A new MPPT algorithm based on ANN in solar PV systems - Details

author：

Zhang, Hong (Zhang, Hong.) ^[1] | Cheng, Shuying (Cheng, Shuying.) ^[2] (Scholars：程树英)

Indexed by：

EI Scopus

Abstract：

To　optimize　the　solar　energy　efficiency,　maximum　power　point　tracking　(MPPT)　algorithm　is　usually　used　in　solar　photovoltaic　(SPV)　systems.　In　this　paper,　a　new　MPPT　method　based　on　artificial　neural　network　(ANN)　has　been　proposed　for　searching　maximum　power　point　(MPP).　The　new　combined　method　is　established　on　the　three-point　comparing　method　and　ANN-based　PV　model　method.　The　three-point　comparing　method　has　the　advantage　of　searching　the　MPP　exactly　when　the　solar　irradiance　changes　sharply,　and　it　can　make　the　system　work　under　a　stable　mode.　The　advantage　of　ANN-based　PV　model　method　is　the　fast　MPP　approximation　according　to　the　parameters　of　PV　panel.　The　proposed　new　MPPT　algorithm　can　search　the　MPP　fast　and　exactly　based　on　the　feedback　voltage　and　current　with　different　solar　irradiance　and　temperature　of　environment.　The　method　is　simulated　and　studied　using　Matlab　software　and　the　results　of　simulation　prove　the　effectiveness　of　the　proposed　algorithm.　©　2011　Springer-Verlag.

Keyword：

Energy efficiency MATLAB Maximum power point trackers Neural networks Photovoltaic cells Solar energy Solar power generation Solar radiation

Community：

[ 1 ] [Zhang, Hong]College of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, Fujian, 350108, China
[ 2 ] [Cheng, Shuying]College of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, Fujian, 350108, China

Reprint 's Address：

Email：

chengsying@yahoo.com.cn

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