Open AccessComparative study of drip irrigation systems using indoor amorphous photovoltaic panels
Author(s) -
Vander Fabio Silveira,
Jair Antônio Cruz Siqueira,
Laís Fernanda Juchem do Nascimento,
Luciene Kazue Tokura,
Alessandra Mayumi Tokura Alovisi,
Márcio Antônio Vilas Boas,
Carlos Eduardo Camargo Nogueira,
Marta Mitiko Kubota de Siqueira,
Carlos Adriano Bohn,
Renan Marques,
Soni Willian Haupenthal,
Cristiano Fernando Lewandoski,
Gilson Debastiani
Publication year - 2021
Publication title -
research, society and development
Language(s) - English
Resource type - Journals
ISSN - 2525-3409
DOI - 10.33448/rsd-v10i11.19288
Subject(s) - photovoltaic system , pyranometer , drip irrigation , environmental science , renewable energy , metre , context (archaeology) , water pumping , environmental engineering , solar energy , hydrology (agriculture) , irrigation , electrical engineering , engineering , geography , physics , mechanical engineering , inlet , ecology , geotechnical engineering , archaeology , astronomy , biology
Solar energy is a clean and renewable energy production option and can be applied to pumping water. Pumping water with photovoltaic solar energy is one of the technologies that has stood out in the country. In this context, the work aimed to evaluate the different methods of a drip irrigation system as a function of the use of an indoor amorphous photovoltaic pumping system, without electrical energy storage. The study was installed at the State University of Western Paraná. Voltage and current data were generated by the photovoltaic panels; solar irradiation was measured by the pyranometer device; the water pump flow rate was determined using the flow meter and in-line drip tube types. Irrigation performance was determined by the water distribution uniformity coefficients (CUD) and Christiansen’s uniformity coefficient (CUC). Tests were performed on open and partially cloudy days. The experiment totaled 40 sampled data, half being collected on sunny days and the other half on partially cloudy days, at 9:45 am; 11:00 am; 1:30 pm and 3:00 pm. The methodology had the greatest influence on the CUD value. For the CUC parameter, the values were approximately 89% for the studied methods. Values remained under control for the Shewhart graph, but with the process capacity index affected.