The rising share of abundant renewable energy inevitably increases volatility in the electricity production. The concept of sector coupling means that the volatility of electricity production to a large degree can be absorbed by dispatching electricity consumption whenever excess renewable energy is available. A system that is dynamically operated based on this principle can lower its total environmental impact. In addition, operational costs might be reducible as electricity prizes strongly depend on the residual load of the energy system. High-performance computing clusters in the field of science represent an ideal testing ground for such dynamic operation. Short-term delays in computing results due to electricity production being associated with high costs or carbon emissions are often negligible, provided that an overall computing target remains constant over long time periods. This study simulates the simplified operation of computing clusters using publicly available data on electricity production in Germany. The optimal utilisation along with associated carbon emission and cost reductions are determined separately. Hardware acquisition costs and embedded emissions are taken into account. The stability of a fixed computing target given the determined utilisation optima is evaluated in two validation periods. Additional simulations with modified parameters are carried out to estimate potential conditions under which dynamic operation of a computing cluster would continue to enable savings in the future.

翻译：可再生能源占比的持续上升不可避免地加剧了电力生产的波动性。部门耦合的概念意味着，只要存在过剩的可再生能源，便可通过调度电力消费在很大程度上吸收电力生产的这种波动。基于这一原则动态运行的系统能够降低其整体环境影响。此外，由于电价在很大程度上取决于能源系统的剩余负荷，运营成本也可能降低。科学领域的高性能计算集群是此类动态运行的理想试验场。只要总体计算目标在较长时期内保持恒定，因高成本或高碳排放的电力生产所导致的计算结果的短期延迟通常可以忽略不计。本研究利用公开的德国电力生产数据，模拟了计算集群的简化运行。分别确定了最优利用率以及相关的碳排放和成本削减量。研究中还考虑了硬件购置成本与隐含排放量。在两个验证期内，评估了在确定的最优利用率下固定计算目标的稳定性。通过修改参数进行额外模拟，以估算未来计算集群动态运行能够继续实现节能减排的潜在条件。