Glowworm Swarm Optimization for photovoltaic model identification
This paper presents a new algorithm for finding the parameters that characterize a photovoltaic panel by using the Glowworm Swarm Optimization algorithm. This new algorithm shows great simplicity, flexibility and precision, being able to precisely locate the global optimum point or multiple global opt...
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| Other Authors: | , , , |
| Format: | article |
| Language: | eng |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10400.6/8211 |
| Country: | Portugal |
| Oai: | oai:ubibliorum.ubi.pt:10400.6/8211 |
| Summary: | This paper presents a new algorithm for finding the parameters that characterize a photovoltaic panel by using the Glowworm Swarm Optimization algorithm. This new algorithm shows great simplicity, flexibility and precision, being able to precisely locate the global optimum point or multiple global optimum points, independently of the initial conditions. The approach here adopted allows the utilization of the algorithm in several existing models to characterize a photovoltaic panel in the current literature. |
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