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      in Energy

      How to clean solar panels without water

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      Solar power is expected to reach 10 percent of global power generation by the year 2030, and much of that is likely to be located in desert areas, where sunlight is abundant. But the accumulation of dust on solar panels or mirrors is already a significant issue — it can reduce the output of photovoltaic panels by as much as 30 percent in just one month — so regular cleaning is essential for such installations.

      But cleaning solar panels currently is estimated to use about 10 billion gallons of water per year — enough to supply drinking water for up to 2 million people. Attempts at waterless cleaning are labor intensive and tend to cause irreversible scratching of the surfaces, which also reduces efficiency. Now, a team of researchers at MIT has devised a way of automatically cleaning solar panels, or the mirrors of solar thermal plants, in a waterless, no-contact system that could significantly reduce the dust problem, they say.

      The new system uses electrostatic repulsion to cause dust particles to detach and virtually leap off the panel’s surface, without the need for water or brushes. To activate the system, a simple electrode passes just above the solar panel’s surface, imparting an electrical charge to the dust particles, which are then repelled by a charge applied to the panel itself. The system can be operated automatically using a simple electric motor and guide rails along the side of the panel. The research is described today in the journal Science Advances, in a paper by MIT graduate student Sreedath Panat and professor of mechanical engineering Kripa Varanasi.

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      Despite concerted efforts worldwide to develop ever more efficient solar panels, Varanasi says, “a mundane problem like dust can actually put a serious dent in the whole thing.” Lab tests conducted by Panat and Varanasi showed that the dropoff of energy output from the panels happens steeply at the very beginning of the process of dust accumulation and can easily reach 30 percent reduction after just one month without cleaning. Even a 1 percent reduction in power, for a 150-megawatt solar installation, they calculated, could result in a $200,000 loss in annual revenue. The researchers say that globally, a 3 to 4 percent reduction in power output from solar plants would amount to a loss of between $3.3 billion and $5.5 billion.

      “There is so much work going on in solar materials,” Varanasi says. “They’re pushing the boundaries, trying to gain a few percent here and there in improving the efficiency, and here you have something that can obliterate all of that right away.”

      Many of the largest solar power installations in the world, including ones in China, India, the U.A.E., and the U.S., are located in desert regions. The water used for cleaning these solar panels using pressurized water jets has to be trucked in from a distance, and it has to be very pure to avoid leaving behind deposits on the surfaces. Dry scrubbing is sometimes used but is less effective at cleaning the surfaces and can cause permanent scratching that also reduces light transmission.

      Water cleaning makes up about 10 percent of the operating costs of solar installations. The new system could potentially reduce these costs while improving the overall power output by allowing for more frequent automated cleanings, the researchers say.

      “The water footprint of the solar industry is mind boggling,” Varanasi says, and it will be increasing as these installations continue to expand worldwide. “So, the industry has to be very careful and thoughtful about how to make this a sustainable solution.”

      Other groups have tried to develop electrostatic based solutions, but these have relied on a layer called an electrodynamic screen, using interdigitated electrodes. These screens can have defects that allow moisture in and cause them to fail, Varanasi says. While they might be useful on a place like Mars, he says, where moisture is not an issue, even in desert environments on Earth this can be a serious problem.

      The new system they developed only requires an electrode, which can be a simple metal bar, to pass over the panel, producing an electric field that imparts a charge to the dust particles as it goes. An opposite charge applied to a transparent conductive layer just a few nanometers thick deposited on the glass covering of the the solar panel then repels the particles, and by calculating the right voltage to apply, the researchers were able to find a voltage range sufficient to overcome the pull of gravity and adhesion forces, and cause the dust to lift away.

      Using specially prepared laboratory samples of dust with a range of particle sizes, experiments proved that the process works effectively on a laboratory-scale test installation, Panat says. The tests showed that humidity in the air provided a thin coating of water on the particles, which turned out to be crucial to making the effect work. “We performed experiments at varying humidities from 5 percent to 95 percent,” Panat says. “As long as the ambient humidity is greater than 30 percent, you can remove almost all of the particles from the surface, but as humidity decreases, it becomes harder.”

      Varanasi says that “the good news is that when you get to 30 percent humidity, most deserts actually fall in this regime.” And even those that are typically drier than that tend to have higher humidity in the early morning hours, leading to dew formation, so the cleaning could be timed accordingly.

      “Moreover, unlike some of the prior work on electrodynamic screens, which actually do not work at high or even moderate humidity, our system can work at humidity even as high as 95 percent, indefinitely,” Panat says.

      In practice, at scale, each solar panel could be fitted with railings on each side, with an electrode spanning across the panel. A small electric motor, perhaps using a tiny portion of the output from the panel itself, would drive a belt system to move the electrode from one end of the panel to the other, causing all the dust to fall away. The whole process could be automated or controlled remotely. Alternatively, thin strips of conductive transparent material could be permanently arranged above the panel, eliminating the need for moving parts.

