Friday, January 27, 2023 | 9am to 1pm
About this Event
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
PREREQUISITES: None (some GAMS/Python familiarity is helpful)
LIMITED: Students welcome to individual sessions