Leveraging Deep Reinforcement Learning for Water Distribution Systems with Large Action Spaces and Uncertainties: DRL-EPANET for Pressure Control-Reference-Cited by-同舟云学术

Leveraging Deep Reinforcement Learning for Water Distribution Systems with Large Action Spaces and Uncertainties: DRL-EPANET for Pressure Control

Published:2024-02 Issue:2 Volume:150 Page:
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Belfadil Anas¹^ORCID,Modesto David²,Meseguer Jordi³^ORCID,Joseph-Duran Bernat⁴,Saporta David⁵,Martin Hernandez Jose Antonio⁶

Affiliation:

1. Ph.D. Candidate, Artificial Intelligence, Dept. of Computer Science, Universitat Politècnica de Catalunya, Jordi Girona, 31, Barcelona 08034, Spain (corresponding author). ORCID: .

2. Established Researcher, Dept. of Computer Applications in Science and Engineering, Barcelona Supercomputing Center—Centro Nacional de Supercomputación, Plaça Eusebi Güell 1-3, Barcelona 08034, Spain.

3. Project Manager/Researcher, Critical Infrastructure Management and Resiliance Area, CETaqua, Water Technology Centre, Ctra. d’Esplugues 75, Cornella del LLobregat, Barcelona 08940, Spain. ORCID: .

4. Project Manager/Researcher, Critical Infrastructure Management and Resiliance Area, CETaqua, Water Technology Centre, Ctra. d’Esplugues 75, Cornella del LLobregat, Barcelona 08940, Spain.

5. Engineer, Aigües de Barcelona, Dept. of Digitalisation and Operational Excellence, General Batet 1-7, Barcelona 08028, Spain.

6. Technical Advisor, Advanced Mathematics, Repsol Technology Lab, P.° de Extremadura, Km 18, Móstoles, Madrid 28935, Spain.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JWRMD5.WRENG-6108

Reference34 articles.

1. Deep reinforcement learning at the edge of the statistical precipice;Agarwal R.;Adv. Neural Inf. Process. Syst.,2021

2. Pressure Control for Leakage Minimisation in Water Distribution Systems Management

3. Berner C. et al. 2019. “Dota 2 with large scale deep reinforcement learning.” Preprint submitted December 13 2019. http://arxiv.org/abs/1912.06680.

4. Energy Recovery and Leakage-Reduction Optimization of Water Distribution Systems Using Hydro Turbines

5. Brockman G. V. Cheung L. Pettersson J. Schneider J. Schulman J. Tang and W. Zaremba. 2016. “OpenAI Gym.” Preprint submitted June 5 2016. http://arxiv.org/abs/1606.01540.

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