      By eliminating the dependency on trucked-in water, by eliminating the buildup of dust that can contain corrosive compounds, and by lowering the overall operational costs, such systems have the potential to significantly improve the overall efficiency and reliability of solar installations, Varanasi says.

      The research was supported by Italian energy firm Eni. S.p.A. through the MIT Energy Initiative. More

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      in Environment

      Using nature’s structures in wooden buildings

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      Concern about climate change has focused significant attention on the buildings sector, in particular on the extraction and processing of construction materials. The concrete and steel industries together are responsible for as much as 15 percent of global carbon dioxide emissions. In contrast, wood provides a natural form of carbon sequestration, so there’s a move to use timber instead. Indeed, some countries are calling for public buildings to be made at least partly from timber, and large-scale timber buildings have been appearing around the world.

      Observing those trends, Caitlin Mueller ’07, SM ’14, PhD ’14, an associate professor of architecture and of civil and environmental engineering in the Building Technology Program at MIT, sees an opportunity for further sustainability gains. As the timber industry seeks to produce wooden replacements for traditional concrete and steel elements, the focus is on harvesting the straight sections of trees. Irregular sections such as knots and forks are turned into pellets and burned, or ground up to make garden mulch, which will decompose within a few years; both approaches release the carbon trapped in the wood to the atmosphere.

      For the past four years, Mueller and her Digital Structures research group have been developing a strategy for “upcycling” those waste materials by using them in construction — not as cladding or finishes aimed at improving appearance, but as structural components. “The greatest value you can give to a material is to give it a load-bearing role in a structure,” she says. But when builders use virgin materials, those structural components are the most emissions-intensive parts of buildings due to their large volume of high-strength materials. Using upcycled materials in place of those high-carbon systems is therefore especially impactful in reducing emissions.

      Mueller and her team focus on tree forks — that is, spots where the trunk or branch of a tree divides in two, forming a Y-shaped piece. In architectural drawings, there are many similar Y-shaped nodes where straight elements come together. In such cases, those units must be strong enough to support critical loads.

      “Tree forks are naturally engineered structural connections that work as cantilevers in trees, which means that they have the potential to transfer force very efficiently thanks to their internal fiber structure,” says Mueller. “If you take a tree fork and slice it down the middle, you see an unbelievable network of fibers that are intertwining to create these often three-dimensional load transfer points in a tree. We’re starting to do the same thing using 3D printing, but we’re nowhere near what nature does in terms of complex fiber orientation and geometry.”

      She and her team have developed a five-step “design-to-fabrication workflow” that combines natural structures such as tree forks with the digital and computational tools now used in architectural design. While there’s long been a “craft” movement to use natural wood in railings and decorative features, the use of computational tools makes it possible to use wood in structural roles — without excessive cutting, which is costly and may compromise the natural geometry and internal grain structure of the wood.

      Given the wide use of digital tools by today’s architects, Mueller believes that her approach is “at least potentially scalable and potentially achievable within our industrialized materials processing systems.” In addition, by combining tree forks with digital design tools, the novel approach can also support the trend among architects to explore new forms. “Many iconic buildings built in the past two decades have unexpected shapes,” says Mueller. “Tree branches have a very specific geometry that sometimes lends itself to an irregular or nonstandard architectural form — driven not by some arbitrary algorithm but by the material itself.”

      Step 0: Find a source, set goals

      Before starting their design-to-fabrication process, the researchers needed to locate a source of tree forks. Mueller found help in the Urban Forestry Division of the City of Somerville, Massachusetts, which maintains a digital inventory of more than 2,000 street trees — including more than 20 species — and records information about the location, approximate trunk diameter, and condition of each tree.

      With permission from the forestry division, the team was on hand in 2018 when a large group of trees was cut down near the site of the new Somerville High School. Among the heavy equipment on site was a chipper, poised to turn all the waste wood into mulch. Instead, the workers obligingly put the waste wood into the researchers’ truck to be brought to MIT.

      In their project, the MIT team sought not only to upcycle that waste material but also to use it to create a structure that would be valued by the public. “Where I live, the city has had to take down a lot of trees due to damage from an invasive species of beetle,” Mueller explains. “People get really upset — understandably. Trees are an important part of the urban fabric, providing shade and beauty.” She and her team hoped to reduce that animosity by “reinstalling the removed trees in the form of a new functional structure that would recreate the atmosphere and spatial experience previously provided by the felled trees.”

      With their source and goals identified, the researchers were ready to demonstrate the five steps in their design-to-fabrication workflow for making spatial structures using an inventory of tree forks.

      Step 1: Create a digital material library

      The first task was to turn their collection of tree forks into a digital library. They began by cutting off excess material to produce isolated tree forks. They then created a 3D scan of each fork. Mueller notes that as a result of recent progress in photogrammetry (measuring objects using photographs) and 3D scanning, they could create high-resolution digital representations of the individual tree forks with relatively inexpensive equipment, even using apps that run on a typical smartphone.

      In the digital library, each fork is represented by a “skeletonized” version showing three straight bars coming together at a point. The relative geometry and orientation of the branches are of particular interest because they determine the internal fiber orientation that gives the component its strength.

