Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach

To maximise the benefits offered by distributed generation (DG) in electric power systems, there is clearly a need to determine the optimum size, as well as the best site of that particular DG unit(s) in the network. Recent research has shown that improper placement of DG units in power systems woul...

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Main Author:	Akorede, Mudathir Funsho
Format:	Thesis
Language:	English
Published:	2011
Subjects:	Electric power systems Genetic algorithms
Online Access:	http://psasir.upm.edu.my/id/eprint/42201/1/FK%202011%2066R.pdf
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spelling	my-upm-ir.422012016-03-10T06:57:44Z Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach 2011-08 Akorede, Mudathir Funsho To maximise the benefits offered by distributed generation (DG) in electric power systems, there is clearly a need to determine the optimum size, as well as the best site of that particular DG unit(s) in the network. Recent research has shown that improper placement of DG units in power systems would not only lead to an increased energy loss cost, but could also jeopardize the system operation. To avert these scenarios and tackle this optimisation problem, this thesis proposes two models to guide electric utilities in determining the optimal capacity and location of DG units in power networks. The first model for meshed electric power networks, which could be employed for subtransmission networks operating at up to 132 kV level, uses two objective functions. The model maximises the system loading margin as well as the profit of the distribution company (DISCO) over the planning period. The other model is designed for radial distribution networks operating at 33 kV and below voltage levels. The main objective functions considered in this model are maximisation of cost savings arising from energy loss, minimisation of line voltage drop, and maximisation of the transfer capability of the system. This model takes into account, the peculiarities of radial distribution networks, such as high R/X (resistance/reactance) ratio, voltage dependency and composite nature of loads.To solve the proposed models, Genetic algorithm (GA) is used as an optimisation technique. In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA’s operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The accuracy of the proposed models is evaluated on test power systems, and the results obtained are compared with those of the existing approaches cited in this literature, which is highly impressive. This thesis also investigates the impact of different penetration levels of DG in both subtransmission and distribution networks. In the study, a 15-bus test system is employed and modelled in detail using Power System Analysis Toolbox (PSAT). However, only synchronous type of DGs is considered since it is the most popular type in use. In this work, the impact of DG of different penetration levels on system stability and power quality are thoroughly examined under different fault scenarios. The results obtained suggest that 20 % penetration level of DG is optimal for both normal and during contingencies in the case study system. This research work is concluded with a software development. The package called Power Flow Analysis and DG Optimisation Tool (PFADOT) is developed using the Graphical User Interface (GUI) of MATLAB. This provides a user friendly interface for the system operator in determining the optimal allocation of a single DG unit in radial distribution networks. The evolved package is tested with several test systems, and the results obtained are validated against an existing related package. The developed package does not only give more optimal results but also does that in a more computationally efficient manner. Electric power systems Genetic algorithms 2011-08 Thesis http://psasir.upm.edu.my/id/eprint/42201/ http://psasir.upm.edu.my/id/eprint/42201/1/FK%202011%2066R.pdf application/pdf en public phd doctoral Universiti Putra Malaysia Electric power systems Genetic algorithms
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Electric power systems Genetic algorithms
spellingShingle	Electric power systems Genetic algorithms Akorede, Mudathir Funsho Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
description	To maximise the benefits offered by distributed generation (DG) in electric power systems, there is clearly a need to determine the optimum size, as well as the best site of that particular DG unit(s) in the network. Recent research has shown that improper placement of DG units in power systems would not only lead to an increased energy loss cost, but could also jeopardize the system operation. To avert these scenarios and tackle this optimisation problem, this thesis proposes two models to guide electric utilities in determining the optimal capacity and location of DG units in power networks. The first model for meshed electric power networks, which could be employed for subtransmission networks operating at up to 132 kV level, uses two objective functions. The model maximises the system loading margin as well as the profit of the distribution company (DISCO) over the planning period. The other model is designed for radial distribution networks operating at 33 kV and below voltage levels. The main objective functions considered in this model are maximisation of cost savings arising from energy loss, minimisation of line voltage drop, and maximisation of the transfer capability of the system. This model takes into account, the peculiarities of radial distribution networks, such as high R/X (resistance/reactance) ratio, voltage dependency and composite nature of loads.To solve the proposed models, Genetic algorithm (GA) is used as an optimisation technique. In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA’s operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The accuracy of the proposed models is evaluated on test power systems, and the results obtained are compared with those of the existing approaches cited in this literature, which is highly impressive. This thesis also investigates the impact of different penetration levels of DG in both subtransmission and distribution networks. In the study, a 15-bus test system is employed and modelled in detail using Power System Analysis Toolbox (PSAT). However, only synchronous type of DGs is considered since it is the most popular type in use. In this work, the impact of DG of different penetration levels on system stability and power quality are thoroughly examined under different fault scenarios. The results obtained suggest that 20 % penetration level of DG is optimal for both normal and during contingencies in the case study system. This research work is concluded with a software development. The package called Power Flow Analysis and DG Optimisation Tool (PFADOT) is developed using the Graphical User Interface (GUI) of MATLAB. This provides a user friendly interface for the system operator in determining the optimal allocation of a single DG unit in radial distribution networks. The evolved package is tested with several test systems, and the results obtained are validated against an existing related package. The developed package does not only give more optimal results but also does that in a more computationally efficient manner.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Akorede, Mudathir Funsho
author_facet	Akorede, Mudathir Funsho
author_sort	Akorede, Mudathir Funsho
title	Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
title_short	Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
title_full	Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
title_fullStr	Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
title_full_unstemmed	Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
title_sort	optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
granting_institution	Universiti Putra Malaysia
publishDate	2011
url	http://psasir.upm.edu.my/id/eprint/42201/1/FK%202011%2066R.pdf
_version_	1747811900113027072

Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach

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