Enactment of Deep Reinforcement Learning Control for Power Management and Enhancement of Voltage Regulation in a DC Micro-Grid System

Nishanthi, B.; Kanakaraj, J.

doi:10.1080/15325008.2023.2227200

Electric Power Components and Systems

2023

DOI: 10.1080/15325008.2023.2227200

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Enactment of Deep Reinforcement Learning Control for Power Management and Enhancement of Voltage Regulation in a DC Micro-Grid System

B. Nishanthi

J. Kanakaraj

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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review

Massaoudi,

Abu-Rub,

Ghrayeb

2023

IEEE Access

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The widespread penetration of inverter-based resources has profoundly impacted the electrical stability of power systems (PSs). Deepening grid integration of photovoltaic and wind systems is introducing unforeseen uncertainties for the electricity sector. As a cutting-edge machine learning technology, deep reinforcement learning (DRL) breakthroughs have been in the spotlight over the last few years with potential contributions to PS stability (PSS). The ubiquitous DRL architecture, by learning from the dynamism inherent in PSs, produces near-optimal actions for PSS. This article provides a rigorous review of the latest research efforts focused on DRL to derive PSS policies while accounting for the unique properties of power grids. Furthermore, this paper highlights the theoretical advantages and the key tradeoffs of the emerging DRL techniques as powerful tools for optimal power flow. For all methods outlined, a discussion on their bottlenecks, research challenges, and potential opportunities in large-scale PSS is also presented. This review aims to support research in this area of DRL algorithms to embrace PSS against unseen faults and different PS topologies.INDEX TERMS Deep reinforcement learning, dynamic security control, electric power systems, power system stability, smart grids. Nomenclature

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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review

Massaoudi,

Abu-Rub,

Ghrayeb

2023

IEEE Access

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Enactment of Deep Reinforcement Learning Control for Power Management and Enhancement of Voltage Regulation in a DC Micro-Grid System

Cited by 1 publication

References 29 publications

Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review

Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review

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