      Step 2: Find the best match between the initial design and the material library

      Like a tree, a typical architectural design is filled with Y-shaped nodes where three straight elements meet up to support a critical load. The goal was therefore to match the tree forks in the material library with the nodes in a sample architectural design.

      First, the researchers developed a “mismatch metric” for quantifying how well the geometries of a particular tree fork aligned with a given design node. “We’re trying to line up the straight elements in the structure with where the branches originally were in the tree,” explains Mueller. “That gives us the optimal orientation for load transfer and maximizes use of the inherent strength of the wood fiber.” The poorer the alignment, the higher the mismatch metric.

      The goal was to get the best overall distribution of all the tree forks among the nodes in the target design. Therefore, the researchers needed to try different fork-to-node distributions and, for each distribution, add up the individual fork-to-node mismatch errors to generate an overall, or global, matching score. The distribution with the best matching score would produce the most structurally efficient use of the total tree fork inventory.

      Since performing that process manually would take far too long to be practical, they turned to the “Hungarian algorithm,” a technique developed in 1955 for solving such problems. “The brilliance of the algorithm is solving that [matching] problem very quickly,” Mueller says. She notes that it’s a very general-use algorithm. “It’s used for things like marriage match-making. It can be used any time you have two collections of things that you’re trying to find unique matches between. So, we definitely didn’t invent the algorithm, but we were the first to identify that it could be used for this problem.”

      The researchers performed repeated tests to show possible distributions of the tree forks in their inventory and found that the matching score improved as the number of forks available in the material library increased — up to a point. In general, the researchers concluded that the mismatch score was lowest, and thus best, when there were about three times as many forks in the material library as there were nodes in the target design.

      Step 3: Balance designer intention with structural performance

      The next step in the process was to incorporate the intention or preference of the designer. To permit that flexibility, each design includes a limited number of critical parameters, such as bar length and bending strain. Using those parameters, the designer can manually change the overall shape, or geometry, of the design or can use an algorithm that automatically changes, or “morphs,” the geometry. And every time the design geometry changes, the Hungarian algorithm recalculates the optimal fork-to-node matching.

      “Because the Hungarian algorithm is extremely fast, all the morphing and the design updating can be really fluid,” notes Mueller. In addition, any change to a new geometry is followed by a structural analysis that checks the deflections, strain energy, and other performance measures of the structure. On occasion, the automatically generated design that yields the best matching score may deviate far from the designer’s initial intention. In such cases, an alternative solution can be found that satisfactorily balances the design intention with a low matching score.

      Step 4: Automatically generate the machine code for fast cutting

      When the structural geometry and distribution of tree forks have been finalized, it’s time to think about actually building the structure. To simplify assembly and maintenance, the researchers prepare the tree forks by recutting their end faces to better match adjoining straight timbers and cutting off any remaining bark to reduce susceptibility to rot and fire.

      To guide that process, they developed a custom algorithm that automatically computes the cuts needed to make a given tree fork fit into its assigned node and to strip off the bark. The goal is to remove as little material as possible but also to avoid a complex, time-consuming machining process. “If we make too few cuts, we’ll cut off too much of the critical structural material. But we don’t want to make a million tiny cuts because it will take forever,” Mueller explains.

      The team uses facilities at the Autodesk Boston Technology Center Build Space, where the robots are far larger than any at MIT and the processing is all automated. To prepare each tree fork, they mount it on a robotic arm that pushes the joint through a traditional band saw in different orientations, guided by computer-generated instructions. The robot also mills all the holes for the structural connections. “That’s helpful because it ensures that everything is aligned the way you expect it to be,” says Mueller.

      Step 5: Assemble the available forks and linear elements to build the structure

      The final step is to assemble the structure. The tree-fork-based joints are all irregular, and combining them with the precut, straight wooden elements could be difficult. However, they’re all labeled. “All the information for the geometry is embedded in the joint, so the assembly process is really low-tech,” says Mueller. “It’s like a child’s toy set. You just follow the instructions on the joints to put all the pieces together.”

      They installed their final structure temporarily on the MIT campus, but Mueller notes that it was only a portion of the structure they plan to eventually build. “It had 12 nodes that we designed and fabricated using our process,” she says, adding that the team’s work was “a little interrupted by the pandemic.” As activity on campus resumes, the researchers plan to finish designing and building the complete structure, which will include about 40 nodes and will be installed as an outdoor pavilion on the site of the felled trees in Somerville.

      In addition, they will continue their research. Plans include working with larger material libraries, some with multibranch forks, and replacing their 3D-scanning technique with computerized tomography scanning technologies that can automatically generate a detailed geometric representation of a tree fork, including its precise fiber orientation and density. And in a parallel project, they’ve been exploring using their process with other sources of materials, with one case study focusing on using material from a demolished wood-framed house to construct more than a dozen geodesic domes.

      To Mueller, the work to date already provides new guidance for the architectural design process. With digital tools, it has become easy for architects to analyze the embodied carbon or future energy use of a design option. “Now we have a new metric of performance: How well am I using available resources?” she says. “With the Hungarian algorithm, we can compute that metric basically in real time, so we can work rapidly and creatively with that as another input to the design process.”

