All Posts
- PowerIO: a fast Rust library that parses power system case files into one typed model and converts losslessly between formats, with Python, Julia, and C bindings.
- Our new work on admittance matrix concentration was accepted at the 1st Annual PowerUp Conference.
- Announcing Marguerite.jl, a minimal and differentiable Frank–Wolfe solver for constrained convex optimization in Julia.
- Seminar series on randomness as a resource for electric power systems, presented at Carnegie Mellon University, University of Michigan, and Johns Hopkins University.
- Demo of the randomized switching algorithm for network reconfiguration: Generate many optimized configurations for a power network.
- Tutorial on linearizing the AC power flow equations, covering DC power flow, sensitivity-based methods, and first-order Taylor approximations.
- Recap of recent conference presentations and workshops in 2025-2026.
- Recap of Harvard PAI seminar on using randomness to scale decision-making algorithms for electric power grids.
- Step-by-step guide for building random graphs and Laplacians in Julia, with sparse matrix tricks and visualization tips.
- Explains how to differentiate DC optimal power flow solutions with respect to problem parameters.
- Shows how to write DC optimal power flow in matrix form.
- Discusses phase retrieval in power systems and conditions for estimating complex injections using only voltage magnitudes.
- Walkthrough for testing whether an admittance matrix corresponds to a radial electric power network using simple counts.