Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization

In the paper, a proposed particle swarm optimization (PPSO) is implemented for dealing with an economic load dispatch (ELD) problem considering the competitive electric market. The main task of the problem is to determine optimal power generation and optimal reserve generation of available thermal g...

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Tác giả chính:	Le Chi Kien, Thanh Long Duong, Van-Duc Phan, Thang Trung Nguyen
Định dạng:	journal-article
Ngôn ngữ:	en_US
Thông tin xuất bản:	2022
Chủ đề:	"competitive electricity market maximum total profit particle swarm optimization total fuel cost total revenue"
Truy cập trực tuyến:	http://repository.vlu.edu.vn:443/handle/123456789/645
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spelling	oai:http:--repository.vlu.edu.vn-:123456789-6452022-11-02T10:02:19Z Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization Le Chi Kien Thanh Long Duong Van-Duc Phan Thang Trung Nguyen "competitive electricity market maximum total profit particle swarm optimization total fuel cost total revenue" In the paper, a proposed particle swarm optimization (PPSO) is implemented for dealing with an economic load dispatch (ELD) problem considering the competitive electric market. The main task of the problem is to determine optimal power generation and optimal reserve generation of available thermal generation units so that total profit of all the units is maximized. In addition, constraints, such as generation limit and reserve limit of each unit, power demand and reserve demand, must be exactly satisfied. PPSO is an improved version of conventional particle swarm optimization (PSO) by combining pseudo gradient method, constriction factor and a newly proposed position update method. On the other hand, in order to support PPSO to reach good results for the considered problem, a new constraint handling method (NCHM) is also proposed for determining maximum reserve generation and correcting reserve generation. Three test systems with 3, 10 and 20 units are employed to evaluate the real performance of PPSO. In addition to the comparisons with previous methods, salp swarm optimization (SSA), modified differential evolution (MDE) and eight other PSO methods are also implemented for comparisons. Through the result comparisons, two main contributions of the study are as follows: (1) NCHM is very effective for PSO methods to reach a high success rate and higher solution quality, (2) PPSO is more effective than other methods. Consequently, NCHM and PPSO are the useful combination for the considered problem. 2022-11-02T03:02:19Z 2022-11-02T03:02:19Z 2020 journal-article http://repository.vlu.edu.vn:443/handle/123456789/645 10.3390/su12031265 en_US Sustainability 2071-1050 application/pdf
institution	Trường Đại học Văn Lang
collection	DSpaceVLU
language	en_US
topic	"competitive electricity market maximum total profit particle swarm optimization total fuel cost total revenue"
spellingShingle	"competitive electricity market maximum total profit particle swarm optimization total fuel cost total revenue" Le Chi Kien Thanh Long Duong Van-Duc Phan Thang Trung Nguyen Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization
description	In the paper, a proposed particle swarm optimization (PPSO) is implemented for dealing with an economic load dispatch (ELD) problem considering the competitive electric market. The main task of the problem is to determine optimal power generation and optimal reserve generation of available thermal generation units so that total profit of all the units is maximized. In addition, constraints, such as generation limit and reserve limit of each unit, power demand and reserve demand, must be exactly satisfied. PPSO is an improved version of conventional particle swarm optimization (PSO) by combining pseudo gradient method, constriction factor and a newly proposed position update method. On the other hand, in order to support PPSO to reach good results for the considered problem, a new constraint handling method (NCHM) is also proposed for determining maximum reserve generation and correcting reserve generation. Three test systems with 3, 10 and 20 units are employed to evaluate the real performance of PPSO. In addition to the comparisons with previous methods, salp swarm optimization (SSA), modified differential evolution (MDE) and eight other PSO methods are also implemented for comparisons. Through the result comparisons, two main contributions of the study are as follows: (1) NCHM is very effective for PSO methods to reach a high success rate and higher solution quality, (2) PPSO is more effective than other methods. Consequently, NCHM and PPSO are the useful combination for the considered problem.
format	journal-article
author	Le Chi Kien Thanh Long Duong Van-Duc Phan Thang Trung Nguyen
author_facet	Le Chi Kien Thanh Long Duong Van-Duc Phan Thang Trung Nguyen
author_sort	Le Chi Kien
title	Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization
title_short	Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization
title_full	Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization
title_fullStr	Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization
title_full_unstemmed	Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization
title_sort	maximizing total profit of thermal generation units in competitive electric market by using a proposed particle swarm optimization
publishDate	2022
url	http://repository.vlu.edu.vn:443/handle/123456789/645
work_keys_str_mv	AT lechikien maximizingtotalprofitofthermalgenerationunitsincompetitiveelectricmarketbyusingaproposedparticleswarmoptimization AT thanhlongduong maximizingtotalprofitofthermalgenerationunitsincompetitiveelectricmarketbyusingaproposedparticleswarmoptimization AT vanducphan maximizingtotalprofitofthermalgenerationunitsincompetitiveelectricmarketbyusingaproposedparticleswarmoptimization AT thangtrungnguyen maximizingtotalprofitofthermalgenerationunitsincompetitiveelectricmarketbyusingaproposedparticleswarmoptimization
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Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization

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