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Combined Heat and Power Units Sizing and Energy Cost Optimization of a Residential Building by Using an Artificial Bee Colony Algorithm
- Source :
- IEEE Access, Vol 8, Pp 218289-218303 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- 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.
- Subjects :
- Battery (electricity)
Mathematical optimization
energy conversion
General Computer Science
Linear programming
Computer science
020209 energy
02 engineering and technology
010501 environmental sciences
01 natural sciences
Cogeneration
CHP unit size optimization
Genetic algorithm
0202 electrical engineering, electronic engineering, information engineering
genetic algorithm
General Materials Science
residential building automation
0105 earth and related environmental sciences
business.industry
cost-benefit analysis
Artificial bee colony
General Engineering
Sizing
Artificial bee colony algorithm
Electricity
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
lcsh:TK1-9971
Efficient energy use
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....379dc19ce04c6b9e81e471ab5f6690fa