Future Energy Systems Center

About the Center

The Future Energy Systems Center examines the accelerating energy transition as emerging technology and policy, demographic trends, and economics reshape the landscape of energy supply and demand. The Center conducts integrated analysis of the energy system, providing insights into the complex multisectoral transformations that will alter the power and transportation systems, industry, and built environment. Our work draws upon MIT research in traditional energy-related disciplines, as well as from cross-disciplinary fields such as energy and environmental policy, climate science, carbon management, energy economics, behavioral science, cybersecurity, information technology, and artificial intelligence. Looking for the Low-Carbon Energy Centers? The Low-Carbon Energy Centers have been integrated into MITEI’s new Future Energy Systems Center, announced in spring 2021 as part of MIT’s Climate Action Plan for the Decade. All existing consortium-based LCEC projects and memberships continue within the Future Energy Systems Center.

How it works

The Future Energy Systems Center serves as a single point of entry into MITEI and the MIT energy research community at large. As a member-supported consortium, the Center continues MITEI’s long history of working with companies throughout the energy sector. Member companies will include both energy suppliers and consumers demonstrating the impact decarbonization will have on a wide range of industries. The Center brings together ongoing technoeconomic and systems-oriented research from MITEI’s Low-Carbon Energy Centers into one unified center, creating a holistic energy system analysis capability with integrated research focus areas. These will initially include electric power, energy storage and low-carbon fuels, transportation, industrial processes, carbon management, and the built environment. Members are invited to participate in all focus area working groups without limit. Our work rests on two pillars: MITEI’s world-class range of capabilities in energy system modeling and analysis; and the cutting-edge campus-wide energy technology research program overseen by MITEI, spanning all of MIT’s departments, as well as our affiliated policy research centers including the Center for Energy and Environmental Policy Research (CEEPR) and the MIT Center for Sustainability Science and Strategy. Combining our deep knowledge of technology and modeling enables us to investigate the potential for emerging supply and demand-side technologies, along with policy to impact the energy system of the future—exposing new opportunities and threats within a host of industries, as well as unmet research needs.

Benefits

Projects

Accelerating commercial building electrification through science-based decision-making toolkit

Decarbonizing commercial buildings through electrification is critical in order for governments and industry stakeholders worldwide to reach their net zero targets. Over the past decades, a number of cost-effective technologies for electrifying office buildings have come online. However, the adoption of such technologies has been hampered by behavioral barriers and market failures. This project is focused on:

1. Designing a streamlined and targeted decision-making toolkit for industrial stakeholders (e.g., commercial building owners, energy firms, energy service companies, and utilities) to estimate the cost and benefit of building electrification
2. Enabling policymakers to evaluate the required size of subsidy and regulatory programs, by providing essential parameters and counterfactual simulations, to enable large-scale electrification adoption in the commercial sector
3. Generating practical recommendations for strategies that governments and practitioners can adopt to mitigate the primary market failures and increase the net benefit of electrification

Principal investigators: Siqi Zheng, Christopher Knittel

Adaptive optimization and learning for daily operation of clean power systems

To combat global warming, the electricity sector has to go through a rapid decarbonization to reach a clean power system by mid-century. Expected features of such a system are significantly more wind and solar generation, substantial storage resources, some carbon capture and storage capability, and much deeper coupling between the power grid and other sectors, such as electrified transportation. This project is focused on:

1. Understanding the potential and limitations of the existing operating methodologies in the new environment of power grids with high penetration of renewables
2. Developing data-driven stochastic and robust optimization models for real-time dispatch and commitment, and machine learning capabilities for reducing wind and solar generation uncertainty and speed-up of real-time decision-making processes

Principal investigator: Andy Sun

Affordable Multiday Energy Storage Using Ammonia, Methanol and/or Hydrogen

Affordable multiday energy storage is a key requirement for decarbonization of electric power. Multiday storage based on battery technology is very challenging because the current costs of lithium-ion batteries are roughly an order of magnitude too high, and new battery technologies have large space requirements. Energy storage systems using low-carbon liquid fuels (ammonia and methanol) produced with renewable electricity could provide an important alternative or complement to new battery technology. We will analyze fuel production, fuel storage, and fuel to electricity subsystems of this approach; identify the most promising pathways; and determine costs and environmental impacts of these pathways. This project is focused on:

1. Analyzing approaches for minimizing cost and GHG emissions of the production of ammonia and methanol
2. Analyzing approaches for converting stored fuel to electricity
3. Assessing costs of the most promising pathways

Principal investigator: Daniel Cohn, Guiyan Zang

Agent-Based Capacity Expansion Modeling for Better Evaluation of Grid Resiliency

Grid reliability is a key consideration in planning future investments in the electricity sector as it decarbonizes. Existing investment planning models attempt to find a balance of transmission expansion, storage, clean firm generation, and other solutions by optimizing the final design of the grid assuming a central planner model and prescriptive policies such as hard emission limits. This undervalues solutions that provide reliability during the transition, even if they are unimportant in the final grid. This project will develop an agent-based investment planning model that explicitly simulates the investment and operation of electricity grids through the energy transition. This project is focused on:

1. Developing an agent-based investment planning model to explicitly simulate the decarbonization of electricity grids
2. Assessing how the results of an agent-based investment planning model compare to those from existing optimization-based investment planning models
3. Using the agent-based model to evaluate which technologies and policies promote grid reliability in the ERCOT and ISO-NE electricity networks

Principal investigator: Ruaridh Macdonald

AI-based optimization for regional electric vehicle charging station networks

Electric vehicles (EVs) are rapidly gaining attention as sustainable transport solutions in the new era of urban mobility to significantly reduce emissions, improve air quality, combat climate change, and drive economic and innovative growth. In this project, we address the pivotal challenge of optimizing electric vehicle charging stations, a critical component of EV infrastructure. This project is focused on:

1. Developing an innovative AI-based method for optimizing the charging infrastructure network, estimating charging demand, and managing energy efficiently.
2. Developing machine learning-based methods to design time-of-use rates to shift electricity usage to off-peak times and to charging locations to minimize overall system costs and wait times.
3. Evaluating and validating the methods developed for optimizing charging station networks and for time-of-use rate management.

Principal investigators: Chuchu Fan, Yossi Sheffi, Charles Fine, Elenna Dugundji

AI-Driven Building Flexibility through Virtual Power Plant (VPP) Operation

Buildings consume a significant portion of global energy but typically operate as passive energy users, limiting their contribution to grid stability and sustainability. Traditional energy management systems cannot dynamically adjust energy use in response to real-time grid demands. This challenge hinders efforts to reduce energy costs, lower carbon emissions, and participate in energy markets without investing in additional energy generation or storage infrastructure. This project will focus on:

• Improving AI-driven building automation models that optimize control of energy consumption in day-ahead and real-time, enabling buildings to respond to grid conditions and pricing signals.
• Implementing dynamic energy consumption strategies that allow buildings to participate in energy and grid services markets without needing physical energy storage.
• Evaluating the role of different building types in supporting Virtual Power Plant (VPP) operations to improve grid stability, reduce carbon emissions, and enhance sustainability.

Principal investigators: Les Norford, Audun Botterund, You Lin

Analyzing the large-scale supply of low-carbon hydrogen in Germany

Low-carbon hydrogen is considered one of the key decarbonization instruments for the energy system. Germany is the largest producer of hydrogen in Europe with a total nominal capacity of 60.8 TWh/yr. This project is focused on:

1. Developing a detailed multi-nodal model of the future low-carbon hydrogen value chain in Germany including hydrogen production, transmission, storage, and demand
2. Identifying the minimum cost hydrogen supply chain design for different scenarios and timeframes
3. Determining the optimal connections of Germany to other regions for importing hydrogen, low-carbon electricity for hydrogen production, and exporting of CO₂. This network analysis includes international hydrogen transport options (liquified hydrogen, ammonia, etc.) specifically from Norway, France, and North Africa.