      This research was supported by MIT’s School of Architecture and Planning via the HASS Award.

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

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      in Energy

      Tuning in to invisible waves on the JET tokamak

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      Research scientist Alex Tinguely is readjusting to Cambridge and Boston.

      As a postdoc with the Plasma Science and Fusion Center (PSFC), the MIT graduate spent the last two years in Oxford, England, a city he recalls can be traversed entirely “in the time it takes to walk from MIT to Harvard.” With its ancient stone walls, cathedrals, cobblestone streets, and winding paths, that small city was his home base for a big project: JET, a tokamak that is currently the largest operating magnetic fusion energy experiment in the world.

      Located at the Culham Center for Fusion Energy (CCFE), part of the U.K. Atomic Energy Authority, this key research center of the European Fusion Program has recently announced historic success. Using a 50-50 deuterium-tritium fuel mixture for the first time since 1997, JET established a fusion power record of 10 megawatts output over five seconds. It produced 59 megajoules of fusion energy, more than doubling the 22 megajoule record it set in 1997. As a member of the JET Team, Tinguely has overseen the measurement and instrumentation systems (diagnostics) contributed by the MIT group.

      A lucky chance

      The postdoctoral opportunity arose just as Tinguely was graduating with a PhD in physics from MIT. Managed by Professor Miklos Porkolab as the principal investigator for over 20 years, this postdoctoral program has prepared multiple young researchers for careers in fusion facilities around the world. The collaborative research provided Tinguely the chance to work on a fusion device that would be adding tritium to the usual deuterium fuel.

      Fusion, the process that fuels the sun and other stars, could provide a long-term source of carbon-free power on Earth, if it can be harnessed. For decades researchers have tried to create an artificial star in a doughnut-shaped bottle, or “tokamak,” using magnetic fields to keep the turbulent plasma fuel confined and away from the walls of its container long enough for fusion to occur.

      In his graduate student days at MIT, Tinguely worked on the PSFC’s Alcator C-Mod tokamak, now decommissioned, which, like most magnetic fusion devices, used deuterium to create the plasmas for experiments. JET, since beginning operation in 1983, has done the same, later joining a small number of facilities that added tritium, a radioactive isotope of hydrogen. While this addition increases the amount of fusion, it also creates much more radiation and activation.

      Tinguely considers himself fortunate to have been placed at JET.

      “There aren’t that many operating tokamaks in the U.S. right now,” says Tinguely, “not to mention one that would be running deuterium-tritium (DT), which hasn’t been run for over 20 years, and which would be making some really important measurements. I got a very lucky spot where I was an MIT postdoc, but I lived in Oxford, working on a very international project.”

      Strumming magnetic field lines

      The measurements that interest Tinguely are of low-frequency electromagnetic waves in tokamak plasmas. Tinguely uses an antenna diagnostic developed by MIT, EPFL Swiss Plasma Center, and CCFE to probe the so-called Alfvén eigenmodes when they are stable, before the energetic alpha particles produced by DT fusion plasmas can drive them toward instability.

      What makes MIT’s “Alfvén Eigenmode Active Diagnostic” essential is that without it researchers cannot see, or measure, stable eigenmodes. Unstable modes show up clearly as magnetic fluctuations in the data, but stable waves are invisible without prompting from the antenna. These measurements help researchers understand the physics of Alfvén waves and their potential for degrading fusion performance, providing insights that will be increasingly important for future DT fusion devices.

      Tinguely likens the diagnostic to fingers on guitar strings.

      “The magnetic field lines in the tokamak are like guitar strings. If you have nothing to give energy to the strings — or give energy to the waves of the magnetic field lines — they just sit there, they don’t do anything. The energetic plasma particles can essentially ‘play the guitar strings,’ strum the magnetic field lines of the plasma, and that’s when you can see the waves in your plasma. But if the energetic particle drive of the waves is not strong enough you won’t see them, so you need to come along and ‘pluck the strings’ with our antenna. And that’s how you learn some information about the waves.”

      Much of Tinguely’s experience on JET took place during the Covid-19 pandemic, when off-site operation and analysis were the norm. However, because the MIT diagnostic needed to be physically turned on and off, someone from Tinguely’s team needed to be on site twice a day, a routine that became even less convenient when tritium was introduced.

      “When you have deuterium and tritium, you produce a lot of neutrons. So, some of the buildings became off-limits during operation, which meant they had to be turned on really early in the morning, like 6:30 a.m., and then turned off very late at night, around 10:30 p.m.”

      Looking to the future

      Now a research scientist at the PSFC, Tinguely continues to work at JET remotely. He sometimes wishes he could again ride that train from Oxford to Culham — which he fondly remembers for its clean, comfortable efficiency — to see work colleagues and to visit local friends. The life he created for himself in England included practice and performance with the 125-year-old Oxford Bach Choir, as well as weekly dinner service at The Gatehouse, a facility that offers free support for the local homeless and low-income communities.

