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    Methane research takes on new urgency at MIT

    One of the most notable climate change provisions in the 2022 Inflation Reduction Act is the first U.S. federal tax on a greenhouse gas (GHG). That the fee targets methane (CH4), rather than carbon dioxide (CO2), emissions is indicative of the urgency the scientific community has placed on reducing this short-lived but powerful gas. Methane persists in the air about 12 years — compared to more than 1,000 years for CO2 — yet it immediately causes about 120 times more warming upon release. The gas is responsible for at least a quarter of today’s gross warming. 

    “Methane has a disproportionate effect on near-term warming,” says Desiree Plata, the director of MIT Methane Network. “CH4 does more damage than CO2 no matter how long you run the clock. By removing methane, we could potentially avoid critical climate tipping points.” 

    Because GHGs have a runaway effect on climate, reductions made now will have a far greater impact than the same reductions made in the future. Cutting methane emissions will slow the thawing of permafrost, which could otherwise lead to massive methane releases, as well as reduce increasing emissions from wetlands.  

    “The goal of MIT Methane Network is to reduce methane emissions by 45 percent by 2030, which would save up to 0.5 degree C of warming by 2100,” says Plata, an associate professor of civil and environmental engineering at MIT and director of the Plata Lab. “When you consider that governments are trying for a 1.5-degree reduction of all GHGs by 2100, this is a big deal.” 

    Under normal concentrations, methane, like CO2, poses no health risks. Yet methane assists in the creation of high levels of ozone. In the lower atmosphere, ozone is a key component of air pollution, which leads to “higher rates of asthma and increased emergency room visits,” says Plata. 

    Methane-related projects at the Plata Lab include a filter made of zeolite — the same clay-like material used in cat litter — designed to convert methane into CO2 at dairy farms and coal mines. At first glance, the technology would appear to be a bit of a hard sell, since it converts one GHG into another. Yet the zeolite filter’s low carbon and dollar costs, combined with the disproportionate warming impact of methane, make it a potential game-changer.

    The sense of urgency about methane has been amplified by recent studies that show humans are generating far more methane emissions than previously estimated, and that the rates are rising rapidly. Exactly how much methane is in the air is uncertain. Current methods for measuring atmospheric methane, such as ground, drone, and satellite sensors, “are not readily abundant and do not always agree with each other,” says Plata.  

    The Plata Lab is collaborating with Tim Swager in the MIT Department of Chemistry to develop low-cost methane sensors. “We are developing chemiresisitive sensors that cost about a dollar that you could place near energy infrastructure to back-calculate where leaks are coming from,” says Plata.  

    The researchers are working on improving the accuracy of the sensors using machine learning techniques and are planning to integrate internet-of-things technology to transmit alerts. Plata and Swager are not alone in focusing on data collection: the Inflation Reduction Act adds significant funding for methane sensor research. 

    Other research at the Plata Lab includes the development of nanomaterials and heterogeneous catalysis techniques for environmental applications. The lab also explores mitigation solutions for industrial waste, particularly those related to the energy transition. Plata is the co-founder of an lithium-ion battery recycling startup called Nth Cycle. 

    On a more fundamental level, the Plata Lab is exploring how to develop products with environmental and social sustainability in mind. “Our overarching mission is to change the way that we invent materials and processes so that environmental objectives are incorporated along with traditional performance and cost metrics,” says Plata. “It is important to do that rigorous assessment early in the design process.”

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    MIT amps up methane research 

    The MIT Methane Network brings together 26 researchers from MIT along with representatives of other institutions “that are dedicated to the idea that we can reduce methane levels in our lifetime,” says Plata. The organization supports research such as Plata’s zeolite and sensor projects, as well as designing pipeline-fixing robots, developing methane-based fuels for clean hydrogen, and researching the capture and conversion of methane into liquid chemical precursors for pharmaceuticals and plastics. Other members are researching policies to encourage more sustainable agriculture and land use, as well as methane-related social justice initiatives. 

    “Methane is an especially difficult problem because it comes from all over the place,” says Plata. A recent Global Carbon Project study estimated that half of methane emissions are caused by humans. This is led by waste and agriculture (28 percent), including cow and sheep belching, rice paddies, and landfills.  

    Fossil fuels represent 18 percent of the total budget. Of this, about 63 percent is derived from oil and gas production and pipelines, 33 percent from coal mining activities, and 5 percent from industry and transportation. Human-caused biomass burning, primarily from slash-and-burn agriculture, emits about 4 percent of the global total.  

    The other half of the methane budget includes natural methane emissions from wetlands (20 percent) and other natural sources (30 percent). The latter includes permafrost melting and natural biomass burning, such as forest fires started by lightning.  

    With increases in global warming and population, the line between anthropogenic and natural causes is getting fuzzier. “Human activities are accelerating natural emissions,” says Plata. “Climate change increases the release of methane from wetlands and permafrost and leads to larger forest and peat fires.”  

    The calculations can get complicated. For example, wetlands provide benefits from CO2 capture, biological diversity, and sea level rise resiliency that more than compensate for methane releases. Meanwhile, draining swamps for development increases emissions. 

    Over 100 nations have signed onto the U.N.’s Global Methane Pledge to reduce at least 30 percent of anthropogenic emissions within the next 10 years. The U.N. report estimates that this goal can be achieved using proven technologies and that about 60 percent of these reductions can be accomplished at low cost. 

    Much of the savings would come from greater efficiencies in fossil fuel extraction, processing, and delivery. The methane fees in the Inflation Reduction Act are primarily focused on encouraging fossil fuel companies to accelerate ongoing efforts to cap old wells, flare off excess emissions, and tighten pipeline connections.  

    Fossil fuel companies have already made far greater pledges to reduce methane than they have with CO2, which is central to their business. This is due, in part, to the potential savings, as well as in preparation for methane regulations expected from the Environmental Protection Agency in late 2022. The regulations build upon existing EPA oversight of drilling operations, and will likely be exempt from the U.S. Supreme Court’s ruling that limits the federal government’s ability to regulate GHGs. 

    Zeolite filter targets methane in dairy and coal 

    The “low-hanging fruit” of gas stream mitigation addresses most of the 20 percent of total methane emissions in which the gas is released in sufficiently high concentrations for flaring. Plata’s zeolite filter aims to address the thornier challenge of reducing the 80 percent of non-flammable dilute emissions. 

    Plata found inspiration in decades-old catalysis research for turning methane into methanol. One strategy has been to use an abundant, low-cost aluminosilicate clay called zeolite.  

    “The methanol creation process is challenging because you need to separate a liquid, and it has very low efficiency,” says Plata. “Yet zeolite can be very efficient at converting methane into CO2, and it is much easier because it does not require liquid separation. Converting methane to CO2 sounds like a bad thing, but there is a major anti-warming benefit. And because methane is much more dilute than CO2, the relative CO2 contribution is minuscule.”  

    Using zeolite to create methanol requires highly concentrated methane, high temperatures and pressures, and industrial processing conditions. Yet Plata’s process, which dopes the zeolite with copper, operates in the presence of oxygen at much lower temperatures under typical pressures. “We let the methane proceed the way it wants from a thermodynamic perspective from methane to methanol down to CO2,” says Plata. 

    Researchers around the world are working on other dilute methane removal technologies. Projects include spraying iron salt aerosols into sea air where they react with natural chlorine or bromine radicals, thereby capturing methane. Most of these geoengineering solutions, however, are difficult to measure and would require massive scale to make a difference.  

    Plata is focusing her zeolite filters on environments where concentrations are high, but not so high as to be flammable. “We are trying to scale zeolite into filters that you could snap onto the side of a cross-ventilation fan in a dairy barn or in a ventilation air shaft in a coal mine,” says Plata. “For every packet of air we bring in, we take a lot of methane out, so we get more bang for our buck.”  

    The major challenge is creating a filter that can handle high flow rates without getting clogged or falling apart. Dairy barn air handlers can push air at up to 5,000 cubic feet per minute and coal mine handlers can approach 500,000 CFM. 

