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 …

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 …

Commercial buildings are significant consumers of electrical power. Also, energy expenses
are an increasing cost factor. Many companies therefore want to save money and reduce …

This paper presents a first attempt to use Dempster-Shafer (DS) evidence theory for the fault
diagnosis of wind turbine (WT) on SCADA alarm data. As two important elements in DS …

Large sized transformers are an important part of global power systems and industrial
infrastructures. An unexpected failure of a power transformer can cause severe production …

Data-driven condition monitoring is an essential function for power plant because of its
potential to enhance asset longevity and reduce the operation and maintenance costs. This …

This study compares four models for industrial condition monitoring including a principal
components analysis (PCA) approach and three deep learning models, one of which is a …

Fault diagnosis and prognosis are important tools for the reliability, availability, and
survivability of navy all-electric ships (AES). Extending the fault detection and diagnosis into …

This paper proposes the concept of Distributed Energy Resource (DER) management,
based on dynamic clustering of energy resources for better coordination of supply and …

This paper describes the use of a combination of anomaly detection and data-trending
techniques encapsulated in a multi-agent framework for the development of a fault detection …