      “Being back is exciting too,” he says. “It’s fun to see how things have changed, how people and projects have grown, what new opportunities have arrived.”

      He refers specifically to a project that is beginning to take up more of his time: SPARC, the tokamak the PSFC supports in collaboration with Commonwealth Fusion Systems. Designed to use deuterium-tritium to make net fusion gains, SPARC will be able to use the latest research on JET to advantage. Tinguely is already exploring how his expertise with Alfvén eigenmodes can support the experiment.

      “I actually had an opportunity to do my PhD — or DPhil as they would call it — at Oxford University, but I went to MIT for grad school instead,” Tinguely reveals. “So, this is almost like closure, in a sense. I got to have my Oxford experience in the end, just in a different way, and have the MIT experience too.”

      He adds, “And I see myself being here at MIT for some time.” More

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      in Energy

      Investors awaken to the risks of climate change

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      Poppy Allonby, a senior financial executive and the former managing director of BlackRock, has been analyzing the link between climate change and investing for more than two decades. “For a lot of that, it was quite lonely,” Allonby said during her December address at the MIT Energy Initiative Fall Colloquium. “There weren’t that many other people looking at this field. And over the last three or four years, that’s completely changed.”

      Increasingly, Allonby said, investors are opening their eyes to the long-term risks of climate change — risks that threaten not only the planet, but also their portfolios. And as more institutional investors come to see climate change as a threat to their beneficiaries, they are taking action to fight it. Still, she cautioned that much more work remains to be done.

      “Various investors are at very different stages in considering climate change,” Allonby said. “Once they realize this is something they need to think about … they need to do a risk assessment, then develop a strategy.” 

      “When you look at different institutions,” she said, “some are just at the very beginning of this journey.”

      A changing landscape

      Although there is a compelling moral case to be made for taking steps to mitigate climate change, Allonby noted that institutional investors such as pension funds are bound by a fiduciary duty to their beneficiaries. That is to say, they are obligated to put their client or member interests ahead of their own.

      “I talk about fiduciary duty, because one of the things that has really changed in the investment space is that more and more investors are beginning to see climate change and climate risk as [impacting] their fiduciary duty,” said Allonby. “That has been a shift. In my mind, it makes total sense. If you’re a long-term investor … and you’re thinking about beneficiaries that need assets over the next 10 or 20 years, and thinking about risks that might materialize — and climate change, in particular — then that makes a lot of sense. But that is not where we were five or 10 years ago.”

      Allonby spent more than 20 years at the multinational investment management corporation BlackRock. For 17 of those years, she was a senior portfolio manager responsible for managing multibillion-dollar funds investing globally in companies across the traditional energy sector, and also those involved in sustainable energy and mitigating climate change. Most recently, she was head of the corporation’s Global Product Group on several continents, where she provided oversight for nearly $1 trillion assets and played a critical role in developing BlackRock’s sustainable product strategy.

      “Where I like to think the finance industry is heading is integration,” she said. “This means thinking holistically about pretty much every decision you make as an investor, and thinking about how climate risk is going to impact that investment. That is a sea change in the mentality around how people invest.”

      Divestment versus engagement

      For many years, activists have pushed for institutions — including MIT — to divest from fossil fuel companies. By keeping fossil fuel companies out of their portfolios, these activists argue, institutions and individuals can exert social, political, and economic pressure on these corporations and help to accelerate the shift to renewable energy.

      However, Allonby argued instead for ongoing engagement with fossil fuel companies, reasoning that this better positions investors to push for change. “My personal view with divesting from oil and gas companies is, that’s not very effective,” Allonby said. “I think there might be examples where you have very specific companies which you don’t think will be involved in the transition [to net zero], and [divestment] might make sense. Or if you’ve got an institutional investor where it is imperative that their investment is entirely aligned with their values — so, certain charities — it might make sense. But if you really care about change, I think you need to keep a seat at the table.”

      In a way, Allonby said, divesting from fossil fuel companies lets leaders at those organizations off the hook, reducing the pressure on them to make meaningful changes to their operations. “Imagine a company that is incredibly polluting and not sustainable, and they have shareholders that are not happy, but they don’t do anything, and those shareholders decide to divest,” she said. “What happens as a result of that, potentially, is the company goes, ‘Oh, that was easy! I didn’t have to do anything, and [the activists] have gone away.’ And potentially, those assets end up being owned by people who care less. So that is a risk, when you think about divestment.”

      Challenges and opportunities         

      Allonby outlined several challenges with climate-focused investing, but also noted a number of opportunities — both for investors looking to make money, and those looking to make a change.

      Among the challenges: For one, some investors simply still need to be convinced that climate change is a problem they should be working to solve. Also, Allonby said, there is a lack both of a formalized methodology and of specialized investment products for climate-focused investing, although she noted that both of these areas are improving. Finally, she said, it remains a challenge to encourage investors to direct capital toward clean-energy projects in developing countries. 

