70 citations · 150 across the 31 of their papers we have counts for
6 papers · 1 filter
Efficient Gradient-Based Optimization for Joint Layout Design and Control of Wind Turbines
James Kotary, Natalie Isenberg, Draguna Vrabie
A central challenge in the design of energy-efficient wind farms is the presence of wake effects between turbines. When a wind turbine harvests energy from free wind, it produces a…
Learning to Solve Constrained Bilevel Control Co-Design Problems
James Kotary, Himanshu Sharma, Ethan King +3
Learning to Optimize (L2O) is a subfield of machine learning (ML) in which ML models are trained to solve parametric optimization problems. The general goal is to learn a fast appr…
Efficient Primal Heuristics for Mixed Binary Quadratic Programs Using Suboptimal Rounding Guidance
Weimin Huang, Natalie M. Isenberg, Jan Drgona +2
Mixed Binary Quadratic Programs (MBQPs) are a class of NP-hard problems that arise in a wide range of applications, including finance, machine learning, and chemical and energy sys…
Model Predictive Control of Discrete-Continuous Energy Systems via Generalized Disjunctive Programming
Arnab Bhattacharya, Xu Ma, Draguna Vrabie
Generalized Disjunctive Programming (GDP) provides an alternative framework to model optimization problems with both discrete and continuous variables. The key idea behind GDP invo…
Prioritized Threshold Allocation for Distributed Frequency Response
Sai Pushpak Nandanoori, Soumya Kundu, Draguna Vrabie +2
Higher penetration of renewable generation will increase the demand for adequate (and cost-effective) controllable resources on the grid that can mitigate and contain the contingen…
Optimal Energy Consumption Forecast for Grid Responsive Buildings: A Sensitivity Analysis
Soumya Kundu, Thiagarajan Ramachandran, Yan Chen +1
It is envisioned that building systems will become active participants in the smart grid operation by controlling their energy consumption to optimize complex criteria beyond ensur…