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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Bibliographic Details
Published inIEEE access Vol. 8; p. 1
Main Authors Habib, Habib Ur Rahman, Wang, Shaorong, Waqar, Asad, Farhan, Bashar Sakeen, Kotb, Kotb M., Kim, Yun-Su
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Artificial bee colony
Artificial bee colony algorithm
Buildings
CHP unit size optimization
Cogeneration
Cost control
Cost-benefit analysis
Energy conversion
Energy costs
Energy management
Genetic algorithm
Genetic algorithms
Linear programming
Optimization
Power management
Residential areas
Residential building automation
Residential buildings
Residential energy
Resistance heating
Search algorithms
Sizing
Swarm intelligence
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Summary: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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3042173