Abstract
Photovoltaic (PV) cell modeling is an important study done to improve solar cell performance before fabrication. Different techniques have been implemented for the extraction of solar cell parameters to generate a high PV power. However, most of these techniques are considered less accurate and suffer some limitations that reduce their effectiveness. In this paper, five different techniques were compared under different cell temperature levels to determine the technique that yields the best results. Findings show that firefly algorithm exhibited the best performance and can be recommended for the extraction of solar cell parameters in PV cells.
| Original language | English |
|---|---|
| Title of host publication | 2021 IEEE Electrical Power and Energy Conference, EPEC 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 184-189 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781665429283 |
| DOIs | |
| Publication status | Published - 2021 |
| Event | 2021 IEEE Electrical Power and Energy Conference, EPEC 2021 - Virtual, Online, Canada Duration: 22 Oct 2021 → 31 Oct 2021 |
Publication series
| Name | 2021 IEEE Electrical Power and Energy Conference, EPEC 2021 |
|---|
Conference
| Conference | 2021 IEEE Electrical Power and Energy Conference, EPEC 2021 |
|---|---|
| Country/Territory | Canada |
| City | Virtual, Online |
| Period | 22/10/21 → 31/10/21 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Cultural algorithm
- Firefly algorithm
- Fminsearch
- Genetic algorithm
- PSO
- PV cells and swarm intelligence
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Automotive Engineering
- Electrical and Electronic Engineering
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