22 citations
5 papers
Economic Battery Storage Dispatch with Deep Reinforcement Learning from Rule-Based Demonstrations
Manuel Sage, Martin Staniszewski, Yaoyao Fiona Zhao
The application of deep reinforcement learning algorithms to economic battery dispatch problems has significantly increased recently. However, optimizing battery dispatch over long…
Low-Dimensional High-Fidelity Kinetic Models for NOX Formation by a Compute Intensification Method
Mark Kelly, Harry Dunne, Gilles Bourque +1
A novel compute intensification methodology to the construction of low-dimensional, high-fidelity "compact" kinetic models for NOX formation is designed and demonstrated. The metho…
Toward Development of Machine Learned Techniques for Production of Compact Kinetic Models
Mark Kelly, Mark Fortune, Gilles Bourque +1
Chemical kinetic models are an essential component in the development and optimisation of combustion devices through their coupling to multi-dimensional simulations such as computa…
Toward Machine Learned Highly Reduce Kinetic Models For Methane/Air Combustion
Mark Kelly, Gilles Bourque, Stephen Dooley
Accurate low dimension chemical kinetic models for methane are an essential component in the design of efficient gas turbine combustors. Kinetic models coupled to computational flu…
Joint Scheduling and Transmission Power Control in Wireless Ad Hoc Networks
Kamal Rahimi Malekshan, Weihua Zhuang
In this paper, we study how to determine concurrent transmissions and the transmission power level of each link to maximize spectrum efficiency and minimize energy consumption in a…