Principal investigator: Emre Gençer

Assessment of Geologic Hydrogen Potential for Sustainable Energy Systems: A Cost and Emission Analysis Perspective

Principal investigator: Guiyan Zang

Assessing the viability of the global low-carbon fuel supply chain for maritime applications

Maritime shipping drives the global economy, carrying over 80% of global trade. With the vast majority of today’s vessels burning fossil fuels, a deliberate and informed transition to low-carbon fuels is needed to decarbonize this critical industry while maintaining a reliable maritime fuel supply chain. A number of alternative fuels have emerged in recent years with potential to decarbonize the sector. This project is focused on:

1. Building a maritime fleet model to perform techno-economic analysis and lifecycle assessment of alternative fuel pathways for a set of representative vessel types and powertrain technologies.
2. Creating a global low-carbon fuel supply chain model to evaluate feedstock requirements, as well as costs and timelines needed to build a robust supply chain for each low-carbon fuel considered.
3. Developing a science-based understanding of theoretical best-case limits for the technologies and processes involved in end use of alternative fuels.

Principal investigators: Elsa Olivetti, Guiyan Zang, Danika MacDonell

Assessing role for natural gas in future low-carbon U.S. electricity systems

Concerns over climate change along with rapidly falling costs of clean energy technologies have led to increased scrutiny over the role of fossil-fuels in a low-carbon energy future. This project is focused on:

1. Evaluating the role of natural gas-fired power plants (NG) in future electrical grids using an advanced, multi-period capacity expansion modeling framework with perfect foresight
2. Modeling cost-optimal grid operations, investments, and retirements through 2050 using a detailed representation of the American Southeast’s electrical grid which includes inter-region transmission, variable renewable energy resource characteristics, brownfield capacity and lifetime and economic retirements
3. Examining several pathways to a highly decarbonized grid, assuming rapid growth in energy demand through mid-century

Principal investigator: Dharik Mallapragada

Assessing vulnerabilities in global terrestrial and atmospheric hydrogen sinks and the risk of unintended future-climate consequences

Hydrogen leakages are inevitable under a global, low-carbon economy fueled by hydrogen-based energy technologies at scale. Atmospheric hydrogen (H₂) is considered an “indirect greenhouse gas,” in that increases in atmospheric H₂ concentrations lead to increased lifetimes of powerful greenhouse gases – primarily methane.  The concentration of atmospheric H₂ is controlled mainly by its consumption by bacteria in the soil. Changes in global soils due to climate and land use/management may reduce H₂ consumption in soil, thereby increasing atmospheric H₂ and amplifying the indirect climate warming effect of H₂ emissions. This project is focused on:

1. Determining the extent that climate change and land use change may impede the global soils’ consumption of atmospheric hydrogen.
2. Assessing how increased atmospheric H₂ due to reduced soil H₂ consumption may increase concentrations and lifetime of methane and other greenhouse gases.
3. Identifying potential tipping points which could dramatically increase the climate impacts of hydrogen leakage.

Principal investigators: C. Adam Schlosser, Ron Prinn, Sebastian Eastham

Atoms-to-enterprise analysis for decarbonization of chemical manufacturing: Case study of ethylene

Addressing climate change will require decarbonizing industrial processes, which accounted for 26% of global CO₂ emissions in 2019. This project is focused on:

1. Studying alternate low-carbon routes for production of ethylene using a multi-scale analysis approach
2. Utilizing techno-economic (TEA) and systems analysis to study the cost, scalability and life cycle environmental impact of four alternative decarbonization approaches for ethylene production
3. Designing and characterizing a new class of active anode materials to enable an emerging decarbonization route via electrochemical oxidative coupling of methane

Principal investigators: Dharik Mallapragada, Elsa Olivetti, Bilge Yildiz

Building Decarbonization Pathway with Technology, Market, and Policy Uncertainty

Decarbonizing commercial and residential buildings is essential for achieving net-zero targets. Despite the recent advances in electrification technologies, adoption has been hindered by behavioral barriers, policy gaps, and market failures. Addressing these challenges requires targeted decision-making tools and actionable strategies to accelerate decarbonization in the building sector. This project will focus on:

• Develop a comprehensive, theory-grounded decision-making framework for stakeholders, such as building owners/tenants, investors, policymakers, utility firms, and property managers, to evaluate costs, benefits, barriers, and incentives of decarbonization pathways at the building and portfolio levels.
• Conduct a real estate project decarbonization case study to validate the framework and provide critical insights into overcoming policy and market barriers.
• Develop a user-friendly toolkit to simulate alternative building decarbonization pathway options at the portfolio level with various scenarios under uncertainties. Generate practical recommendations for strategies that governments and practitioners can adopt to design and advocate for effective incentives, stakeholder collaboration, to accelerate building decarbonization.

Principal investigators: Siqi Zheng, Christopher Knittel

Can Mobility-as-a-Service (MaaS) really disrupt private car ownership?

This project is focused on:

1. Understanding the factors influencing consumer willingness to adopt MaaS as a substitute for private vehicle ownership
2. Measuring the "option value" of owning a car separately from the utility of using a car in the U.S.
3. Exploring the system-level attributes of MaaS that will be most important in determining its competitiveness with the private automobile

Principal investigators: David Keith, Joanna Moody

Can Strategically Designed Industrial Carbon Hubs Enable Widespread CCUS Adoption?

Carbon capture, utilization and storage (CCUS) will play a key role in industrial decarbonization in the United States. The hardest-to-abate (HtA) and highest emitting industrial sectors (e.g., cement, steel, chemicals) face increased pressure for achieving net zero targets and are likely first-movers for CCUS deployment. The objective of this research is to investigate cost-effective strategies to implement CO2 capture, transport, and storage infrastructure at scale for HtA industries. Using spatial-economic optimization, the potential for a large-scale pipeline network based around the location of “carbon hubs” – collections of nearby industrial facilities – is analyzed to understand opportunities to maximize capture potential by lowering investment barriers. This project is focused on:

1. Characterizing the costs associated with building out carbon capture, transport, and storage infrastructure for the hardest-to-abate industries at scale
2. Quantifying the role that carbon hubs can play in enabling broader industrial decarbonization
3. Exploring the willingness-to-pay for CCUS investment and perception and barriers to CCUS technologies through semi-structured interviews with key stakeholders

Principal investigators: Randolph Kirchain, Franz-Josef Ulm

Characterizing the Trade-Off between CO2 Capture Rate and Energy Efficiency in Amine-Based Carbon Capture under Variable Feed Conditions

Amine-based carbon capture technology is playing a pivotal role in mitigating carbon emissions across industries that lack scalable decarbonization solutions, such as power generation, refining, and chemical production. The state-of-the-art design practices for the amine-based carbon capture process aim to determine optimal sizing of the key process units, including absorbers, strippers, and heat exchangers, minimizing energy consumption and capital costs while achieving target carbon capture rates (e.g., 95%) under a fixed flue gas condition. However, to ensure their robust performance in practice, the design optimization problem must account for multiple scenarios in the feed conditions to ensure their robustness. Furthermore, there exists a trade-off between carbon capture rate and energy efficiency that must be quantitatively characterized to make informed design decision-making. This project will focus on:

• First-Principles Modeling: Develop and enhance first-principles models of amine-based carbon capture plants that incorporate transient behaviors and chemical reaction kinetics. This will enable the formulation of the design optimization problem.
• Stochastic Design Optimization: Formulate a stochastic optimization problem that maximizes energy efficiency while meeting specified CO2 capture rate goals across multiple dynamic scenarios. By integrating the developed process and uncertainty models, the optimization will identify optimal design configurations that balance high carbon capture rates with energy and cost efficiencies under uncertain and variable operating conditions.
• Trade-off Analysis: To quantitatively characterize the trade-off, the design optimization problem will be solved with a range of carbon capture rate goals. This result will precisely quantify the trade-off and will enable informed decisions on making carbon capture rate goals.

