A data-driven demand response recommender system

摘要: Unprecedented amounts of information from millions of smart meters and thermostats installed in recent years has left the door open for systems engineers and data scientists to better understand, analyze and use the insights that raw data can provide, about the power consumption patterns of a building. The challenge now, with using data-driven approaches, is to close the loop for near real time control and decision making in large scale cyber physical energy systems. Furthermore, providing a technological solution alone is not enough, the solution must also be human centric. We present a method called DR-Advisor called DR-Advisor, which acts as a recommender system for the building's facilities manager and provides suitable control actions to meet the desired load curtailment while maintaining operations and maximizing the economic reward. We evaluate the performance of DR-Advisor for demand …