Development and optimisation of a robust energy yield prediction methodology is the ultimate aim of this research.
Outdoor performance of the PV module is determined by the influences of a variety of interlinked factors related to the environment and device technologies. There are two basic measurement data sets required for any energy yield prediction model. Firstly, characterisation of specific PV module technology under different operating conditions and secondly site specific meteorological data. Based on these two datasets a calculation procedure is required in any specific location energy yield estimation.
This research established a matrix based multi-dimensional measurement set points for module characterisation which is independent of PV technologies. This novel approach has been established by demonstrating an extended correlation of different environmental factors (irradiance, temperature and spectral irradiance) and their influences on the commercial PV device technologies. Utilisation of the site specific meteorological data is the common approach applied in this yield prediction method. A series of modelling approach, including a tri-linear interpolation method is then applied for energy yield calculation.
A novel Monte Carlo simulation is demonstrated for uncertainty analysis of irradiance (pyranometer CM 11) & temperature (PT 1000) measurements and ultimately the yield prediction of c-Si and CIGS modules. The degree of uncertainties of irradiance is varies from ±2% to ±6.2% depending on the level of monthly irradiation. The temperature measurement uncertainty is calculated in the range of ±0.18°C to ±0.46%°C in different months of the year. The calculated uncertainty of the energy yield prediction of c-Si and CIGS module are ±2.78% and ±15.45%.
This research validated different irradiance translation models to identify the best matched model for UK climate for horizontal to in-plane irradiance. Ultimately, the validation results of the proposed Fast Energy Yield Calculation (FEnYCs), shows a good agreement against measured values i.e. 5.48%, 6.97% and 3.1% for c-Si, a-Si and CIGS module respectively.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.