      Investors can both set themselves up for financial success and mitigate climate change, Allonby said, through savvy investments in either distressed or underpriced assets. “If you can buy assets that are discounted or cheaper because people have real concerns about their environmental footprint, then you can work with those companies to improve it and therefore reduce the risk and improve the valuation,” she said.

      Allonby, pointing to the high cost of waterfront property in areas that are vulnerable to rising sea levels, also suggested that the long-term risks of climate change have not been fully priced into many assets. “My view is that we haven’t really gotten our arms around that,” she said. “From a purely investment perspective, that’s also an opportunity.”

      Additionally, Allonby noted the recent rise of ESG funds, which invest with environmental, social, and corporate governance guidelines in mind. Some of these funds, she noted, have outperformed the larger market over the past several years.

      “When we talk about climate change, one has a range of emotions,” Allonby said. “Sometimes it can feel like we’re not making enough progress. And one of the nice things about being here at MIT is that whenever I’m here, I always feel hopeful about the future, and quite hopeful about all of the technologies and work that you are doing to transition energy systems and move things forward. When you look at what’s happening in the financial services sector, there’s still a huge amount to do, but it’s also quite a hopeful story.” More

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      in Energy

      Preparing global online learners for the clean energy transition

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      After a career devoted to making the electric power system more efficient and resilient, Marija Ilic came to MIT in 2018 eager not just to extend her research in new directions, but to prepare a new generation for the challenges of the clean-energy transition.

      To that end, Ilic, a senior research scientist in MIT’s Laboratory for Information and Decisions Systems (LIDS) and a senior staff member at Lincoln Laboratory in the Energy Systems Group, designed an edX course that captures her methods and vision: Principles of Modeling, Simulation, and Control for Electric Energy Systems.

      EdX is a provider of massive open online courses produced in partnership with MIT, Harvard University, and other leading universities. Ilic’s class made its online debut in June 2021, running for 12 weeks, and it is one of an expanding set of online courses funded by the MIT Energy Initiative (MITEI) to provide global learners with a view of the shifting energy landscape.

      Ilic first taught a version of the class while a professor at Carnegie Mellon University, rolled out a second iteration at MIT just as the pandemic struck, and then revamped the class for its current online presentation. But no matter the course location, Ilic focuses on a central theme: “With the need for decarbonization, which will mean accommodating new energy sources such as solar and wind, we must rethink how we operate power systems,” she says. “This class is about how to pose and solve the kinds of problems we will face during this transformation.”

      Hot global topic

      The edX class has been designed to welcome a broad mix of students. In summer 2021, more than 2,000 signed up from 109 countries, ranging from high school students to retirees. In surveys, some said they were drawn to the class by the opportunity to advance their knowledge of modeling. Many others hoped to learn about the move to decarbonize energy systems.

      “The energy transition is a hot topic everywhere in the world, not just in the U.S.,” says teaching assistant Miroslav Kosanic. “In the class, there were veterans of the oil industry and others working in investment and finance jobs related to energy who wanted to understand the potential impacts of changes in energy systems, as well as students from different fields and professors seeking to update their curricula — all gathered into a community.”

      Kosanic, who is currently a PhD student at MIT in electrical engineering and computer science, had taken this class remotely in the spring semester of 2021, while he was still in college in Serbia. “I knew I was interested in power systems, but this course was eye-opening for me, showing how to apply control theory and to model different components of these systems,” he says. “I finished the course and thought, this is just the beginning, and I’d like to learn a lot more.” Kosanic performed so well online that Ilic recruited him to MIT, as a LIDS researcher and edX course teaching assistant, where he grades homework assignments and moderates a lively learner community forum.

      A platform for problem-solving

      The course starts with fundamental concepts in electric power systems operations and management, and it steadily adds layers of complexity, posing real-world problems along the way. Ilic explains how voltage travels from point to point across transmission lines and how grid managers modulate systems to ensure that enough, but not too much, electricity flows. “To deliver power from one location to the next one, operators must constantly make adjustments to ensure that the receiving end can handle the voltage transmitted, optimizing voltage to avoid overheating the wires,” she says.

      In her early lectures, Ilic notes the fundamental constraints of current grid operations, organized around a hierarchy of regional managers dealing with a handful of very large oil, gas, coal, and nuclear power plants, and occupied primarily with the steady delivery of megawatt-hours to far-flung customers. But historically, this top-down structure doesn’t do a good job of preventing loss of energy due to sub-optimal transmission conditions or due to outages related to extreme weather events.

      These issues promise to grow for grid operators as distributed resources such as solar and wind enter the picture, Ilic tells students. In the United States, under new rules dictated by the Federal Energy Regulatory Commission, utilities must begin to integrate the distributed, intermittent electricity produced by wind farms, solar complexes, and even by homes and cars, which flows at voltages much lower than electricity produced by large power plants.

      Finding ways to optimize existing energy systems and to accommodate low- and zero-carbon energy sources requires powerful new modes of analysis and problem-solving. This is where Ilic’s toolbox comes in: a mathematical modeling strategy and companion software that simplifies the input and output of electrical systems, no matter how large or how small. “In the last part of the course, we take up modeling different solutions to electric service in a way that is technology-agnostic, where it only matters how much a black-box energy source produces, and the rates of production and consumption,” says Ilic.

