This thesis work aimed to develop solar Photovoltaic (PV) powered smart street post. The post was set to serve on highways for wild animals’ detection and warn vehicles of possible crossings. The main aim was to design reliable standalone PV system via PVSyst software and experimenting four different PV technologies including a bifacial module under. Another aim was to select and develop the hardware and software terms of the smart street pot. Radar sensor and analog to digital (A/D) data acquisition (DAQ) card were set to be used for the motion detection. RF wireless communication module was used for communicating with nearby posts to send data and trigger warning light emitting diodes (LED) sign. A Raspberry Pi microcontroller was programmed to control the operation of the street post through processing the signal from radar sensor and communicating with nearby posts. The PV system design included generation of street post’s daily profile, sizing and selection of the components of the system including the module, battery, charge controller and power stage circuit. The later was designed to provide suitable voltage level and interface for the loads connected. PVSyst model was built and set to be located in Ulm, Germany. The design parameters were set, and different set of orientations were tested for each module. The simulation results showed bifacial module delivered a reliable PV system in case of south and south-east orientation and achieved better performance in other orientations in comparison to the other PV modules implemented. Due to limitations in PVSyst software the results provided had an overall uncertainty of 5%. The microcontroller was able to process the data from the radar sensor and DAQ card and perform fast Fourier transform (FFT). However, further processing of motion detection was complex to be included in the thesis work. The radar sensor and DAQ card provided signals with uncertainty of ± 3.4 mV. The RF wireless communication module transmitted signal over various ranges up to 150 m with time delay of 500 ms.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:du-28184 |
Date | January 2018 |
Creators | ElSherif, Khaled |
Publisher | Högskolan Dalarna, Energiteknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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