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.
| Original language | English |
|---|---|
| Article number | 9279200 |
| Pages (from-to) | 218289-218303 |
| Number of pages | 15 |
| Journal | IEEE Access |
| Volume | 8 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2013 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Artificial bee colony
- CHP unit size optimization
- cost-benefit analysis
- energy conversion
- genetic algorithm
- residential building automation
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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