    Plata is exploring engineering options including fluidized bed reactors with floating catalyst particles. Another filter solution, based in part on catalytic converters, features “higher-order geometric structures where you have a porous material with a long path length where the gas can interact with the catalyst,” says Plata. “This avoids the challenge with fluidized beds of containing catalyst particles in the reactor. Instead, they are fixed within a structured material.”  

    Competing technologies for removing methane from mine shafts “operate at temperatures of 1,000 to 1,200 degrees C, requiring a lot of energy and risking explosion,” says Plata. “Our technology avoids safety concerns by operating at 300 to 400 degrees C. It reduces energy use and provides more tractable deployment costs.” 

    Potentially, energy and dollar costs could be further reduced in coal mines by capturing the heat generated by the conversion process. “In coal mines, you have enrichments above a half-percent methane, but below the 4 percent flammability threshold,” says Plata. “The excess heat from the process could be used to generate electricity using off-the-shelf converters.” 

    Plata’s dairy barn research is funded by the Gerstner Family Foundation and the coal mining project by the U.S. Department of Energy. “The DOE would like us to spin out the technology for scale-up within three years,” says Plata. “We cannot guarantee we will hit that goal, but we are trying to develop this as quickly as possible. Our society needs to start reducing methane emissions now.”  More

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    Processing waste biomass to reduce airborne emissions

    To prepare fields for planting, farmers the world over often burn corn stalks, rice husks, hay, straw, and other waste left behind from the previous harvest. In many places, the practice creates huge seasonal clouds of smog, contributing to air pollution that kills 7 million people globally a year, according to the World Health Organization.

    Annually, $120 billion worth of crop and forest residues are burned in the open worldwide — a major waste of resources in an energy-starved world, says Kevin Kung SM ’13, PhD ’17. Kung is working to transform this waste biomass into marketable products — and capitalize on a billion-dollar global market — through his MIT spinoff company, Takachar.

    Founded in 2015, Takachar develops small-scale, low-cost, portable equipment to convert waste biomass into solid fuel using a variety of thermochemical treatments, including one known as oxygen-lean torrefaction. The technology emerged from Kung’s PhD project in the lab of Ahmed Ghoniem, the Ronald C. Crane (1972) Professor of Mechanical Engineering at MIT.

    Biomass fuels, including wood, peat, and animal dung, are a major source of carbon emissions — but billions of people rely on such fuels for cooking, heating, and other household needs. “Currently, burning biomass generates 10 percent of the primary energy used worldwide, and the process is used largely in rural, energy-poor communities. We’re not going to change that overnight. There are places with no other sources of energy,” Ghoniem says.

    What Takachar’s technology provides is a way to use biomass more cleanly and efficiently by concentrating the fuel and eliminating contaminants such as moisture and dirt, thus creating a “clean-burning” fuel — one that generates less smoke. “In rural communities where biomass is used extensively as a primary energy source, torrefaction will address air pollution head-on,” Ghoniem says.

    Thermochemical treatment densifies biomass at elevated temperatures, converting plant materials that are typically loose, wet, and bulky into compact charcoal. Centralized processing plants exist, but collection and transportation present major barriers to utilization, Kung says. Takachar’s solution moves processing into the field: To date, Takachar has worked with about 5,500 farmers to process 9,000 metric tons of crops.

    Takachar estimates its technology has the potential to reduce carbon dioxide equivalent emissions by gigatons per year at scale. (“Carbon dioxide equivalent” is a measure used to gauge global warming potential.) In recognition, in 2021 Takachar won the first-ever Earthshot Prize in the clean air category, a £1 million prize funded by Prince William and Princess Kate’s Royal Foundation.

    Roots in Kenya

    As Kung tells the story, Takachar emerged from a class project that took him to Kenya — which explains the company’s name, a combination of takataka, which mean “trash” in Swahili, and char, for the charcoal end product.

    It was 2011, and Kung was at MIT as a biological engineering grad student focused on cancer research. But “MIT gives students big latitude for exploration, and I took courses outside my department,” he says. In spring 2011, he signed up for a class known as 15.966 (Global Health Delivery Lab) in the MIT Sloan School of Management. The class brought Kung to Kenya to work with a nongovernmental organization in Nairobi’s Kibera, the largest urban slum in Africa.

    “We interviewed slum households for their views on health, and that’s when I noticed the charcoal problem,” Kung says. The problem, as Kung describes it, was that charcoal was everywhere in Kibera — piled up outside, traded by the road, and used as the primary fuel, even indoors. Its creation contributed to deforestation, and its smoke presented a serious health hazard.

    Eager to address this challenge, Kung secured fellowship support from the MIT International Development Initiative and the Priscilla King Gray Public Service Center to conduct more research in Kenya. In 2012, he formed Takachar as a team and received seed money from the MIT IDEAS Global Challenge, MIT Legatum Center for Development and Entrepreneurship, and D-Lab to produce charcoal from household organic waste. (This work also led to a fertilizer company, Safi Organics, that Kung founded in 2016 with the help of MIT IDEAS. But that is another story.)

    Meanwhile, Kung had another top priority: finding a topic for his PhD dissertation. Back at MIT, he met Alexander Slocum, the Walter M. May and A. Hazel May Professor of Mechanical Engineering, who on a long walk-and-talk along the Charles River suggested he turn his Kenya work into a thesis. Slocum connected him with Robert Stoner, deputy director for science and technology at the MIT Energy Initiative (MITEI) and founding director of MITEI’s Tata Center for Technology and Design. Stoner in turn introduced Kung to Ghoniem, who became his PhD advisor, while Slocum and Stoner joined his doctoral committee.

    Roots in MIT lab

    Ghoniem’s telling of the Takachar story begins, not surprisingly, in the lab. Back in 2010, he had a master’s student interested in renewable energy, and he suggested the student investigate biomass. That student, Richard Bates ’10, SM ’12, PhD ’16, began exploring the science of converting biomass to more clean-burning charcoal through torrefaction.

    Most torrefaction (also known as low-temperature pyrolysis) systems use external heating sources, but the lab’s goal, Ghoniem explains, was to develop an efficient, self-sustained reactor that would generate fewer emissions. “We needed to understand the chemistry and physics of the process, and develop fundamental scaling models, before going to the lab to build the device,” he says.

    By the time Kung joined the lab in 2013, Ghoniem was working with the Tata Center to identify technology suitable for developing countries and largely based on renewable energy. Kung was able to secure a Tata Fellowship and — building on Bates’ research — develop the small-scale, practical device for biomass thermochemical conversion in the field that launched Takachar.

    This device, which was patented by MIT with inventors Kung, Ghoniem, Stoner, MIT research scientist Santosh Shanbhogue, and Slocum, is self-contained and scalable. It burns a little of the biomass to generate heat; this heat bakes the rest of the biomass, releasing gases; the system then introduces air to enable these gases to combust, which burns off the volatiles and generates more heat, keeping the thermochemical reaction going.

    “The trick is how to introduce the right amount of air at the right location to sustain the process,” Ghoniem explains. “If you put in more air, that will burn the biomass. If you put in less, there won’t be enough heat to produce the charcoal. That will stop the reaction.”

    About 10 percent of the biomass is used as fuel to support the reaction, Kung says, adding that “90 percent is densified into a form that’s easier to handle and utilize.” He notes that the research received financial support from the Abdul Latif Jameel Water and Food Systems Lab and the Deshpande Center for Technological Innovation, both at MIT. Sonal Thengane, another postdoc in Ghoniem’s lab, participated in the effort to scale up the technology at the MIT Bates Lab (no relation to Richard Bates).

    The charcoal produced is more valuable per ton and easier to transport and sell than biomass, reducing transportation costs by two-thirds and giving farmers an additional income opportunity — and an incentive not to burn agricultural waste, Kung says. “There’s more income for farmers, and you get better air quality.”

    Roots in India

    When Kung became a Tata Fellow, he joined a program founded to take on the biggest challenges of the developing world, with a focus on India. According to Stoner, Tata Fellows, including Kung, typically visit India twice a year and spend six to eight weeks meeting stakeholders in industry, the government, and in communities to gain perspective on their areas of study.

