Perturbed stochastic fractal search for solar PV parameter estimation
Chen, Xu and Yue, Hong and Yu, Kunjie (2019) Perturbed stochastic fractal search for solar PV parameter estimation. Energy, 189. ISSN 1873-6785 (https://doi.org/10.1016/j.energy.2019.116247)
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Abstract
Following the widespread use of solar energy all over the world, the design of high quality photovoltaic (PV) cells has attracted strong research interests. To properly evaluate, control and optimize solar PV systems, it is crucial to establish a reliable and accurate model, which is a challenging task due to the presence of non-linearity and multi-modality in the PV systems. In this work, a new meta-heuristic algorithm (MHA), called perturbed stochastic fractal search (pSFS), is proposed to estimate the PV parameters in an optimization framework. The novelty lies in two aspects: (i) employ its own searching operators, i.e., diffusion and updating, to achieve a balance between the global exploration and the local exploitation; and (ii) incorporate a chaotic elitist perturbation strategy to improve the searching performance. To examine the effectiveness of pSFS, this method is applied to solve three PV estimation problems for different PV models, including single diode, double diode and PV modules. Experimental results and statistical analysis show that the proposed pSFS has improved estimation accuracy and robustness compared with several other algorithms recently developed.
ORCID iDs
Chen, Xu, Yue, Hong ORCID: https://orcid.org/0000-0003-2072-6223 and Yu, Kunjie;-
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Item type: Article ID code: 70051 Dates: DateEvent15 December 2019Published3 October 2019Published Online30 September 2019Accepted22 April 2019SubmittedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 08 Oct 2019 08:56 Last modified: 26 Nov 2024 21:02 URI: https://strathprints.strath.ac.uk/id/eprint/70051