The MIT Energy Initiative’s (MITEI) Future Energy Systems Center will fund ten new energy projects, with topics ranging from the intersections between energy and artificial intelligence (AI) to long duration energy storage, all focused on advancing the energy transition. Multiple projects relate to the energy demand of AI and data centers, as well as the promise of AI to enable more efficient energy use, which have been common themes in MITEI’s work and conferences this year. The selected projects will receive a combined total of $1.6 million in funding.
As MITEI’s industry research consortium, the Future Energy Systems Center conducts integrated energy system analyses to provide insight into the technology, policy, and economics behind the evolving energy landscape—drawing from both traditional energy-related disciplines and cross-disciplinary fields. Since its founding, the Center has supported 53 projects dedicated to this approach.
This was the Center’s sixth round of project selections, which are selected twice a year by a Steering Committee comprised of MIT faculty members based on nominations from Center Member companies, project impact, and balancing of the Center’s portfolio. MITEI will host kick-off meetings for each of these new projects at the Center’s May 2025 workshop.
Brief descriptions of each of the new projects follow.
Agricultural waste end use
The modern industrialized agricultural sector produces 7.6 gigatons of agricultural residues each year. Common end-use practices, such as leaving or burning the residue, cycle CO2 back into the atmosphere, but more environmentally beneficial end uses, such as incorporation into biofuel production or long-term carbon storage, lack adequate incentives. This project will develop a geospatially resolved tool to identify the best use for agricultural waste based on environmental costs, benefits, and systems-level impacts. This tool will conduct cradle-to-gate life cycle assessments for each end-use scenario, incorporating location-specific energy, efficiency, and transportation terms.
PI: Desirée Plata, co-director of the MIT Climate and Sustainability Consortium and associate professor of civil and environmental engineering
Amine-based carbon capture
Carbon capture, utilization, and storage technology can effectively reduce carbon emissions in industries lacking scalable decarbonization options. In the amine-based carbon capture process, key pieces of equipment must be sized to minimize energy consumption and capital costs while still achieving target capture rates under multiple feed conditions, such as carbon dioxide (CO2) concentrations and flow rates. This project will examine the trade-offs between carbon capture rates and energy efficiency in carbon capture plant design under varying feed conditions. The research team will ultimately perform techno-economic analysis characterizing the trade-offs between carbon capture rate and operational expenses of carbon capture plants.
PIs: Sungho Shin, assistant professor of chemical engineering, and Guiyan Zang, research scientist at MITEI
Building decarbonization pathways with uncertainties
Decarbonizing the built environment is critical for achieving net-zero emission goals, but market adoption of electrification technologies for buildings is hindered by social, political, and market-based uncertainties. This project will design a streamlined and practical framework to evaluate the financial, environmental, and social costs of building decarbonization pathways and the impact of uncertainties. The research team will generate recommendations for practitioners and policy makers to enhance the benefits and mitigate the costs of building decarbonization.
PI: Siqi Zheng, professor of urban and real estate sustainability
Data centers and power systems
The rapid growth of data centers presents both challenges and opportunities for modern power systems. While growing data center deployment may strain existing grids and increase emissions, the energy flexibility of data centers allows them to participate in demand response programs and support variable renewable energy development. This project will investigate generation capacity investments, energy pricing, emissions, and decarbonization goals to determine how data center deployment impacts the U.S. power system. The research team will create a power system model that incorporates data center load forecasts, develop a siting optimization framework, and assess policy options to incentivize optimal behavior.
PI: Christopher Knittel, associate dean of climate and sustainability and professor of energy economics
Flexible computing loads and energy storage
In their unprecedented expansion, data centers have significantly stressed energy grid supply, necessitating near-term solutions to provide cost-effective power while still achieving decarbonization goals. This project proposes that onsite, long duration energy storage and flexible computing loads be used in tandem to address both concerns and maintain the data center’s quality of service. Once developed, the research team’s joint optimization model can be used as a system-wide planning tool.
PIs: Deep Deka, research scientist at MITEI, and Sungho Shin, assistant professor of chemical engineering
Future of power conversion
As a key component of future electrification, power electronics must evolve alongside a rapidly electrifying world, especially with growth in key industries such as transportation, data centers, and renewable energy integration. This project will analyze current and projected trends in electricity demand, identifying and prioritizing areas for advancement in efficiency, cost, reliability, size, and sustainability. Once the future role of power conversion in electrification is quantified, the research team will create a roadmap for areas of innovation in power conversion and provide actionable insights for decision makers and stakeholders.
PI: Samantha Coday, assistant professor of electrical engineering
Low-cost, resilient power systems
Significant build-out of renewable energy sources is needed to decarbonize energy systems and meet growing demand, but renewables siting must account for the uncertainty of future climate conditions as the frequency and intensity of extreme weather events worsen. This project aims to advance the design of low-cost, extreme event resilient power systems. The research team will identify geophysical and meteorological factors that contribute to system resiliency, and develop strategies for decarbonization pathways in diverse regions, including New England, Texas, and California.
PIs: Michael Howland, assistant professor of civil and environmental engineering, and Saurabh Amin, associate professor of civil and environmental engineering
Power resource accreditation and weather variability
The transition to renewable energy poses a challenge to electricity supply reliability as many sources—particularly wind and solar—are impacted by weather variability. This phenomenon is exacerbated by the rise in extreme weather events brought on by climate change, making existing methods of assessing resource adequacy insufficient. This project will create a modeling framework that incorporates weather data into resource accreditation calculations. The objective is to more precisely represent the capacity value of various resources and analyze long-term market equilibrium effects under different market designs. This research will contribute to more efficient and reliable resource investment in future power systems.
PIs: Audun Botterud, principal research scientist at the MIT Laboratory for Information and Decision Systems (LIDS)
Thermal long duration energy storage
Energy storage is essential for decarbonization to balance production and demand at low costs. Thermal energy storage (TES) coupled with nuclear reactors avoids the losses associated with the initial conversion to electricity, giving it an efficiency advantage, but TES systems are expensive and best suited for short-duration storage. Alternative TES technologies, like hot rock energy storage, have much lower cost profiles and could be better suited to long-duration energy storage (LDES). This project will assess the value of alternative TES technologies for alternative LDES applications across grids with different portfolios of generation and carbon intensity. The research team will study how generation and storage assets drive price volatility, identify the competitive space for LDES, and evaluate the optimal design for a coupled TES system.
PIs: Charles Forsberg, principal research scientist in the Department of Nuclear Science and Engineering, and John Parsons, deputy director for research at the MIT Center for Energy and Environmental Policy Research
Virtual power plant (VPP) operation
To meet net-zero emission goals for 2050, significant investments in infrastructure, land-use, and technology adoption will be necessary to allow for large-scale electrification and integration of renewable energy sources. This project will explore the ability of buildings to function as virtual power plants (VPPs). The research team will develop AI optimization algorithms to improve the efficiency and sustainability of buildings without requiring additional energy generation or storage infrastructure. Ultimately, the team will create an AI-driven building automation model that optimizes real-time and day-ahead energy electricity market participation, while minimizing costs and greenhouse gas emissions.
PIs: Leslie Norford, professor of architecture, and Audun Botterud, principal research scientist at MIT LIDS