Virtual Power Systems, Inc.

Other

Cato

Karimulla Raja Shaikh

Shankar Ramamurthy

Ravi S Subramaniam

Nikhil Sharma

Martin P Leslie

Clark A Jeria Frias

Akshay Krishnamoorthy

Denis Kouroussis

Ryan Kennedy

Erich Karl Nachbar

Rajeev P Huralikoppi

Pranthik Samal

Rajaram Soundararajan

Andrew Sy

Wade Floren Schott

Dhanaraja Kasinathan

Craig Broadbent

In disclosed techniques, simulations are performed to determine data center performance under certain conditions. The simulations are dynamic and allow for changes in power demand due to temporal data center activities. In order to accommodate predicted and unpredicted fluctuations in power demand of a data center, one or more power caches are configured to supply additional power during periods of peak demand. Power caches provide supplemental power during periods of peak demand. The simulations are used for a variety of purposes, including determining the effects of power caches going offline under various conditions. Disclosed techniques can simulate the cycling of a power cache and can determine if additional configuration changes to the data center are warranted to maintain optimal health of the power caches. Thus, power scenario simulation of a data center can provide information vital to efficient operation of the data center.

Data center power scenario simulation

In disclosed techniques, datacenter power management uses AC and DC power sources. An AC power distribution topology within a datacenter provides one or more AC power sources to computing devices. A DC power distribution topology within the datacenter provides one or more DC power sources to computing devices. An uninterruptible power supply (UPS) is provisioned to a rack of computing devices, wherein the UPS is capable of receiving the one or more AC power sources using the AC power distribution topology and the one or more DC power sources using the DC power distribution topology. The one or more DC power sources are evaluated for energizing the DC power distribution topology. The one or more DC power sources are connected to the UPS which is provisioned to the rack of computing devices, based on the evaluating and a datacenter power requirement.

Datacenter power management using AC and DC power sources

Embodiments provide techniques for datacenter power management using variable power sources. Power from the variable power sources is stored in a power cache. An optimization engine receives input criteria such as power availability from non-variable and variable power sources, as well as one or more power management goals. The optimization engine implements a dispatch strategy that dispatches stored energy from the power cache and feeds it to the datacenter, resulting in a mixture of non-variable and variable power sources used to achieve the power management goals, such as reduced power cost, increased power availability, and lowered carbon footprint for the datacenter.

Datacenter power management using variable power sources

Dynamic tiering of datacenter power for workloads is disclosed. A power capacity, including redundant power capacity and granular power capacity values within a datacenter, is determined. An outage time duration requirement for the power capacity that was determined is evaluated, where the outage time duration requirement is a number of minutes. A hold time duration requirement for the power capacity is evaluated, where the hold time duration is a number of minutes. A number of allowable occurrences of power outage for the power capacity is evaluated. A power requirement metric, based on the outage time duration requirement, the hold time duration requirement, and the number of occurrences, is calculated. A power topology within the datacenter is modified based on the power requirement metric. The modifying provides dynamic power tiering within the datacenter. The dynamic tiering includes a variable service level agreement for power within the datacenter.

Dynamic tiering of datacenter power for workloads

Disclosed techniques include time-varying power management within datacenters. A set of power policies for managing power within a datacenter is obtained. The set of policies varies over time. A priority is determined for a policy within the set of policies for managing the power within the datacenter. The policy within the set varies over time. A situation within the datacenter is identified where the situation matches that described in the policy within the set of policies. A power arrangement within the datacenter is modified based on the policy within the set of policies. The power arrangement within the datacenter applies to a section of the datacenter including one or more IT racks. The modifying includes powering a set of loads within the datacenter by a specific power source, changing a topology within the datacenter, powering down a portion of the datacenter, or changing a service level agreement support level.

Time varying power management within datacenters

In disclosed techniques, augmented power control within a datacenter uses predictive modeling. A power usage by a first data rack within a datacenter is measured, using one or more processors, over a first period of time. A predicted power usage by the first data rack over a second period of time is generated on a computing device, wherein the second period of time is subsequent to the first period of time. A power correlation model is calculated that correlates a power prediction to an actual power usage. The predicted power usage for the second period of time is refined, based on the predicted power usage and the power correlation model. The refining is accomplished using a power prediction model comprising the predicted power usage and the power correlation model. Datacenter power structure is configured, based on the refined power usage prediction.

Augmented power control within a datacenter using predictive modeling

In disclosed techniques, secure communication initiation and execution is used for datacenter power control. Information relating to power control is encrypted for inclusion in a first data payload. The first data payload is used for datacenter power infrastructure control. The first data payload is sent from a first component within a datacenter to a second component within the datacenter. The first component and the second component enable power infrastructure power control of the datacenter. The datacenter power infrastructure control is modified based on decryption of the first data payload by the second component within the datacenter. The first data payload provides for intelligent power control within the datacenter. Modifying the datacenter power infrastructure control dynamically changes power control within the datacenter. The changing power control changes power policies within the datacenter. The first component is authenticated using the first data payload. Encryption includes obscurity. The decryption ignores the obscurity.

Secure communication initiation and execution for datacenter power control

Disclosed techniques enable power manipulation within a data center based on power policies. Power policies are used to establish behavior based on limits for power consumption, power generation, and other criteria. Rules are established to provide fractional power sharing and control under certain conditions. Power caches are used to supplement power sources under conditions of peak power requirements. When power requirements are below a threshold set forth in a power policy, the power caches are replenished.

Data center power manipulation

Techniques for datacenter power management using dynamic redundancy are disclosed. A power control switch is configured to selectively apply power to one or two power cords of a dual-corded electronic apparatus. When the power control switch energizes both power cords, the electronic apparatus operates in 2N redundancy. When the power control switch energizes only one of the power cords, the electronic apparatus operates in 1N redundancy. The power control switch is configured to dynamically change the redundancy mode based on service level agreement (SLA) criteria, power policies, power supply and demand, and environmental factors.

Datacenter power management using dynamic redundancy

Multi-level data center using consolidated power control is disclosed. One or more controllers communicate with one or more power supplies and sensors to adapt to dynamic load requirements and to distribute DC-power efficiently across multiple IT racks. The distributed DC-power includes one or more DC-voltages. Batteries can be temporarily switched into a power supply circuit to supplement the power supply during spikes in power load demand while a controller reconfigures power supplies to meet the new demand. One or more DC-to-AC converters handle legacy power loads. The DC-to-AC converters are modular and are paralleled for redundancy. The DC-to-AC converters are sourced from the one or more AC-to-DC converters. The AC power is synchronized for correct power flow control. The one or more controllers communicate with the one or more AC-power supplies to dynamically allocate AC-power from the DC-to-AC converters to the multiple legacy IT racks.

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Cupertino, CA, United States of America

Karimulla Raja Shaikh