MAE PhD Energy Systems Track


The Mechanical and Aerospace Engineering Ph.D. in power and energy systems equips students for a research career focused on accelerating the transition to a sustainable zero-carbon energy system. All students in Power and Energy Systems must satisfy the requirements of the MAE Doctoral Program as described on the MAE website. The following core and track courses are designed to support the organization of the Department Qualifying Exam (DQE), which is ultimately up to the student’s committee.


Most students will take the core courses. Depending on the students specialization, these can vary with the advisor's support.

Fundamentals of Energy Systems (MAE 206)

This course is designed to introduce students to the fundamentals of the energy system and outline its possible futures given the need to radically reduce global carbon emissions. UC San Diego has several courses that investigate different aspects of the energy system, including the fundamental science and engineering behind promising new technologies (mainly in JSOE) and the political economy of energy (in GPS and Economics).

None of these offers an explanation of how the system is structured, the imperatives and constraints under which it operates, and how it is likely to evolve given the competing demands it serves and the range of challenges facing its constituent technologies. The goal of this course is to impart a knowledge of these realities, and to help students develop the skills to critically evaluate the technology, economic, and policy choices that will have to be made when modernizing it, with a key focus on innovation in creating new opportunities. It is designed to help students build a foundation for future coursework on energy systems.

Electric Power Systems Modeling (MAE 243)

This course will teach students constrained optimization problems and associated solution methods, how to implement and apply linear and mixed integer linear programs to solve such problems using Julia/JuMP, and the practical application of such techniques in energy systems engineering. The course will first introduce students to the theory and mathematics of constrained optimization problems and provide a brief introduction to linear programming, including problem formation and solution algorithms. Next, to build hands-on experience with optimization methods for energy systems engineering, the course will introduce students to several canonical problems in electric power systems planning and operations, including: economic dispatch, unit commitment, optimal network power flow, and capacity planning. Finally, several datasets of realistic power systems are provided which students will use in conjunction with building a model for a course project that answers a specific power systems question. Course Repo.

Convex Optimization for Engineers (MAE 227)

This course focuses on convex optimization theory, convexification of non-convex problems, engineering applications, modeling and implementation in a programming language (MATLAB or choice). This course covers: convex sets and functions, convex optimization problems (LP, QP, SOCP, SDP, robust and stochastic optimization), weak and strong duality, optimality conditions (complementary slackness, Karush-Kuhn-Tucker), and solution and shadow price interpretation. Some applications include: design in mechanical engineering, optimal control problems, machine learning, energy, transportation, etc. Prerequisites: nongraduate students may enroll with consent of instructor.

Research Tracks

Students should expect to take 3-6 additional courses--forming a “minor”--up to the discretion of their doctoral committee. It is not required to stay within a single track.

Advanced Control

Economics, Policy, and Engineering of the Power Grid

Advanced Energy Technologies

Climate and Atmospheric Sciences

Other Courses

Optimization courses

Undergraduate energy courses

Undergraduate power systems courses