    “A unique part of Tata is that you’re considering the ecosystem as a whole,” says Kung, who interviewed hundreds of smallholder farmers, met with truck drivers, and visited existing biomass processing plants during his Tata trips to India. (Along the way, he also connected with Indian engineer Vidyut Mohan, who became Takachar’s co-founder.)

    “It was very important for Kevin to be there walking about, experimenting, and interviewing farmers,” Stoner says. “He learned about the lives of farmers.”

    These experiences helped instill in Kung an appreciation for small farmers that still drives him today as Takachar rolls out its first pilot programs, tinkers with the technology, grows its team (now up to 10), and endeavors to build a revenue stream. So, while Takachar has gotten a lot of attention and accolades — from the IDEAS award to the Earthshot Prize — Kung says what motivates him is the prospect of improving people’s lives.

    The dream, he says, is to empower communities to help both the planet and themselves. “We’re excited about the environmental justice perspective,” he says. “Our work brings production and carbon removal or avoidance to rural communities — providing them with a way to convert waste, make money, and reduce air pollution.”

    This article appears in the Spring 2022 issue of Energy Futures, the magazine of the MIT Energy Initiative. More

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    New England renewables + Canadian hydropower

    The urgent need to cut carbon emissions has prompted a growing number of U.S. states to commit to achieving 100 percent clean electricity by 2040 or 2050. But figuring out how to meet those commitments and still have a reliable and affordable power system is a challenge. Wind and solar installations will form the backbone of a carbon-free power system, but what technologies can meet electricity demand when those intermittent renewable sources are not adequate?

    In general, the options being discussed include nuclear power, natural gas with carbon capture and storage (CCS), and energy storage technologies such as new and improved batteries and chemical storage in the form of hydrogen. But in the northeastern United States, there is one more possibility being proposed: electricity imported from hydropower plants in the neighboring Canadian province of Quebec.

    The proposition makes sense. Those plants can produce as much electricity as about 40 large nuclear power plants, and some power generated in Quebec already comes to the Northeast. So, there could be abundant additional supply to fill any shortfall when New England’s intermittent renewables underproduce. However, U.S. wind and solar investors view Canadian hydropower as a competitor and argue that reliance on foreign supply discourages further U.S. investment.

    Two years ago, three researchers affiliated with the MIT Center for Energy and Environmental Policy Research (CEEPR) — Emil Dimanchev SM ’18, now a PhD candidate at the Norwegian University of Science and Technology; Joshua Hodge, CEEPR’s executive director; and John Parsons, a senior lecturer in the MIT Sloan School of Management — began wondering whether viewing Canadian hydro as another source of electricity might be too narrow. “Hydropower is a more-than-hundred-year-old technology, and plants are already built up north,” says Dimanchev. “We might not need to build something new. We might just need to use those plants differently or to a greater extent.”

    So the researchers decided to examine the potential role and economic value of Quebec’s hydropower resource in a future low-carbon system in New England. Their goal was to help inform policymakers, utility decision-makers, and others about how best to incorporate Canadian hydropower into their plans and to determine how much time and money New England should spend to integrate more hydropower into its system. What they found out was surprising, even to them.

    The analytical methods

    To explore possible roles for Canadian hydropower to play in New England’s power system, the MIT researchers first needed to predict how the regional power system might look in 2050 — both the resources in place and how they would be operated, given any policy constraints. To perform that analysis, they used GenX, a modeling tool originally developed by Jesse Jenkins SM ’14, PhD ’18 and Nestor Sepulveda SM ’16, PhD ’20 while they were researchers at the MIT Energy Initiative (MITEI).

    The GenX model is designed to support decision-making related to power system investment and real-time operation and to examine the impacts of possible policy initiatives on those decisions. Given information on current and future technologies — different kinds of power plants, energy storage technologies, and so on — GenX calculates the combination of equipment and operating conditions that can meet a defined future demand at the lowest cost. The GenX modeling tool can also incorporate specified policy constraints, such as limits on carbon emissions.

    For their study, Dimanchev, Hodge, and Parsons set parameters in the GenX model using data and assumptions derived from a variety of sources to build a representation of the interconnected power systems in New England, New York, and Quebec. (They included New York to account for that state’s existing demand on the Canadian hydro resources.) For data on the available hydropower, they turned to Hydro-Québec, the public utility that owns and operates most of the hydropower plants in Quebec.

    It’s standard in such analyses to include real-world engineering constraints on equipment, such as how quickly certain power plants can be ramped up and down. With help from Hydro-Québec, the researchers also put hour-to-hour operating constraints on the hydropower resource.

    Most of Hydro-Québec’s plants are “reservoir hydropower” systems. In them, when power isn’t needed, the flow on a river is restrained by a dam downstream of a reservoir, and the reservoir fills up. When power is needed, the dam is opened, and the water in the reservoir runs through downstream pipes, turning turbines and generating electricity. Proper management of such a system requires adhering to certain operating constraints. For example, to prevent flooding, reservoirs must not be allowed to overfill — especially prior to spring snowmelt. And generation can’t be increased too quickly because a sudden flood of water could erode the river edges or disrupt fishing or water quality.

    Based on projections from the National Renewable Energy Laboratory and elsewhere, the researchers specified electricity demand for every hour of the year 2050, and the model calculated the cost-optimal mix of technologies and system operating regime that would satisfy that hourly demand, including the dispatch of the Hydro-Québec hydropower system. In addition, the model determined how electricity would be traded among New England, New York, and Quebec.

    Effects of decarbonization limits on technology mix and electricity trading

    To examine the impact of the emissions-reduction mandates in the New England states, the researchers ran the model assuming reductions in carbon emissions between 80 percent and 100 percent relative to 1990 levels. The results of those runs show that, as emissions limits get more stringent, New England uses more wind and solar and extends the lifetime of its existing nuclear plants. To balance the intermittency of the renewables, the region uses natural gas plants, demand-side management, battery storage (modeled as lithium-ion batteries), and trading with Quebec’s hydropower-based system. Meanwhile, the optimal mix in Quebec is mostly composed of existing hydro generation. Some solar is added, but new reservoirs are built only if renewable costs are assumed to be very high.

    The most significant — and perhaps surprising — outcome is that in all the scenarios, the hydropower-based system of Quebec is not only an exporter but also an importer of electricity, with the direction of flow on the Quebec-New England transmission lines changing over time.

    Historically, energy has always flowed from Quebec to New England. The model results for 2018 show electricity flowing from north to south, with the quantity capped by the current transmission capacity limit of 2,225 megawatts (MW).

    An analysis for 2050, assuming that New England decarbonizes 90 percent and the capacity of the transmission lines remains the same, finds electricity flows going both ways. Flows from north to south still dominate. But for nearly 3,500 of the 8,760 hours of the year, electricity flows in the opposite direction — from New England to Quebec. And for more than 2,200 of those hours, the flow going north is at the maximum the transmission lines can carry.

    The direction of flow is motivated by economics. When renewable generation is abundant in New England, prices are low, and it’s cheaper for Quebec to import electricity from New England and conserve water in its reservoirs. Conversely, when New England’s renewables are scarce and prices are high, New England imports hydro-generated electricity from Quebec.

    So rather than delivering electricity, Canadian hydro provides a means of storing the electricity generated by the intermittent renewables in New England.

    “We see this in our modeling because when we tell the model to meet electricity demand using these resources, the model decides that it is cost-optimal to use the reservoirs to store energy rather than anything else,” says Dimanchev. “We should be sending the energy back and forth, so the reservoirs in Quebec are in essence a battery that we use to store some of the electricity produced by our intermittent renewables and discharge it when we need it.”

    Given that outcome, the researchers decided to explore the impact of expanding the transmission capacity between New England and Quebec. Building transmission lines is always contentious, but what would be the impact if it could be done?

    Their model results shows that when transmission capacity is increased from 2,225 MW to 6,225 MW, flows in both directions are greater, and in both cases the flow is at the new maximum for more than 1,000 hours.

    Results of the analysis thus confirm that the economic response to expanded transmission capacity is more two-way trading. To continue the battery analogy, more transmission capacity to and from Quebec effectively increases the rate at which the battery can be charged and discharged.

