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Courses

EC 500 Control of Sustainable Power Systems (Spring-2025).
Course contents: This course focuses on computational methods for control of modern power systems, with particular emphasis on renewable generation and system sustainability. To build background, the course covers basics of linear systems, feedback control, and convex optimization. With this groundwork, the course explores methods that are currently utilized to optimize gen- eration in today’s operation of power grids; these methods include the economic dispatch, unit commitment, DC optimal power flow (OPF), and AC OPF at the power transmission level. The course then covers primary frequency control methods, secondary control methods, and automatic generation control, along with an analysis of system stability. The contribu- tion of inverter-based resources to stability and grid-forming setups under massive renewable generation integration is discussed. At the power distribution level, the course addresses for- mulations and solution methods for demand response problems and the AC OPF, with an emphasis on modern distribution grids with distributed energy resources (DERs). The course emphasizes the understanding of the convergence and optimality properties of optimization algorithms used to solve demand response and OPF tasks. Finally, the course introduces advanced algorithms for real-time demand response and AC OPF, focusing on computational methods for the reliable integration of DERs and decarbonization of the power grid.

Previous courses at CU Boulder

ECEN 3300 Linear Systems (Spring-2020, Spring-2021, Spring-2022).
Course contents: Characterization of linear time-invariant systems in time and frequency domains. Continuous-time systems are analyzed using differential equations and Laplace and Fourier transforms. Discrete-time systems are analyzed using difference equations and discrete-time Fourier transforms. Sampling and reconstruction of signals using the sampling theorem. Applications of linear systems include communications, signal processing, and control systems.

ECEN 5007 Optimization for Energy Systems (Spring-2019)
Course contents: Elements of convex optimization and distributed computing; convex relaxation; network modeling; power flow equations; optimization of power transmission and distribution systems; optimization of wind farms. The techniques and methodologies presented in the course are introduced through problems in power systems such as economic dispatch, DC optimal power flow (OPF), AC OPF, demand response; estimation; optimization of wind farms.

ECEN 5478 Online Convex Optimization and Learning (Fall 2020, Fall 2021)
Course contents: Basics of convex optimization; online learning, time-varying optimization, online first-order methods, learning problems over networks, zeroth-order methods, Gaussian processes, distributed methods for online convex optimization. Application domains considered in the course include Machine Learning, Signal Processing, and Data-driven Control.

ECEN 5678 Control of Multi-agent Systems (Fall 2018, Fall 2020, Fall 2022)
Course contents: Basics of matrix theory and graph theory; distributed averaging and consensus methods on graphs; fixed-point theory and parallel computation of fixed points; basics of convex optimization; parallel and distributed computation methods for unconstrained and constrained convex problems; convergence analysis; elements of online optimization; regret analysis. The techniques and methodologies presented in the course are introduced through application setups including Internet of Things, power and energy systems, sensor networks, transportation systems, and social networks.