Effect of Saharan dust storm events on the forecast of photovoltaic power generation in Hungary

The expansion of renewable energy sources is a major issue from the sustainability, climate policy and energy security perspectives. All of this expansion can be optimal if its potential is exploited to the best possible effect, and accurate forecasting of irradiance levels, both for existing and planned capacity, is essential. Solar forecasting is the process of predicting the expected solar output from a photovoltaic (PV) system over a given period. This process is important for power system operators and utility companies who need to ensure that they can meet the electricity demand of their customers by balancing the supply and demand of energy on the grid. Our research investigated the impact of mineral dust on photovoltaic power generation and day-ahead forecast. We analysed the year 2022, when the number of Saharan dust storm events identified in Hungary (n=16) set a new record. Our methods included satellite measurements, numerical simulations, air mass movement trajectory calculations and synoptic meteorological analyses, as well as laboratory analyses of the dust material that washed out with precipitation during Saharan dust storm events. During some episodes, a deficit of up to 500 MW between actual and predicted output was periodically detected, which required the use of expensive and polluting back-up capacity. We have shown that the semi-direct effect of atmospheric dust particles on high-level cloud formation rather than their direct irradiance-reducing effect is responsible for the reduced accuracies of e short-term (24-h) PV energy production forecasts during these events. The results were published in Varga et al. (2024). Effect of Saharan dust episodes on the accuracy of photovoltaic energy production forecast in Hungary (Central Europe). Renewable and Sustainable Energy Reviews 193, https://doi.org/10.1016/j.rser.2024.114289 The research was supported by the NRDI projects FK138692 and RRF-2.3.1-21-2021. The research was funded by the Sustainable Development and Technologies National Programme of the Hungarian Academy of Sciences (FFT NP FTA).