The Energy Future is Smart: Grid-Interactive Efficient Buildings
It’s time to remake our buildings into a flexible energy resource.
Earlier this summer, the U.S. Department of Energy released a National Roadmap for grid-interactive efficient buildings, or GEBs. These ultra-smart buildings combine energy efficiency and demand flexibility with technologies and communications that enable greater affordability, comfort, productivity and high performance to our homes and commercial buildings.
In July, we were joined by roadmap authors Andy Satchwell of Berkeley Lab and Ryan Hledik of Brattle Group, alongside David Jacot of the LA Department of Water and Power and Kevin Powell of the GSA’s Green Proving Ground program.
Below is an excerpt of some of the key points our guests covered, edited for brevity and clarity. Watch the full webinar for more details.
LABBC Executive Director Dave Hodgins:
New acronym alert! GEBs—another word for smart buildings. We’re going to hear more about what this new term precisely means today. This comes at a time when we’re heading into the summer cooling season, another big wildfire season in front of us and, I hate to say, probably a drought. So our buildings need to be smart. We need to be turning our buildings into a resource.
Welcome guys!
Roadmap Co-author Ryan Hledik, Brattle Group:
Thank you, Dave, great to be here. We’re going to give a quick overview of the roadmap today. It’s a 150-page report, so we’re just going to talk through the highlights.
The first question that we want to answer here as we talk about GEBs is why do we want buildings to be more efficient and flexible? The answer to that question is: because buildings really have the capability to do a lot of the things that the grid needs today and will need in greater quantities in the future.
What is a grid-interactive efficient building? GEBs are energy efficient buildings that are connected, smart and flexible. They’re technology-based solutions that can communicate with each other, with the grid and with consumers to leverage sensors and controls to not just reduce energy use but to reduce use at the times when it’s most valuable to do so.
In creating the roadmap, we came up with an estimate that GEBs could save up to $18 billion per year in avoided power system costs by 2030, and looking out over 20 years, that could amount to between $100 billion and $200 billion in cost savings. Based on different assumptions about the extent to which GEB technologies are adopted, or the extent to which the power grid evolves over time, those value estimates can vary. But pretty much across the board, all the scenarios where we analyzed the benefits that we’re talking about here, the cost savings are significant.
We also wanted to look at what this can mean in terms of emissions reductions. There what we've estimated is that nationally GEBs could save about 80 million tons of carbon dioxide annually by 2030, which is about 6% of all power sector CO2 emissions, just through voluntary adoption of these measures among residential and commercial consumers. That's equivalent to retiring about 50 medium-sized coal plants or taking 17 million combustion engine light duty vehicles off the road.
A lot of these benefits that we've quantified sound like big numbers, but these are actually pretty conservative estimates, and there are several potential additional sources of value that GEBs could provide that could significantly increase these forecasts.
Roadmap Co-author Andy Satchwell:
One of the key pieces of GEBs in the field is really combining attributes of energy efficiency with demand flexibility capabilities. For example, something like network lighting controls, where you get efficiency gains for more efficient lighting, the controls allow you to use occupancy sensors and other controls to move that lighting load into times when the grid might need it.
We reached out to some building technology experts and tried to lay out some of the high opportunity technologies. Things like smart thermostats, automated window attachments and efficient and grid-connected water heaters are available today and can provide a significant piece of the demand flexibility opportunity. At the same time, there’s a whole host of technologies—exciting ones—that are in development. Thermal energy storage, for example, is a large opportunity for demand flexibility that’s still in development or being deployed in limited pilots.
Barriers for implementation of GEBs range from technology development, deployment, adoption and utilization. In thinking about development specific to building technologies and controls, for example, some often cited barriers include lack of standardization and interoperability, as well as nascent technology development around thermal storage that could provide some additional flexibility.
We should also recognize the fact that there’s regulation support and facilitation that kind of sits underneath all of this, related to the role that state and federal policy makers and regulators, as well as advocacy groups and researchers, play. Some of the barriers they face are status quo bias, or lack of solid information upon which to base their policy decisions.
Watch the webinar or read the complete roadmap for details on barriers and recommendations.
