Integrating Renewable Energy Using Data Analytics Systems: Challenges and Opportunities
The variable and intermittent nature of many renewable energy sources makes integrating them into the electric grid challenging and limits their penetration. The current grid requires expensive, large-scale energy storage and peaker plants to match such supplies to conventional loads. The authors present an alternative solution, in which supply-following loads adjust their power consumption to match the avail-able renewable energy supply. They show Internet data centers running batched, data analytic workloads are well suited to be such supply-following loads. They are large energy consumers, highly instrumented, agile, and contain much scheduling slack in their workloads. They explore the problem of scheduling the workload to align with the time-varying available wind power.