One way to achieve energy efficiency in manufacturing consists of equipping plants with on-site renewable energy generation systems to partially power industrial processes. However, renewable energy sources are highly intermittent and their availability is difficult to be predicted accurately. We thus investigate an integrated industrial production planning and energy supply problem under uncertain renewable energy availability. We propose a two-stage stochastic programming model for this problem. The first decision stage consists of building a production plan for a proportional lot-sizing and scheduling problem in a single-machine multi-item setting. The second decision stage considers a discrete set of scenarios representing potential realizations of the stochastic generation of renewable energy over the planning horizon and aims at building an energy supply plan for each scenario. Computational experiments will be presented to show the practical efficiency of the proposed approach.