LADWP Director of Efficiency Solutions David Jacot:
In an emissions profile for California, residential and commercial buildings comprise 12% of on-site emissions, typically through natural gas use. Transportation, meanwhile, is 41%. In terms of the massive decarbonization efforts that really need to be made, buildings serve up an opportunity, but transportation is the big score. In Los Angeles, electrification is a big part of that.
We’ve looked at what it would take to electrify transportation and buildings, and it more than doubles our retail kilowatt hours, the amount of energy we sell. We generally retail about 24,000 gigawatt hours of electricity every year. Fully electrifying transportation and buildings takes us close to 60,000 gigawatt hours—and in fact maybe over 62,000. That’s 2.5 times as much energy as we retail today, so when we talk about decarbonizing our grid, we can’t just look at the static load we serve today. We have to look at the impacts of electrification as well.
In that spirit, LADWP and the City of LA commissioned NREL to create the LA100 Study. This study is a scenario analysis to identify multiple pathways to get to completely renewable, completely decarbonized electricity by 2035. It also identified what the cost of that might be, and it estimated the cost to be between $50 billion and $80 billion. Now that’s a big range. Turns out the lowest cost pathway depends heavily on energy efficiency, demand response and flexibility, on-site solar and storage, building electrification and electric vehicle chargers all eventually being integrated into grid-interactive efficient buildings.
Energy efficiency is foundational to all of it. It helps make everything else smaller in the system. So are the rest of the distributed energy resources. Then, when you tie them together to really make smart buildings—or GEBs as we’re calling them now—it really combines to push us to that $50 billion range, as opposed to the $80 billion range. For relatively modest investment in GEBs throughout our service territory, we can get to the low end of that significant investment range. In fact, we have identified that the rate impacts of this transition for the most part track with inflation. That’s significant.
GSA Green Proving Ground Director Kevin Powell:
GEBs hold a lot of benefit, not just to the grid operator, but to the facility owner as well. GSA is the landlord for the federal government, operating about 370 million square feet of space on 8,800 properties. That makes ours the single largest portfolio of commercial real estate in the U.S., so we have a lot of interest in how we manage that efficiently.
The Green Proving Ground program that I lead takes first-user risk for GSA, so we bridge the gap between great innovative ideas that have made it out of the lab and seem ready for full commercialization to that promised land of broad market adoption. We publish an RFI annually, and back in 2020 the topic was GEBs. We had 35 vendor teams that submitted technical proposals, 11 were selected as semifinalists and we selected three for testbed evaluation at GSA facilities. We’re about to kick off those test beds now, somewhat delayed because of COVID-19.
The three sites will take different approaches to the GEB model:
Occupancy-based GEB Platform: The first one here takes a holistic approach, operating buildings for the people in them. The idea here is that if you know in real time how many people are in the building, and where in the building they are, you can operate that building to provide for their best comfort and health. The secret sauce here is an extraordinary amount of interoperability and converging—in real time—of a lot of information. There’s all sorts of front-of-house data from air quality and light sensors to temperature and humidity sensors, with back-of-house data that tracks the real time performance of building equipment, as well as some outside information such as utility costs, weather and so on. Using machine learning technology, it applies machine learning to make increasingly better suggestions, where eventually the operator has sufficient confidence in these suggestions that they turn that entire supervisory control over to the software to do autonomously, within some well-defined parameters.
Gamified GEB Platform: This next approach is based on the idea that if you empower facility managers with data that will help them operate their facilities in a way that is more grid efficient and effective, and you track that according to some common metrics, that can foster an environment of friendly sporting competition with other facility operators. This approach is in some ways very low touch. It doesn’t require that supervisory control, but it empowers people to be working at their best.
Open Source GEB Platform: This last one you can think of as your personal assistant, or like a NEST thermostat on steroids. It’s easy to install with minimal up-front setup, it’s easy to interact with, and within a narrower band of data and control than the first one we saw, it essentially automates what you are already doing. It looks at what you override and learns from that, providing effective data visualization and reporting to demonstrate that you’re doing your job at your best. The developer’s hunch is that there will be a community that will add to the open source software this is built on and improve it.