CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities-Reference-Cited by-同舟云学术

CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities

Published:2023-11-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
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Author:

Nweye Kingsley¹^ORCID,Kaspar Kathryn²^ORCID,Buscemi Giacomo³^ORCID,Pinto Giuseppe³^ORCID,Li Han⁴^ORCID,Hong Tianzhen⁵^ORCID,Ouf Mohamed²^ORCID,Capozzoli Alfonso³^ORCID,Nagy Zoltan¹^ORCID

Affiliation:

1. The University of Texas at Austin, United States of America

2. Concordia University, Canada

3. Politecnico di Torino, Italy

4. Lawrence Berkeley National Laboratory, USA

5. Lawrence Berkeley National Laboratory, United States of America

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3600100.3626257

Reference14 articles.

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2. Javier Arroyo Lucas Verleyen Lucas Bex Louis Hermans Muhammad Saeed Yucun Lu Joris Depoortere Attila Bálint Erik Delarue Johan Driesen Geert Deconinck David Blum and L. Helsen. 2023. Prototyping the DOPTEST Framework for Simulation-Based Testing of System Integration Strategies in Districts. Javier Arroyo Lucas Verleyen Lucas Bex Louis Hermans Muhammad Saeed Yucun Lu Joris Depoortere Attila Bálint Erik Delarue Johan Driesen Geert Deconinck David Blum and L. Helsen. 2023. Prototyping the DOPTEST Framework for Simulation-Based Testing of System Integration Strategies in Districts.

3. Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings

4. All you need to know about model predictive control for buildings

5. A high-fidelity building performance simulation test bed for the development and evaluation of advanced controls