ACEEE - Experts & Thought Leaders

The 887-page Project 2025 policy agenda for a conservative administration swings an axe at federal clean energy programs. The Heritage Foundation-led plan would repeal the Inflation Reduction Act and the Infrastructure Investment and Jobs Act and eliminate many Department of Energy programs. That includes efficiency tax credits, home energy rebates, industrial demonstrations, appliance standards, the entire Office of Energy Efficiency and Renewable Energy, ARPA-E research, loans for clean energy projects, and much more.  Project 2025 To pick one important example, while Project 2025 does not mention “weatherization” once, it says the whole “Office of State and Community Energy Programs . . . should be eliminated or reformed” (page 369). That office includes the Weatherization Assistance Program (WAP). The proposal echoes budgets President Trump proposed while in office, which would have also zeroed out WAP. Ending federal weatherization assistance would stop tens of thousands of low-income households annually from getting home improvements that lower their bills year after year while making homes safer and healthier. It would be a painful mistake. A proven program for reducing utility bills It funds and trains a network of CAPs around the country to implement the weatherization work Created in 1976 by a law signed by President Gerald Fold, WAP has improved the energy efficiency of more than 7 million homes of low-income families. It funds and trains a network of community action programs (CAPs) around the country to implement the weatherization work, either through contractors or their direct employees.  Reducing winter heating costs After an energy assessor identifies problems in a home, weatherization workers make needed improvements, such as sealing air leaks, adding insulation, and replacing old HVAC equipment. The improvements reduce winter heating costs (for gas, electricity, propane, or oil) and summer cooling costs (for electricity). Households that have been weatherized with the program's assistance save an average of $372 every year, according to a national laboratory evaluation. Safety and health Well-sealed home can maintain safe temperatures for days longer if heating or air-conditioning is lost Weatherization also protects safety and health. It helps residents keep their homes from getting dangerously cold or hot, and it reduces indoor allergens and irritants, including dust and mold. This reduces asthma rates, ER visits, medical costs, and missed work and school days. And with power outages from extreme weather becoming more frequent, a well-insulated, well-sealed home can maintain safe temperatures for days longer if heating or air-conditioning is lost, saving lives.  Basic home repairs In addition, many homes receive basic repairs, like mold remediation or fixes to leaking roofs, that are needed before energy work can begin (if the “pre-weatherization” is extensive, CAPs use other funds). More than 68,000 homes were weatherized through the program with federal funds in 2022, according to data from the National Association for State Community Services Programs. Program funding Terminating the central program in the Department of Energy would likely shut down the entire network The number of homes weatherized has varied significantly over the years based on funding; the 2021 Infrastructure Investment and Jobs Act provided a significant boost set to last across five years. Funding for the program comes from a combination of the Department of Energy, the federal Low Income Home Energy Assistance Program, states, and utilities. Terminating the central program in the Department of Energy would likely shut down the entire network. Weatherization improves lives For the families helped by WAP, the benefits are meaningful. Bennie Tillman Jr., of Athens, Georgia, said his house was drafty in the winter and expensive to cool in the summer. However, after contractors paid for by the weatherization program, added insulation, and sealed gaps, Tillman’s monthly bills in the hottest and coldest months were reduced by roughly $200. Or consider Nikia Pickett of Baltimore, whose young son experienced frequent asthma attacks. Weatherization helped significantly. “Not having the exposure to the outside elements and the things that trigger his asthma—those things significantly decreased his asthma attacks,” said Pickett. Weatherization has been attacked before Both chambers of Congress advanced appropriations bills largely maintaining or increasing funding President Trump proposed four budgets that would have eliminated funding for WAP. However, both chambers of Congress advanced appropriations bills largely maintaining or increasing funding for the program, and over the four years increased the program’s funding by 27% in real dollars. Trump administration delays in the implementation of weatherization funding received bipartisan rebukes. Eliminating WAP would require congressional action. But Trump has previously attempted to impound funds to withhold dollars allocated by Congress in several areas, and some powerful conservative voices are calling for him to do so again more widely if he is elected in November. More weatherization funding, not less, is needed The next presidential administration and Congress should increase funding for weatherization, not cut or shrink a program with a strong record of reducing costs for American families. WAP’s budget is small compared to the task at hand. About 30% of households meet the program's income requirements; many have high energy bills, drafty homes with poor insulation and old heating and cooling equipment, or members with asthma. It is easy to casually suggest eliminating a federal program. For a family that sees its energy bill reduced by hundreds of dollars year after year because of weatherization or has a child with asthma who can breathe well again, it is no small matter.