      This black-box modeling approach, which Ilic pioneered in her research, enables students to see, for instance, “what is happening with their own household consumption, and how it affects the larger system,” says Rupamathi Jaddivada PhD ’20, a co-instructor of the edX class and a postdoc in electrical engineering and computer science. “Without getting lost in details of current or voltage, or how different components work, we think about electric energy systems as dynamical components interacting with each other, at different spatial scales.” This means that with just a basic knowledge of physical laws, high school and undergraduate students can take advantage of the course “and get excited about cleaner and more reliable energy,” adds Ilic.

      What Jaddivada and Ilic describe as “zoom in, zoom out” systems thinking leverages the ubiquity of digital communications and the so-called “internet of things.” Energy devices of all scales can link directly to other devices in a network instead of just to a central operations hub, allowing for real-time adjustments in voltage, for instance, vastly improving the potential for optimizing energy flows.

      “In the course, we discuss how information exchange will be key to integrating new end-to-end energy resources and, because of this interactivity, how we can model better ways of controlling entire energy networks,” says Ilic. “It’s a big lesson of the course to show the value of information and software in enabling us to decarbonize the system and build resilience, rather than just building hardware.”

      By the end of the course, students are invited to pursue independent research projects. Some might model the impact of a new energy source on a local grid or investigate different options for reducing energy loss in transmission lines.

      “It would be nice if they see that we don’t have to rely on hardware or large-scale solutions to bring about improved electric service and a clean and resilient grid, but instead on information technologies such as smart components exchanging data in real time, or microgrids in neighborhoods that sustain themselves even when they lose power,” says Ilic. “I hope students walk away convinced that it does make sense to rethink how we operate our basic power systems and that with systematic, physics-based modeling and IT methods we can enable better, more flexible operation in the future.”

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

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      MIT Energy Initiative launches the Future Energy Systems Center

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      The MIT Energy Initiative (MITEI) has launched a new research consortium — the Future Energy Systems Center — to address the climate crisis and the role energy systems can play in solving it. This integrated effort engages researchers from across all of MIT to help the global community reach its goal of net-zero carbon emissions. The center examines the accelerating energy transition and collaborates with industrial leaders to reform the world’s energy systems. The center is part of “Fast Forward: MIT’s Climate Action Plan for the Decade,” MIT’s multi-pronged effort announced last year to address the climate crisis.

      The Future Energy Systems Center investigates the emerging technology, policy, demographics, and economics reshaping the landscape of energy supply and demand. The center conducts integrative analysis of the entire energy system — a holistic approach essential to understanding the cross-sectorial impact of the energy transition.

      “We must act quickly to get to net-zero greenhouse gas emissions. At the same time, we have a billion people around the world with inadequate access, or no access, to electricity — and we need to deliver it to them,” says MITEI Director Robert C. Armstrong, the Chevron Professor of Chemical Engineering. “The Future Energy Systems Center combines MIT’s deep knowledge of energy science and technology with advanced tools for systems analysis to examine how advances in technology and system economics may respond to various policy scenarios.”  

      The overarching focus of the center is integrative analysis of the entire energy system, providing insights into the complex multi-sectorial transformations needed to alter the three major energy-consuming sectors of the economy — transportation, industry, and buildings — in conjunction with three major decarbonization-enabling technologies — electricity, energy storage and low-carbon fuels, and carbon management. “Deep decarbonization of our energy system requires an economy-wide perspective on the technology options, energy flows, materials flows, life-cycle emissions, costs, policies, and socioeconomics consequences,” says Randall Field, the center’s executive director. “A systems approach is essential in enabling cross-disciplinary teams to work collaboratively together to address the existential crisis of climate change.”

      Through techno-economic and systems-oriented research, the center analyzes these important interactions. For example:

      •  Increased reliance on variable renewable energy, such as wind and solar, and greater electrification of transportation, industry, and buildings will require expansion of demand management and other solutions for balancing of electricity supply and demand across these areas.

      •  Likewise, balancing supply and demand will require deploying grid-scale energy storage and converting the electricity to low-carbon fuels (hydrogen and liquid fuels), which can in turn play a vital role in the energy transition for hard-to-decarbonize segments of transportation, industry, and buildings.

      •  Carbon management (carbon dioxide capture from industry point sources and from air and oceans; utilization/conversion to valuable products; transport; storage) will also play a critical role in decarbonizing industry, electricity, and fuels — both as carbon-mitigation and negative-carbon solutions.

      As a member-supported research consortium, the center collaborates with industrial experts and leaders — from both energy’s consumer and supplier sides — to gain insights to help researchers anticipate challenges and opportunities of deploying technology at the scale needed to achieve decarbonization. “The Future Energy Systems Center gives us a powerful way to engage with industry to accelerate the energy transition,” says Armstrong. “Working together, we can better understand how our current technology toolbox can be more effectively put to use now to reduce emissions, and what new technologies and policies will ultimately be needed to reach net-zero.”

