Data driven models that integrate advanced analytics involving statistical and machine learning algorithms are widely applied for simulating and predicting energy demand at the community level. These models are used to inform various energy efficiency measures, infrastructure development, planning and investment decision. The paper presents an innovative framework for simulating and projecting climate change impacts on the future dynamics of community energy demand. The modelling framework selectively couples some of the most advanced analytical approaches and its potential are demonstrated using a case study community “Auroville” located in India.
|Publication status||Published - 5 Sept 2023|
|Event||18th International IBPSA Conference and Exhibition: Building Simulation 2023 - Shanghai, China|
Duration: 4 Sept 2023 → 6 Sept 2023
|Conference||18th International IBPSA Conference and Exhibition|
|Period||4/09/23 → 6/09/23|