Energy is becoming an increasingly valuable and environmentally-sensitive resource. At PRECISE we are developing scheduling algorithms for control systems to improve the energy efficiency of homes and buildings. Inputs like weather, time-of-day, human occupancy, and other plant dynamics influence energy-minimal scheduling which must still maintain human comfort.
Papers from 2018
Learning and Control using Gaussian Processes, Achin Jain, Truong X Nghiem, Manfred Morari, and Rahul Mangharam
Papers from 2017
Data Predictive Control for building energy management, Achin Jain, Madhur Behl, and Rahul Mangharam
Data Predictive Control using Regression Trees and Ensemble Learning, Achin Jain, Francesco Smarra, and Rahul Mangharam
Papers from 2016
Data-Driven Modeling, Control and Tools for Cyber-Physical Energy Systems, Madhur Behl, Achin Jain, and Rahul Mangharam
DR-Advisor: A Data-Driven Demand Response Recommender System, Madhur Behl, Francesco Smarra, and Rahul Mangharam
Data Predictive Control for Peak Power Reduction, Achin Jain, Madhur Behl, and Rahul Mangharam
Papers from 2015
Sometimes, Money Does Grow On Trees: Data-Driven Demand Response with DR-Advisor, Madhur Behl and Rahul Mangharam
Sometimes, Money Does Grow on Trees: DR-Advisor, A Data Driven Demand Response Recommender System, Madhur Behl and Rahul Mangharam
DR-Advisor: A Data Driven Demand Response Recommender System, Madhur Behl, Truong X. Nghiem, and Rahul Mangharam
Campus-Wide Integrated Building Energy Simulation, Willy Bernal, Madhur Behl, Truong X. Nghiem, and Rahul Mangharam
Scalable Scheduling of Energy Control Systems, Truong X. Nghiem and Rahul Mangharam
Sensor Attack Detection in the Presence of Transient Faults, Junkil Park, Radoslav Ivanov, James Weimer, Miroslav Pajic, and Insup Lee
Papers from 2014
Evaluation of DR-Advisor on the ASHRAE Great Energy Predictor Shootout Challenge, Madhur Behl and Rahul Mangharam