Principal investigator: Sungho Shin, Guiyan Zang

Chemistry and climate effects of potential hydrogen leakage

While hydrogen itself is not a greenhouse gas, any leakage of hydrogen used in the energy system has the potential to affect climate because of its atmospheric chemistry. This project is focused on:

1. Carrying out model calculations to evaluate the Global Warming Potential (GWP) and temperature impacts of potential hydrogen leakage in the current and future atmosphere.
2. Identify key uncertainties in hydrogen GWPs for long and short timescales.
3. Evaluate the potential for hydrogen fuel use to contribute to avoiding exceedance of the 1.5 and 2°C thresholds identified by the Paris agreement for various scenarios of usage and leakage.

Principal investigator: Susan Solomon

CO2 capture and conversion: The where, what, and who of co-location

The capture and transformation of CO₂ into useful products is a promising approach towards net-zero emissions with the potential to reshape the global economy. Co-location of the capture and conversion processes within the same operational plant may convey significant benefits by eliminating the need to compress and transport CO₂ between the capture location and the conversion location, thereby reducing energy and capital requirements. This project is focused on:

1. Examining optimal product-CO₂ source-geographic location combinations while assessing scalability and costs.
2. Developing technoeconomic models to estimate the end-to-end cost of carbon capture and conversion including comparison of capture and conversion as separate steps versus integrated capture and conversion (ICC).
3. Identifying a specific industry, geographical location, and product that provides the most attractive opportunity for co-located capture and conversion.

Principal investigator: Kripa K. Varanasi

Comparative analysis of decarbonization strategies for transportation via direct air capture of CO2

Tough-to-decarbonize transportation (aviation, maritime shipping, and heavy-duty trucking) currently emits between 2 and 4 billion metric tons (Gt) of CO₂ per year. By 2050, these modes alone might deplete around 25% of the remaining 1.5°C carbon budget. This project is focused on:

1. Comparing the economy-wide net emissions, systems costs, and abatement costs associated with two alternative Direct Air Capture-based strategies for fueling transportation: a) use of captured CO₂ plus green hydrogen to make synthetic fuels, and b) permanently store captured CO₂ to offset carbon emissions associated with the continued use of petroleum-derived fuels
2. Determining under what conditions each Direct Air Capture-based option is cost effective, and how these costs compare to other low-carbon fuel options for transportation
3. Understanding how the results may be affected by uncertainty in future pathway designs, as well as various policy and market conditions and levels of technology development and scale-up

Principal investigator: Steven Barrett

Comparative assessment of low-carbon liquid energy carriers for long-haul trucking

Long-haul trucking is one of the most difficult sectors to decarbonize, but decarbonization of this growing transportation mode is required to meet climate change mitigation goals. Long-haul trucking requires a high energy density energy carrier to provide long driving range without inordinate impact on the freight carrying capacity. This makes electrification and direct use of the hydrogen quite challenging for long-haul trucking. Low-carbon liquid energy carriers are a promising approach for decarbonizing trucking due to their much higher energy densities than is possible with batteries or hydrogen. This project is focused on:

1. Assessing the life-cycle cost and greenhouse gas emissions of several liquid energy carriers that are candidates for long-haul trucking. These options will include drop-in fuels, methanol, ammonia, and liquid organic hydrogen carriers.
2. Developing and demonstrating a consistent comparative assessment platform for the cost and emission impact of liquid energy carrier operations
3. Clarifying issues/challenges associated with each of the liquid fuels options, including some of the interactions with other sectors (e.g. electric grid, aviation, shipping, agriculture & forestry).

Principal investigators: Emre Gençer, William Green

Competitive Profiles for Thermal Long Duration Energy Storage

Energy storage is likely to play an important role in decarbonized grids. A variety of new technologies are being developed, many focused on long duration energy storage. One class is thermal energy storage technologies, including, for example, crushed rock technologies. Better insight into the drivers of the competitiveness of thermal energy storage is needed. Understanding the drivers can be vital to optimizing investments across charge and discharge capacity as well as storage capacity, and to efficiently targeting technology development across these features. This project is focused on:

• Determining whether alternative forms of thermal energy storage can compete as viable options for long-duration energy storage.
• Evaluating the optimal design of a coupled thermal storage system—the size of charge capacity, size of stored energy capacity, and size of discharge capacity—depending on the technology and cost parameters.
• Understanding how the competitive space for long duration energy storage varies across different grids and identifying which ones can benefit the most.

Principal investigators: Charles Forsberg, John Parsons

Contribution of methane pyrolysis (turquoise hydrogen) by-products to the sustainability of the built environment

Hydrogen is widely viewed as a vital energy carrier for economy-wide decarbonization. One of the low-carbon pathways for hydrogen production is methane pyrolysis, which converts methane to hydrogen and solid carbon.  To improve the economic viability of this hydrogen pathway, the carbon by-products need to generate revenue. The construction sector may be the largest market for methane pyrolysis by-products. In some cases, incorporating carbon by-products (carbon fibers and nanotubes) into concrete can improve mechanical performance and contribute to lowering the embodied and operational GHGs of buildings and pavements. This project is focused on:

1. Estimating the potential quantity of carbon by-products that can be accommodated in the US building and pavement sectors.
2. Calculating how much less construction materials would be required by incorporating carbon by-products to strengthen concrete structures.
3. Projecting how much energy and emissions can be saved by improving rolling resistance for vehicles traveling on road surfaces improved by the inclusion of carbon fibers and nanotubes.

Principal investigators: Randolph Kirchain, Richard Roth

Cost-performance analysis and benchmarking of CO2 capture systems for hard-to-abate industries

Carbon capture and storage (CCS) is one of the most effective ways to decarbonize hard-to-abate industries like iron, steel, cement, and chemical production. Many of these emissions are generated at significantly higher temperatures (300 to >1400 C) depending on the process. Use of conventional amine systems requires cooling to much lower capture temperature, while molten salts can capture carbon dioxide at elevated temperatures. This project is focused on:

1. Quantifying the potential of molten salts, as exemplar versatile-temperature capture media, for post-combustion CO₂ capture from various industrial flue gas streams and comparing against more mature carbon capture technologies
2. Examining opportunities for temperature-matching emissions streams with sorbents at similar conditions and with representative emissions properties appropriate to several key industries
3. Performing techno-economic assessments and comparisons of promising CCS technologies (molten salts, solvents, and adsorbents) for each of five industries (steel, cement, ethylene, aluminum, copper)

Principal investigators: Guiyan Zang, Betar Gallant, T. Alan Hatton

Developing trustworthy MRV for marine Carbon Dioxide Removal (mCDR)

Utilizing the ocean to remove anthropogenic CO2 has profound potential to mitigate climate change, but it faces major challenges. Foremost among these challenges is the trustworthy quantification of CO2 drawdown – commonly referred to as Measurement, Reporting, and Verification (MRV) – that is critical to underpin a global carbon market. MRV is particularly demanding due to the vast and dynamic transport nature of the oceans, and thus it is important to monitor in close proximity (near-field) to a marine Carbon Dioxide Removal (mCDR) site. This project is focused on:

1. Reviewing the near-field physics of a trial coastal mCDR operation and identifying what must be accounted for to achieve trustworthy Measurement, Reporting, and Verification (MRV).
2. Demonstrating the importance of the near-field to the broader mCDR community by focusing on a particular type of mCDR intervention, called direct ocean capture (DOC).
3. Developing a program with the MIT Policy Lab to connect with national (e.g. OSTP, NOAA, DOE) and international (e.g. UN, OECD) policymakers and advisors.

