The selection of an optimal data center location for running a computational workload is based on multiple energy criteria. The location is chosen based on multivariate and predictive analysis of total direct and indirect energy costs, and other user-defined factors. Among the direct and indirect costs are power costs and cooling costs as well as structural and other details of a given data center. Among the other factors to be considered that can have an impact on present and future costs are weather patterns, data and forecasts, availability of energy providers, and energy attributes. A forecaster factors these direct and indirect costs along with extrinsic information such as historical trends and predictive sources into a forecast which is then input to a decision engine along with user defined criteria and with anticipated compute tasks and requirements to select a final location or locations for handling the workload.