Renewable Energy Curtailment via Incentivized Inter-datacenter Workload Migration
Continuous Grid balancing is essential for ensuring the reliable operation of modern smart grids. Current smart grid systems lack practical large-scale energy storage capabilities and therefore their supply and demand levels must always be kept equal in order to avoid system instability and failure. Grid balancing has become more relevant in recent years following the increasing desire to integrate more Renewable Energy Sources (RESs) into the generation mix of modern grids. RESs produce intermittent energy supply that can’t always be predicted accurately  and necessitates that effective balancing mechanisms are put in place to compensate for their supply variability [2, 3]. In this work, we propose a new energy curtailment scheme for balancing excess RESs energy using data centers as managed loads. Our scheme uses incentivized inter-datacenter workload migration to increase the computational energy consumption at a destination datacenter by the amount necessary to balance the grid. Incentivised workload migration is achieved by offering discounted energy prices (in the form of Energy Credits) to large-scale cloud clients in order to influence their workload placement algorithms to favor datacenters where the energy credits can be used. Implementations of our system using the CPLEX ILP solver as well as the Best Fit Decreasing (BFD) heuristic  for workload placement on data centers showed that using energy credits is an effective mechanism to speed-up/control the energy consumption rates at datacenters especially at low system loads and that they result in increased profits for the cloud clients due to the higher profit margins associated with using the proposed credits.
|Lecture Notes in Computer Science|
|Organisation||School of Information Technology|
Abada, A. (Ahmed), & St-Hilaire, M. (2018). Renewable Energy Curtailment via Incentivized Inter-datacenter Workload Migration. In Lecture Notes in Computer Science. doi:10.1007/978-3-319-94295-7_10