most citedData-driven Predictive Control for Unlocking Building Energy Flexibility: A Review

309 citations · 761 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2021★ 60 cited

Development of a Soft Actor Critic Deep Reinforcement Learning Approach for Harnessing Energy Flexibility in a Large Office Building

Anjukan Kathirgamanathan, Eleni Mangina, Donal P. Finn

This research is concerned with the novel application and investigation of `Soft Actor Critic' (SAC) based Deep Reinforcement Learning (DRL) to control the cooling setpoint (and he…

cs.LG2020★ 21 cited

A Centralised Soft Actor Critic Deep Reinforcement Learning Approach to District Demand Side Management through CityLearn

Anjukan Kathirgamanathan, Kacper Twardowski, Eleni Mangina +1

Reinforcement learning is a promising model-free and adaptive controller for demand side management, as part of the future smart grid, at the district level. This paper presents th…

eess.SY2020★ 309 cited

Data-driven Predictive Control for Unlocking Building Energy Flexibility: A Review

Anjukan Kathirgamanathan, Mattia De Rosa, Eleni Mangina +1

Managing supply and demand in the electricity grid is becoming more challenging due to the increasing penetration of variable renewable energy sources. As significant end-use consu…

cs.CY2020★ 107 cited

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…

stat.AP2020★ 264 cited

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…