Affiliations: [a] Computer Architecture and Networks Group. School of Computer Science, University of Castilla-La Mancha, Ciudad Real, Spain | [b] School of Industrial Engineering, University of Castilla-La Mancha, Ciudad Real, Spain | Department of Computer Science and Engineering, University of Minnesota, 4-192 EE/CS Building, 200 Union Street S.E., Minneapolis, MN 55455-0159, USA
Correspondence:
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Corresponding author. Dr. Maria Jose Santofimia, E-mail: [email protected].
Abstract: Problems derived from the power quality aspects of a power grid are turning the monitoring and diagnosis tasks into an appealing field for electrical power researchers. This interest is mainly founded on the great importance of providing highly reliable power grids, but also because of the relatively simple task (computationally speaking) required to accomplish the measurements. Despite its potential importance, efforts are mainly targeted at collecting data and comparing them to quality standards, rather than identifying problems, providing solutions or anticipating power faults. Aware of this shortcoming, this work is intended to bridge the gap that leads to self-sufficient systems, capable of anticipating and reacting to power faults, instead of a simple data gathering. This work also provides a characterization of the power quality domain, proposing a qualitative behavioral model that supports the multi-agent system in its task to anticipate and wisely react to power faults, and improve power quality.
Keywords: Qualitative reasoning, power quality, multi-agent systems
