Multi-agent systems in a distributed smart grid: Design and implementation

By Manisa Pipattanasomporn, Hassan Feroze, Saifur Rahman. IEEE PES Power Systems Conference and Exposition, 2009

767 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6c6aab2c6c272ec1e3ca5d8b3a93bccac2539d73

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In Computer Networks and Communications

In Control and Systems Engineering

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Citations in the corpus

Smart Agents in Industrial Cyber–Physical Systems (2016, background): “…to maintain the balance between the energy demand and supply through a selective shedding of non-priority loads [18, 52, 55], and the Intelligent Distributed Autonomous Power Systems (IDAPS) project aims to supply the critical loads when a failure with the utility grid connection is detected [51].”
A survey on the communication architectures in smart grid (2011, unknown): “For field based applications, agent-based architectures [36] [37] [38] are considered where the agents communicate with each other in a peer to peer manner for local control and protection with the centralized SCADA control center.”
The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, background): “This is also demonstrated by the large number of multi-agent systems that have been designed for a variety of smart grid applications, including power system restoration [256,257], fault diagnosis [258–261], management of distributed energy resources [262–264], demand-side management [265], manageme”
Multiagent-Based Distributed-Energy-Resource Management for Intelligent Microgrids (2013, methodology): “Apart from market simulation, MAS was also used to control and incorporate necessary intelligence to detect faults on utility feeders thereby switching microgrid to island mode [19].”
Learning Attentional Communication for Multi-Agent Cooperation (2018, background): “Similarly, communication can be crucially important in multi-agent reinforcement learning (MARL) for cooperation, especially for the scenarios where a large number of agents work in a collaborative way, such as autonomous vehicles planning [1], smart grid control [20], and multi-robot control [14].”
Multi-agent control system with information fusion based comfort model for smart buildings (2012, methodology): “It has been proven that the multi-agent technology is an effective method to deal with extremely complex system in various fields [2–4].”
State of the Art in Research on Microgrids: A Review (2015, background): “In [245], a MAS architecture is designed to provide control to a microgrid and smooth its transition from grid-connected to an islanded mode during upstream outages.”
Learning Efficient Communication in Cooperative Multi-Agent Environment (2019, background): “In multi-agent reinforcement learning (MARL) collaboration, communication is critical, especially for scenarios where a large number of agents work collaboratively, such as autonomous vehicles planning [3], smart grid control [12], and multi-robot control [10].”
A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity (2017, background): “Examples are ubiquitous in energy applications, for example, to implement a network to distribute electricity (Pipattanasomporn et al., 2009) or to coordinate the charging of electric vehicles (Valogianni et al.”