      A steering committee, made up of 11 MIT professors and led by Armstrong, selects projects to create a research program with high impact on decarbonization, while leveraging MIT strengths and addressing interests of center members in pragmatic and scalable solutions. “MIT — through our recently released climate action plan — is committed to moving with urgency and speed to help wring carbon dioxide emissions out the global economy to resolve the growing climate crisis,” says Armstrong. “We have no time to waste.”

      The center members to date are: AECI, Analog Devices, Chevron, ConocoPhillips, Copec, Dominion, Duke Energy, Enerjisa, Eneva, Eni, Equinor, Eversource, Exelon, ExxonMobil, Ferrovial, Iberdrola, IHI, National Grid, Raizen, Repsol, Rio Tinto, Shell, Tata Power, Toyota Research Institute, and Washington Gas. More

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      Pricing carbon, valuing people

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      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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      Seeing the plasma edge of fusion experiments in new ways with artificial intelligence

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      To make fusion energy a viable resource for the world’s energy grid, researchers need to understand the turbulent motion of plasmas: a mix of ions and electrons swirling around in reactor vessels. The plasma particles, following magnetic field lines in toroidal chambers known as tokamaks, must be confined long enough for fusion devices to produce significant gains in net energy, a challenge when the hot edge of the plasma (over 1 million degrees Celsius) is just centimeters away from the much cooler solid walls of the vessel.

      Abhilash Mathews, a PhD candidate in the Department of Nuclear Science and Engineering working at MIT’s Plasma Science and Fusion Center (PSFC), believes this plasma edge to be a particularly rich source of unanswered questions. A turbulent boundary, it is central to understanding plasma confinement, fueling, and the potentially damaging heat fluxes that can strike material surfaces — factors that impact fusion reactor designs.

      To better understand edge conditions, scientists focus on modeling turbulence at this boundary using numerical simulations that will help predict the plasma’s behavior. However, “first principles” simulations of this region are among the most challenging and time-consuming computations in fusion research. Progress could be accelerated if researchers could develop “reduced” computer models that run much faster, but with quantified levels of accuracy.

      For decades, tokamak physicists have regularly used a reduced “two-fluid theory” rather than higher-fidelity models to simulate boundary plasmas in experiment, despite uncertainty about accuracy. In a pair of recent publications, Mathews begins directly testing the accuracy of this reduced plasma turbulence model in a new way: he combines physics with machine learning.

      “A successful theory is supposed to predict what you’re going to observe,” explains Mathews, “for example, the temperature, the density, the electric potential, the flows. And it’s the relationships between these variables that fundamentally define a turbulence theory. What our work essentially examines is the dynamic relationship between two of these variables: the turbulent electric field and the electron pressure.”

      In the first paper, published in Physical Review E, Mathews employs a novel deep-learning technique that uses artificial neural networks to build representations of the equations governing the reduced fluid theory. With this framework, he demonstrates a way to compute the turbulent electric field from an electron pressure fluctuation in the plasma consistent with the reduced fluid theory. Models commonly used to relate the electric field to pressure break down when applied to turbulent plasmas, but this one is robust even to noisy pressure measurements.

      In the second paper, published in Physics of Plasmas, Mathews further investigates this connection, contrasting it against higher-fidelity turbulence simulations. This first-of-its-kind comparison of turbulence across models has previously been difficult — if not impossible — to evaluate precisely. Mathews finds that in plasmas relevant to existing fusion devices, the reduced fluid model’s predicted turbulent fields are consistent with high-fidelity calculations. In this sense, the reduced turbulence theory works. But to fully validate it, “one should check every connection between every variable,” says Mathews.

      Mathews’ advisor, Principal Research Scientist Jerry Hughes, notes that plasma turbulence is notoriously difficult to simulate, more so than the familiar turbulence seen in air and water. “This work shows that, under the right set of conditions, physics-informed machine-learning techniques can paint a very full picture of the rapidly fluctuating edge plasma, beginning from a limited set of observations. I’m excited to see how we can apply this to new experiments, in which we essentially never observe every quantity we want.”

      These physics-informed deep-learning methods pave new ways in testing old theories and expanding what can be observed from new experiments. David Hatch, a research scientist at the Institute for Fusion Studies at the University of Texas at Austin, believes these applications are the start of a promising new technique.

      “Abhi’s work is a major achievement with the potential for broad application,” he says. “For example, given limited diagnostic measurements of a specific plasma quantity, physics-informed machine learning could infer additional plasma quantities in a nearby domain, thereby augmenting the information provided by a given diagnostic. The technique also opens new strategies for model validation.”

      Mathews sees exciting research ahead.

      “Translating these techniques into fusion experiments for real edge plasmas is one goal we have in sight, and work is currently underway,” he says. “But this is just the beginning.”

      Mathews was supported in this work by the Manson Benedict Fellowship, Natural Sciences and Engineering Research Council of Canada, and U.S. Department of Energy Office of Science under the Fusion Energy Sciences program.​ More