This is the first part of a two-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group.Part I of this paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multiagent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part II of this paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented.Index Terms-Multi-agent systems.

This paper describes a set of anomaly-detection techniques and their applicability to wind turbine fault identification. It explains how the anomaly-detection techniques have been adopted to analyse supervisory control and data acquisition data acquired from a wind farm, automating and simplifying the operators' analysis task by interpreting the volume of data available. The techniques are brought together into one system to collate their output and provide a single decision support environment for an operator. The framework used is a novel multi-agent system architecture that offers the opportunity to corroborate the output of the various interpretation techniques in order to improve the accuracy of fault detection. The results presented demonstrate that the interpretation techniques can provide performance assessment and early fault identification, thereby giving the operators sufficient time to make more informed decisions regarding the maintenance of their machines

T. (2007) Multi-agent systems for power engineering applicationspart 2: technologies, standards and tools for building multi-agent systems. IEEE Transactions on Power Systems, 22 (4). pp. 1753-1759.

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