Monday, January 27-Friday, January 31, 2025
9:00 am - 1:00 pm ET each day (5 classes)
Location: 3-133
Register by Saturday, January 25. Email Pablo Duenas (pduenas@mit.edu)

For the 16th consecutive year, this five-session hands-on learning experience continues to evolve, delving into mathematical modeling to understand and accelerate the transition toward net-zero targets. With a primary focus on electricity systems, the course examines their pivotal role in a carbon-constrained economy. Participants will address critical challenges, such as the deployment of renewable energy resources, the surge in active demand response and electric vehicle integration, the synergies between electricity and hydrogen to support deep decarbonization, and the pending expansion of energy access in non-electrified areas of Africa, Latin America, and Asia. These challenges require advanced mathematical models for optimizing and analyzing complex decision-making processes. In addition to theoretical insights, the course offers practical tools, enabling participants to run case studies and explore the impact of different mathematical formulations. Real-world applications will be showcased to underscore the power to inform key stakeholders and public opinion, providing a robust foundation for driving collective action toward a net-zero future.

No prior experience is required, although basic familiarity with Python and Julia programming can be helpful. Participants are welcome to attend individual sessions.

Monday, January 27

Part 0: How mathematical models contribute to achieving the net-zero target on time

• Carbon emitters, decarbonization solutions, and the pivotal role of electricity
• Leveraging models to inform policymakers, stakeholders, and public opinion
• Introduction to fundamentals on optimization techniques

Part 1: Removing carbon emissions at the community level

• Scheduling a decarbonized Home Energy Management System (HEMS)
• Energy communities and enabling active participation of buildings

Tuesday, January 28

Part 2: Removing carbon emissions from daily electricity production

• Unit-Commitment (UC): daily dispatch of electricity generation units
• Managing uncertainty through stochastic optimization of UC

Wednesday, January 29

Part 3: Removing carbon emissions from annual electricity production

• Medium-term operation planning
• Managing uncertainty through stochastic hydro-thermal coordination

Part 4: The network as the backbone of electric systems

• Understanding the role of the electricity network
• Managing network constraints with Locational Marginal Pricing

Thursday, January 30

Part 5: Models for informing utility-scale investments

• Basic concepts: optimal mix problem by screening curves
• DOLPHYN: an expansion model for studying low-carbon energy futures

Friday, January 31

Part 6: Electrification and energy transition: openTEPES, REM, DECARB

• openTEPES: informing infrastructure needs across Africa
• REM: developing national electrification plans worldwide
• DECARB: is the distribution grid ready for wide electrification?

Instructors

Pablo Duenas, Research Scientist, MIT Energy Initiative (pduenas@mit.edu)

Andres Ramos, Professor, Universidad Pontificia Comillas (arght@mit.edu)

Javier Garcia-Gonzalez, Professor, Universidad Pontificia Comillas (javiergg@mit.edu)

Ruaridh Macdonald, Energy Systems Research Lead, MIT Energy Initiative (rmacd@mit.edu)

Yifu Ding, Postdoctoral Associate, MIT Energy Initiative (yifuding@mit.edu)

Invited speakers

Graham Turk, Deputy Director of Utility Regulation, Connecticut Public Utilities Regulatory Authority