A novel Elite Opposition-based Jaya algorithm for parameter estimation of photovoltaic cell models
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 351-356 |
| Journal / Publication | Optik |
| Volume | 155 |
| Online published | 23 Oct 2017 |
| Publication status | Published - Feb 2018 |
Link(s)
Abstract
Parameter estimation of photovoltaic (PV) cell models using a novel Elite Opposition-based Jaya (EO-Jaya) algorithm is studied in this letter. The EO-Jaya is a swarm intelligence algorithm without algorithm specific parameters. Compared with the generic Jaya algorithm, the Elite Opposition Learning strategy is incorporated into the solution updating phase, which increases the solution diversity. The effectiveness of the EO-Jaya algorithm is validated via estimating model parameters of a real PV cell. The computational results prove the superiority of the proposed algorithm compared to newly published estimation methods.
Research Area(s)
- Jaya algorithm, Meta-heuristic search, Parameter estimation, Photovoltaic cell
Citation Format(s)
A novel Elite Opposition-based Jaya algorithm for parameter estimation of photovoltaic cell models. / Wang, Long; Huang, Chao.
In: Optik, Vol. 155, 02.2018, p. 351-356.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