Regulators in Massachusetts recently approved a utility’s plan to offer households with heat pumps a lower electric rate during the winter and to offer a further discounted rate for low-income households. This approach from Unitil, which serves a small portion of the commonwealth, should be improved upon and replicated across the country as regulators consider similar proposals from other utilities.   principles and goals  To maximize benefits for energy-burdened households and the entire electric system, utilities, and their regulators should consider several broad principles and goals as they consider new rates to support heat pumps:  Maintain a price signal for efficient heating, especially during times of peak demand;   Limit participation to households with heat pumps;  Reduce energy burdens for low-income households; and  Get efficient heat pumps for low-income households.  Opportunities to improve differing rate proposals  With typical electric rates, households that use heat pumps for winter heating are often being overcharged The actual cost of distributing electricity to households is usually lower in the winter, in part because utilities build their systems to meet the highest electric demands, which are most often on hot summer days. With typical electric rates, households that use heat pumps for winter heating are often being overcharged relative to their costs to the electric system.  Lower volumetric distribution rate Unitil’s plan, approved late last month, will offer households with heat pumps a significantly lower volumetric distribution rate, the distribution cost per amount of electricity used during the winter months. The company will offset some of that rate reduction with a slightly higher fixed charge each month, but a household using a heat pump for space heating will still save a lot of money, potentially hundreds of dollars a year. Unitil will also offer participating low-income households a further 40% discount on that rate.  Electric space heating rate Under National Grid’s proposal, low-income households wouldn’t be able to apply for a discount  National Grid, another Massachusetts utility, took a different approach for its proposed optional rate, eliminating the volumetric distribution rate in favor of a fixed charge for any participating household, regardless of the heating source. Under National Grid’s proposal, low-income households wouldn’t be able to apply a discount if they chose that rate option. In Minnesota, Xcel also has proposed an electric space heating rate. Like Unitil, Xcel is proposing a lower volumetric rate in the winter, but it would vary the rate based on the time of day and automatically apply a discount for low-income households.  new rates lines How each proposal for new rates lines up with the four principles above has significantly influenced support or opposition: nobody commented in opposition to Xcel’s proposal in Minnesota, Unitil’s proposal received support from the Massachusetts Department of Energy Resources, but National Grid’s proposal has been opposed by many stakeholders in the Commonwealth. Evaluating the three proposals based on the four principles listed above, it becomes clear why the Unitil and Xcel plans were better received than National Grid’s plan:   Maintain a price signal for efficient heating, especially during times of peak demand. While there is usually plenty of room for new electric demand in the winter, that doesn’t mean we should incentivize inefficient use and waste. Unitil’s proposal would reduce the volumetric rate without eliminating it, helping maintain a price signal for efficient electricity consumption. Xcel goes even further in the right direction, adjusting rates upward during times of high electricity demand and downward when there’s less electricity use (known as a “time of use” rate), providing an incentive for shifting use away from the most expensive hours of the day. National Grid’s proposal to charge a flat distribution fee regardless of consumption does not maintain that price signal.  Limit participation to households with heat pumps. Not all electric heating is efficient—heat pumps are, but electric resistance is not. Utilities should limit participation in electric heating rates to households that have a heat pump. This is where Unitil’s proposal is the best of the lot. Xcel’s would enable participation for any electric space heating, not just heat pumps, which could incentivize inefficient electric resistance heating. National Grid’s proposal also moves in the wrong direction, enabling participation by any household regardless of heating fuel, a recipe for simply subsidizing inefficient electric use.  Reduce energy burdens for low-income households. Too many households are struggling to afford their energy bills, often with disastrous consequences. Any rate design proposal should lower energy burdens for low-income households. Unfortunately, National Grid wouldn’t allow any low-income household participating in its proposed optional rate to also receive a discount for energy assistance. This contributed to vigorous stakeholder opposition to its proposal. Again, Unitil’s proposal was better, allowing low-income households to participate in the heat pump rate and receive the 40% discount on top of that. Xcel’s proposal has one even better feature: applying the discount for energy assistance automatically for all eligible low-income households, to keep energy burdens below 4%. Get efficient heat pumps for low-income households. Admittedly this last principle isn’t rate design, but it is equally important and intertwined. If only wealthier households are adding heat pumps, then a reduced winter electric rate for households with heat pumps will be regressive, with lower-income households paying higher rates. So any heat pump rate has to be paired with a robust program to fund the installation of efficient heat pumps for low-income households. Those low-income households with heat pumps should automatically be given the heat pump rate and energy assistance to ensure their overall energy burden doesn’t increase.   efficient and affordable electric heating The recent proposals in Massachusetts and Minnesota are among the earliest for new optional rates to account for the differing costs and benefits of electric heating, but they won’t be the last. The Colorado legislature has mandated a proposal from utilities to encourage heat pump adoption in coming years, and more states are expected to do the same. The early proposals offer important lessons for other utilities and state regulators on the right and wrong, ways to encourage efficient and affordable electric heating. 

