An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles

Research article (Sustainable Cities and Society, 2024) · cited 60× · AI/ML
Press Enter · cited answer in seconds

An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles

Summary

An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles is a scholarly article[1].

Key Facts

  • An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles's instance of is recorded as scholarly article[2].

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-applied-deep-reinforcement-learning-approach-to-control-active-networked-microgrids-in-smart-cities-with-multi-level-
MLA “An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-applied-deep-reinforcement-learning-approach-to-control-active-networked-microgrids-in-smart-cities-with-multi-level-.
BibTeX @misc{4ortxyz_an-applied-deep-reinforcement-learning-approach-to-control-active-networked-microgrids-in-smart-cities-with-multi-level-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles}}, year = {2026}, url = {https://4ort.xyz/entity/an-applied-deep-reinforcement-learning-approach-to-control-active-networked-microgrids-in-smart-cities-with-multi-level-}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An applied deep reinforcement learning approach to control active networked microgrids in smart cities with multi-level participation of battery energy storage system and electric vehicles — https://4ort.xyz/entity/an-applied-deep-reinforcement-learning-approach-to-control-active-networked-microgrids-in-smart-cities-with-multi-level- (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/an-applied-deep-reinforcement-learning-approach-to-control-active-networked-microgrids-in-smart-cities-with-multi-level- · Last refreshed: