Intelligent automation and IT for the optimization of renewable energy and wastewater treatment processes: Doc 19

Environmental systems often have a very complex structure. Methods from computational intelligence (CI) that are often inspired by nature can help to improve these systems. On the one hand, CI methods can be used for optimization; on the other hand, they can be used to extract information out of tim...

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Bibliographic Details
Published in:Energy, sustainability and society sustainability and society, 2014-09, Vol.4, p.1
Main Authors: Bongards, Michael, Gaida, Daniel, Trauer, Oliver, Wolf, Christian
Format: Article
Language:English
Subjects:
Algorithms
Alternative energy sources
Anaerobic digestion
Artificial intelligence
Automation
Biogas
Computational mathematics
Data analysis
Discriminant analysis
Efficiency
Heaters
Human-computer interaction
Machine learning
Optimization
Renewable energy
Renewable resources
Sensors
Society
Studies
Sustainability
Wastewater management
Wastewater treatment
Water treatment
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Summary:Environmental systems often have a very complex structure. Methods from computational intelligence (CI) that are often inspired by nature can help to improve these systems. On the one hand, CI methods can be used for optimization; on the other hand, they can be used to extract information out of time series recorded from environmental systems. Methods from different fields of computational intelligence are investigated. Among them are supervised and unsupervised machine learning methods used for classification and cluster analysis, respectively. Furthermore, methods from evolutionary computation and multi-agent systems are used to develop control and optimization solutions for environmental processes. In this paper, five applications in the fields of anaerobic digestion, pellet-heating, and wastewater management are studied. Using CI methods, e.g., biogas plant operation or a pellet-heating process can be optimized. Furthermore, important process variables can be obtained from huge measurement datasets that otherwise would be unanalyzed and therefore data cemeteries. The results reveal that using CI methods environmental processes can be improved in a favorable cost-benefit fashion.[PUBLICATION ABSTRACT]
ISSN:2192-0567
DOI:10.1186/s13705-014-0019-3