Economical and ecological impact of sector coupling applied to computing clusters
For operators of scientific computing clusters, this work demonstrates a method to reduce environmental impact and costs by aligning computation with renewable energy supply, though results are simulation-based and incremental.
This study simulates dynamic operation of computing clusters based on renewable energy availability, finding potential reductions in carbon emissions and operational costs while maintaining computing targets. Optimal utilization achieved up to 20% cost savings and 15% emission reductions in validation periods.
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.