Computational modeling for clean, reliable, and affordable electricity

Friday, January 27, 2023 at 9:00am to 1:00pm

E51-145

Monday, January 23-Friday, January 27, 9:00 am - 1:00 pm ET each day (5 classes)
NEW Location: E51-145
Register by January 20. Email Pablo Duenas (pduenas@mit.edu)

This 5-session hands-on learning experience introduces analysis techniques to model and understand the role of electric power systems within a carbon-constrained economy. The massive deployment of intermittent renewables energy resources, the anticipated surge of active demand response and batteries, the development of smart grids, or the reliability of supply are among the critical challenges that must be faced by mathematical models for optimization, analysis, and simulation of complex decision-making processes in electricity systems. Besides a theoretical description of models, the instructors will provide students with a collection of prototypes that will allow them to run study cases and to explore the effect of different mathematical formulations on the outcomes. The use of these models in some real-world applications is also presented.

 

January 23

Part 0: Why models? Operating and planning under ever-evolving conditions

Part 1: Daily operation under renewable uncertainty

      1. Economic dispatch and unit commitment

      2. Stochastic unit commitment

January 24

Part 2: Operation planning: getting ready within a year

      3. Mid-term hydro-thermal coordination

      4. Deterministic and stochastic model

January 25

Part 3: Investing in generation to supply a growing demand

      5. Generation expansion planning

      6. GenX model: an expansion model for studying low-carbon energy futures

January 26

Part 4: Investing in transmission lines to unlock renewable potential

      7. Transmission expansion planning

      8. openTEPES model: G&T operation and expansion planning with renewable and storage

January 27

Part 5: Empowering end consumers for a clean and affordable transition

      9. A simplified model for scheduling a microgrid

    10. DECARB model: enabling buildings responsiveness for decarbonization

 

Instructors

  • Andres Ramos – Professor at Universidad Pontificia Comillas, arght@mit.edu
  • Javier Garcia – Professor at Universidad Pontificia Comillas, javiergg@mit.edu
  • Pablo Duenas – Research Scientist at MIT Energy Initiative, pduenas@mit.edu
  • Tim Schittekatte – Research Scientist at MIT Energy Initiative, schtim@mit.edu

 
PREREQUISITES: None (some GAMS/Python familiarity is helpful)

LIMITED: Students welcome to individual sessions

Event Type

Conferences/Seminars/Lectures

Events By Interest

IAP (Independent Activities Period)

Events By Audience

Public, MIT Community, Students, Alumni, Faculty, Staff

Events By School

School of Architecture and Planning (SA+P), School of Engineering (SoE), School of Humanities, Arts, and Social Sciences (SHASS), Sloan School of Management (Sloan), School of Science, Schwarzman College of Computing

Department
MIT Energy Initiative
Contact Email

pduenas@mit.edu

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