This document describes Kostas Hatalis's research on using recurrent neural networks for multi-step time series prediction of renewable power generation. It discusses using nonlinear autoregressive networks and particle swarm optimization learning in time delayed recurrent neural networks to forecast ocean wave characteristics. Evaluation of the models found the particle swarm optimization approach improved accuracy over nonlinear autoregressive networks, particularly for noisier, longer term predictions.