abstract: Utility scale solar energy is generated by photovoltaic (PV) cell arrays, which are often deployed in remote areas. A PV array monitoring system is considered where smart sensors are attached to the PV modules and transmit data to a monitoring station through wireless links. These smart monitoring devices may be used for fault detection and management of connection topologies. In this thesis, a compact hardware simulator of the smart PV array monitoring system is described. The voltage, current, irradiance, and temperature of each PV module are monitored and the status of each panel along with all data is transmitted to a mobile device. LabVIEW and Arduino board programs have been developed to display and visualize the monitoring data from all sensors. All data is saved on servers and mobile devices and desktops can easily access analytics from anywhere. Various PV array conditions including shading, faults, and loading are simulated and demonstrated.
Additionally, Electrical mismatch between modules in a PV array due to partial shading causes energy losses beyond the shaded module, as unshaded modules are forced to operate away from their maximum power point in order to compensate for the shading. An irradiance estimation algorithm is presented for use in a mismatch mitigation system. Irradiance is estimated using measurements of module voltage, current, and back surface temperature. These estimates may be used to optimize an array’s electrical configuration and reduce the mismatch losses caused by partial shading. Propagation of error in the estimation is examined; it is found that accuracy is sufficient for use in the proposed mismatch mitigation application. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2016
| Identifer | oai:union.ndltd.org:asu.edu/item:39460 |
| Date | January 2016 |
| Contributors | Peshin, Shwetang (Author), Spanias, Andreas (Advisor), Tepedelenlioglu, Cihan (Advisor), Srinivasan, Devarajan (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 86 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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