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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jiang Cong Xue Lingyun Song Deyun Wang Jian |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Automation, Hangzhou Dianzi University, China (Jiang Cong; Xue Lingyun) || Research and Development Department, Hangzhou Yuhang Electric Apparatus Ltd., China (Song Deyun; Wang Jian) |
| Abstract | Existing solar cells performance testing and modeling algorithms possess several drawbacks such as high complexity, low measuring accuracies and poor robustness to the small change of operating condition. A new approach is proposed to solve these problems. Firstly, the method introduced a series of semiempirical formula to separate and quantify the influence of all significant factors. Secondly, a chaos particle swarm optimization algorithm (CPSO) was used for extracting model parameters, in which the global search performance and local convergence of particle swarm optimization (PSO) were improved by the proposed chaotic search strategy. The application results of solar cells I-V characteristics test and measurement system demonstrate that the measured data and the calculated data, where the performance model parameters derived from the approach have been employed, represent conformity excellently. |
| Starting Page | 562 |
| Ending Page | 566 |
| File Size | 455174 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467314107 |
| e-ISBN | 9781467314114 |
| DOI | 10.1109/CSIP.2012.6308916 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-08-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Chaotic search Solar cells performance model Data models Parameter estimation and optimization Particle swarm optimization |
| Content Type | Text |
| Resource Type | Article |
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