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      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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      A tool to speed development of new solar cells

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      In the ongoing race to develop ever-better materials and configurations for solar cells, there are many variables that can be adjusted to try to improve performance, including material type, thickness, and geometric arrangement. Developing new solar cells has generally been a tedious process of making small changes to one of these parameters at a time. While computational simulators have made it possible to evaluate such changes without having to actually build each new variation for testing, the process remains slow.

      Now, researchers at MIT and Google Brain have developed a system that makes it possible not just to evaluate one proposed design at a time, but to provide information about which changes will provide the desired improvements. This could greatly increase the rate for the discovery of new, improved configurations.

      The new system, called a differentiable solar cell simulator, is described in a paper published today in the journal Computer Physics Communications, written by MIT junior Sean Mann, research scientist Giuseppe Romano of MIT’s Institute for Soldier Nanotechnologies, and four others at MIT and at Google Brain.

      Traditional solar cell simulators, Romano explains, take the details of a solar cell configuration and produce as their output a predicted efficiency — that is, what percentage of the energy of incoming sunlight actually gets converted to an electric current. But this new simulator both predicts the efficiency and shows how much that output is affected by any one of the input parameters. “It tells you directly what happens to the efficiency if we make this layer a little bit thicker, or what happens to the efficiency if we for example change the property of the material,” he says.

      In short, he says, “we didn’t discover a new device, but we developed a tool that will enable others to discover more quickly other higher performance devices.” Using this system, “we are decreasing the number of times that we need to run a simulator to give quicker access to a wider space of optimized structures.” In addition, he says, “our tool can identify a unique set of material parameters that has been hidden so far because it’s very complex to run those simulations.”

      While traditional approaches use essentially a random search of possible variations, Mann says, with his tool “we can follow a trajectory of change because the simulator tells you what direction you want to be changing your device. That makes the process much faster because instead of exploring the entire space of opportunities, you can just follow a single path” that leads directly to improved performance.

      Since advanced solar cells often are composed of multiple layers interlaced with conductive materials to carry electric charge from one to the other, this computational tool reveals how changing the relative thicknesses of these different layers will affect the device’s output. “This is very important because the thickness is critical. There is a strong interplay between light propagation and the thickness of each layer and the absorption of each layer,” Mann explains.

      Other variables that can be evaluated include the amount of doping (the introduction of atoms of another element) that each layer receives, or the dielectric constant of insulating layers, or the bandgap, a measure of the energy levels of photons of light that can be captured by different materials used in the layers.

      This simulator is now available as an open-source tool that can be used immediately to help guide research in this field, Romano says. “It is ready, and can be taken up by industry experts.” To make use of it, researchers would couple this device’s computations with an optimization algorithm, or even a machine learning system, to rapidly assess a wide variety of possible changes and home in quickly on the most promising alternatives.

      At this point, the simulator is based on just a one-dimensional version of the solar cell, so the next step will be to expand its capabilities to include two- and three-dimensional configurations. But even this 1D version “can cover the majority of cells that are currently under production,” Romano says. Certain variations, such as so-called tandem cells using different materials, cannot yet be simulated directly by this tool, but “there are ways to approximate a tandem solar cell by simulating each of the individual cells,” Mann says.

      The simulator is “end-to-end,” Romano says, meaning it computes the sensitivity of the efficiency, also taking into account light absorption. He adds: “An appealing future direction is composing our simulator with advanced existing differentiable light-propagation simulators, to achieve enhanced accuracy.”

      Moving forward, Romano says, because this is an open-source code, “that means that once it’s up there, the community can contribute to it. And that’s why we are really excited.” Although this research group is “just a handful of people,” he says, now anyone working in the field can make their own enhancements and improvements to the code and introduce new capabilities.

      “Differentiable physics is going to provide new capabilities for the simulations of engineered systems,” says Venkat Viswanathan, an associate professor of mechanical engineering at Carnegie Mellon University, who was not associated with this work. “The  differentiable solar cell simulator is an incredible example of differentiable physics, that can now provide new capabilities to optimize solar cell device performance,” he says, calling the study “an exciting step forward.”

      In addition to Mann and Romano, the team included Eric Fadel and Steven Johnson at MIT, and Samuel Schoenholz and Ekin Cubuk at Google Brain. The work was supported in part by Eni S.p.A. and the MIT Energy Initiative, and the MIT Quest for Intelligence. More

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

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      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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      Coupling power and hydrogen sector pathways to benefit decarbonization

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      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

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      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

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      in Energy

      MIT Solar Electric Vehicle Team wins 2021 American Solar Challenge

      by

      After three years of hard work, the MIT Solar Electric Vehicle Team took first place at the 2021 American Solar Challenge (ASC) on August 7 in the Single Occupancy Vehicle (SOV) category. During the five-day race, their solar car, Nimbus — designed and built entirely by students — beat eight other SOVs from schools across the country, traversing 1,109 miles and maintaining an average speed of 38.4 miles per hour.

      Held every two years, the ASC has traditionally been a timed event. This year, however, the race was based on the total distance traveled. Each team followed the same prescribed route, from Independence, Missouri, to Las Vegas, New Mexico. But teams could drive additional miles within each of the three stages — if their battery had enough juice to continue. Nimbus surpassed the closest runner-up, the University of Kentucky, by over 100 miles.

