Electrifying Your Home? The Open Data Key to Unlocking Savings

Back in 2012, I decided to start the process of replacing all of the gas appliances in our home with electric versions. When I would share this with friends or relatives, they could not understand why I would want to do such a thing. Even in the Pacific Northwest where we have very affordable electric rates, gas is a less expensive energy source. At the time, I knew of people who were adding gas lines to their existing home in order to access this cheaper energy. The idea of choosing to use electricity over gas was so foreign to those around me. Whenever I pointed out that burning fossil fuels was the primary driver of climate change and that “natural,” i.e. methane, gas is part of the problem and needs to be replaced, people were still bought into the idea that methane gas was a “cleaner” and more “sustainable” fuel source. Note: from herein I will refer to this as methane gas and not “natural” gas as that name is a whitewashing campaign of the fossil fuel industry.

Fast forward more than a decade and many people have caught on to the idea of electrification of everything. The need to end our dependence on all fossil fuels, including methane gas, is clear. This is just one part of the broader, critical effort to electrify our world in order to avoid the worst of the climate crisis. As I transitioned my home to electric appliances, added EV charging, rooftop solar power, and battery backup, there were times when the hunt for reliable information about tax credits and rebates became an unexpected hurdle. Depending on the entity offering the incentive - Federal, State, and/or Local Utility - the information available was sometimes not easy to find and/or was unclear. Uncertain about eligibility and struggling to find clear information, I realized the need for a centralized and user-friendly resource for electrification incentives. Thankfully there are organizations that are trying to make this information more accessible and understandable. One such organization is the NODE Collective .

As the NODE Collective states it, the challenge is a fragmented incentive data ecosystem. “Billions in IRA rebates present a transformative opportunity for electrification. Yet, a fractured incentive data landscape is causing confusion and friction for businesses and consumers alike, and slowing innovation when time is of the essence. Addressing the climate crisis requires a shift to open data, transforming incentive information into a public asset. This fosters rapid innovation, breaks down inefficiencies, and calls for a unified, decentralized strategy that transcends individual agendas.” The NODE Collective’s founding members are from Eli Technologies , the Building Decarbonization Coalition , Rewiring America , RMI (founded as Rocky Mountain Institute), and the North Carolina Clean Energy Technology Center. You can learn more details from their press release.

One of their guiding principles is Standardization of Incentive Data. It is this topic that grabbed my attention and made me want to dig in a bit deeper. Inconsistent data structures have caused similar problems in other data domains, leading to friction in innovation and slow progress. This often results in the creation of standards-setting bodies to address these issues. It made me curious to learn if there might be opportunities to learn from those other efforts and apply those learnings to NODE Collective’s endeavor.

In the book “Sharing Clinical Research Data” the chapter “Standardization to Enhance Data Sharing” mentions some challenges in data sharing that are similar to the challenges the NODE Collective is working to address:

• Lack of universal standards and data heterogeneity: This is similar to the challenge faced by the NODE Collective in establishing a common format for capturing and sharing information about electrification incentives across different programs and governmental bodies. Data is collected and stored in various formats and structures from different sources, making it difficult to integrate and analyze.
• Incomplete or inaccurate data: The chapter mentions the problem of missing or inaccurate data in clinical records. This can also be an issue with electrification incentive data if programs don't have robust mechanisms to ensure data reliability.
• Evolving standards: The healthcare field constantly evolves, and keeping data standards up-to-date can be challenging. Similarly, the landscape of electrification incentives might change over time, requiring the NODE Collective to adapt its data standards to accommodate new program features or technologies.

Given the similarities, it is important to look at the challenges that were faced in the data standardization process itself. In that we can find some learnings to apply to the NODE Collective’s efforts:

• Stakeholder buy-in: The chapter mentions the importance of getting agreement from various stakeholders, such as healthcare providers, researchers, and IT professionals, on a common data standard. Similarly, the NODE Collective might face challenges in achieving consensus among diverse stakeholders in the electrification incentive landscape. This could include state energy offices, utilities, program administrators, and advocacy groups. Each stakeholder might have their own preferences for data collection and presentation.
• Technical complexity: The chapter acknowledges the technical complexities involved in designing and implementing data standards. This can involve complex data modeling, ensuring data compatibility across different IT systems, and addressing security and privacy concerns. The NODE Collective might face similar technical hurdles in establishing a robust data infrastructure for managing and sharing electrification incentive data.
• Legacy systems: The chapter mentions the challenge of integrating standardized data with existing legacy systems used in healthcare institutions. The NODE Collective might face a similar challenge if some program administrators or utilities rely on older data management systems that are not easily compatible with new standards or have difficulty reliably delivering the data.
• Ongoing maintenance: The chapter highlights the need for ongoing maintenance and updates to data standards to keep pace with evolving technologies and best practices. The NODE Collective would also need to consider a long-term strategy for maintaining and updating their data standards to ensure continued relevance and effectiveness.

By keeping these challenges in mind and addressing them in their approach, the NODE Collective can make the “shift to open data, transforming incentive information into a public asset.” Standardized data will improve user experience, streamline program administration, and ultimately accelerate electrification.

Looking back on my own experiences over more than a decade of transitioning to an electrified household, having clear and reliable information about incentives would have saved me many hours of research and eased some of my uncertainty. By overcoming these challenges and establishing a robust data exchange, the NODE Collective has the potential to revolutionize the way electrification incentives are accessed and utilized. Visit their website or their members’ websites to learn more about their ongoing efforts and how you can get involved in supporting a cleaner, electrified future.