Principal investigator: Thomas Peacock

Development of a building retrofit adoption model

To transition to a carbon neutral building stock by 2050, the annual retrofit rate of less than 1% today will need to increase to 4-5% while all new construction will need to be carbon neutral by 2030. This project is focused on:

1. Developing a techno-economic adoption model for various building retrofit packages
2. Calibrating the model based on a combination of historic adoption costs of select technologies including photovoltaics, double pane windows and solid-state lighting, as well as new user surveys

Principal investigator: Christoph Reinhart

Development of Distributed Energy Consumption in Actively Responsive Buildings (DECARB) model

Buildings are a major source of carbon emissions. Their decarbonization demands two main actions: electrifying the heating loads to eliminate emissions from gas or oil burning, and implementing energy efficiency measures, particularly, weatherization to reduce the energy consumption. This project is focused on:

1. Improving MIT's DECARB model by characterizing heat pumps and batteries accurately
2. Improving the thermal enclosure representation of buildings in the DECARB model
3. Adding socioeconomic features into the model to compensate the energy transition "losers"—typically, low-income consumers

Principal investigators: Pablo Duenas-Martinez, Karen Tapia-Ahumada

Dual-Energy Climate Challenge: Enhancing Infrastructure Resilience with Satellite Earth Observation (EO) Data and AI

Renewable energy infrastructure is crucial for mitigating climate change and addressing the dual energy-climate challenge. However, these systems are highly susceptible to the impacts of climate change, including extreme weather events such as high temperatures, severe droughts, and flooding, reducing the efficiency and lifespan of renewable energy installations and affecting energy supply and demand. As the frequency and severity of climate-related events increase, this project focuses on leveraging advanced technologies such as satellite Earth Observation (EO) data, AI, and advanced data visualizations to enhance the resilience of renewable energy infrastructure. This project is focused on:

1. Utilizing satellite EO data and advanced data visualization tools to identify critical climate-related hazards affecting energy systems
2. Leveraging AI-driven predictive models to enhance climate risk planning and resilience for existing energy infrastructure
3. Developing a data-decision framework using advanced EO and AI technologies to optimize site selection for renewable energy infrastructure to enhance efficiency and resilience

Principal investigators: Dava Newman, Minoo Rathnasabapathy

Electricity retail rate design to support decarbonized power systems and economy-wide electrification

Increased electrification without tapping the potential of demand flexibility would render decarbonization efforts unnecessarily inefficient and expensive and would thus endanger an inclusive energy transition. This project is focused on:

1. Investigating alternative rate structures that allow the variability in the value of electricity across time to be passed through to customers to provide better incentives to consume electricity efficiently, while limiting the risk associated with excessively high prices
2. Applying a mix of empirical methods, simulation, and optimization to explore how to appropriately evaluate alternative retail rate designs and determine what type of alternative retail rate designs are suitable in different power system contexts characterized by a supply mix dominated by intermittent generation and varying attributes of demand-side participation
3. Assessing the fitness of the current regulatory framework to incentivize the adoption of innovative retail rates as well as the general properties of innovative alternatives

Principal investigators: Dharik Mallapragada, Tim Schittekatte, Christopher Knittel, Paul Joskow

End use of agricultural waste: Fuel or carbon storage?

Agricultural residues present a 3-8 Gt/year potential resource derived from atmospheric CO2 that currently are primarily left on the field or burned in place – both practices fast-cycling carbon back to the atmosphere. Changing the end use of agricultural residues presents an opportunity for climate beneficial practices such as conversion to biofuel or long-term carbon storage. The “best” end use will likely depend on the location and proximity to processing facilities or storage opportunities, such that a geospatial analysis weighing climate benefits, cost, and systems-level impacts is needed for implementation. This project will focus on:

• Modeling the availability of agricultural wastes globally with current uses to identify where the largest opportunities to reduce greenhouse gas (GHG) emissions are (i.e., by avoiding burning residues).
• Calculating life-cycle emissions for different agricultural waste end use scenarios (burned in place, pyrolyzed to fuel, long-term carbon storage as char, among other scenarios), with location-specific energy, efficiency, and transportation included.
• Developing a geospatially-resolved tool to help guide decision making regarding the “best” use of agricultural wastes in a specific location.

Principal investigators: Desiree Plata

Ensuring a financially sustainable, just, and inclusive energy transition

Geopolitical unrest and extreme climate events can greatly raise electricity prices. Furthermore, power system decarbonization and the energy transition will lead to increased electricity price volatility, more frequent periods of sustained high prices and the potential for huge energy costs to be passed on to consumers. These can result in affordability issues for a significant share of consumers and competition challenges for industry. The standard objective of power market design and regulation is to organize the power sector as efficiently as possible. At the same time, electricity should be affordable for all citizens, as it is a basic need in our modern society. Thus, to facilitate a financially sustainable, just, and inclusive energy transition, innovative regulatory and policy ideas are needed. This project is focused on:

1. Developing realistically implementable affordability mechanisms to protect vulnerable tranches of end users while respecting the basic market competition rules and avoiding any distortion of the short-term market price signal
2. Conducting an in-depth review of current programs and the best international practices on energy poverty with the aim of not only proposing innovative policies to efficiently protect vulnerable customers, but also to enable these customers to actively participate in the energy transition

Principal investigators: Tim Schittekatte, Carlos Batlle, Christopher Knittel

Evaluating the Impact of Data Center Deployments on the US Power System

The rapid growth of data centers is reshaping the global energy landscape, presenting both challenges and opportunities for power systems. In the U.S., data centers impose large demands on power grids due to their constant need for reliable energy. At the same time, the inherent flexibility of data centers, including their ability to shift workloads across space and time, positions them as potential assets for grid stability and demand response initiatives, which will gain importance with increased penetration of renewables. These countervailing effects raise critical questions about their implications for generation capacity investments, energy pricing, emissions, and decarbonization goals. This project will focus on:

• Designing and solving cost/multi-objective optimization problems to determine optimal Data Center locations and demand response approaches.
• Investigating the impacts of Data Center load on US power system using the GenX capacity expansion model
• Crafting and assessing policy options to incentivize data centers in capturing system benefits

Principal investigators: Christopher Knittel

Exploring the Interplay Between H2 Production and Renewable Fuel Synthesis

Hydrogen is a promising fuel for decarbonization; however, its adoption is often stunted by the high delivery cost if it is transported as a cryogenic liquid or compressed gas. A way to bypass these difficulties involves the conversion of hydrogen to liquid energy carriers such as methanol, ammonia, and liquid organic hydrogen carriers. Our project centers on using the waste heat from these conversion processes in the production of hydrogen to improve system efficiency and emissions. Heat requirements and availability for hydrogen and liquid energy carrier production processes differ greatly by the process choice, and the favorability of each process is region-dependent due to differences in utility prices and local resources. Thus, the optimal pairing of hydrogen production and liquid energy carrier conversion processes is location-dependent. This project is focused on:

1. Identifying which liquid fuel production pairs best with each hydrogen production method in each region.
2. Exploring different waste-heat use cases, such as biomass drying for methanol production and carbon capture solvent regeneration.
3. Performing a detailed technoeconomic assessment to quantify the value of integration between hydrogen production and conversion to liquid fuels.

Principal investigators: William Green

Flexibility and firm power in future zero-carbon power systems

In this research we aim to understand how increasing amounts of solar and wind energy can be integrated into the power system while maintaining energy affordability and reliability. Our project aims to uncover how near-term and medium-term investment decisions regarding capacity expansion in the power system can best be aligned with a longer-term goal of a net-zero-carbon energy system. This project is focused on:

1. Using a multi-dimensional analysis to identify favorable technology portfolios that represent robust net-zero-carbon solutions under conditions of uncertainty in the evolution of technologies and energy systems.
2. Investigating the role of energy storage, transmission, demand response, supplemental fuels, and thermal generation in providing firm power and flexibility in zero-carbon power systems
3. Advancing an approach to expansion modeling that identifies desired levels of detail and abstraction based on sources of uncertainty, research questions of interest, and applications of insights to decision-support.