    Effects of two-way trading on the energy mix

    What impact would the advent of two-way trading have on the mix of energy-generating sources in New England and Quebec in 2050?

    Assuming current transmission capacity, in New England, the change from one-way to two-way trading increases both wind and solar power generation and to a lesser extent nuclear; it also decreases the use of natural gas with CCS. The hydro reservoirs in Canada can provide long-duration storage — over weeks, months, and even seasons — so there is less need for natural gas with CCS to cover any gaps in supply. The level of imports is slightly lower, but now there are also exports. Meanwhile, in Quebec, two-way trading reduces solar power generation, and the use of wind disappears. Exports are roughly the same, but now there are imports as well. Thus, two-way trading reallocates renewables from Quebec to New England, where it’s more economical to install and operate solar and wind systems.

    Another analysis examined the impact on the energy mix of assuming two-way trading plus expanded transmission capacity. For New England, greater transmission capacity allows wind, solar, and nuclear to expand further; natural gas with CCS all but disappears; and both imports and exports increase significantly. In Quebec, solar decreases still further, and both exports and imports of electricity increase.

    Those results assume that the New England power system decarbonizes by 99 percent in 2050 relative to 1990 levels. But at 90 percent and even 80 percent decarbonization levels, the model concludes that natural gas capacity decreases with the addition of new transmission relative to the current transmission scenario. Existing plants are retired, and new plants are not built as they are no longer economically justified. Since natural gas plants are the only source of carbon emissions in the 2050 energy system, the researchers conclude that the greater access to hydro reservoirs made possible by expanded transmission would accelerate the decarbonization of the electricity system.

    Effects of transmission changes on costs

    The researchers also explored how two-way trading with expanded transmission capacity would affect costs in New England and Quebec, assuming 99 percent decarbonization in New England. New England’s savings on fixed costs (investments in new equipment) are largely due to a decreased need to invest in more natural gas with CCS, and its savings on variable costs (operating costs) are due to a reduced need to run those plants. Quebec’s savings on fixed costs come from a reduced need to invest in solar generation. The increase in cost — borne by New England — reflects the construction and operation of the increased transmission capacity. The net benefit for the region is substantial.

    Thus, the analysis shows that everyone wins as transmission capacity increases — and the benefit grows as the decarbonization target tightens. At 99 percent decarbonization, the overall New England-Quebec region pays about $21 per megawatt-hour (MWh) of electricity with today’s transmission capacity but only $18/MWh with expanded transmission. Assuming 100 percent reduction in carbon emissions, the region pays $29/MWh with current transmission capacity and only $22/MWh with expanded transmission.

    Addressing misconceptions

    These results shed light on several misconceptions that policymakers, supporters of renewable energy, and others tend to have.

    The first misconception is that the New England renewables and Canadian hydropower are competitors. The modeling results instead show that they’re complementary. When the power systems in New England and Quebec work together as an integrated system, the Canadian reservoirs are used part of the time to store the renewable electricity. And with more access to hydropower storage in Quebec, there’s generally more renewable investment in New England.

    The second misconception arises when policymakers refer to Canadian hydro as a “baseload resource,” which implies a dependable source of electricity — particularly one that supplies power all the time. “Our study shows that by viewing Canadian hydropower as a baseload source of electricity — or indeed a source of electricity at all — you’re not taking full advantage of what that resource can provide,” says Dimanchev. “What we show is that Quebec’s reservoir hydro can provide storage, specifically for wind and solar. It’s a solution to the intermittency problem that we foresee in carbon-free power systems for 2050.”

    While the MIT analysis focuses on New England and Quebec, the researchers believe that their results may have wider implications. As power systems in many regions expand production of renewables, the value of storage grows. Some hydropower systems have storage capacity that has not yet been fully utilized and could be a good complement to renewable generation. Taking advantage of that capacity can lower the cost of deep decarbonization and help move some regions toward a decarbonized supply of electricity.

    This research was funded by the MIT Center for Energy and Environmental Policy Research, which is supported in part by a consortium of industry and government associates.

    This article appears in the Autumn 2021 issue of Energy Futures, the magazine of the MIT Energy Initiative. More

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    Pricing carbon, valuing people

    In November, inflation hit a 39-year high in the United States. The consumer price index was up 6.8 percent from the previous year due to major increases in the cost of rent, food, motor vehicles, gasoline, and other common household expenses. While inflation impacts the entire country, its effects are not felt equally. At greatest risk are low- and middle-income Americans who may lack sufficient financial reserves to absorb such economic shocks.

    Meanwhile, scientists, economists, and activists across the political spectrum continue to advocate for another potential systemic economic change that many fear will also put lower-income Americans at risk: the imposition of a national carbon price, fee, or tax. Framed by proponents as the most efficient and cost-effective way to reduce greenhouse gas emissions and meet climate targets, a carbon penalty would incentivize producers and consumers to shift expenditures away from carbon-intensive products and services (e.g., coal or natural gas-generated electricity) and toward low-carbon alternatives (e.g., 100 percent renewable electricity). But if not implemented in a way that takes differences in household income into account, this policy strategy, like inflation, could place an unequal and untenable economic burden on low- and middle-income Americans.         

    To garner support from policymakers, carbon-penalty proponents have advocated for policies that recycle revenues from carbon penalties to all or lower-income taxpayers in the form of payroll tax reductions or lump-sum payments. And yet some of these proposed policies run the risk of reducing the overall efficiency of the U.S. economy, which would lower the nation’s GDP and impede its economic growth.

    Which begs the question: Is there a sweet spot at which a national carbon-penalty revenue-recycling policy can both avoid inflicting economic harm on lower-income Americans at the household level and degrading economic efficiency at the national level?

    In search of that sweet spot, researchers at the MIT Joint Program on the Science and Policy of Global Change assess the economic impacts of four different carbon-penalty revenue-recycling policies: direct rebates from revenues to households via lump-sum transfers; indirect refunding of revenues to households via a proportional reduction in payroll taxes; direct rebates from revenues to households, but only for low- and middle-income groups, with remaining revenues recycled via a proportional reduction in payroll taxes; and direct, higher rebates for poor households, with remaining revenues recycled via a proportional reduction in payroll taxes.

    To perform the assessment, the Joint Program researchers integrate a U.S. economic model (MIT U.S. Regional Energy Policy) with a dataset (Bureau of Labor Statistics’ Consumer Expenditure Survey) providing consumption patterns and other socioeconomic characteristics for 15,000 U.S. households. Using the combined model, they evaluate the distributional impacts and potential trade-offs between economic equity and efficiency of all four carbon-penalty revenue-recycling policies.

    The researchers find that household rebates have progressive impacts on consumers’ financial well-being, with the greatest benefits going to the lowest-income households, while policies centered on improving the efficiency of the economy (e.g., payroll tax reductions) have slightly regressive household-level financial impacts. In a nutshell, the trade-off is between rebates that provide more equity and less economic efficiency versus tax cuts that deliver the opposite result. The latter two policy options, which combine rebates to lower-income households with payroll tax reductions, result in an optimal blend of sufficiently progressive financial results at the household level and economy efficiency at the national level. Results of the study are published in the journal Energy Economics.

    “We have determined that only a portion of carbon-tax revenues is needed to compensate low-income households and thus reduce inequality, while the rest can be used to improve the economy by reducing payroll or other distortionary taxes,” says Xaquin García-Muros, lead author of the study, a postdoc at the MIT Joint Program who is affiliated with the Basque Centre for Climate Change in Spain. “Therefore, we can eliminate potential trade-offs between efficiency and equity, and promote a just and efficient energy transition.”

    “If climate policies increase the gap between rich and poor households or reduce the affordability of energy services, then these policies might be rejected by the public and, as a result, attempts to decarbonize the economy will be less efficient,” says Joint Program Deputy Director Sergey Paltsev, a co-author of the study. “Our findings provide guidance to decision-makers to advance more well-designed policies that deliver economic benefits to the nation as a whole.” 