      “It’s still a little surreal,” says SEVT captain Aditya Mehrotra, a rising senior in electrical engineering and computer science. “We were all hopeful, but I don’t think you ever go into racing like, ‘We got this.’ It’s more like, ‘We’re going to do our best and see how we fare.’ In this case, we were fortunate enough to do really well. The car worked beautifully, and — more importantly — the team worked beautifully and we learned a lot.”

      Team work makes the dream work

      Two weeks before the ASC race, each solar car was put through its paces in the Formula Sun Grand Prix at Heartland Motorsports Park in Topeka, Kansas. First, vehicles had to perform a series of qualifying challenges, called “scrutineering.” Cars that passed could participate in a track race in hopes of qualifying for ASC. Nimbus placed second, completing a total of 239 laps around the track over three days (equivalent to 597.5 miles).

      In the process, SEVT member and rising junior in mechanical engineering Cameron Kokesh tied the Illinois State driver for the fastest single lap time around the track, clocking in at three minutes and 19 seconds. She’s not one to rest on her laurels, though. “It would be fun to see if we could beat that time at the next race,” she says with a smile.

      Nimbus’s performance at the Formula Sun Grand Prix and ASC is a manifestation of team’s proficiency in not only designing and building a superior solar vehicle, but other skills, as well, including managing logistics, communications, and teamwork. “It’s a huge operation,” says Mehrotra. “It’s not like we drive the car straight down the highway during the race.”

      Indeed, Nimbus travels with an impressive caravan of seven vehicles manned by about two dozen SEVT members. A scout vehicle is at the front, monitoring road and weather conditions, followed by a lead car that oversees navigation. Nimbus is third in the caravan, trailed by a chase vehicle, in which the strategy team manages tasks like monitoring telemetry data, calculating how much power the solar panels are generating and the remaining travel distance, and setting target speeds. Bringing up the rear are the transport truck and trailer, a media car, and “Cupcake,” a support vehicle with food, supplies, and camping gear.

      Leading up to the three-week event, the team devoted three years to designing, building, refining, and testing Nimbus. (The ASC was scheduled for 2020, but it was postponed until this year due to the Covid-19 pandemic.) They spent countless hours in the MIT Edgerton Center’s machine shop in Building N51, making, building, and iterating. They drove the car in the greater-Boston area, up to Salem, Massachusetts, and to Cape Cod. In the spring, they traveled to Palmer Motorsports Park in Palmer, Massachusetts, to practice various components of the race. They performed scrutineering tasks like the slalom test and figure eight test, conducted team operations training to optimize the caravan’s performance, and, of course, the “shakedown.” 

      “Shakedown is just, you drive the car around the track and you basically see what falls off and then you know what you need to fix,” Mehrotra explains. “Hopefully nothing too major falls off!”

      The road ahead

      At the conclusion of the race, Mehotra officially stepped down and handed SEVT’s reins to its new leaders: Kotesh will take the helm as team captain, and rising sophomore Sydney Kim, an ocean engineering major, will serve as vice-captain. The long drive back from the Midwest gave them time to reflect on the win and future plans.

      Although Nimbus performed well, there were a few instructive glitches here and there, mostly during scrutineering. But there was nothing the team couldn’t handle. For example, the canopy latch didn’t always hold, so the clear acrylic bubble covering the driver would pop open. (A little spring adjustment and tape did the trick.) In addition, Nimbus had a tendency to skid when the driver slammed on the brakes. (Driver training, and letting some air out of the tires, improved the traction.)

      Then there were the unpredictable variables, beyond the team’s control. On one day, with little sun, Nimbus had to chug along the highway at a mere 15 miles per hour. And there was the time that the Kansas State Police pulled the entire caravan over. “They didn’t realize we were coming through,” Mehrotra explains.

      Kim thinks one of the keys to the team’s success is that Nimbus is quite reliable. “We didn’t have wheels falling off on the road. Once we got the car rolling, things didn’t go wrong mechanically or electrically. Also, it’s very energy efficient because it’s lightweight and the shape of the vehicle is very aerodynamic. On a nice sunny day, it allows us to drive 40 miles per hour energy-neutral — the battery stays at the same amount of charge as we drive,” she says.

      The next ASC will take place in 2022, so this year the team will focus on refining Nimbus to race it again next summer. Also, they’ve set their sights on building a car to enter in the Multiple Occupancy Vehicle (MOV) class in the 2024 race — something the team has never done. “It will definitely take the three years to build a good car to compete,” Kotesh muses. “But it’s a really good transition period, after doing so well on this race, so our team is excited about it.”

      “It will be challenging for them, but I wouldn’t put it anything past them,” says Patrick McAtamney, the Edgerton Center technical instructor and shop manager who works with all the student clubs and teams, from solar vehicles to Formula race cars to rockets. He attended ASC, too, and has the utmost admiration for SEVT. “It’s totally student-run. They do all the designing and machining themselves. I always tell people that sometimes I feel like my only job is to make sure they have 10 fingers when they leave the shop.”

      In the meantime, before the school year begins, SEVT has another challenge: deciding where to put the trophy. “It’s huge,” McAtamney says. “It’s about the size of the Stanley Cup!” More