Augmented power control within a datacenter using predictive modeling

A computer program product embodied in a non-transitory computer readable medium for power management, the computer program product comprising code which causes one or more processors to perform operations of:

• measuring a power usage by a first data rack within a datacenter over a first period of time;
• generating a predicted power usage by the first data rack over a second period of time, wherein the second period of time is subsequent to the first period of time;
• calculating, using a neural network, a power correlation model that correlates a power prediction to an actual power usage for the datacenter;
• refining the predicted power usage for the second period of time, based on the predicted power usage and the power correlation model resulting in a refined power usage prediction, wherein the refining includes adjusting at least one coefficient or weight in the power correlation model and wherein the refining includes adding a power buffer margin calibrated over time;
• and
• configuring a power structure for the datacenter, based on the refined power usage prediction.

A computer system for power management comprising:

• a memory which stores instructions;
• one or more processors attached to the memory wherein the one or more processors, when executing the instructions which are stored, are configured to:
• measure, using the one or more processors, a power usage by a first data rack within a datacenter over a first period of time;
• generate, on a computing device, a predicted power usage by the first data rack over a second period of time, wherein the second period of time is subsequent to the first period of time;
• calculate, on the computing device using a neural network, a power correlation model that correlates a power prediction to an actual power usage for the datacenter;
• refine, on the computing device, the predicted power usage for the second period of time, based on the predicted power usage and the power correlation model resulting in a refined power usage prediction, wherein refining the predicted power usage includes adjusting at least one coefficient or weight in the power correlation model and wherein the refining includes adding a power buffer margin calibrated over time;
• and
• configure, using the one or more processors, a power structure for the datacenter, based on refined power usage prediction.