4 papers
Addressing Terminal Constraints in Data-Driven Demand Response Scheduling
Maximilian Bloor, Martha White, Ehecatl Antonio del Rio Chanona +1
Electrified chemical processes are incentivized by exposure to time-varying electricity markets to operate flexibly, but participating in demand response schemes can require satisf…
Survey and Tutorial of Reinforcement Learning Methods in Process Systems Engineering
Maximilian Bloor, Max Mowbray, Ehecatl Antonio Del Rio Chanona +1
Sequential decision making under uncertainty is central to many Process Systems Engineering (PSE) challenges, where traditional methods often face limitations related to controllin…
Hierarchical RL-MPC for Demand Response Scheduling
Maximilian Bloor, Ehecatl Antonio Del Rio Chanona, Calvin Tsay
This paper presents a hierarchical framework for demand response optimization in air separation units (ASUs) that combines reinforcement learning (RL) with linear model predictive…
PC-Gym: Benchmark Environments For Process Control Problems
Maximilian Bloor, José Torraca, Ilya Orson Sandoval +6
PC-Gym is an open-source tool for developing and evaluating reinforcement learning (RL) algorithms in chemical process control. It features environments that simulate various chemi…