Adams, Joshua Lindsay (2017) Renewable Energy Site Selection Tool. [USQ Project]
Abstract
Renewable energy is a crucial step forward in today’s society and renewable energy power plants are becoming an increasingly popular choice for many investors. Analysing potential renewable energy sites for a particular location is extremely important for any proponent in order to optimise potential returns. Ergon Energy strongly encourages these new power plants to be created and connected to the state-wide grid to help meet the electricity demand and enhance the current renewable energy business model (Ergon Energy 2016). The aim of this study is to identify the main performance considerations of both wind turbines and PV power plants and highlight a range of factors which may affect the suitability of a potential site. From these observations, a state-wide model was created to allow proponents to easily identify the viability of suitable locations and visually identify the optimal locations. It was found that a range of features including solar radiance and wind availability, environmental and geographical sensitivities were all to be considered for the algorithm to be developed. Several different resources were used to gather this data including the BOM, Q-Spatial Catalogue and the ABS. These factors were given corresponding weightings according to the AHP method which mathematically verified the results. The model created, showed extremely interesting features and found that proponents must carefully analyse a particular site in order to create an optimal system for maximum financial gain. The data from the model was validated using the ratings of the existing USQ carpark solar array and the proposed Coopers Gap Wind farm.
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| Item Type: | USQ Project |
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| Item Status: | Live Archive |
| Additional Information: | Bachelor of Engineering (Electrical and Electronic) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Bowtell, Les; Springall, Glenn |
| Date Deposited: | 07 Sep 2022 05:18 |
| Last Modified: | 07 Sep 2022 05:18 |
| Uncontrolled Keywords: | renewable energy; potential sites |
| URI: | https://sear.unisq.edu.au/id/eprint/40873 |
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