341 citations · 391 across the 9 of their papers we have counts for
14 papers
Learning -function approximations for hybrid control problems
Sandeep Menta, Joseph Warrington, John Lygeros +1
The main challenge in controlling hybrid systems arises from having to consider an exponential number of sequences of future modes to make good long-term decisions. Model predictiv…
Reliable Power Grid: Long Overdue Alternatives to Surge Pricing
Hala Ballouz, Joel Mathias, Sean Meyn +2
This paper takes a fresh look at the economic theory that is motivation for pricing models, such as critical peak pricing (CPP), or surge pricing, and the demand response models ad…
Robust MPC with data-driven demand forecasting for frequency regulation with heat pumps
Felix Bünning, Joseph Warrington, Philipp Heer +2
With the increased amount of volatile renewable energy sources connected to the electricity grid, and the phase-out of fossil fuel based power plants, there is an increased need fo…
State Space Collapse in Resource Allocation for Demand Dispatch
Joel Mathias, Robert Moye, Sean Meyn +1
Demand dispatch is the science of extracting virtual energy storage through the automatic control of deferrable loads to provide balancing or regulation services to the grid, while…
Learning continuous Q-Functions using generalized Benders cuts
Joseph Warrington
Q-functions are widely used in discrete-time learning and control to model future costs arising from a given control policy, when the initial state and input are given. Although so…
Two-Stage Dual Dynamic Programming with Application to Nonlinear Hydro Scheduling
Benjamin Flamm, Annika Eichler, Joseph Warrington +1
We present an approximate method for solving nonlinear control problems over long time horizons, in which the full nonlinear model is preserved over an initial part of the horizon,…
Accelerated Point-wise Maximum Approach to Approximate Dynamic Programming
Paul N. Beuchat, Joseph Warrington, John Lygeros
We describe an approximate dynamic programming approach to compute lower bounds on the optimal value function for a discrete time, continuous space, infinite horizon setting. The a…
Two-stage stochastic approximation for dynamic rebalancing of shared mobility systems
Joseph Warrington, Dominik Ruchti
Mobility systems featuring shared vehicles are often unable to serve all potential customers, as the distribution of demand does not coincide with the positions of vehicles at any…
A Two-Stage Polynomial Approach to Stochastic Optimization of District Heating Networks
Marc Hohmann, Joseph Warrington, John Lygeros
In this paper, we use stochastic polynomial optimization to derive high-performance operating strategies for heating networks with uncertain or variable demand. The heat flow in di…
A Moment and Sum-of-Squares Extension of Dual Dynamic Programming with Application to Nonlinear Energy Storage Problems
Marc Hohmann, Joseph Warrington, John Lygeros
We present a finite-horizon optimization algorithm that extends the established concept of Dual Dynamic Programming (DDP) in two ways. First, in contrast to the linear costs, dynam…
Optimal Linearizations of Power Systems with Uncertain Supply and Demand
Marc Hohmann, Joseph Warrington, John Lygeros
Linearized models of power systems are often desirable to formulate tractable control and optimization problems that still reflect real-world physics adequately under various opera…
Generalized Dual Dynamic Programming for Infinite Horizon Problems in Continuous State and Action Spaces
Joseph Warrington, Paul N. Beuchat, John Lygeros
We describe a nonlinear generalization of dual dynamic programming theory and its application to value function estimation for deterministic control problems over continuous state…
Dynamic vehicle redistribution and online price incentives in shared mobility systems
Julius Pfrommer, Joseph Warrington, Georg Schildbach +1
This paper considers a combination of intelligent repositioning decisions and dynamic pricing for the improved operation of shared mobility systems. The approach is applied to Lond…
Policy-based reserves for power systems
Joseph Warrington, Paul Goulart, Sebastien Mariethoz +1
This paper introduces the concept of affine reserve policies for accommodating large, fluctuating renewable infeeds in power systems. The approach uses robust optimization with rec…