformers and other supporting infrastructure.

With all these insights, electric and gas utilities can vastly improve their system forecasting capabilities through improved data-driven assumptions around technology adoption and expected system impacts down to the individual customer level. Not only can that provide a clearer look into future capacity and distribution needs across the electric and gas systems, but it can also support integrated energy planning—an emerging regulatory focus area—to ensure that customers continue to have reliable access to both electricity and gas, even under extreme situations.

In the next part of this blog series, we’ll explore how an AMx framework can help enable larger-scale data-driven load flexibility for the electric and gas systems to help support evolving system dynamics and better manage peak demand challenges. We hope you’ll join us!