We have developed a model for electricity prices which is a hybrid of the bottom-up "stack-based" pricing traditionally used in the power engineering community with the top-down financial time-series driven model customary in quantitative finance. Our model allows engineering data on plant failure and meteorological data on power demand to be used to estimate model parameters - important in the case of electricity markets for which spot price data is often either limited or nonexistent. We simplify and adapt our model to optimize it for the task of pricing a simple swing option to buy electrical power. The resulting pricing model may be written in terms of mixtures of Poisson distributions. The swing option may then be priced using relatively straightforward backward recursion techniques.