Collinsville solar thermal project: Yield forecasting – Final report

William Bell, Phillip Wild and John Foster ()

MPRA Paper from University Library of Munich, Germany

Abstract: The primary aim of this report is to produce hourly yield projections of electricity power for the proposed LFR plant at Collinsville, Queensland, Australia based on the environmental condition between 2007 and 2013. However, the techniques and methods used to overcome the inadequacies of the environmental, site-specific datasets provide a wider appeal for the report. The dataset inadequacies make accurate projections of future income streams and the subsequent securing of funding difficult (Cebecauer et al. 2011; Lovegrove, Franklin & Elliston 2013; Stoffel et al. 2010). The hourly power yield projections from this report are used in our subsequent report called ‘Energy economics and dispatch forecasting’ (Bell, Wild & Foster 2014a), to calculate the lifetime revenue of the proposed plant and perform sensitivity analysis on gas prices. This report compares the yield from the proposed Collinsville LFR plant using two different calculation methods. One method simply uses complete historical datasets from three nearby sites: MacKay, Rockhampton, and Townsville in Queensland. The other method uses datasets derived from a meteorological model developed from three sources: - BoM’s hourly solar satellite data - BoM’s Collinsville Post Office weather station - Allen’s (2013) datasets The overarching research question for the report is: Can modelling the weather with limited datasets produce greater yield predictive power than using the historically more complete datasets from nearby sites?

Keywords: Climate change; Collinsville; electricity demand; Demand management; dispatch forecasting; Electricity; Energy Consumption; Energy economics; Future proofing; LFR; Linear Fresnel Reflector; mitigation; Australian national electricity market; NEM; power purchase agreements; PPA; Queensland; Australia; Renewable energy; solar energy; solar thermal (search for similar items in EconPapers)
JEL-codes: O3 Q4 Q5 (search for similar items in EconPapers)
Date: 2014-11-04
New Economics Papers: this item is included in nep-ene and nep-env
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https://mpra.ub.uni-muenchen.de/59647/1/MPRA_paper_59647.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/60090/1/MPRA_paper_60090.pdf revised version (application/pdf)

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