My Journey from Home Performance Contractor to Energy Data Analytics

This is the story of my journey from home performance contractor to energy data analytics, and why OpenEE has changed its name to Recurve -- a name which may sound familiar to many of you.

In 2004, I founded an energy efficiency retrofit company called Sustainable Spaces after a stint in the solar industry. You could say I got the efficiency bug. Our goal, then as now, was to figure out how building owners could save energy and, in the process, help save the planet. 

At the time, efficiency was pretty straightforward. Insulation worked. Windows could usually be better sealed. LEDs for standard lighting were non-existent or astronomically expensive, but there were savings to be had by switching to CFLs. The grid, even in California, was still mostly fossil-fuel powered, which meant that saving energy at any time of day was good for the climate.

The focus was on building tools to help contractors make their businesses more efficient and scalable. However, we ran into serious headwinds. 

Utility programs that paid customers based on average deemed incentives sent exactly the wrong signal into the market. Contractors made the most money by doing the least they could get away with, as there was no accountability or value in savings that were delivered. To compensate, these programs were heavily regulated, leaving little room for innovation.

Sustainable Spaces started as a home performance contractor providing building science-based, whole house home retrofits. We rebranded to Recurve 1.0 as we began developing software tools to help home performance contractors streamline the performance upgrade process by taking the guesswork out of which measures to apply in given situations. 

My goal was always about achieving scale. Energy efficiency represents an enormous potential resource, but to achieve an impact that can help mitigate climate change, it has to grow by orders of magnitude.

The Recurve 1.0 software was way ahead of its time. Running simulations in the cloud, the platform leveraged tablet computing to enable contractors to audit, create a work scope and generate a proposal in one visit. Our efforts, I believe, helped push the energy efficiency industry forward. If you are interested, check out some of our old videos (including that time I audited Ellen Degeneres's house or that time I testified before Congress). Recurve was eventually sold to Tendril Networks. Its software was merged Tendril's platform and the name retired (or so everyone thought).

What I learned from being a contractor and trying to solve for the last mile in deploying energy efficiency is that the industry had much bigger problems that software for individual contractors couldn't solve. The fundamental economics were misaligned and undervalued. Doing low quality work, when paid on average in advance, was more profitable than investing in solutions that drive real results. 

The savings were also fundamentally undervalued, as homeowners and utilities had little confidence that savings were real or reliable, and often had no visibility into results until the very end of the process. Even then, the methods employed in evaluations were bespoke and generally useless as a means to improve implementations.

The problem is that conventional measurement and verification of savings is often obscured by complex, proprietary models, with results not available until months or even years after a retrofit happens. Without a standard "weights and measures" for what counts as efficiency, there are as many answers as analysts.

The logical answer is to move away from paying providers based on predetermined savings values for efficiency measures ("deemed" savings) and instead pay only for actual savings measured at the meter. 

But, how does one use meter data to consistently calculate savings in a way that is reliable and accurate, but also transparent and replicable by all parties? This was the challenge that I set out to solve in the next phase of my career. 

Working together with leading efficiency experts, data scientists and utility stakeholders, we led a stakeholder process to develop a set of empirically tested methods to standardize the way normalized meter-based changes in energy consumption are measured and reported. The CalTRACK process was created by a ruling of the CPUC, lead by PG&E, and funded by the CA IOUs. When CalTRACK is implemented through open source software such as the open source OpenEEmeter, these methods can be used to support the procurement of energy efficiency, electrification, and other distributed energy resources.

Our company, then called OpenEE, was proud to take the lead in developing the OpenEEmeter, a 100% open source software engine that runs the CalTRACK methods, originally funded by the CEC.

In order to function as a standard, the CalTRACK Methods and the OpenEEmeter open source code base must be available to all parties without restriction--measurement in a market cannot be a black box. 

While both CalTRACK and the OpenEEmeter have always been open source, we believed that they would best be served under the auspices of an organization that was dedicated to such projects, which is why we recently contributed these open source projects to Linux Foundation Energy (LFE). The Linux Foundation hosts many of the most important open source projects in the world, including Linux. By joining a community with more than 1,000 companies backing tens of thousands of active developers, our projects will now be able to harness the full power of the broader open source community to fuel innovation at unmatched speed and scale. 

Together, CalTRACK and the OpenEEmeter support procurement of energy efficiency, electrification, and other distributed energy resources, and are now being used as the basis for pay-for-performance efficiency in California, New York, Oregon, and other places.

But even as we worked on solutions that would streamline M&V and make performance-based efficiency possible, we knew we needed to address the other elephant in the efficiency room: the changing nature of the grid.

In the years since I founded Sustainable Spaces and Recurve 1.0, California, Texas and the Midwest began installing huge quantities of solar and wind. Deployment of these resources represents huge progress in the long-term goal of finally decarbonizing our economy.

But because they are intermittent, large amounts of solar and wind also cause problems for the grid by creating excess supply during times of the day when demand is low and falling off when demand is higher. This pattern is already creating large periods of negative pricing when there is literally nothing to do with all of the clean electrons on the grid. The standard answer to this problem is to add more storage. But storage is expensive, and there's no way deployment of batteries or EVs can keep pace with the load balancing needs of the grid due to the rapid rollout of renewable generation.

In theory, efficiency could be a complementary solution. But efficiency based on monthly average saving doesn't do anything to help manage the challenges of intermittent generation. In fact, saving energy at the wrong time could make grid problems worse, without doing anything to reduce our carbon footprints.

But we knew that if we could use AMI data to meter the hourly load-shape impacts of specific sets of interventions on portfolios of projects, we could help utilities identify those interventions that would be most valuable to meet their grid needs.

We call this hourly change in energy consumption the resource curve.

The resource curve allows utilities to procure exactly what they need to address load-shape problems. By breaking down “energy efficiency” into classes of projects that deliver more valuable resource curves, we can make savings worth more when they have the biggest impact, giving market players the tools and incentives they need to optimize their offerings to deliver the most valuable results to the grid and the best deal to customers.

As OpenEE, we were proud to develop the first standard, open source methods and tools for calculating behind-the-meter changes in demand. By extending those tools to encompass hourly methods, we were creating a way for utilities to procure long-term demand flexibility with enough confidence to begin treating it like a grid resource.

As Recurve we are excited about the future of a much broader range of behind the meter flexibility resources. 

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Recurve connects the dots between efficiency, electrification, renewable energy, and DERs to enable demand flexibility to become a market-based procurable resource. The transition is underway and accelerating.