Award Date

12-15-2018

Degree Type

Thesis

Degree Name

Master of Science in Electrical Engineering (MSEE)

Department

Electrical and Computer Engineering

First Committee Member

Venkatesan Muthukumar

Second Committee Member

Emma Regentova

Third Committee Member

Yahia Baghzouz

Fourth Committee Member

Robert Boehm

Number of Pages

140

Abstract

Solar irradiation forecasting is essential for PV connected electrical grids to maintain reliability, stability, and effective matching of real-time demand to power distribution. This research paper develops and evaluates proposed forecasting methods using wireless sensor networks. Each node of the network is capable of monitoring illuminance data and communicate it through RF and/or WiFi. The nodes are calibrated with respect to irradiance data from an industry-standard pyranometer. Power consumption of each node type is also collected at different operating states. The proposed sensor network can estimate a cloud motion vector or a cloud shadow’s speed and direction from the data collected. By processing the collected data further, a forecasted solar irradiance ramp-down time-of-arrival is possible. The results are evaluated for both artificial and on-site cloud shadows.

Keywords

Cloud Motion Vector; Gradient Matrix; Microgrid; Peak Matching; PV System; Wireless Sensor Network

Disciplines

Computer Engineering | Electrical and Computer Engineering

File Format

pdf

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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