Principal investigators: Audun Botterud, Jessika Trancik

Future of work and urban mobility: Integrated public transit and shared mobility

Over 60% of hiring managers in the U.S. plan to increase the location and schedule flexibility of work arrangements on a permanent basis. This disruption of the status quo and uncertainty about future travel demand creates a need for a more responsive mobility system that adapts to constantly evolving demand patterns. This project is focused on:

1. Collecting primary data to understand the spatial and temporal changes in travel demand caused by a shift towards the future of work
2. Developing a planning framework to design a transit-centric multimodal urban mobility system supported by shared mobility
3. Generating insights into future travel demand evolution and developing the tools needed to support a transition towards sustainable urban mobility

Principal investigator: Jinhua Zhao

High fidelity monitoring for carbon sequestration: Integrated geophysical and geochemical investigation of field and laboratory data

A promising geologic carbon sequestration strategy is CO₂ mineralization, the conversion of gaseous CO₂ into carbonate minerals. Basaltic rocks, because of their widespread occurrence and high reactivity have received great attention as an attractive sequestration approach. However, many challenges to geologic carbon sequestration in basaltic reservoirs remain regarding rock deformation, fluid flow and reaction rates. This project is focused on:

1. Developing a better understanding of rock deformation of mineralization, and the concomitant volume, stress changes, and reaction rates
2. Understanding the mechanical properties and pore structure changes that affect both geophysical parameters and fluid flow
3. Developing and calibrating in a laboratory setting, sensitive monitoring methods for the geophysical and geochemical changes accompanying sequestration

Principal investigator: Matej Pec

Identification of the best steel decarbonization options for different regions

Steel production is responsible for more than 2.5 gigatons of carbon emission and is one of the more difficult sectors to decarbonize.  The options for decarbonization differ by resources available in each region and by the quality of the iron ore. This project is focused on:

1. Identifying the best decarbonization scenarios for steel production in India, U.S., China, Japan, Germany, Turkey, and Brazil
2. Comparing the cost and emissions of low-carbon scenarios by the combination of BF, SR, DRI, and EAF based on the regional steel production market
3. Identifying the best practical steel decarbonization scenarios by region based on cost, emissions, and demand

Principal investigators: Guiyan Zang, Emre Gençer

Impact of multi-dimensional uncertainty in long-term investment planning

Planning for the long-term evolution of the power system requires consideration of the uncertainty in key technology, economic, and policy drivers. Existing approaches to incorporate uncertainty in power system planning generally rely on formulating scenario-based stochastic programs, which are limited in the number of scenarios and investment stages that can be considered while maintaining computational tractability. This project is focused on:

1. Exploring new models for investment planning under uncertainty that use linear decision rules to incorporate multiple dimensions of uncertainty in a computationally scalable manner
2. Demonstrating the value of the proposed multi-stage generation-planning formulation by exploring the collective impact of uncertainty in carbon policies, technology costs, and system demand on near-term investments in generation, networks and storage capacity

Principal investigator: Dharik Mallapragada, Audun Botterund

Implications of broad electrification on the power networks and large penetration of distributed energy resources

The potential growth in electricity demand in the building and transportation sectors would put pressure on local, low-voltage power networks causing significant grid operational challenges that will require mitigation measures and a better understanding the role of Distributed Energy Resources (DERs). This project is focused on:

1. Understanding the current landscape towards energy transition in terms of available technologies, business models, and evolving regulation
2. Understanding the impacts of DERs in electricity distribution networks
3. Investigating the role of efficient economic signals (cost-reflective electricity tariffs) in driving adoption of DERS and their operation

Principal investigators: Pablo Duenas-Martinez, Karen Tapia-Ahumada

Incorporating Weather Information into Power Resource Accreditation and Capacity Mechanisms in Wholesale Electricity Markets

To address the global climate challenge, electric power systems are transitioning towards clean resources dominated by weather-driven variable renewable energy (VRE) like wind and solar. However, the shift to VRE technologies brings challenges to reliable electricity supply due to the uncertainty, variability, and limited dispatchability of these resources.Existing methods for assessing resource adequacy may no longer suffice, especially as extreme weather events linked to climate change increase. Current capacity market rules may allow overestimation of the contribution towards system reliability from individual resources, reducing incentives for investment in dependable capacity. Addressing these issues requires better integration of weather data and extreme events into resource planning. This project will focus on:

• Proposing a new stochastic resource accreditation framework with an improved representation of weather impacts on both VRE and thermal generators.
• Proposing an economically efficient resource accreditation method to quantify capacity value and inform market participation strategies under different weather scenarios for industrial stakeholders (e.g., generation companies, utilities, large consumers).
• Using the framework to model long-term market equilibrium under different market designs, and assess the economic efficiency (e.g., investment mix and system cost) in incentivizing power resource adequacy for policy makers and system operators

Principal investigators: Audun Botterund

Liquid air energy storage technoeconomic analysis

Liquid air energy storage is the only clean and locatable long-duration energy storage technology currently capable of delivering multiple GWh of energy storage. This project is focused on:

1. Evaluating the potential for widespread adoption of liquid air energy storage systems by performing a techno-economic assessment using a novel non-smooth analysis approach with optimization
2. Utilizing nonconvex optimization formulations to determine simultaneously the fixed design and operating decisions that maximize the net present value of the liquid air energy storage project over its lifespan
3. Performing optimizations of results and conducting sensitivity analyses with respect to design and cost parameters to establish a baseline for the technical and economic performance of liquid air energy storage systems, which can inform future research and guide investment decision-making

Principal investigator: Paul Barton

Long-haul freight on highways: Techno-economic assessment of options for powertrains and fuels

In many countries most long-haul freight is carried by diesel trucks on highways, always with significant CO₂ emissions and sometimes with significant particulate and NO_x emissions. This project is focused on:

1. Assessing alternative powertrains and fuels combinations to see which offer significant advantages at reasonable cost
2. Examining the emissions reduction potential of alternative powertrains and fuels
3. Understanding the obstacles to deployment of alternative powertrains and fuels

Principal investigator: William Green

Lower cost, CO2-free, H2 production from CH4 using liquid tin

Hydrogen production is responsible for about 1% of global CO₂ emissions, which predominantly come from steam methane reforming (SMR). To eliminate CO₂ emissions, economically competitive approaches to making CO₂-free hydrogen are needed. This project is focused on:

1. Developing an extreme temperature methane pyrolysis process to achieve close to 100% single-pass conversion facilitated by an inert liquid metal (Tin) to avoid solid carbon plugging of the reactor
2. Developing models of the pyrolysis reactor to better understand the conversion performance and temperature dependence
3. Assessing the techno-economics and life cycle emissions of this pyrolysis process relative to alternative hydrogen production options

Principal investigators: Paul Barton, Asegun Henry

Maximizing security and resilience to cyber-attacks in a power grid

Large-scale and unforeseen cyber-attacks impacting critical infrastructure are becoming a daily occurrence. A combined presence of both cyber and physical attacks require entirely new tools for analysis of an emerging cyber-physical energy grid that is rich in distributed energy resources including decarbonized variable energy resources. This project is focused on:

1. Categorizing various cyber physical attacks in terms of types and impact on the energy grid
2. Increasing the visibility for system operators into the distribution grid by providing them with the situational awareness (SA) about the complete system in real-time
3. Developing resilience scores for all subsystems in the energy grid for risk assessment

Principal investigators: Anuradha Annaswamy, John Williams

Medium-term impact of COVID-19 on urban mobility: Behavior, preference, and energy consumption

