Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed

In a generation operating system planning, avoided utility cost (AUC) is customarily implemented to attain the optimal economic benefits in a generating system by taking into account intriguing issues on the energy efficiency, renewable energy sources or conservation programs. In this thesis a new a...

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Main Author:	Mohammed, Daw Saleh Sasi
Format:	Thesis
Language:	English
Published:	2016
Subjects:	Managerial control systems
Online Access:	https://ir.uitm.edu.my/id/eprint/106775/1/106775.pdf
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id	my-uitm-ir.106775
record_format	uketd_dc
spelling	my-uitm-ir.1067752024-11-22T08:14:17Z Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed 2016 Mohammed, Daw Saleh Sasi Managerial control systems Computer engineering. Computer hardware In a generation operating system planning, avoided utility cost (AUC) is customarily implemented to attain the optimal economic benefits in a generating system by taking into account intriguing issues on the energy efficiency, renewable energy sources or conservation programs. In this thesis a new approaches of optimal dispatch of limited energy unit (ODLEU) and demand side management (DSM) using computational intelligence approach is proposed for AUC improvement. Contrary to the conventional approaches, which mainly rely on dispatching of each limited energy unit (LEU) in sequential order, the proposed algorithm comprising with optimization technique is used as an alternative for performing LEU dispatch; which has a tangible impact to improve and increase the AUC value. In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). The AUC is originated from the summation of avoided energy cost, avoided expected cycle cost and avoided capacity cost of the generating system… 2016 Thesis https://ir.uitm.edu.my/id/eprint/106775/ https://ir.uitm.edu.my/id/eprint/106775/1/106775.pdf text en public phd doctoral Universiti Teknologi MARA Institute of Graduate Studies, UiTM
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Managerial control systems Managerial control systems
spellingShingle	Managerial control systems Managerial control systems Mohammed, Daw Saleh Sasi Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed
description	In a generation operating system planning, avoided utility cost (AUC) is customarily implemented to attain the optimal economic benefits in a generating system by taking into account intriguing issues on the energy efficiency, renewable energy sources or conservation programs. In this thesis a new approaches of optimal dispatch of limited energy unit (ODLEU) and demand side management (DSM) using computational intelligence approach is proposed for AUC improvement. Contrary to the conventional approaches, which mainly rely on dispatching of each limited energy unit (LEU) in sequential order, the proposed algorithm comprising with optimization technique is used as an alternative for performing LEU dispatch; which has a tangible impact to improve and increase the AUC value. In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). The AUC is originated from the summation of avoided energy cost, avoided expected cycle cost and avoided capacity cost of the generating system…
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohammed, Daw Saleh Sasi
author_facet	Mohammed, Daw Saleh Sasi
author_sort	Mohammed, Daw Saleh Sasi
title	Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed
title_short	Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed
title_full	Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed
title_fullStr	Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed
title_full_unstemmed	Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed
title_sort	computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / daw saleh sasi mohammed
granting_institution	Universiti Teknologi MARA
granting_department	Institute of Graduate Studies, UiTM
publishDate	2016
url	https://ir.uitm.edu.my/id/eprint/106775/1/106775.pdf
_version_	1818588183764402176

Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed

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