Agent-based substation automation

Buse, D.P.; Sun, Pu; Fitch, J.

doi:10.1109/mpae.2003.1192026

Cited by 69 publications

(36 citation statements)

References 2 publications

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“…In the last decade, intelligent agent and multiagent technologies had been adopted for various aspects of power grid systems management, such as restoration [5], relaying [6], maintenance [7], substation automation [8] and state estimation [9]. In this paper, we focus on power grid systems restoration when one or several generators in a power grid system are out of order.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Multiagent Framework With Q-Learning for Power Grid Systems Restoration

Zhang

Sutanto

2011

IEEE Trans. Power Syst.

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Abstract-This paper presents a hybrid multi-agent framework with a Q-learning algorithm to support rapid restoration of power grid systems following catastrophic disturbances involving loss of generators. This framework integrates the advantages of both centralised and decentralised architectures to achieve accurate decision making and quick responses when potential cascading failures are detected in power systems. By using this hybrid framework, which does not rely on a centralised controller, the single point of failure in power grid systems can be avoided. Further, the use of the Q-learning algorithm developed in conjunction with the restorative framework can help the agents to make accurate decisions to protect against cascading failures in a timely manner without requiring a global reward signal. Simulation results demonstrate the effectiveness of the proposed approach in comparison with the typical centralised and decentralised approaches based on several evaluation attributes.

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Section: Related Workmentioning

confidence: 99%

A Hybrid Multiagent Framework With Q-Learning for Power Grid Systems Restoration

Zhang

Sutanto

2011

IEEE Trans. Power Syst.

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“…Based on these advantages, MAS technology has been applied in electric grids for a range of applications, including power system disturbance diagnosis [31], condition monitoring [32], power system restoration [33], market simulation [34,35], power system secondary voltage control [36], power system visualization [37] and automation [38]. Moreover, the technology is maturing to the point where the first MAS are now being migrated from the laboratory to the utilities, allowing industry to gain experience in the use of MAS and also to evaluate their effectiveness [39].…”

Section: Communication and Control System Based On Masmentioning

confidence: 99%

Hierarchical MAS Based Control Strategy for Microgrid

Xiao

Huang

et al. 2010

Energies

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Abstract:Microgrids have become a hot topic driven by the dual pressures of environmental protection concerns and the energy crisis. In this paper, a challenge for the distributed control of a modern electric grid incorporating clusters of residential microgrids is elaborated and a hierarchical multi-agent system (MAS) is proposed as a solution. The issues of how to realize the hierarchical MAS and how to improve coordination and control strategies are discussed. Based on MATLAB and ZEUS platforms, bilateral switching between grid-connected mode and island mode is performed under control of the proposed MAS to enhance and support its effectiveness.

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“…Mobile agents provide this mechanism through code migration; for instance, if an agent is to be replaced on a particular remote node, a new agent can be dispatched from a central location to take the place of the old agent, calling for its deletion on arrival to its new location. Mobile agent technology has previously been applied to power engineering applications by authors such as Wu et al [8] and Kezunovic [9] Mobile agents for sensor networks has become a popular research area, and to the authors knowledge there are at least four research groups that have published work regarding mobile agent-based sensor networks [10], [11], [12], [13]. The focus of these platforms has been the use of mobile agents to navigate through a sensor network, performing local data analysis on each node before returning to a central location for both code update and data retrieval purposes.…”

Section: A Mobile Vs Static Agentsmentioning

confidence: 99%

Data Management of On-Line Partial Discharge Monitoring Using Wireless Sensor Nodes Integrated with a Multi-Agent System

Baker

McArthur

Judd

2007

2007 International Conference on Intelligent Systems Applications to Power Systems

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Abstract-On-line partial discharge monitoring has been the subject of significant research in previous years but little work has been carried out with regard to the management of onsite data. To date, on-line partial discharge monitoring within a substation has only been concerned with single plant items, so the data management problem has been minimal. As the age of plant equipment increases, so does the need for condition monitoring to ensure maximum lifespan. This paper presents an approach to the management of partial discharge data through the use of embedded monitoring techniques running on wireless sensor nodes. This method is illustrated by a case study on partial discharge monitoring data from an ageing HVDC reactor.

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Agent-based substation automation

Cited by 69 publications

References 2 publications

A Hybrid Multiagent Framework With Q-Learning for Power Grid Systems Restoration

A Hybrid Multiagent Framework With Q-Learning for Power Grid Systems Restoration

Hierarchical MAS Based Control Strategy for Microgrid

Data Management of On-Line Partial Discharge Monitoring Using Wireless Sensor Nodes Integrated with a Multi-Agent System

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