    The study’s novel integration of a national economic model with household microdata creates a new and powerful platform to further investigate key differences among households that can help inform policies aimed at a just transition to a low-carbon economy. More

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    An energy-storage solution that flows like soft-serve ice cream

    Batteries made from an electrically conductive mixture the consistency of molasses could help solve a critical piece of the decarbonization puzzle. An interdisciplinary team from MIT has found that an electrochemical technology called a semisolid flow battery can be a cost-competitive form of energy storage and backup for variable renewable energy (VRE) sources such as wind and solar. The group’s research is described in a paper published in Joule.

    “The transition to clean energy requires energy storage systems of different durations for when the sun isn’t shining and the wind isn’t blowing,” says Emre Gençer, a research scientist with the MIT Energy Initiative (MITEI) and a member of the team. “Our work demonstrates that a semisolid flow battery could be a lifesaving as well as economical option when these VRE sources can’t generate power for a day or longer — in the case of natural disasters, for instance.”

    The rechargeable zinc-manganese dioxide (Zn-MnO2) battery the researchers created beat out other long-duration energy storage contenders. “We performed a comprehensive, bottom-up analysis to understand how the battery’s composition affects performance and cost, looking at all the trade-offs,” says Thaneer Malai Narayanan SM ’18, PhD ’21. “We showed that our system can be cheaper than others, and can be scaled up.”

    Narayanan, who conducted this work at MIT as part of his doctorate in mechanical engineering, is the lead author of the paper. Additional authors include Gençer, Yunguang Zhu, a postdoc in the MIT Electrochemical Energy Lab; Gareth McKinley, the School of Engineering Professor of Teaching Innovation and professor of mechanical engineering at MIT; and Yang Shao-Horn, the JR East Professor of Engineering, a professor of mechanical engineering and of materials science and engineering, and a member of the Research Laboratory of Electronics (RLE), who directs the MIT Electrochemical Energy Lab.

    Going with the flow

    In 2016, Narayanan began his graduate studies, joining the Electrochemical Energy Lab, a hotbed of research and exploration of solutions to mitigate climate change, which is centered on innovative battery chemistry and decarbonizing fuels and chemicals. One exciting opportunity for the lab: developing low- and no-carbon backup energy systems suitable for grid-scale needs when VRE generation flags.                                                  

    While the lab cast a wide net, investigating energy conversion and storage using solid oxide fuel cells, lithium-ion batteries, and metal-air batteries, among others, Narayanan took a particular interest in flow batteries. In these systems, two different chemical (electrolyte) solutions with either negative or positive ions are pumped from separate tanks, meeting across a membrane (called the stack). Here, the ion streams react, converting electrical energy to chemical energy — in effect, charging the battery. When there is demand for this stored energy, the solution gets pumped back to the stack to convert chemical energy into electrical energy again.

    The duration of time that flow batteries can discharge, releasing the stored electricity, is determined by the volume of positively and negatively charged electrolyte solutions streaming through the stack. In theory, as long as these solutions keep flowing, reacting, and converting the chemical energy to electrical energy, the battery systems can provide electricity.

    “For backup lasting more than a day, the architecture of flow batteries suggests they can be a cheap option,” says Narayanan. “You recharge the solution in the tanks from sun and wind power sources.” This renders the entire system carbon free.

    But while the promise of flow battery technologies has beckoned for at least a decade, the uneven performance and expense of materials required for these battery systems has slowed their implementation. So, Narayanan set out on an ambitious journey: to design and build a flow battery that could back up VRE systems for a day or more, storing and discharging energy with the same or greater efficiency than backup rivals; and to determine, through rigorous cost analysis, whether such a system could prove economically viable as a long-duration energy option.

    Multidisciplinary collaborators

    To attack this multipronged challenge, Narayanan’s project brought together, in his words, “three giants, scientists all well-known in their fields”:  Shao-Horn, who specializes in chemical physics and electrochemical science, and design of materials; Gençer, who creates detailed economic models of emergent energy systems at MITEI; and McKinley, an expert in rheology, the physics of flow. These three also served as his thesis advisors.

    “I was excited to work in such an interdisciplinary team, which offered a unique opportunity to create a novel battery architecture by designing charge transfer and ion transport within flowable semi-solid electrodes, and to guide battery engineering using techno-economics of such flowable batteries,” says Shao-Horn.

    While other flow battery systems in contention, such as the vanadium redox flow battery, offer the storage capacity and energy density to back up megawatt and larger power systems, they depend on expensive chemical ingredients that make them bad bets for long duration purposes. Narayanan was on the hunt for less-pricey chemical components that also feature rich energy potential.

    Through a series of bench experiments, the researchers came up with a novel electrode (electrical conductor) for the battery system: a mixture containing dispersed manganese dioxide (MnO2) particles, shot through with an electrically conductive additive, carbon black. This compound reacts with a conductive zinc solution or zinc plate at the stack, enabling efficient electrochemical energy conversion. The fluid properties of this battery are far removed from the watery solutions used by other flow batteries.

    “It’s a semisolid — a slurry,” says Narayanan. “Like thick, black paint, or perhaps a soft-serve ice cream,” suggests McKinley. The carbon black adds the pigment and the electric punch. To arrive at the optimal electrochemical mix, the researchers tweaked their formula many times.

    “These systems have to be able to flow under reasonable pressures, but also have a weak yield stress so that the active MnO2 particles don’t sink to the bottom of the flow tanks when the system isn’t being used, as well as not separate into a battery/oily clear fluid phase and a dense paste of carbon particles and MnO2,” says McKinley.

    This series of experiments informed the technoeconomic analysis. By “connecting the dots between composition, performance, and cost,” says Narayanan, he and Gençer were able to make system-level cost and efficiency calculations for the Zn-MnO2 battery.

    “Assessing the cost and performance of early technologies is very difficult, and this was an example of how to develop a standard method to help researchers at MIT and elsewhere,” says Gençer. “One message here is that when you include the cost analysis at the development stage of your experimental work, you get an important early understanding of your project’s cost implications.”

    In their final round of studies, Gençer and Narayanan compared the Zn-MnO2 battery to a set of equivalent electrochemical battery and hydrogen backup systems, looking at the capital costs of running them at durations of eight, 24, and 72 hours. Their findings surprised them: For battery discharges longer than a day, their semisolid flow battery beat out lithium-ion batteries and vanadium redox flow batteries. This was true even when factoring in the heavy expense of pumping the MnO2 slurry from tank to stack. “I was skeptical, and not expecting this battery would be competitive, but once I did the cost calculation, it was plausible,” says Gençer.

    But carbon-free battery backup is a very Goldilocks-like business: Different situations require different-duration solutions, whether an anticipated overnight loss of solar power, or a longer-term, climate-based disruption in the grid. “Lithium-ion is great for backup of eight hours and under, but the materials are too expensive for longer periods,” says Gençer. “Hydrogen is super expensive for very short durations, and good for very long durations, and we will need all of them.” This means it makes sense to continue working on the Zn-MnO2 system to see where it might fit in.

    “The next step is to take our battery system and build it up,” says Narayanan, who is working now as a battery engineer. “Our research also points the way to other chemistries that could be developed under the semi-solid flow battery platform, so we could be seeing this kind of technology used for energy storage in our lifetimes.”

    This research was supported by Eni S.p.A. through MITEI. Thaneer Malai Narayanan received an Eni-sponsored MIT Energy Fellowship during his work on the project. More

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    Design’s new frontier

    In the 1960s, the advent of computer-aided design (CAD) sparked a revolution in design. For his PhD thesis in 1963, MIT Professor Ivan Sutherland developed Sketchpad, a game-changing software program that enabled users to draw, move, and resize shapes on a computer. Over the course of the next few decades, CAD software reshaped how everything from consumer products to buildings and airplanes were designed.

    “CAD was part of the first wave in computing in design. The ability of researchers and practitioners to represent and model designs using computers was a major breakthrough and still is one of the biggest outcomes of design research, in my opinion,” says Maria Yang, Gail E. Kendall Professor and director of MIT’s Ideation Lab.