All transportation modes, including driving, walking, and cycling, have been impacted by the spread of COVID-19. Even when the virus is no longer a threat to public health, residual effects may influence activity, destination, and mode choices which in turn will impact transportation sector energy consumption. This project is focused on:

1. Quantifying the behavioral and preference change in the medium term after COVID-19
2. Analyzing the change with sociodemographic data, built environment data, and different operational strategies of transportation
3. Understanding the impact of COVID-19 on mobility for different social groups, and what operational strategies, infrastructure and equipment changes may help them recover, and translate the behavioral changes into energy consumption estimates

Principal investigator: Jinhua Zhao

Modeling thermal energy storage: Differentiating technologies by industrial application

Thermal energy storage (TES) could significantly contribute to decarbonization of energy systems including industrial applications. It is cheap enough to scale to GWh of storage, and a more mature technology than alternative candidates for long duration energy storage. However, operating TES can be more complicated than electrochemical systems such as Li-ion batteries. Our present models of TES in capacity expansion planning tools do not reflect these operational challenges. This project is focused on:

1. Reviewing the most promising TES technologies including latent and sensible heat storage systems.
2. Building computationally efficient models and testing a variety of approximations for each technology to understand the trade-off between accuracy and computational cost.
3. Evaluating how accurate TES models impact the results of two real-world case studies: the Dallas-area electricity grid, and a cluster of Houston-area industrial heat and electricity consumers.

Principal investigators: Ruaridh Macdonald, Guiyan Zang

Multi-Scale Production Cost Modeling for Optimal Storage Investment

This project aims to develop computational and modeling capabilities to estimate the economic value of energy storage within utility grids. It is essential for utility providers seeking to invest in energy storage to help decarbonize their energy portfolios. The traditional metrics, like the levelized cost of storage, inadequately capture the value of energy storage as they neglect system-specific factors and uncertainties. We propose to address this issue with a multi-scale production cost modeling approach, where a tailored value of energy storage is computed by running simulations. We will further enhance this capability with uncertainty quantification and high-performance computing techniques. This project is focused on:

1. Developing the multi-scale production cost model for utility grids with renewables and energy storage, focusing on capturing the energy storage operations at sub-hourly time scales.
2. Providing multi-faceted characterization of the value of storage by quantifying uncertainties in the estimated marginal value of storage
3. Exploring the computational strategies to reduce the high computational cost of long-term production cost simulations and uncertainty quantification

Principal investigators: Sungho Shin

Multi-vector energy systems analysis for low-carbon power and transportation

A promising pathway for decarbonization of heavy-duty transport includes the use of hydrogen directly, or producing synthetic fuels from electricity and/or H₂ and captured CO₂ streams that can directly substitute for current petroleum-based, hydrocarbon fuels such as diesel. This project is focused on:

1. Evaluating the system-wide greenhouse (GHG) emissions and cost impacts of pursuing transport decarbonization via different penetration levels of electricity, H₂, and synthetic fuels
2. Expanding energy systems modeling tools on electricity-H₂ infrastructure planning to include alternative CO₂ supply sources and synthetic fuel production pathways while accounting for their operating and investment costs as well as power system impacts
3. Applying expanded energy systems modeling tools to investigate pathways for power and transport sector decarbonization for European countries near the North Sea

Principal investigator: Dharik Mallapragada

Negative emissions technologies: A question of scale

Mitigation of global warming trends caused by rapid CO₂ accumulation in the environment requires carbon dioxide removal. There are potential opportunities for distributed smaller-scale capture units to be placed strategically where high CO₂ concentration levels could provide enhanced thermodynamic and kinetic performance, and/or that take advantage of existing and planned infrastructure. This project is focused on:

1. Assessing the technical feasibility of carbon removal from urban and non-urban environments using distributed capture units, with consideration to logistics of collection and disposal/use of captured CO₂, aesthetics, societal acceptance, and policy
2. Developing a clear picture of the appropriate research and technology development needs, and an assessment of their relative merits, for collecting CO₂ from a wide variety of locations (large-scale units, distributed units, off-shore or on-shore ocean water, rivers, lakes, and dams, etc.)
3. Identifying materials and engineering needs to ensure acceptable capital and operational costs of such systems

Principal investigators: Betar Gallant, T. Alan Hatton

Optimal energy distribution infrastructure for EV fast-charging and hydrogen stations

Decarbonization of the transportation sector through a transition to electric and hydrogen vehicles requires adequate infrastructure for electric vehicle (EV) fast-charging and hydrogen fueling. This project is focused on:

1. Developing a novel energy distribution optimization tool (OP-EVH2) for local planning of EV fast-charging and hydrogen fueling stations to study the impact of investments on local electricity distribution networks
2. Investigating the role of distributed energy resources such as solar PV, energy storage, and electrolyzers in decreasing the burden on the electricity distribution system
3. Developing a planning and operation optimization framework accounting for the local electricity and hydrogen demands from the transportation sector, local renewables and energy storage investments, and on-site hydrogen production

Principal investigator: Audun Botterud

Optimization for the joint resiliency of power grid and e-transportation

As both the electric power system and the transportation system decarbonize, their interdependence will increase dramatically. If managed well, this interdependency could also be a huge asset for helping enhance the resiliency of the two systems. This project is focused on:

1. Developing comprehensive optimization models for the joint planning and operation of the electric grid and electrified public transit systems to improve their resiliency and adaptability to severe weather events.
2. Studying the welfare and fairness impacts of the electrification of public transit system on different communities.
3. Studying how renewable resources, advanced battery storage technologies, and V2G could be used to support the growth of electric transportation systems and their resiliency.

Principal investigator: Andy Sun

Pathways towards gigaton scale low-carbon H2 production

Hydrogen has the potential to play a central role in a future low-carbon energy system. However, realizing its full potential will require annual production of hydrogen at the gigaton scale, orders of magnitude higher than current production levels. This project is focused on:

1. Benchmarking the costs and life cycle emissions of hydrogen production via natural gas autothermal reforming (ATR) with carbon capture
2. Performing techno-economic analysis of three types of existing electrolysis technologies (PEM, Alkaline, Solid-Oxide) and two emerging electrolysis approaches (anion exchange membranes (AEM) and intermediate temperature)
3. Investigating the potential of intermediate temperature (200 to 500 °C) electrolysis technologies using nano-composite gel electrolytes

Principal investigators: Dharik Mallapragada, Yogesh Surendranath, Guiyan Zang

Pricing and location strategies of electric vehicle charging networks

In transitioning toward a low-carbon transportation system, refueling infrastructure is crucial for the viability of alternative fuel vehicles but requires significant government and private investment. This project is focused on:

1. Conducting research on travel patterns, electric vehicle charging demand, and electric vehicle adoption to develop a model of consumer vehicle and travel choices
2. Utilizing the data to look for evidence of complementarity spillovers across space in refueling, which is the idea that one location may be more valuable to the rest of the refueling network than its own profits
3. Simulating the profits of electric vehicle charging networks as well as adoption rates of electric vehicles with different pricing and location strategies of charging networks

Principal investigator: Jing Li

Quantifying Cost, Schedule & Licensing Hurdles of Small Modular Reactors for Industrial Settings

Major grid modeling studies have emphasized the role of dispatchable carbon-free electricity sources in the net-zero world, resulting in increased interest in nuclear energy technologies. Small Modular Reactors hold the promise of balancing the financing hurdles of large reactors while lowering the schedule overruns, commonly seen in nuclear construction projects, because of their smaller overall installation scope. For deployment in an industrial setting, additional hurdles ranging from licensing to operation & maintenance need to be quantified. We will leverage state-of-art cost and risk modeling tools to study two promising industrial sites. This project is focused on:

