264 citations · 690 across the 9 of their papers we have counts for
9 papers
MERLIN: Multi-agent offline and transfer learning for occupant-centric energy flexible operation of grid-interactive communities using smart meter data and CityLearn
Kingsley Nweye, Siva Sankaranarayanan, Zoltan Nagy
The decarbonization of buildings presents new challenges for the reliability of the electrical grid as a result of the intermittency of renewable energy sources and increase in gri…
Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives
H. Li, H. Johra, F. de Andrade Pereira +15
Energy flexibility, through short-term demand-side management (DSM) and energy storage technologies, is now seen as a major key to balancing the fluctuating supply in different ene…
Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings
Kingsley Nweye, Bo Liu, Peter Stone +1
Building upon prior research that highlighted the need for standardizing environments for building control research, and inspired by recently introduced challenges for real life re…
MARTINI: Smart Meter Driven Estimation of HVAC Schedules and Energy Savings Based on WiFi Sensing and Clustering
Kingsley Nweye, Zoltan Nagy
HVAC systems account for a significant portion of building energy use. Nighttime setback scheduling is an energy conservation measure where cooling and heating setpoints are increa…
GridLearn: Multiagent Reinforcement Learning for Grid-Aware Building Energy Management
Aisling Pigott, Constance Crozier, Kyri Baker +1
Increasing amounts of distributed generation in distribution networks can provide both challenges and opportunities for voltage regulation across the network. Intelligent control o…
CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management
Jose R Vazquez-Canteli, Sourav Dey, Gregor Henze +1
Rapid urbanization, increasing integration of distributed renewable energy resources, energy storage, and electric vehicles introduce new challenges for the power grid. In the US,…
The ASHRAE Great Energy Predictor III competition: Overview and results
Clayton Miller, Pandarasamy Arjunan, Anjukan Kathirgamanathan +8
In late 2019, ASHRAE hosted the Great Energy Predictor III (GEPIII) machine learning competition on the Kaggle platform. This launch marked the third energy prediction competition…
The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition
Clayton Miller, Anjukan Kathirgamanathan, Bianca Picchetti +7
This paper describes an open data set of 3,053 energy meters from 1,636 non-residential buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 meas…
Quick-cast: A method for fast and precise scalable production of fluid-driven elastomeric soft actuators
Bratislav Svetozarevic, Moritz Begle, Stefan Caranovic +2
Fluid-driven elastomeric actuators (FEAs) are among the most popular actuators in the emerging field of soft robotics. Intrinsically compliant, with continuum of motion, large stro…