EFFECT OF WEATHER CONDITIONS ON PERFORMANCE OF SOLAR ENERGY SYSTEMS
Solar energy is increasingly in demand as a clean, sustainable source of energy without a carbon footprint. This thesis examines the effect of weather conditions on the performance of photovoltaic (PV), photovoltaic thermal (PVT), and thermal solar energy applications. The aim is to maximize the utilized energy, to reduce the costs of energy and emissions. The analysis is conducted by using a dataset of weather conditions in a North American city over a period of one year. First, the effect of weather conditions on the generation of harmonics in PV systems is investigated. A PV model, including the inverting stage, is considered. Three converter techniques, which form the basis for the majority of converters, are used to validate the proposed approach: A square-wave inverter with 60Hz switching, a square-wave inverter with blanking angle and 60Hz switching, and pulse width modulation (PWM). Probability density functions and probability distribution models are determined as aids for improving the quality of the power generated. The long-term effects of weather conditions on harmonics produced by PV inverters are considered. The results show the variability in the amplitude of each harmonic component, the boundaries of each harmonic component, and which harmonic magnitudes occur more frequently. Secondly, the effect of weather conditions on the PV cell ratio of a PVT system is analyzed. The maximum overall thermal energy (OTE) and the CO2 emission reduction of the PVT system is obtained for an entire year. Constant and variable flow rate values are applied in the simulated study for different time spans over a year. To validate the proposed work, three-time span levels are evaluated: A macro level (annual), meso level (seasonal) and micro level (monthly). Simulated models are developed to obtain the appropriate PV coverage area to maximize the OTE. Thirdly, global solar radiation (GSR) prediction models are proposed which achieve improved performance in terms of error values and structural simplicity. The proposed models are based on the weather conditions of the specific location. Finally, a practical application is developed on the basis of the proposed GSR predictions, which help to maximize the utilized energy.