1. Assessing the site-specific impact of deploying two small modular reactor technologies on two industrial sites to perform a detailed bottom-up analysis
2. Quantifying the impact of licensing, project management, regulation, engineering, procurement, and construction
3. Projecting levelized cost of electricity, including operation and maintenance costs for a range of scenarios with different risk profiles

Principal investigator: Koroush Shirvan

Reinforcement learning for guiding drivers to reduce congestion in the developing world

Recent work has shown that introducing 5-10% of actuated vehicles (e.g. autonomous vehicles (AVs)) can significantly alleviate congestion in idealized traffic scenarios. Teaching human drivers congestion-mitigation techniques, which are currently implementable by AVs, can have significant beneficial impact. This project is focused on:

1. Developing a machine learning approach for designing driver guidance to enable improvements in congestion
2. Studying the approaches, capabilities and implementation trade-offs using numerical experiments to derive theoretical performance guarantees, and perform a region-specific cost-benefit analysis
3. Creating a personalized app that will provide drivers with basic suggestions to help modify their driving in real-time to improve congestion at scale and in resource-constrained contexts

Principal investigator: Cathy Wu

Renewable Energy Siting for Low-Cost and Extreme Event-Resilient Power Systems Under Climate Change

Global power generation is increasingly decarbonized with renewable production, demand is electrifying and growing, and climate, weather, and extreme events are changing. Together, this results in an increasingly complex coupling between climate and energy systems where energy generation and demand depend more strongly on variations in weather and climate. Cost effective power system decarbonization requires system-wide coordination accounting for regional, spatiotemporal variabilities in renewable resources, time-varying energy demand, and power system constraints. Critical uncertainties in future climate conditions and their impacts on renewable supply and energy demand will pose risks to the resilience of future energy systems if they are not addressed in planning. This project is focused on:

• Developing a modeling framework for assessing and minimizing the risk to low-carbon energy systems from the uncertain effects of climate change and extreme events on energy supply and demand
• Elucidating best practices for renewable energy plant siting across real-world decarbonization pathways in diverse climate/geographic regions with minimized risk from climate change and extreme events
• Revealing geophysical and regional power grid drivers of resilient, low-cost power system designs for generalizable insights while capturing opportunities in local solutions to guide strategic investments

Principal investigator: Michael Howland

Scalability of biomass availability for producing transportation fuels

Replacing fossil fuels with biofuels is one of the major ways to decarbonize transportation. This project is focused on:

1. Assessing the scalability of biomass availability from dedicated land use and from waste and residues, and evaluating global and regional transportation demands, with a particular focus on aviation and shipping
2. Quantifying the tradeoffs for biomass supply and demand, utilizing and enhancing the global multi-region multi-sector economy-wide MIT Economic Projection and Policy Analysis (EPPA) model, considering many complex physical and socio-economic relationships and feedbacks
3. Developing an understanding of the opportunities for biomass feedstocks for fuels, chemicals, and other uses and assessing different sectors of the economy where biomass use will generate the highest value in terms of accelerating the energy transition

Principal investigators: Sergey Paltsev, Kristala Prather

Sector coupling in the context of energy transition: New approaches for investment planning

There is growing interest among policymakers, regulators and utilities to expand electrification to an increasing number of end-use sectors as a way to meet long-term economy-wide decarbonization goals. Electrification effectively shifts the burden of emission reductions to the power sector, where the availability of multiple zero-carbon generation and storage technologies lowers barriers to decarbonization. This project is focused on:

1. Developing scalable decision-support frameworks for joint infrastructure planning with adequate representation of temporal and spatial variability in cross-sectoral interactions in order to understand the merits of electrification of various end-uses
2. Developing extensions to power system capacity expansion models (e.g. GenX) to include possible investment in alternative energy vectors for decarbonizing difficult-to-electrify sectors
3. Examining modeling interactions between electricity and gas infrastructure and the possibility of retrofitting existing gas infrastructure to be compatible with hydrogen use

Principal investigator: Dharik Mallapragada

Slow Charging: A Techno-Economic Analysis Towards Accessible and Affordable Charging

For widespread electric vehicle (EV) adoption, charging must be affordable and accessible. While significant attention has been given to advancing fast charging geared towards long-distance travel, such costly solutions are not essential for daily commuting needs. In fact, 90% of individuals in the U.S. drive 30 miles or less per day, making slow charging more than sufficient to meet their daily requirements. Slow charging, or Level 1 charging, can adequately charge for this range during work hours or overnight. In this study, we aim to explore the potential impact of slow chargers on facilitating affordable and widespread EV adoption. This project is focused on:

1. An analysis of the impact of slow charging on the power grid and charging infrastructure, considering both grid-to-vehicle and vehicle-to-grid power flow.
2. The optimization of bidirectional on-board converters to efficiently support a wide range of power levels.
3. An identification of any necessary technology advancements required to leverage slow charging for mass EV adoption.

Principal investigator: Samantha Coday

Stored energy reserve market for grid resource adequacy

Grid operators are tasked with ensuring that there are enough generation and storage assets available and that these assets are optimally utilized to ensure resource adequacy to meet electricity demand. A key concern for grid operators regarding energy storage assets is their ability to contribute to resource adequacy, especially in anticipation of stressed events. Storage assets’ state of charge at any time is a function of how they are utilized, and therefore, storage assets are distinctly different from generation assets. Thus, capacity market rules must incentivize storage investment and operation to match the system’s resource adequacy needs. This project is focused on:

1. Determining what is the optimal system utilization and investment in storage assets, and how this optimum varies with uncertainty.
2. Assessing how competitive, profit-maximizing owners make investment and operating decisions regarding storage assets.
3. Exploring what energy reserve market design can incentivize the optimal utilization and investment in storage assets.

Principal investigator: John Parsons

Supply chain analysis of ammonia as a hydrogen carrier

As the world transitions to a low-carbon economy, the importance of low-carbon fuels in achieving this energy transition is increasingly evident.  The potential role of ammonia as an energy and hydrogen carrier is gaining prominence in global decarbonization discourse. Ammonia’s ability to be easily transported and stored in liquid form presents a significant advantage over hydrogen, making it a new focus in hydrogen decarbonization strategies. This project is focused on:

1. Examining what the future global ammonia supply chain will look like if optimized based on costs and emissions.
2. Collecting regional data regarding availability of energy sources for ammonia production and projected hydrogen and ammonia demand.
3. Developing a framework for optimization of the global ammonia supply chain in the years 2030 and 2050 to represent short-term and long-term scenarios.

Principal investigators: Guiyan Zang, Daniel Cohn, Leslie Bromberg, Ruaridh Macdonald

System impacts of decarbonization pathways for space heating in cold climates

Use of electrification in space heating of buildings is attractive as it eliminates distributed sources of CO₂ emissions, has associated efficiency benefits, leverages existing infrastructure and could provide a potentially flexible demand-side resource to support variable renewable energy (VRE) integration. However, it could also introduce significant seasonal fluctuations in electricity demand, lead to winter peaking electricity systems in cold climate regions like the U.S. Northeast and increase the complexity of planning low-carbon grids of the future, which are also resilient to extreme weather events. This project is focused on:

1. Understanding demand-side impacts of heat electrification under various technology adoption scenarios at sufficiently granular spatial and temporal resolution to support decision-making.
2. Assessing distribution network operation and planning to quantify levels of beneficial electrification achievable across typical feeder architectures under a range of technology and policy scenarios, spanning alternative retail tariff design and DER deployment.
3. Exploring the bulk energy system impacts of heating electrification vs. the use of other approaches, such as use of hydrogen produced from electricity or other low-carbon fuels, that is subsequently distributed via the existing gas infrastructure. Specific attention is on understanding system resiliency and its implication on cost of alternative decarbonization pathways.

