46 citations · 414 across the 52 of their papers we have counts for
14 papers · 2 filters
Mitigating Investment Risk Using Modular Technologies
Yue Shao, Yicheng Hu, Victor M. Zavala
We study logistical investment flexibility provided by modular processing technologies for mitigating risk. Specifically, we propose a multi-stage stochastic programming formulatio…
Graph-Based Modeling and Decomposition of Energy Infrastructures
Sungho Shin, Carleton Coffrin, Kaarthik Sundar +1
Nonlinear optimization problems are found at the heart of real-time operations of critical infrastructures. These problems are computationally challenging because they embed comple…
Dual Dynamic Programming for Multi-Scale Mixed-Integer MPC
Ranjeet Kumar, Michael J. Wenzel, Mohammad N. ElBsat +3
We propose a dual dynamic integer programming (DDIP) framework for solving multi-scale mixed-integer model predictive control (MPC) problems. Such problems arise in applications th…
Economic Properties of Multi-Product Supply Chains
Philip A. Tominac, Victor M. Zavala
We interpret multi-product supply chains (SCs) as coordinated markets; under this interpretation, a SC optimization problem is a market clearing problem that allocates resources an…
A Graph-Based Modeling Abstraction for Optimization: Concepts and Implementation in Plasmo.jl
Jordan Jalving, Sungho Shin, Victor M. Zavala
We present a general graph-based modeling abstraction for optimization that we call an OptiGraph. Under this abstraction, any optimization problem is treated as a hierarchical hype…
On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control
Sen Na, Sungho Shin, Mihai Anitescu +1
We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs). The algorithm decomposes the time domai…
Multiscale Model Predictive Control of Battery Systems for Frequency Regulation Markets using Physics-Based Models
Yankai Cao, Seong Beom Lee, Venkat R. Subramanian +1
We propose a multiscale model predictive control (MPC) framework for stationary battery systems that exploits high-fidelity models to trade-off short-term economic incentives provi…
A Sigmoidal Approximation for Chance-Constrained Nonlinear Programs
Yankai Cao, Victor M. Zavala
We propose a sigmoidal approximation for the value-at-risk (that we call SigVaR) and we use this approximation to tackle nonlinear programs (NLPs) with chance constraints. We prove…
Overlapping Schwarz Decomposition for Constrained Quadratic Programs
Sungho Shin, Mihai Anitescu, Victor M. Zavala
We present an overlapping Schwarz decomposition algorithm for constrained quadratic programs (QPs). Schwarz algorithms have been traditionally used to solve linear algebra systems…
Multi-Grid Schemes for Multi-Scale Coordination of Energy Systems
Sungho Shin, Victor M. Zavala
We discuss how multi-grid computing schemes can be used to design hierarchical coordination architectures for energy systems. These hierarchical architectures can be used to manage…
Stochastic Model Predictive Control for Central HVAC Plants
Ranjeet Kumar, Michael J. Wenzel, Mohammad N. ElBsat +3
We present a stochastic model predictive control (MPC) framework for central heating, ventilation, and air conditioning (HVAC) plants. The framework uses real data to forecast and…
Computing Economic-Optimal and Stable Equilibria for Droop-Controlled Microgrids
Sungho Shin, Victor M. Zavala
We consider the problem of computing equilibria (steady-states) for droop-controlled, islanded, AC microgrids that are both economic-optimal and dynamically stable. This work is mo…
A Hierarchical Optimization Architecture for Large-Scale Power Networks
Sungho Shin, Philip Hart, Thomas Jahns +1
We present a hierarchical optimization architecture for large-scale power networks that overcomes limitations of fully centralized and fully decentralized architectures. The archit…
Diffusing-Horizon Model Predictive Control
Sungho Shin, Victor M. Zavala
We analyze a time-coarsening strategy for model predictive control (MPC) that we call diffusing-horizon MPC. This strategy seeks to overcome the computational challenges associated…