J. Boland and Z. Zekanovic (Australia)
Solar energy, optimization, stochastic programming, spreadsheet model.
Optimisation of the orientation of Photovoltaic cells to match electricity demand was carried out for Adelaide. This study involves analysis of solar radiation and temperature time series as well as stochastic programming. Time series were split into 2 parts, deterministic and stochastic components, and analysed separately by Fourier methods and Box and Jenkins techniques respectively. It is found that the stochastic component for daily averaged solar radiation and temperature series is best described by the first and second order autoregressive processes respectively. In addition we generated a number of synthetic solar radiation, temperature and demand series using stochastic programming. These are later used as inputs for an innovative Excel spreadsheet model to find the optimal slope and azimuth for each generation. Results i.e. set of slopes and azimuths, are analysed in order to make general recommendation for the optimal orientation of photovoltaic cells to match electricity demand for Adelaide. This spreadsheet model can be adapted to any location desired.
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