As increased demand of cloud computing leads to increased electricity costs for cloud providers, there is an incentive to investigate in new methods to lower electricity costs in data centers. Electricity price markets suffer from sudden price spikes as well as irregularities between different geographical electricity markets.
This thesis investigates in whether it is possible to leverage these volatilities and irregularities between different electricity price markets, to offload or move storage in order to reduce electricity price costs for data storage.
By forecasting four different electricity price markets it was possible to predict sudden price spikes and leverage these forecasts in a simple optimization model to offload storage of data in data centers and successfully reduce electricity costs for data storage.