Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat

Electrical industry is no longer seen as a service to fulfill electrical requirement. Nowadays, the industry is more on business, and the utilities seek profits through efficient energy generation and supply. In order to maximize profits, the energy providers or utilities conduct economic load dispa...

Full description

Saved in:

Bibliographic Details
Main Author:	Rahmat, Nur Azzammudin
Format:	Thesis
Language:	English
Published:	2016
Online Access:	https://ir.uitm.edu.my/id/eprint/18630/1/TP_NUR%20AZZAMMUDIN%20RAHMAT%20EE%2016_5.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.18630
record_format	uketd_dc
spelling	my-uitm-ir.186302018-01-10T03:29:55Z Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat 2016 Rahmat, Nur Azzammudin Electrical industry is no longer seen as a service to fulfill electrical requirement. Nowadays, the industry is more on business, and the utilities seek profits through efficient energy generation and supply. In order to maximize profits, the energy providers or utilities conduct economic load dispatch (ELD) process, where energy is feasibly generated and delivered to satisfy consumers' needs. However, the method is restricted by several constraints that cause challenges in providing satisfying energy dispatch. Therefore, this research proposes a new computational technique termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT) as an approach to solve the complex economic dispatch process. DEIANT is developed through hybridizing Ant Colony Optimization (ACO), Differential Evolution (DE) and Artificial Immune System (AIS) together. The coding were written in MATLAB (Matrix Laboratory) software. The development of DEIANT technique is consequently utilized to solve ELD, which is performed on IEEE 30, 57 and 118 Reliable Test Systems (RTS). These test systems are also used to perform the study for the whole research. New economic emission dispatch (EED) solving techniques termed as pollutant-based and fuel-based EED have been consequently developed. This is to address the emission release during energy producing process. For this study, three fossil-fuels namely petroleum, coal, and natural gas are highlighted. These fossil-fuels combustion produces different pollutants including carbon oxides (COₓ), sulphur oxides (SOₓ), and nitrogen oxides (NOₓ). The pollutant-based EED determines the type and level of the pollutants. On the other hand, fuel-based EED determines the emission level based on the type of fuel consumed by a particular generator. DEIANT is utilized as the optimization engine to minimize the emission level. Combined load-emission dispatch (CLED) technique, which combines ELD and EED simultaneously is proposed. Multi-objective approach is used to solve the CLED through the implementation of weight-sum technique. This approach allows utilities to create trade-off relations or preferences between the operating cost and emission level. DEIANT technique is also utilized to optimize the operating cost and emission level. Next, this research proposes fuzzy logic multi-fuelled dynamic economic load dispatch (FzMF-DELD) to solve multi-fuel selection process. Multi-fuel selection occurs on generators that consume more than one type of fuel. However, different level of output power requires different type of fuel. FzMF-DELD uses fuzzy logic to select the suitable fuel based on the fuel price and required output power. This technique is proven to provide better fuel-selection as compared to conventional piecewise fuel-selection method. DEIANT is utilized to optimize the operating cost and emission level based on the selected fuel. Based on the comparative studies between DEIANT, ACO, PSO, and EP, it is revealed that the proposed optimization technique is superior and more reliable in terms of computing lower operating cost, emission level, power loss, and computation time. 2016 Thesis https://ir.uitm.edu.my/id/eprint/18630/ https://ir.uitm.edu.my/id/eprint/18630/1/TP_NUR%20AZZAMMUDIN%20RAHMAT%20EE%2016_5.pdf text en public phd doctoral Universiti Teknologi MARA Faculty of Electrical Engineering
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
description	Electrical industry is no longer seen as a service to fulfill electrical requirement. Nowadays, the industry is more on business, and the utilities seek profits through efficient energy generation and supply. In order to maximize profits, the energy providers or utilities conduct economic load dispatch (ELD) process, where energy is feasibly generated and delivered to satisfy consumers' needs. However, the method is restricted by several constraints that cause challenges in providing satisfying energy dispatch. Therefore, this research proposes a new computational technique termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT) as an approach to solve the complex economic dispatch process. DEIANT is developed through hybridizing Ant Colony Optimization (ACO), Differential Evolution (DE) and Artificial Immune System (AIS) together. The coding were written in MATLAB (Matrix Laboratory) software. The development of DEIANT technique is consequently utilized to solve ELD, which is performed on IEEE 30, 57 and 118 Reliable Test Systems (RTS). These test systems are also used to perform the study for the whole research. New economic emission dispatch (EED) solving techniques termed as pollutant-based and fuel-based EED have been consequently developed. This is to address the emission release during energy producing process. For this study, three fossil-fuels namely petroleum, coal, and natural gas are highlighted. These fossil-fuels combustion produces different pollutants including carbon oxides (COₓ), sulphur oxides (SOₓ), and nitrogen oxides (NOₓ). The pollutant-based EED determines the type and level of the pollutants. On the other hand, fuel-based EED determines the emission level based on the type of fuel consumed by a particular generator. DEIANT is utilized as the optimization engine to minimize the emission level. Combined load-emission dispatch (CLED) technique, which combines ELD and EED simultaneously is proposed. Multi-objective approach is used to solve the CLED through the implementation of weight-sum technique. This approach allows utilities to create trade-off relations or preferences between the operating cost and emission level. DEIANT technique is also utilized to optimize the operating cost and emission level. Next, this research proposes fuzzy logic multi-fuelled dynamic economic load dispatch (FzMF-DELD) to solve multi-fuel selection process. Multi-fuel selection occurs on generators that consume more than one type of fuel. However, different level of output power requires different type of fuel. FzMF-DELD uses fuzzy logic to select the suitable fuel based on the fuel price and required output power. This technique is proven to provide better fuel-selection as compared to conventional piecewise fuel-selection method. DEIANT is utilized to optimize the operating cost and emission level based on the selected fuel. Based on the comparative studies between DEIANT, ACO, PSO, and EP, it is revealed that the proposed optimization technique is superior and more reliable in terms of computing lower operating cost, emission level, power loss, and computation time.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Rahmat, Nur Azzammudin
spellingShingle	Rahmat, Nur Azzammudin Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat
author_facet	Rahmat, Nur Azzammudin
author_sort	Rahmat, Nur Azzammudin
title	Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat
title_short	Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat
title_full	Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat
title_fullStr	Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat
title_full_unstemmed	Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat
title_sort	computational intelligence based technique for solving economic dispatch problem / nur azzammudin rahmat
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Electrical Engineering
publishDate	2016
url	https://ir.uitm.edu.my/id/eprint/18630/1/TP_NUR%20AZZAMMUDIN%20RAHMAT%20EE%2016_5.pdf
_version_	1783733701163614208

Computational intelligence based technique for solving economic dispatch problem / Nur Azzammudin Rahmat

Similar Items