Principal investigators: Christopher Knittel, Dharik Mallapragada

Techno-economic analysis and life-cycle assessment of solid-state batteries

Solid-state batteries are considered the next-generation batteries for energy storage application. They have several advantages over liquid-electrolyte batteries: higher energy density, lower safety risk, and better design flexibility. There are various options of electrolytes, anodes, and designs for solid-state batteries. Currently, the development of solid-state batteries is preparing for large-scale applications. At this point, understanding the economic and emission features of different technologies is critical for future large-scale deployment. This project is focused on:

1. Building a universal framework that can be used to compare cost and emissions for major solid-state battery technology options including multiple electrolyte and anode synthesis routes.
2. Comparing the detailed features of full-solid-state and semi-solid-state batteries and implications for cost and emissions.
3. Providing material, energy, cost, and emissions footprint for each solid-state battery technology.

Principal investigators: Sili Deng, Jianan Zhang, Guiyan Zang

The competitive landscape for distributed nuclear cogeneration

Cogeneration facilities in the U.S. currently total 80 GW of electrical generation capacity. Also known as combined heat and power, or CHP, cogeneration had long been encouraged for its substantial improvements in energy utilization and thereby its contribution to reducing carbon emissions. In addition, cogeneration is often co-located with substantial power loads, which can improve grid performance, and cogeneration can anchor microgrids which helps provide resilience. However, almost all cogeneration capacity in the U.S. is fossil fired. As the goal for emission reductions tightens, and states chart pathways to net zero emissions, merely improving the efficiency in fossil fuel consumption is no longer adequate. Nuclear generation offers a low-carbon option for cogeneration. The new generation of small modular reactors (SMRs) offers a range of sizes and thermal capabilities that may be well suited to the diverse cogeneration market. This project is focused on:

1. Developing a site-specific optimization model of electric generation and heating equipment to meet the owner’s heat and electricity needs.
2. Applying MIT’s GenX capacity expansion and dispatch model, including a heat/cogeneration module, to evaluate how incorporating cogeneration at sites on the grid lowers total system cost and examine the feedback from the system analysis to the individual site optimization.
3. Integrating these results with MIT’s Nuclear Cost Estimation Tool (NCET) code to develop cost targets at which SMRs can be competitive providing cogeneration.

Principal investigators: John Parsons, Jacopo Buongiorno, Koroush Shirvan

The Future of Power Conversion

Power electronics play a critical role in future electrification. While earlier work has highlighted the need for increased efficiency, the evolving demands of industries such as electrified transportation, data centers, and renewable energy integration require a more comprehensive approach. This work develops a roadmap to address the future needs of power electronics in a rapidly electrifying world. By quantifying the future role of power conversion in electrification, we aim to provide actionable insights for researchers and industry members. This project is focused on:

• Identifying and analyzing current power conversion energy flow based on energy sources and consumption in the United States.
• Determining key areas of anticipated growth through literature review, data analysis and discussion with area experts.
• Defining the technology roadmap to meet future power electronics requirements, including efficiency, power density, reliability and cost.

Principal investigators: Samantha Coday

Towards a clean, reliable, and affordable grid with a DER-rich grid edge

Motivated by concerns about climate change and sustainability, the generation assets in an electricity grid are transitioning from fossil fuel-based sources to renewable sources such as wind and solar power. This introduces distributed energy resources (DER) including photovoltaics, storage devices such as batteries, as well as flexible loads. Accompanied by decreasing costs of solar and storage, DERs are expected to penetrate the distribution grid in increasing amounts over the coming years. Increased integration of DERs can introduce several challenges, such as variability and intermittency in a generation, uncertainties in load patterns, stress on grid infrastructure due to bi-directional power flows, and significant operational complexity to grid operators. This project is focused on:

1. Modeling distribution grids in different U.S regions with different asset mixes, for three levels of DER penetration: (1) small (10 to 25%); (2) medium (30 to 70%); (3) large (75 to 100%)
2. Developing a suite of hierarchical market structures with suitably collocated market operators to simultaneously accommodate grid physics, consumer preferences, and encourage DER investments
3. Analyzing the impact of DER-penetration on (i) dependency on the main-grid and the phenomenon of grid defection, and (ii) the ability to increase hosting capacity using cyber tools rather than infrastructure upgrades
4. Investigating current price-signals and incentives (such as FERC Order 2222) and analyzing barriers for entry for DER owners

Principal investigators: Anuradha Annaswamy

Unifying inverter control for stable systems with renewables

There is an imminent need for fast automatic control during faults and reconfigurations as electric power grids accommodate higher penetration of renewables.  This need is driven by the wide-area fast electromagnetic transient (EMT) instabilities created by inadequate inverter control of interactions between different components. Today’s approaches of derating capacity limits and forcing fast protection for service interruptions result in an overall under-utilization of grid capacity and renewables, and yet still do not eliminate EMT problems for the operating ranges of interest. This project is focused on:

1. Demonstrating typical EMT problems caused by the current control induced system stability.
2. Performing state-of-the-art droop control-based analysis of systems showing the ability of our multi-layered simulator to model and analyze EMT dynamical problems.
3. Demonstrating the potential improvements of system response to faults and reconfigurations with the proposed unified inverter control framework.

Principal investigator: Marija Ilić

Unlocking hydrogen end-use applications using separation technologies

Green hydrogen is pivotal for the decarbonization of various industries. To expand the access of green hydrogen to end-uses such as passenger vehicles, maritime operations, and building heating, it is important to leverage existing natural gas distribution infrastructure; however, existing natural gas infrastructure cannot be used for hydrogen transport because the carbon-based steels used to make these pipelines are prone to embrittlement. This project is focused on:

1. Evaluating separation technologies tailored for diverse end-use applications.
2. Assessing the progress made by emerging materials in carrying out these separation technologies both economically and efficiently.
3. Providing a direction for future innovation in separation systems to unlock hydrogen end-use applications.

Principal investigator: Zachary Smith

Watts v/s Bytes: Energy Storage Impact Analysis on Flexible Computing Loads

The unprecedented growth of data center loads in recent years has severely stressed the grid’s current assets necessitates near-term solutions to provide cost-effective power that also achieves decarbonization goals. To that end, this project proposes a judicious merger between the spatio-temporal flexible profile of datacenter loads and local energy storage, to quantifiably reduce the energy and carbon needs of datacenter loads, while ensuring quality of service requirements. This project will focus on:

• A spatio-temporal flexibility model for data-center loads for different computing paradigms, including AI training, inference and data management. This model will incorporate deadlines and costs/constraints associated with shifting different jobs across time and between data-centers.
• A stochastic optimization framework that combines the datacenter model in (a) with a cost and flexibility model for different energy storage types, and optimizes their joint operation under varying energy and carbon signals. To mitigate uncertainty in future cost and operations, the optimization model will built using model predictive control framework.
• An impact analysis on the benefits from joint operation of storage and flexible data center loads for different load type, storage sizes and costs, and quality of load and price forecasts. The impact analysis will be conducted for a single data center and then extended to a group of datacenters within a given geographical footprint. Once developed, this impact analysis and models can potentially be merged into tools for system-wide grid planning to serve expanding loads.

Principal investigator: Sungho Shin

What is the best hydrogen carrier for long-distance distribution and storage?

Hydrogen is expected to gain increasing importance as a carbon-free energy vector despite current challenges in scaling its storage and transporting it. This project is focused on:

1. Comparing mass and energy conversion efficiency of six hydrogen carriers with liquid hydrogen from a cradle-to-grave boundary
2. Conducting techno-economic analysis (TEA) and life cycle analysis (LCA) on the six hydrogen carriers to compare their cost, greenhouse gas (GHG) emissions, and criteria air pollutants (CAP)
3. Developing a framework to find the best options for long-distance hydrogen distribution and storage, which produces hydrogen in Australia and supplies in Japan

Principal investigator: Guiyan Zang

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