EET 110: Power and Energy Management II
Course Information
- Semester: Spring Semester 2025
- Instructor: Parikshit Pareek (email: pareek AT ee.iitr.ac.in)
- Lectures: Tue • 09:00 AM – 11:00 AM; 05:00 PM – 07:00 PM @ EED 109
- Venue: EED 109
- Piazza: Same as EET 109 Course
- TA: Ayushi Jolotia(ayushi_j AT ee.iitr.ac.in)
Announcements
- 2026‑04-18: ACOPF Notes and videos link added. Video link is a playlist where first eight videos are part of the course. Rest are optional.
- 2026‑02-10: Homeworks for Lecture 2 have been released: PDF and Notebook.
- 2026‑02‑02: The Term Paper timeline and deliverables are published in the final section of this webpage.
- 2026‑01‑20: Term paper form is available on Piazza. Submission deadline: next Tuesday.
- 2025‑12‑10: Initial Course website launched.
Course Objectives
This is not a traditional classroom-based course, nor is it a lab course focused on running experiments. This is a TEC: Talent Enhancement Course, Part II.
Designed for individuals who are already highly capable, this course aims to challenge your thinking and expand your potential. It will be largely hands-off in terms of direct implementation, encouraging independent exploration, creative problem-solving, and pushing beyond your current limits. Briefly, our objectives in this course are:
- Develop a solid understanding of optimization algorithms behind operations of power grid.
- Implement various optimal power flow methods on CPU and GPU with parallelization capabilities for speed & accuracy.
- Explore advanced ML surrogates for Constrained Optimization Problem.
Course Content
| Index | Topics | Slides | Homeworks |
|---|---|---|---|
| 0 | Introduction to EET110 | Slides | Find The Term Paper Topic |
| 1 | Introduction to Optimization | Slides | PDF1 |
| 2 | Linear Programming | Slides | PDF1 · Notebook2 |
| 3 | Linear Programming Practical | Slides | |
| 4, 5, 6 | Polyhedral, Convexity, LP Bounds, Dual, Simplex (Self-Learning) | PDF1 | |
| 7 | DCOPF Lab | Slides | PDF1 |
| 8, 9 | Least Square, Equality Constrained LS, Regression | PDF1 · PDF2 | |
| 10, 11 | Second-Order Cone Programming, SDP | Slides | PDF1 · PDF2 |
| 12 | ACOPF Formulation & Relaxation (Self-Study) | Slides | Video Link1 |
Assignments
- Python and Julia are default programming languages for the course. You should use any of these for programming your assignments unless otherwise explicitly allowed.
- Submit via Moodle or GitHub—- as specified in each assignment.
- Viva will accompany each assignment — your explanation during the viva carries significant weight in grading.
- Honor Code: Any cases of copying will be awarded a zero on the assignment. More severe penalties may follow.
- Late submissions will incur penalties, as annouced with assignment.
References & Resources
Course Resources:
Reference Books:
- S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004.
- Available for free: stanford.edu/~boyd/cvxbook/
- H.P. Williams. Model Building in Mathematical Programming, 5th Edition. Wiley, 2013.
Grading Policy (Tentative)
- CWS+PRE+PRS (50 Marks)
- Lab Assignments — 20 Marks
- Term Paper / Project — 30 Marks
- Mid Term (20 Marks) — Exam
- End Term (30 Marks) — Exam
Lab Assignments (Coding Tasks):
- Lab 1: Linear Programming (Dispatch)
- Lab 2: MILP (Unit Commitment)
- Lab 3: NLP (AC-OPF)
- Lab 4: Relaxations (SOCP/SDP)
Term Paper Timeline and Deliverables
| Week (Date) | Milestone | Requirement |
|---|---|---|
| Week 4 (Feb 10, 2026) | Proposal | 1-page abstract + Selected “Base Paper” |
| Week 8 (Mar 10, 2026) | Update | Mathematical formulation finalized (LaTeX) |
| Week 10 (Mar 24, 2026) | Code Check | Working code (in a notebook; will be made public) |
| Week 12 (Apr 14, 2026) | Final | Final report + 10-minute presentation |
Student Submissions of Term Paper
| S.No. | Team Name | Members | Submissions |
|---|---|---|---|
| 1 | Aletheia | Reenav Ray, Aryan Mehra, Sachin Saini, Rahul, Nischay Sanjay Jiwankar | Abstract Math |
| 2 | OptiML | Tharun Rathod, Ayush Bairwa, Chirag Bundela | Abstract Math |
| 3 | Khoji | Adithya Jaiswal, Aditi, Naman Meena, Swastic Keshari | Abstract Math |
| 4 | Sleeping Pizza | Medha Bhutani | Abstract Math |
| 5 | Onyttig | Kaustubh Sharma | Abstract Math |
| 6 | Optimus Primes | Anushree Gupta, Daiwik Vohra, Jaineel Lakesh Dalsania, Rishit Saini | Abstract Math |
| 7 | UC DecompX Lab | Sreemayi Yavvari, Annam Sai Sumanjali | Abstract Math |
| 8 | Black KAPSS | Shashank Shekhar, Abhinav Karn, Shivam Bansal, Kris Keshav, Lakhote Pranad Nilesh | Abstract Math |
| 9 | Vanguard | Akshat Odiya, Aniruddh Yadav, Harendra | Abstract Math |
| 10 | NearOptimal | Mahankali Vinoothna | Abstract Math |
Exam Papers
– Quiz 1
– Quiz 2