Abstract/Summary

Energy systems across the globe are evolving to meet climate mitigation targets. This requires rapid reductions in fossil fuel consumption and significant uptake of renewable generation. Renewable energy sources are weather-dependent, causing production to vary at timescales from minutes to decades ahead. A consequence of this variability is that there will be periods of low renewable energy production, here termed renewable energy droughts. This energy security challenge needs to be addressed to ensure grid stability. India is chosen as a study area as it is a region that has both a large proportion of renewable generation and good subseasonal predictability. In this study, we use synthetic wind and solar photovoltaic production timeseries, previously derived for the Indian energy grid using ERA5 reanalysis from 1979–2022, to identify historical renewable energy droughts. These are defined as periods where wind and solar potential is in the lowest 2.5% compared to climatology. These events commonly occur from November–February, with the longest historical event being nine days long. We identify the weather regimes that cause the largest renewable energy droughts over India and investigate potential sources of predictability. Existing large-scale daily weather types and impact-based patterns are used to investigate the different weather patterns causing renewable energy droughts. Renewable energy droughts are caused by low seasonal wind speeds in combination with weather patterns bringing high cloud cover. These are mainly weak northeast monsoon and western disturbances. Sources of potential subseasonal predictability are considered for the largest renewable energy droughts, including the Madden Julian Oscillation and Boreal Summer Intraseasonal Oscillation. Although both have a stronger relationship with high energy potential days, links between phases of these two oscillations and renewable energy drought days are identified. These could help to provide early warnings for challenging security of supply conditions in the future.