oa Modeling the Impact of Weather Conditions on the Generation Output of PV-DGs

Photovoltaic distributed generation (PV-DG) systems are one of the fastest-growing types of renewable energy resources being integrated worldwide onto distribution networks. As the price of solar cells continues to decrease, residential and utility-scale PV installations are becoming popular energy options in the United States and other Western countries. Similarly, in line with the National Vision 2030, Qatar is aiming to embrace solar technology by 20% to meet its growing demand and reduce carbon emissions. The short-term goal for KAHRAMAA Utility in Qatar is to reach 10 MW solar generation in the next years. Qatar resides in the Arabian Peninsula and is blessed with abundant solar resources. For instance, the Global Horizontal Irradiance for Qatar is measured as 2140 kWh/m²/year in 2012, which is one of the highest in the world. However, local weather conditions significantly degrade the performance of the PV output. Some of the major issues include: (1) the temperature on PV panels is significantly higher than the ambient temperature. This affects the performance of the power electronics devices that are attached to the PV panels, such as inverters, and also the PV output due to the stress on the materials; (2) Qatar is prone to frequent foggy weather during the Winter. Thus often leads to sudden drops in the PV outputs; (3) PV panels often need cleaning in Qatar due to soiling; and (4) during winter months, the humidity increases significantly in Qatar, and the scheduling of anti-dust cleaning as well as considering the impact of late cleaning become more important. The above region-specific issues further emphasize the challenges in integrating PV-DGs in Qatar and the potential need for modeling the impacts of weather conditions on the generation out of PV-DGs on the distribution network. The main goals are to devise probability distribution functions for overloading of transformers and cables and failures of different system components. The outcome of this work will be used to (1) quantify the costs of poor power quality on customer premises and system elements; (2) compute the electric system average interruption duration index (SAIDI) and the system average interruption frequency index (SAIFI); and (3) create rare event techniques to simulate the adverse impacts of PV integration. Moreover, the developed model can be used to find the relationship between the energy storage size, which are likely to assist PV integration at the distribution network, and the unexpected weather events.