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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Main Authors: Habib Ur Rahman Habib, Shaorong Wang, Asad Waqar, Bashar Sakeen Farhan, Kotb M. Kotb, Yun-Su Kim
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
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.
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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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