    Innovations in 3D printing during the 1980s and 1990s expanded CAD’s capabilities beyond traditional injection molding and casting methods, providing designers even more flexibility. Designers could sketch, ideate, and develop prototypes or models faster and more efficiently. Meanwhile, with the push of a button, software like that developed by Professor Emeritus David Gossard of MIT’s CAD Lab could solve equations simultaneously to produce a new geometry on the fly.

    In recent years, mechanical engineers have expanded the computing tools they use to ideate, design, and prototype. More sophisticated algorithms and the explosion of machine learning and artificial intelligence technologies have sparked a second revolution in design engineering.

    Researchers and faculty at MIT’s Department of Mechanical Engineering are utilizing these technologies to re-imagine how the products, systems, and infrastructures we use are designed. These researchers are at the forefront of the new frontier in design.

    Computational design

    Faez Ahmed wants to reinvent the wheel, or at least the bicycle wheel. He and his team at MIT’s Design Computation & Digital Engineering Lab (DeCoDE) use an artificial intelligence-driven design method that can generate entirely novel and improved designs for a range of products — including the traditional bicycle. They create advanced computational methods to blend human-driven design with simulation-based design.

    “The focus of our DeCoDE lab is computational design. We are looking at how we can create machine learning and AI algorithms to help us discover new designs that are optimized based on specific performance parameters,” says Ahmed, an assistant professor of mechanical engineering at MIT.

    For their work using AI-driven design for bicycles, Ahmed and his collaborator Professor Daniel Frey wanted to make it easier to design customizable bicycles, and by extension, encourage more people to use bicycles over transportation methods that emit greenhouse gases.

    To start, the group gathered a dataset of 4,500 bicycle designs. Using this massive dataset, they tested the limits of what machine learning could do. First, they developed algorithms to group bicycles that looked similar together and explore the design space. They then created machine learning models that could successfully predict what components are key in identifying a bicycle style, such as a road bike versus a mountain bike.

    Once the algorithms were good enough at identifying bicycle designs and parts, the team proposed novel machine learning tools that could use this data to create a unique and creative design for a bicycle based on certain performance parameters and rider dimensions.

    Ahmed used a generative adversarial network — or GAN — as the basis of this model. GAN models utilize neural networks that can create new designs based on vast amounts of data. However, using GAN models alone would result in homogeneous designs that lack novelty and can’t be assessed in terms of performance. To address these issues in design problems, Ahmed has developed a new method which he calls “PaDGAN,” performance augmented diverse GAN.

    “When we apply this type of model, what we see is that we can get large improvements in the diversity, quality, as well as novelty of the designs,” Ahmed explains.

    Using this approach, Ahmed’s team developed an open-source computational design tool for bicycles freely available on their lab website. They hope to further develop a set of generalizable tools that can be used across industries and products.

    Longer term, Ahmed has his sights set on loftier goals. He hopes the computational design tools he develops could lead to “design democratization,” putting more power in the hands of the end user.

    “With these algorithms, you can have more individualization where the algorithm assists a customer in understanding their needs and helps them create a product that satisfies their exact requirements,” he adds.

    Using algorithms to democratize the design process is a goal shared by Stefanie Mueller, an associate professor in electrical engineering and computer science and mechanical engineering.

    Personal fabrication

    Platforms like Instagram give users the freedom to instantly edit their photographs or videos using filters. In one click, users can alter the palette, tone, and brightness of their content by applying filters that range from bold colors to sepia-toned or black-and-white. Mueller, X-Window Consortium Career Development Professor, wants to bring this concept of the Instagram filter to the physical world.

    “We want to explore how digital capabilities can be applied to tangible objects. Our goal is to bring reprogrammable appearance to the physical world,” explains Mueller, director of the HCI Engineering Group based out of MIT’s Computer Science and Artificial Intelligence Laboratory.

    Mueller’s team utilizes a combination of smart materials, optics, and computation to advance personal fabrication technologies that would allow end users to alter the design and appearance of the products they own. They tested this concept in a project they dubbed “Photo-Chromeleon.”

    First, a mix of photochromic cyan, magenta, and yellow dies are airbrushed onto an object — in this instance, a 3D sculpture of a chameleon. Using software they developed, the team sketches the exact color pattern they want to achieve on the object itself. An ultraviolet light shines on the object to activate the dyes.

    To actually create the physical pattern on the object, Mueller has developed an optimization algorithm to use alongside a normal office projector outfitted with red, green, and blue LED lights. These lights shine on specific pixels on the object for a given period of time to physically change the makeup of the photochromic pigments.

    “This fancy algorithm tells us exactly how long we have to shine the red, green, and blue light on every single pixel of an object to get the exact pattern we’ve programmed in our software,” says Mueller.

    Giving this freedom to the end user enables limitless possibilities. Mueller’s team has applied this technology to iPhone cases, shoes, and even cars. In the case of shoes, Mueller envisions a shoebox embedded with UV and LED light projectors. Users could put their shoes in the box overnight and the next day have a pair of shoes in a completely new pattern.

    Mueller wants to expand her personal fabrication methods to the clothes we wear. Rather than utilize the light projection technique developed in the PhotoChromeleon project, her team is exploring the possibility of weaving LEDs directly into clothing fibers, allowing people to change their shirt’s appearance as they wear it. These personal fabrication technologies could completely alter consumer habits.

    “It’s very interesting for me to think about how these computational techniques will change product design on a high level,” adds Mueller. “In the future, a consumer could buy a blank iPhone case and update the design on a weekly or daily basis.”

    Computational fluid dynamics and participatory design

    Another team of mechanical engineers, including Sili Deng, the Brit (1961) & Alex (1949) d’Arbeloff Career Development Professor, are developing a different kind of design tool that could have a large impact on individuals in low- and middle-income countries across the world.

    As Deng walked down the hallway of Building 1 on MIT’s campus, a monitor playing a video caught her eye. The video featured work done by mechanical engineers and MIT D-Lab on developing cleaner burning briquettes for cookstoves in Uganda. Deng immediately knew she wanted to get involved.

    “As a combustion scientist, I’ve always wanted to work on such a tangible real-world problem, but the field of combustion tends to focus more heavily on the academic side of things,” explains Deng.

    After reaching out to colleagues in MIT D-Lab, Deng joined a collaborative effort to develop a new cookstove design tool for the 3 billion people across the world who burn solid fuels to cook and heat their homes. These stoves often emit soot and carbon monoxide, leading not only to millions of deaths each year, but also worsening the world’s greenhouse gas emission problem.

    The team is taking a three-pronged approach to developing this solution, using a combination of participatory design, physical modeling, and experimental validation to create a tool that will lead to the production of high-performing, low-cost energy products.

    Deng and her team in the Deng Energy and Nanotechnology Group use physics-based modeling for the combustion and emission process in cookstoves.

    “My team is focused on computational fluid dynamics. We use computational and numerical studies to understand the flow field where the fuel is burned and releases heat,” says Deng.

    These flow mechanics are crucial to understanding how to minimize heat loss and make cookstoves more efficient, as well as learning how dangerous pollutants are formed and released in the process.

    Using computational methods, Deng’s team performs three-dimensional simulations of the complex chemistry and transport coupling at play in the combustion and emission processes. They then use these simulations to build a combustion model for how fuel is burned and a pollution model that predicts carbon monoxide emissions.

    Deng’s models are used by a group led by Daniel Sweeney in MIT D-Lab to test the experimental validation in prototypes of stoves. Finally, Professor Maria Yang uses participatory design methods to integrate user feedback, ensuring the design tool can actually be used by people across the world.

    The end goal for this collaborative team is to not only provide local manufacturers with a prototype they could produce themselves, but to also provide them with a tool that can tweak the design based on local needs and available materials.

    Deng sees wide-ranging applications for the computational fluid dynamics her team is developing.

    “We see an opportunity to use physics-based modeling, augmented with a machine learning approach, to come up with chemical models for practical fuels that help us better understand combustion. Therefore, we can design new methods to minimize carbon emissions,” she adds.

    While Deng is utilizing simulations and machine learning at the molecular level to improve designs, others are taking a more macro approach.

