Calibration 02: Predicting Residential Demand

Andreas Koch, Donal Finn, Jennifer Lynn Williamson, Lisa Scanu
Date of Recording:
Long Description

This is a recording of a Building Simulation 2017 session presentation, held on August 8, 2017. Building Simulation 2017 brought together practitioners and researchers from around the world to share information about the state of the art in simulation tools and applications and to discuss new developments. The conference featured updates and insights regarding new research to improve simulation capabilities for advanced low-energy building systems, case studies from successful projects that demonstrate the key role that simulation plays, and ongoing efforts to enable compliance and building rating software to support radiant and other energy efficient systems.

Session Title: Calibration 02: Predicting Residential Demand​

Chair: Pieter de Wilde


WITHDRAWN: Predicting Heating Energy Needs for Residential Building Clusters Using a Non-Linear Data-Driven Approach
Andreas Koch, European Institut for Energy Research, Germany

Prediction of Residential Building Demand Response Potential Using DataDriven Techniques
Donal Finn, University College Dublin, Ireland

An Improved Methodology for Calibrating Residential Building Energy Models Using Hourly Utility Data
Jennifer Lynn Williamson, The Catholic University of America, USA

Model Tuning Approach for Energy Management of Office and Apartment Settings
Lisa Scanu, Univ. Grenoble Alpes, France

BS2017, building simulation 2017, calibration, utility data, demand response potential, Residential Building Energy Models, Residential Demand