期刊
ENERGY CONVERSION AND MANAGEMENT
卷 86, 期 -, 页码 1173-1185出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2014.06.026
关键词
Solar cell; PEM fuel cell; Biogeography-based optimization; Mutation strategy; Parameter estimation
资金
- National Natural Science Foundation of China [61273040]
- Shanghai Rising-Star Program [12QA1401100]
- project of Shanghai Municipal Education Commission [12YZ020]
- Engineering and Physical Sciences Research Council [EP/L001063/1] Funding Source: researchfish
- EPSRC [EP/L001063/1] Funding Source: UKRI
Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells. (C) 2014 Elsevier Ltd. All rights reserved.
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