    Designing intelligent systems

    When it comes to intelligent design, Navid Azizan thinks big. He hopes to help create future intelligent systems that are capable of making decisions autonomously by using the enormous amounts of data emerging from the physical world. From smart robots and autonomous vehicles to smart power grids and smart cities, Azizan focuses on the analysis, design, and control of intelligent systems.

    Achieving such massive feats takes a truly interdisciplinary approach that draws upon various fields such as machine learning, dynamical systems, control, optimization, statistics, and network science, among others.

    “Developing intelligent systems is a multifaceted problem, and it really requires a confluence of disciplines,” says Azizan, assistant professor of mechanical engineering with a dual appointment in MIT’s Institute for Data, Systems, and Society (IDSS). “To create such systems, we need to go beyond standard approaches to machine learning, such as those commonly used in computer vision, and devise algorithms that can enable safe, efficient, real-time decision-making for physical systems.”

    For robot control to work in the complex dynamic environments that arise in the real world, real-time adaptation is key. If, for example, an autonomous vehicle is going to drive in icy conditions or a drone is operating in windy conditions, they need to be able to adapt to their new environment quickly.

    To address this challenge, Azizan and his collaborators at MIT and Stanford University have developed a new algorithm that combines adaptive control, a powerful methodology from control theory, with meta learning, a new machine learning paradigm.

    “This ‘control-oriented’ learning approach outperforms the existing ‘regression-oriented’ methods, which are mostly focused on just fitting the data, by a wide margin,” says Azizan.

    Another critical aspect of deploying machine learning algorithms in physical systems that Azizan and his team hope to address is safety. Deep neural networks are a crucial part of autonomous systems. They are used for interpreting complex visual inputs and making data-driven predictions of future behavior in real time. However, Azizan urges caution.

    “These deep neural networks are only as good as their training data, and their predictions can often be untrustworthy in scenarios not covered by their training data,” he says. Making decisions based on such untrustworthy predictions could lead to fatal accidents in autonomous vehicles or other safety-critical systems.

    To avoid these potentially catastrophic events, Azizan proposes that it is imperative to equip neural networks with a measure of their uncertainty. When the uncertainty is high, they can then be switched to a “safe policy.”

    In pursuit of this goal, Azizan and his collaborators have developed a new algorithm known as SCOD — Sketching Curvature of Out-of-Distribution Detection. This framework could be embedded within any deep neural network to equip them with a measure of their uncertainty.

    “This algorithm is model-agnostic and can be applied to neural networks used in various kinds of autonomous systems, whether it’s drones, vehicles, or robots,” says Azizan.

    Azizan hopes to continue working on algorithms for even larger-scale systems. He and his team are designing efficient algorithms to better control supply and demand in smart energy grids. According to Azizan, even if we create the most efficient solar panels and batteries, we can never achieve a sustainable grid powered by renewable resources without the right control mechanisms.

    Mechanical engineers like Ahmed, Mueller, Deng, and Azizan serve as the key to realizing the next revolution of computing in design.

    “MechE is in a unique position at the intersection of the computational and physical worlds,” Azizan says. “Mechanical engineers build a bridge between theoretical, algorithmic tools and real, physical world applications.”

    Sophisticated computational tools, coupled with the ground truth mechanical engineers have in the physical world, could unlock limitless possibilities for design engineering, well beyond what could have been imagined in those early days of CAD. More

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    Coupling power and hydrogen sector pathways to benefit decarbonization

    Governments and companies worldwide are increasing their investments in hydrogen research and development, indicating a growing recognition that hydrogen could play a significant role in meeting global energy system decarbonization goals. Since hydrogen is light, energy-dense, storable, and produces no direct carbon dioxide emissions at the point of use, this versatile energy carrier has the potential to be harnessed in a variety of ways in a future clean energy system.

    Often considered in the context of grid-scale energy storage, hydrogen has garnered renewed interest, in part due to expectations that our future electric grid will be dominated by variable renewable energy (VRE) sources such as wind and solar, as well as decreasing costs for water electrolyzers — both of which could make clean, “green” hydrogen more cost-competitive with fossil-fuel-based production. But hydrogen’s versatility as a clean energy fuel also makes it an attractive option to meet energy demand and to open pathways for decarbonization in hard-to-abate sectors where direct electrification is difficult, such as transportation, buildings, and industry.

    “We’ve seen a lot of progress and analysis around pathways to decarbonize electricity, but we may not be able to electrify all end uses. This means that just decarbonizing electricity supply is not sufficient, and we must develop other decarbonization strategies as well,” says Dharik Mallapragada, a research scientist at the MIT Energy Initiative (MITEI). “Hydrogen is an interesting energy carrier to explore, but understanding the role for hydrogen requires us to study the interactions between the electricity system and a future hydrogen supply chain.”

    In a recent paper, researchers from MIT and Shell present a framework to systematically study the role and impact of hydrogen-based technology pathways in a future low-carbon, integrated energy system, taking into account interactions with the electric grid and the spatio-temporal variations in energy demand and supply. The developed framework co-optimizes infrastructure investment and operation across the electricity and hydrogen supply chain under various emissions price scenarios. When applied to a Northeast U.S. case study, the researchers find this approach results in substantial benefits — in terms of costs and emissions reduction — as it takes advantage of hydrogen’s potential to provide the electricity system with a large flexible load when produced through electrolysis, while also enabling decarbonization of difficult-to-electrify, end-use sectors.

    The research team includes Mallapragada; Guannan He, a postdoc at MITEI; Abhishek Bose, a graduate research assistant at MITEI; Clara Heuberger-Austin, a researcher at Shell; and Emre Gençer, a research scientist at MITEI. Their findings are published in the journal Energy & Environmental Science.

    Cross-sector modeling

    “We need a cross-sector framework to analyze each energy carrier’s economics and role across multiple systems if we are to really understand the cost/benefits of direct electrification or other decarbonization strategies,” says He.

    To do that analysis, the team developed the Decision Optimization of Low-carbon Power-HYdrogen Network (DOLPHYN) model, which allows the user to study the role of hydrogen in low-carbon energy systems, the effects of coupling the power and hydrogen sectors, and the trade-offs between various technology options across both supply chains — spanning production, transport, storage, and end use, and their impact on decarbonization goals.

    “We are seeing great interest from industry and government, because they are all asking questions about where to invest their money and how to prioritize their decarbonization strategies,” says Gençer. Heuberger-Austin adds, “Being able to assess the system-level interactions between electricity and the emerging hydrogen economy is of paramount importance to drive technology development and support strategic value chain decisions. The DOLPHYN model can be instrumental in tackling those kinds of questions.”

    For a predefined set of electricity and hydrogen demand scenarios, the model determines the least-cost technology mix across the power and hydrogen sectors while adhering to a variety of operation and policy constraints. The model can incorporate a range of technology options — from VRE generation to carbon capture and storage (CCS) used with both power and hydrogen generation to trucks and pipelines used for hydrogen transport. With its flexible structure, the model can be readily adapted to represent emerging technology options and evaluate their long-term value to the energy system.

    As an important addition, the model takes into account process-level carbon emissions by allowing the user to add a cost penalty on emissions in both sectors. “If you have a limited emissions budget, we are able to explore the question of where to prioritize the limited emissions to get the best bang for your buck in terms of decarbonization,” says Mallapragada.

    Insights from a case study

    To test their model, the researchers investigated the Northeast U.S. energy system under a variety of demand, technology, and carbon price scenarios. While their major conclusions can be generalized for other regions, the Northeast proved to be a particularly interesting case study. This region has current legislation and regulatory support for renewable generation, as well as increasing emission-reduction targets, a number of which are quite stringent. It also has a high demand for energy for heating — a sector that is difficult to electrify and could particularly benefit from hydrogen and from coupling the power and hydrogen systems.

