Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm
Battery manufacturing and recycling are expensive; combined heat and power (CHP) units are optimal for residential premises. CHP units can enhance energy efficiency and reduce energy costs, but appropriately sized units must be chosen. Here, we optimize CHP unit sizing to minimize the energy costs o...
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Language: | English |
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IEEE
2020-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/9279200/ |
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author | Habib Ur Rahman Habib Shaorong Wang Asad Waqar Bashar Sakeen Farhan Kotb M. Kotb Yun-Su Kim |
author_facet | Habib Ur Rahman Habib Shaorong Wang Asad Waqar Bashar Sakeen Farhan Kotb M. Kotb Yun-Su Kim |
author_sort | Habib Ur Rahman Habib |
collection | DOAJ |
description | Battery manufacturing and recycling are expensive; combined heat and power (CHP) units are optimal for residential premises. CHP units can enhance energy efficiency and reduce energy costs, but appropriately sized units must be chosen. Here, we optimize CHP unit sizing to minimize the energy costs of residential areas. Sizing is based on both the electricity and heat loads; it is possible to optimally rate the various types of CHP units. We compare an artificial bee colony (ABC) optimization method to a genetic algorithm (GA) when various strategies are adopted. Electricity and heat loads are considered together when sizing CHP units and optimizing costs using the ABC algorithm and the GA. The optimization outcomes are compared to a base case; the ABC method performs better than the GA. The average daily energy cost savings possible using the ABC method were higher for all three seasons (by 25.9, 4.4, and 10.8% respectively) compared to those possible when residential premises lacked CHP units. |
first_indexed | 2024-12-17T05:14:23Z |
format | Article |
id | doaj.art-371bc38248db4e7a99da0919a3e27434 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-12-17T05:14:23Z |
publishDate | 2020-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-371bc38248db4e7a99da0919a3e274342022-12-21T22:02:10ZengIEEEIEEE Access2169-35362020-01-01821828921830310.1109/ACCESS.2020.30421739279200Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony AlgorithmHabib Ur Rahman Habib0https://orcid.org/0000-0003-2640-3185Shaorong Wang1https://orcid.org/0000-0001-6239-2845Asad Waqar2https://orcid.org/0000-0001-6500-0990Bashar Sakeen Farhan3https://orcid.org/0000-0002-5746-8638Kotb M. Kotb4https://orcid.org/0000-0002-9601-6167Yun-Su Kim5https://orcid.org/0000-0002-6803-929XState Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, ChinaState Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Electrical Engineering, Bahria University, Islamabad, PakistanElectrical Engineering Department, Engineering College, Al-Iraqia University, Baghdad, IraqElectrical Power and Machines Engineering Department, Faculty of Engineering, Tanta University, Tanta, EgyptGraduate School of Energy Convergence, Gwangju Institute of Science and Technology (GIST), Gwangju, South KoreaBattery manufacturing and recycling are expensive; combined heat and power (CHP) units are optimal for residential premises. CHP units can enhance energy efficiency and reduce energy costs, but appropriately sized units must be chosen. Here, we optimize CHP unit sizing to minimize the energy costs of residential areas. Sizing is based on both the electricity and heat loads; it is possible to optimally rate the various types of CHP units. We compare an artificial bee colony (ABC) optimization method to a genetic algorithm (GA) when various strategies are adopted. Electricity and heat loads are considered together when sizing CHP units and optimizing costs using the ABC algorithm and the GA. The optimization outcomes are compared to a base case; the ABC method performs better than the GA. The average daily energy cost savings possible using the ABC method were higher for all three seasons (by 25.9, 4.4, and 10.8% respectively) compared to those possible when residential premises lacked CHP units.https://ieeexplore.ieee.org/document/9279200/Artificial bee colonycost-benefit analysisCHP unit size optimizationenergy conversiongenetic algorithmresidential building automation |
spellingShingle | Habib Ur Rahman Habib Shaorong Wang Asad Waqar Bashar Sakeen Farhan Kotb M. Kotb Yun-Su Kim Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm IEEE Access Artificial bee colony cost-benefit analysis CHP unit size optimization energy conversion genetic algorithm residential building automation |
title | Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm |
title_full | Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm |
title_fullStr | Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm |
title_full_unstemmed | Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm |
title_short | Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm |
title_sort | combined heat and power units sizing and energy cost optimization of a residential building by using an artificial bee colony algorithm |
topic | Artificial bee colony cost-benefit analysis CHP unit size optimization energy conversion genetic algorithm residential building automation |
url | https://ieeexplore.ieee.org/document/9279200/ |
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