Automated Demand Response Considering Consumer Satisfaction and Congestion Relief Potential

This study develops a smart building HVAC management system considering consumer’s and distributor’s perspectives. A mathematical model will be formulated such that the total cost and dissatisfaction are minimized and the building’s potential to provide congestion relief in the area will be measured. In order to overcome the complexity of the problem, a group of deep reinforcement learning methods will be developed to manage the electricity flow in the building. The results will be validated by the real data provided by BrainBox AI and will be applied on some different clusters of the consumers. Moreover, some cost and benefit investment analysis will be carried out to provide policy making recommendations.

Faculty Supervisor:

Pierre-Olivier Pineau

Student:

Partner:

BrainBox AI

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

HEC Montréal

Program: