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dc.contributor.authorNkwajju, Angello
dc.contributor.authorMwanje, Brian
dc.date.accessioned2022-03-01T09:30:39Z
dc.date.available2022-03-01T09:30:39Z
dc.date.issued2022-02
dc.identifier.issn10.1080/23311916.2021.1981520.
dc.identifier.urihttp://hdl.handle.net/20.500.12281/11212
dc.description.abstractPV modules are the most important part of a Photo-voltaic (PV) solar system as light energy from the sun is converted into electrical energy. The basic component of a PV module is a solar cell that has the capacity of producing about 0.5V of electricity. A solar panel or module is a combination of several solar cells connected in series to generate usable voltage. PV modules are often installed as an array. A PV array is a collection of PV modules connected in either series or parallel or a combination of both series and parallel to form a single unit that feeds power to the PV system. In Uganda, energy losses due to faults (shading, dusting, open circuit, and short circuit) represent almost 50 % of the total energy production from a PV array. The aim of this project is to design and implement a solar array diagnostic system that detects and identifies faults on the DC side of the PV array in particular shading, soiling or dusting on the panels, and open circuit in the PV array. This was achieved by first collecting the PV array time series data using a data acquisition system which we built, then the collected PV array time series data was processed using MATLAB and MS Excel, it was then statistically analysed using MATLAB, then the statistical algorithm was modelled from the MATLAB analysis results. The algorithm was then implemented in form of an Arduino code using Arduino IDE. Then the prototype of a solar array diagnostic algorithm was tested by manually creating the faults in PV array system and then examining what the system displays in the Arduino serial monitor. The key results obtained included labelled PV array time series data for normal operation, open circuit, dusting, and shading conditions. Pre-processed data from MATLAB. Plotted graphs of different categories of labelled data for different PV operating conditions. An algorithm modelled from the statistic functions of the plotted graphs for each category of labelled data. In conclusion, the necessity of such a PV array fault detection system in PV systems should be made a priority to prevent avoidable energy loses.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectSolar systemen_US
dc.subjectLight energyen_US
dc.subjectElectric energyen_US
dc.subjectRenewable energyen_US
dc.titleDesign and implementation of solar array diagnostic systemen_US
dc.typeThesisen_US


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