Artificial intelligence will either add to the burden on their already-strained electrical grid or people can use it to solve their most complex demand optimization problems, paving the way to a secure energy future. The choice is theirs. It is encouraging to see American homes, vehicles, and new industrial facilities moving away from fossil fuels in favor of clean electricity. A less welcome trend is the rapid growth in electricity demand that the power grid is unprepared for. The proliferation of data centers to meet the growing demand for artificial intelligence (AI) is exacerbating this problem. AI offers enormous potential to advance knowledge Everyone’s daily digital lives depend on energy-intensive computing power. When working in the cloud, shopping online, streaming TV, using social media, or calling a ride, electricity is used. AI models are among the most energy-hungry digital processes seen in decades. AI offers enormous potential to advance knowledge and convenience, and accelerate the digitalization of modern cities, buildings, transportation, farms, and factories. It can also help keep the electricity supply affordable and reliable, even as demand surges. Accelerate advanced clean electricity technologies Building more generation and transmission capacity alone cannot resolve the new energy crisis Companies like Google and Microsoft/Open AI are leveraging their procurement power to accelerate advanced clean electricity technologies. Similar efforts have primarily focused on supply-side solutions, such as wind and solar in the immediate future, and eventually advanced nuclear, enhanced geothermal, hydrogen, and long-term storage. These are worthy initiatives, but building more generation and transmission capacity alone cannot resolve the new energy crisis, at least not within the limited time left for to combat climate change. All these innovative technologies won’t be widely adopted for decades. In the meantime, the grid will continue to strain under the power demands of AI, electric vehicles, and other electric equipment and devices in a more connected world. The solution: optimize demand and never waste an electron Data centers use massive amounts of energy to train and sustain the large language models that enable AI. Energy use by these data centers is already skyrocketing, compounding the strain on an electrical grid ill-equipped to handle the ever-growing electricity demands. Nevertheless, AI may be the best hope of solving these problems. How? By optimizing both the timing of energy use and the type of energy used. When renewable sources like solar are at their peak, people should do their most energy-intensive work and optimize energy storage. Otherwise, that extra clean energy is curtailed to maintain the power supply and demand balance. For example, in 2023, 2.6 million megawatt hours of utility-scale wind and solar output were curtailed in California - clean energy that could have powered nearly 380,000 California households for that same year. Energy efficiency remains the most affordable energy source Energy efficiency has remained the most affordable, fastest-to-deploy energy resource for decades Energy efficiency has remained the most affordable, fastest-to-deploy energy resource for decades. Increasing the efficiency of the entire electricity system can reduce the need for additional transmission and distribution build out. Given competing demands on the grid - buildings, transportation, industry - continuously improving system efficiency is an optimization problem of almost infinite complexity; it has too many variables for even a large team of brilliant human engineers to handle. AI can help solve complex energy optimization problems This is where AI comes in: it can accelerate the capabilities of the human intellect, harnessing the power of the best available digital technologies. It can learn how to solve complex energy optimization problems and scale that learning so that less energy is wasted and there is optimum use of available resources. Although the electrical grid is strained during peak demand (e.g., hot summer afternoons), most of the time the actually utilization is less than 50% of the grid capacity (including generation, transmission, and distribution). AI could help balance this uneven demand daily, seasonally, and annually, giving more reliable electricity and reducing carbon emissions by using renewable energy when it has the greatest benefit. AI-powered platform that plans logistics Picture an AI system that dynamically adjusts the speed of manufacturing production lines to align with periods of clean, low-cost electricity, while meeting delivery deadlines. Envision an AI-powered platform that plans logistics, minimizing energy consumption while ensuring timely delivery of goods. Imagine an AI-assisted building management system that accounts for local energy generation and consumption patterns, while anticipating building occupants’ activities and needs. AI can help all electric customers charge and discharge their energy storage at the most opportune times, maximizing values for their investments and benefits for the grid.  