Authors:
Miguel Kpakpo
;
Mhamed Itmi
and
Alain Cardon
Affiliation:
Normandie Université, INSA and LITIS, France
Keyword(s):
Cost Optimization, Decision Support Systems, Maintenance Strategy, MAS, O&M.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
The aim of this work is to propose a new method of analysis and optimization of maintenance strategy for
wind farms. The objective is to help wind farm operator to carry out the optimization of the maintenance
costs through profitability analysis of the wind farm according to failures, planned shutdown situations and
maintenance budgets. Such approach has the advantage of combining the O&M (optimization and
maintenance) technical vision and the financial vision within the meaning of profitability. The platform
model is based on multi-agent systems. It aims to realize the calculation and optimization of scenarios.
Agents have been identified from the knowledge of the windfarm O&M domain thanks to the wind farm
operator’s point of view. The platform we’re developing is named PROMEEO, a French acronym for O&M
onshore wind farms rationalization and optimization’s platform.