# APCr
Data centers can achieve higher sustainability by adjusting their operations to the tune of clean energy production (e.g. load shifting). DC4Cities proposed in 2014 a metric which captures how much the energy consumption profile of a data center matches the availability of renewable and green energy: Adaptability Power Curve at Renewable Energies.
Details
Unit: **NA**
Minimum: **1.0**
Maximum: -**∞**
Ideal: **1.0**
## Formula
$$
APC\_{ren} = 1 - \frac{\sum\_{i=1}^{n} |K E\_{Ren i} - E\_{DC i}|} {\sum\_{i=1}^{n} E\_{Ren i}}
$$
$$
K = \frac{\sum\_{i=1}^{n} E\_{DC i}} {\sum\_{i=1}^{n} E\_{Ren i}}
$$
Where
* *Ereni* is the renewable energy production on the grid (or onsite) in kWh,
* *EDCi* is the total energy consumption of the data center in kWh,
* *K* serves as an adjustment factor to meaningfully compute $E\_{ren i}$ against $E\_{DC i}$,
* *i* is the time period, and
* *n* is the sample size
As the amount of renewable electricity on the grid is far higher than what a data center consumes, K is needed to equalize their magnitudes.
## Evaluation
Has not been used in the industry.
## Improvement Strategies
Load shifting.
## Sources
\[1] [Cluster Activities Task 3](https://www.smartcitiescluster.eu/publications/FP7ProjectCluster-NewEnergyEfficiencyMetricsforDataCentres-task3.pdf)
\[2] [Metrics for Assessing Flexibility and Sustainability of Next Generation Data Centers](https://ieeexplore.ieee.org/document/7414182) [\[pdf\]](https://www.researchgate.net/profile/Alexis-Aravanis/publication/286923163_Metrics_for_Assessing_Flexibility_and_Sustainability_of_Next_Generation_Data_Centers/links/566fe20a08ae4d9a42593fc5/Metrics-for-Assessing-Flexibility-and-Sustainability-of-Next-Generation-Data-Centers.pdf)
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