Bridging the technology-behavior gap is vital for optimization As machine learning, the engine behind today’s AI, gained prominence across various disciplines several years ago As machine learning, the engine behind today’s AI, gained prominence across various disciplines several years ago, the concept of ‘smart’ solutions for energy and sustainability also proliferated: smart grids, smart cities, smart buildings, smart manufacturing, smart devices, and more. The promise of these technologies was immense. In practice, many of these smart solutions have yet to meet expectations. Their underperformance often stems from a fundamental disconnect between technology and human behavior. While these solutions are technically sophisticated, they usually fail to account for the complexities of human decision-making. For example, a smart thermostat offers a convenient way to set indoor temperatures lower at night or when occupants are away. However, that thermostat is not intelligent enough to coordinate energy use with other home devices or other buildings in a neighborhood - which may result in a higher peak-time energy demand for the local utility network. Can smart solutions be intelligent in a human sense In contrast, a simple text alert – ‘Turn off or reduce nonessential power if health allows, now until 9pm’ - from the California Governor’s Office reduced power demand by 1,200 megawatts within minutes to avoid blackouts on a sweltering day in 2022. That text harnessed real human intelligence (and arguably emotion).  In other words, the machines can learn, but they don’t learn like humans. The new devices may seem ‘dumb’ because they don’t fully align with human intuition or adapt to their behavior. Can AI bridge this gap and truly make these smart solutions intelligent in a human sense? AI’s potential to handle immense complexity is a reason to be optimistic. Harnessing AI’s potential to ease the energy transition will require intervention and collaboration With their capacity for intelligent decision-making and advanced data processing and analytics, AI-based tools could revolutionize demand-side solutions by minimizing energy waste without compromising comfort or convenience. However, without intentional policy support, AI investments may prioritize applications that cater to individual consumer interests or encourage people to buy more and consume more, which may exacerbate the energy and climate crises and deepen environmental and social inequities. Blockchain Look at blockchain, a technology with transformative potential to benefit society Look at blockchain, a technology with transformative potential to benefit society that has largely been used for energy-intensive cryptomining. Let’s not let the same thing happen with AI. For instance, some AI tools can enhance building renderings or let occupants view a future building through augmented reality. AI tools may replace architects and engineers one day to reduce labor costs. But instead of focusing on (or fearing) replacement, there is a need to incentivize software companies to create AI tools that assist engineers in producing the most efficient and adaptable design solutions - and they can best do this by collaborating with - i.e., learning from - design professionals. Such solutions minimize energy and material usage, while ensuring that buildings meet evolving societal needs. AI applications in transportation Similarly, AI applications in transportation have predominantly focused on developing autonomous vehicles. Replacing human drivers with machines may benefit some groups, but AI would be more beneficial for nearly everyone if it were used to - i.e., taught to - reduce traffic congestion (travel time and fuel consumption) and ease mobility. AI solutions can revolutionize shipping and logistics by optimizing freight and last-mile deliveries based on multiple factors, including vehicle capacities, charging schedules, and delivery timelines. AI has potential to enhance effectiveness of smart solutions AI holds the potential to enhance the effectiveness of smart solutions to optimize energy demand, enhance grid reliability, and accelerate an equitable clean energy transition. It is essential to steer AI development toward solutions that contribute positively to energy efficiency, sustainability, and resilience. This requires proactive policy measures, collaborative partnerships, and a shared commitment to leveraging AI for the collective benefit of society and the planet. While AI is creating a tremendous energy demand challenge, it also holds the key to reducing energy demand far beyond its consumption - but only if it is taught to do so.