Decision tree-based approach for online management of pem fuel cells for residential application

This thesis demonstrates a new intelligent technique for the online optimal management of PEM fuel cells units for on site energy production to supply residential utilizations. Classical optimization techniques were based on offline calculations and cannot provide the necessary computational s...

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Main Author:	Mohamed, Mohd Rusllim
Format:	Thesis
Language:	English English English
Published:	2004
Subjects:	TK Electrical engineering Electronics Nuclear engineering TK2896-2985 Production of electricity by direct energy conversion
Online Access:	http://eprints.uthm.edu.my/7679/1/24p%20MOHD%20RUSLLIM%20MOHAMED.pdf http://eprints.uthm.edu.my/7679/2/MOHD%20RUSLLIM%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7679/3/MOHD%20RUSLLIM%20MOHAMED%20WATERMARK.pdf
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id	my-uthm-ep.7679
record_format	uketd_dc
spelling	my-uthm-ep.76792022-09-12T00:59:54Z Decision tree-based approach for online management of pem fuel cells for residential application 2004-11 Mohamed, Mohd Rusllim TK Electrical engineering. Electronics Nuclear engineering TK2896-2985 Production of electricity by direct energy conversion This thesis demonstrates a new intelligent technique for the online optimal management of PEM fuel cells units for on site energy production to supply residential utilizations. Classical optimization techniques were based on offline calculations and cannot provide the necessary computational speed for online performance. In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. The main idea was to employ a classification technique, trained on a sufficient subset of data, to produce an estimate of the optimal setting without repeating the optimization process. A database was extracted from a previously�performed Genetic Algorithm (GA)-based optimization that has been used to create a suitable decision tree, which was intended for generalizing the optimization results. The approach provides the flexibility of adjusting the settings of the fuel cell online according to the observed variations in the tariffs and load demands. Results at different operating conditions are presented to confirm the high accuracy of the proposed generalization technique. The accuracy of the decision tree has been tested by evaluating the relative error with respect to the optimized values. Then, the possibility of pruning the tree has been investigated in order to simplify its structure without affecting the accuracy of the results. In addition, the accuracy of the DTs to approximate the optimal performance of the fuel cell is compared to that of the Artificial Neural Networks (ANNs) used for the same purpose. The results show that the DTs can somewhat outperform the ANNs with certain pruning levels. 2004-11 Thesis http://eprints.uthm.edu.my/7679/ http://eprints.uthm.edu.my/7679/1/24p%20MOHD%20RUSLLIM%20MOHAMED.pdf text en public http://eprints.uthm.edu.my/7679/2/MOHD%20RUSLLIM%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/7679/3/MOHD%20RUSLLIM%20MOHAMED%20WATERMARK.pdf text en validuser mphil masters Kolej Universiti Teknologi Tun Hussein Onn Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TK Electrical engineering Electronics Nuclear engineering TK2896-2985 Production of electricity by direct energy conversion
spellingShingle	TK Electrical engineering Electronics Nuclear engineering TK2896-2985 Production of electricity by direct energy conversion Mohamed, Mohd Rusllim Decision tree-based approach for online management of pem fuel cells for residential application
description	This thesis demonstrates a new intelligent technique for the online optimal management of PEM fuel cells units for on site energy production to supply residential utilizations. Classical optimization techniques were based on offline calculations and cannot provide the necessary computational speed for online performance. In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. The main idea was to employ a classification technique, trained on a sufficient subset of data, to produce an estimate of the optimal setting without repeating the optimization process. A database was extracted from a previously�performed Genetic Algorithm (GA)-based optimization that has been used to create a suitable decision tree, which was intended for generalizing the optimization results. The approach provides the flexibility of adjusting the settings of the fuel cell online according to the observed variations in the tariffs and load demands. Results at different operating conditions are presented to confirm the high accuracy of the proposed generalization technique. The accuracy of the decision tree has been tested by evaluating the relative error with respect to the optimized values. Then, the possibility of pruning the tree has been investigated in order to simplify its structure without affecting the accuracy of the results. In addition, the accuracy of the DTs to approximate the optimal performance of the fuel cell is compared to that of the Artificial Neural Networks (ANNs) used for the same purpose. The results show that the DTs can somewhat outperform the ANNs with certain pruning levels.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohamed, Mohd Rusllim
author_facet	Mohamed, Mohd Rusllim
author_sort	Mohamed, Mohd Rusllim
title	Decision tree-based approach for online management of pem fuel cells for residential application
title_short	Decision tree-based approach for online management of pem fuel cells for residential application
title_full	Decision tree-based approach for online management of pem fuel cells for residential application
title_fullStr	Decision tree-based approach for online management of pem fuel cells for residential application
title_full_unstemmed	Decision tree-based approach for online management of pem fuel cells for residential application
title_sort	decision tree-based approach for online management of pem fuel cells for residential application
granting_institution	Kolej Universiti Teknologi Tun Hussein Onn
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2004
url	http://eprints.uthm.edu.my/7679/1/24p%20MOHD%20RUSLLIM%20MOHAMED.pdf http://eprints.uthm.edu.my/7679/2/MOHD%20RUSLLIM%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7679/3/MOHD%20RUSLLIM%20MOHAMED%20WATERMARK.pdf
_version_	1747831179749359616

Decision tree-based approach for online management of pem fuel cells for residential application

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