We explores a periodic time series analysis in the context of unobserved components models which decompose a time series into components like trends and seasonals. We compare five approaches. Standard nonperiodic structural time series modelling, periodic univariate unobserved components modelling of seasonal subseries, homogeneous multivariate unobserved components modelling, common trend modelling and seemingly unrelated unobserved components time series modelling. We confine ourselves to cases where estimation, diagnostic checking and forecasting can be carried out easily and interactively using existing user-friendly software packages. We apply the methods to quarterly time series of energy consumption.