Large-scale entry of intermittent renewables needs to be balanced with a source of flexibility to retain generation adequacy. Storage offers such flexibility but sufficient capacities are currently available only indirectly via hydropower reservoirs. Yet hydropower is not insulated from adequacy concerns because reservoir levels also depend on the weather. This paper shows how to estimate the availability of intermittent renewables and long-term hydro storage from historic data with the use of modern regression techniques. The novelty of the paper is to introduce a robust methodology to add the estimated availability distributions directly to the computationally light and transparent recursive convolution approach; and the principles extend to other computational methods. An application to the Finnish power system makes it clear how both the short-term availability shocks from intermittent renewables and the long-term shocks from hydropower availability should be properly accounted for to avoid misguided generation adequacy estimates.

间歇性可再生能源的大规模进入需要与保持发电充足性的灵活性来源相平衡。存储提供了这种灵活性，但目前只有通过水电水库间接获得足够的容量。然而，水电并不能避免充足性问题，因为水库水位也取决于天气。本文展示了如何使用现代回归技术从历史数据中估计间歇性可再生能源和长期水电储存的可用性。该论文的新颖之处在于引入了一种稳健的方法，将估计的可用性分布直接添加到计算量轻且透明的递归卷积方法中；并且这些原理扩展到其他计算方法。