    The researchers find that when combining the power and hydrogen sectors through electrolysis or hydrogen-based power generation, there is more operational flexibility to support VRE integration in the power sector and a reduced need for alternative grid-balancing supply-side resources such as battery storage or dispatchable gas generation, which in turn reduces the overall system cost. This increased VRE penetration also leads to a reduction in emissions compared to scenarios without sector-coupling. “The flexibility that electricity-based hydrogen production provides in terms of balancing the grid is as important as the hydrogen it is going to produce for decarbonizing other end uses,” says Mallapragada. They found this type of grid interaction to be more favorable than conventional hydrogen-based electricity storage, which can incur additional capital costs and efficiency losses when converting hydrogen back to power. This suggests that the role of hydrogen in the grid could be more beneficial as a source of flexible demand than as storage.

    The researchers’ multi-sector modeling approach also highlighted that CCS is more cost-effective when utilized in the hydrogen supply chain, versus the power sector. They note that counter to this observation, by the end of the decade, six times more CCS projects will be deployed in the power sector than for use in hydrogen production — a fact that emphasizes the need for more cross-sectoral modeling when planning future energy systems.

    In this study, the researchers tested the robustness of their conclusions against a number of factors, such as how the inclusion of non-combustion greenhouse gas emissions (including methane emissions) from natural gas used in power and hydrogen production impacts the model outcomes. They find that including the upstream emissions footprint of natural gas within the model boundary does not impact the value of sector coupling in regards to VRE integration and cost savings for decarbonization; in fact, the value actually grows because of the increased emphasis on electricity-based hydrogen production over natural gas-based pathways.

    “You cannot achieve climate targets unless you take a holistic approach,” says Gençer. “This is a systems problem. There are sectors that you cannot decarbonize with electrification, and there are other sectors that you cannot decarbonize without carbon capture, and if you think about everything together, there is a synergistic solution that significantly minimizes the infrastructure costs.”

    This research was supported, in part, by Shell Global Solutions International B.V. in Amsterdam, the Netherlands, and MITEI’s Low-Carbon Energy Centers for Electric Power Systems and Carbon Capture, Utilization, and Storage. More

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    Making the case for hydrogen in a zero-carbon economy

    As the United States races to achieve its goal of zero-carbon electricity generation by 2035, energy providers are swiftly ramping up renewable resources such as solar and wind. But because these technologies churn out electrons only when the sun shines and the wind blows, they need backup from other energy sources, especially during seasons of high electric demand. Currently, plants burning fossil fuels, primarily natural gas, fill in the gaps.

    “As we move to more and more renewable penetration, this intermittency will make a greater impact on the electric power system,” says Emre Gençer, a research scientist at the MIT Energy Initiative (MITEI). That’s because grid operators will increasingly resort to fossil-fuel-based “peaker” plants that compensate for the intermittency of the variable renewable energy (VRE) sources of sun and wind. “If we’re to achieve zero-carbon electricity, we must replace all greenhouse gas-emitting sources,” Gençer says.

    Low- and zero-carbon alternatives to greenhouse-gas emitting peaker plants are in development, such as arrays of lithium-ion batteries and hydrogen power generation. But each of these evolving technologies comes with its own set of advantages and constraints, and it has proven difficult to frame the debate about these options in a way that’s useful for policymakers, investors, and utilities engaged in the clean energy transition.

    Now, Gençer and Drake D. Hernandez SM ’21 have come up with a model that makes it possible to pin down the pros and cons of these peaker-plant alternatives with greater precision. Their hybrid technological and economic analysis, based on a detailed inventory of California’s power system, was published online last month in Applied Energy. While their work focuses on the most cost-effective solutions for replacing peaker power plants, it also contains insights intended to contribute to the larger conversation about transforming energy systems.

    “Our study’s essential takeaway is that hydrogen-fired power generation can be the more economical option when compared to lithium-ion batteries — even today, when the costs of hydrogen production, transmission, and storage are very high,” says Hernandez, who worked on the study while a graduate research assistant for MITEI. Adds Gençer, “If there is a place for hydrogen in the cases we analyzed, that suggests there is a promising role for hydrogen to play in the energy transition.”

    Adding up the costs

    California serves as a stellar paradigm for a swiftly shifting power system. The state draws more than 20 percent of its electricity from solar and approximately 7 percent from wind, with more VRE coming online rapidly. This means its peaker plants already play a pivotal role, coming online each evening when the sun goes down or when events such as heat waves drive up electricity use for days at a time.

    “We looked at all the peaker plants in California,” recounts Gençer. “We wanted to know the cost of electricity if we replaced them with hydrogen-fired turbines or with lithium-ion batteries.” The researchers used a core metric called the levelized cost of electricity (LCOE) as a way of comparing the costs of different technologies to each other. LCOE measures the average total cost of building and operating a particular energy-generating asset per unit of total electricity generated over the hypothetical lifetime of that asset.

    Selecting 2019 as their base study year, the team looked at the costs of running natural gas-fired peaker plants, which they defined as plants operating 15 percent of the year in response to gaps in intermittent renewable electricity. In addition, they determined the amount of carbon dioxide released by these plants and the expense of abating these emissions. Much of this information was publicly available.

    Coming up with prices for replacing peaker plants with massive arrays of lithium-ion batteries was also relatively straightforward: “There are no technical limitations to lithium-ion, so you can build as many as you want; but they are super expensive in terms of their footprint for energy storage and the mining required to manufacture them,” says Gençer.

    But then came the hard part: nailing down the costs of hydrogen-fired electricity generation. “The most difficult thing is finding cost assumptions for new technologies,” says Hernandez. “You can’t do this through a literature review, so we had many conversations with equipment manufacturers and plant operators.”

    The team considered two different forms of hydrogen fuel to replace natural gas, one produced through electrolyzer facilities that convert water and electricity into hydrogen, and another that reforms natural gas, yielding hydrogen and carbon waste that can be captured to reduce emissions. They also ran the numbers on retrofitting natural gas plants to burn hydrogen as opposed to building entirely new facilities. Their model includes identification of likely locations throughout the state and expenses involved in constructing these facilities.

    The researchers spent months compiling a giant dataset before setting out on the task of analysis. The results from their modeling were clear: “Hydrogen can be a more cost-effective alternative to lithium-ion batteries for peaking operations on a power grid,” says Hernandez. In addition, notes Gençer, “While certain technologies worked better in particular locations, we found that on average, reforming hydrogen rather than electrolytic hydrogen turned out to be the cheapest option for replacing peaker plants.”

    A tool for energy investors

    When he began this project, Gençer admits he “wasn’t hopeful” about hydrogen replacing natural gas in peaker plants. “It was kind of shocking to see in our different scenarios that there was a place for hydrogen.” That’s because the overall price tag for converting a fossil-fuel based plant to one based on hydrogen is very high, and such conversions likely won’t take place until more sectors of the economy embrace hydrogen, whether as a fuel for transportation or for varied manufacturing and industrial purposes.

    A nascent hydrogen production infrastructure does exist, mainly in the production of ammonia for fertilizer. But enormous investments will be necessary to expand this framework to meet grid-scale needs, driven by purposeful incentives. “With any of the climate solutions proposed today, we will need a carbon tax or carbon pricing; otherwise nobody will switch to new technologies,” says Gençer.

    The researchers believe studies like theirs could help key energy stakeholders make better-informed decisions. To that end, they have integrated their analysis into SESAME, a life cycle and techno-economic assessment tool for a range of energy systems that was developed by MIT researchers. Users can leverage this sophisticated modeling environment to compare costs of energy storage and emissions from different technologies, for instance, or to determine whether it is cost-efficient to replace a natural gas-powered plant with one powered by hydrogen.

    “As utilities, industry, and investors look to decarbonize and achieve zero-emissions targets, they have to weigh the costs of investing in low-carbon technologies today against the potential impacts of climate change moving forward,” says Hernandez, who is currently a senior associate in the energy practice at Charles River Associates. Hydrogen, he believes, will become increasingly cost-competitive as its production costs decline and markets expand.

    A study group member of MITEI’s soon-to-be published Future of Storage study, Gençer knows that hydrogen alone will not usher in a zero-carbon future. But, he says, “Our research shows we need to seriously consider hydrogen in the energy transition, start thinking about key areas where hydrogen should be used, and start making the massive investments necessary.”

    Funding for this research was provided by MITEI’s Low-Carbon Energy Centers and Future of Storage study. More