Student research opportunities

Automated Collection and Distribution of Solar Radiation and Meteorological Data from a Distributed Sensor Network

Project Code: CECS_847

This project is available at the following levels:
CS single semester, Engn4200, Engn R&D
Please note that this project is only for undergraduate students.

Keywords:

Data Collection 3G Mobile Database Design and Development Programming Solar Energy PV

Supervisor:

Frank Mills

Outline:

This project will design and develop a system that can collect data from a distributed network of sensors, incorporate appropriate metadata in accord with international standards, archive the data into a database, and distribute subsets of the curated data automatically to other sites. This data, collected by sensors located throughout Canberra, will be used to characterise the real-time local solar radiation environment and real-time production of solar energy from rooftop PV arrays.

1. One set of data will be from remote data loggers that will communicate with the data collection system over the 3G mobile network. These data loggers will provide real-time information from rooftop PV systems.

2. A second set of data will be from data loggers on campus that will communicate with the data collection system over the ANU intranet through multiple firewalls. These data loggers will provide real-time information on the solar radiation and meteorological environment across the ANU campus.

3. The third set of data will be from publicly-accessible Web sites, such as PVoutput.org and SunnyPortal.com, which collect PV output data from people who are voluntarily posting their PV output on those sites.

Goals of this project

The aim of this project is to design and develop a system that can automatically collect data transmitted over both the Internet and the 3G mobile network from a distributed network of sensors, incorporate the metadata required to meet international standards for scientific data archives, archive the data, and distribute appropriate subsets of the data to other systems or archives. This will be done in support of an ANU-NICTA collaboration to use machine learning and computer vision to provide short term forecasts of the power output from collections of PV systems. This project also supports ANU research efforts developing advanced solar thermal energy and PV technologies in the Research School of Engineering and climate research and education initiatives in the Fenner School of Environment and Society and the Research School of Physics and Engineering.

Requirements/Prerequisites

Strong computer programming skills in at least one programming language. The student must be confident in operating within the Linux/Unix environment. Experience with communications protocols and/or database design would be very useful. Prior experience with solar energy technologies is not required.

Student Gain

The student will benefit by enhancing their knowledge in a demanding technological field, develop important computer programming skills in an important open-source technological framework, and gain practical research and development experience.

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