Optimal Scheduling in IoT-Driven Smart Isolated Microgrids Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Optimal Scheduling in IoT-Driven Smart Isolated Microgrids Based on Deep Reinforcement Learning

Published:2023-09-15 Issue:18 Volume:10 Page:16284-16299
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Qi Jiaju¹,Lei Lei¹^ORCID,Zheng Kan²^ORCID,Yang Simon X.¹^ORCID,Shen Xuemin³^ORCID

Affiliation:

1. School of Engineering, University of Guelph, Guelph, Canada

2. College of Electrical Engineering and Computer Sciences, Ningbo University, Ningbo, China

3. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada

Funder

Natural Sciences and Engineering Research Council (NSERC) of Canada

University of Guelph through CARE-AI Seed Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10242177/10107374.pdf?arnumber=10107374

Reference42 articles.

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3. A Two-Stage Model Predictive Control Strategy for Economic Diesel-PV-Battery Island Microgrid Operation in Rural Areas

4. Intelligent Multi-Microgrid Energy Management Based on Deep Neural Network and Model-Free Reinforcement Learning

5. Assessing the impact of a two-layer predictive dispatch algorithm on design and operation of off-grid hybrid microgrids

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