Energy Internet Corporation

Virtual Power Systems, Inc.

Other

Cato

Energy Harbors Corporation, Inc.

Shankar Ramamurthy

Karimulla Raja Shaikh

Nikhil Sharma

Shankar Nataraj

Ravi S Subramaniam

Denis Kouroussis

Ryan Kennedy

Erich Karl Nachbar

Martin P Leslie

Rajaram Soundararajan

Andrew Sy

Rajeev P Huralikoppi

Pranthik Samal

Robert A Gingell, Jr

Akshay Krishnamoorthy

Sudhir Ramtirth Joshi

Clark A Jeria Frias

Wade Floren Schott

Sushant Shankar

Andrew L Wang

K David Lin

Dhanaraja Kasinathan

Frank Chuang

Milind Kukanur

Craig Broadbent

Ashok S Krishna

Disclosed techniques include liquid purification with pressure vessels. Access to a set of at least two pressure vessels is obtained. The pressure vessels are interconnected using piping and computer-controlled switching valves. A first pressure vessel of the set is filled with a liquid. A second pressure vessel of the set is filled with a pressurized gas. The pressurized gas is sharp interface immiscible with the liquid. Switching valves are controlled to enable the pressurized gas in the second pressure vessel to force the liquid from the first pressure vessel into a purification chamber. Additional switching valves are controlled to enable a third pressure vessel to fill with liquid while a fourth pressure vessel is filled with purification chamber retentate. The liquid is prepurified prior to filling the first pressure vessel. The prepurifying is enabled by compressed air. The purification chamber includes a reverse osmosis chamber.

Liquid purification with pressure vessels

Disclosed techniques include energy transfer using high-pressure vessels. Liquid is pumped into a high-pressure vessel to pressurize a gas. The gas can include air. Liquid is sprayed into the high-pressure vessel to cool the gas. Heat exchange is performed to cool the liquid before spraying the liquid into the high-pressure vessel. The spraying liquid into the top and the bottom of the high-pressure vessel is accomplished using nozzles in a top portion and nozzles in a bottom portion of the high-pressure vessel. The pressurized gas is transferred into a storage reservoir. The storage reservoir can include an underground cavern or aquifer. Gas from the storage reservoir is delivered to drive a turbine to recover stored energy. The extracting gas from the storage reservoir is accomplished using an additional high-pressure vessel. Heat exchange is performed to warm the liquid before spraying the liquid into the additional high-pressure vessel.

Energy transfer using high-pressure vessel

Disclosed techniques include enabling controlled refrigeration and liquefaction and energy management. A liquid is pumped into a closed chamber to compress a vapor. Pressure is increased in the closed chamber by pumping additional liquid into the closed chamber. The increasing pressure enables assimilation of the vapor into the liquid. The heat of compression is removed from the vapor simultaneously with compression. The liquid containing the vapor that was assimilated is withdrawn from the chamber. It is flashed to release at least a portion of the vapor that was assimilated. The flashing results in absorbing a latent heat of vaporization from surfaces in thermal contact with the liquid. A first and second heating/cooling circuit are controlled. Gas within the first heating/cooling circuit is cooled and compressed using a liquid piston. A gas is warmed within the second heating/cooling circuit, and expansion is accomplished using a liquid piston.

Controlled refrigeration and liquefaction using compatible materials for energy management

Disclosed techniques include controlled liquefaction and energy management. A gas within a first pressure containment vessel is pressurized using a column of liquid. The gas that is being pressurized is cooled using a liquid spray, wherein the liquid spray is introduced into the first pressure containment vessel in a region occupied by the gas. The liquid spray keeps the pressurizing to be isothermal. The gas that was pressurized is metered into a second pressure containment vessel, wherein the metering enables liquefaction of the gas. The gas that was pressurized is stored in a gas capacitor prior to the metering. The gas that was liquefied in the second pressure containment vessel is pushed into a holding tank, wherein the holding tank stores a liquefied state of the gas, and wherein the pushing is accomplished by the pressure of the gas that was metered into the second pressure containment vessel.

Controlled liquefaction and energy management

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

Disclosed techniques include energy management based on modularized energy control using pooling. Operating data is obtained from a plurality of energy modules within an energy storage system. The plurality of energy modules is pooled. One or more operating goals are obtained for the plurality of energy modules. The operating goals can be based on cost, availability, or energy module status. One or more processors are used to analyze the operating data, the one or more operating goals, energy demand, and energy module operating health. The operation of one or more of the plurality of energy modules is controlled based on the analysis. The energy modules can be a pooled homogeneous bank of energy modules. The homogeneous banks can be pooled into heterogeneous energy modules. The pools can include dynamically added energy module peers.

Modularized energy management using pooling

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

Disclosed techniques include desalination using pressure vessels. Access to a set of at least three pressure vessels is obtained. The pressure vessels are interconnected using piping and computer-controlled switching valves. A first pressure vessel of the set is filled with a prepurified liquid. A second pressure vessel of the set is filled with a pressurized gas. The pressurized gas is sharp interface immiscible with the prepurified liquid. The switching valves are controlled to enable the pressurized gas in the second pressure vessel to force the prepurified liquid from the first pressure vessel into a reverse osmosis chamber. The switching valves are controlled to enable a third pressure vessel of the set to fill with additional prepurified liquid. The switching valves are controlled to enable the pressurized gas that entered the first pressure vessel to force the additional prepurified liquid from the third pressure vessel into the reverse osmosis chamber.

Desalination using pressure vessels

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

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

Disclosed techniques include power management across point of source to point of load. Energy is obtained from points of energy generation, where data obtained at a time of energy generation includes information on energy and metadata about the energy. Connection is enabled from the points of energy generation to a large-scale energy storage subsystem. Load information is received from points of load, where the points of load are connected to an energy grid. Processors are used to calculate an energy control policy, based on information on the energy, the energy metadata, availability of the large-scale energy storage subsystem, and the load information. Routing of the energy is controlled from the points of energy generation to the points of load based on the energy control policy. The large-scale energy storage subsystem is controlled based on the energy control policy.

Power management across point of source to point of load

Disclosed techniques include energy storage and management using pumping. An energy source is connected to a pump-turbine energy management system, wherein the pump-turbine energy management system includes a pump-energy storage subsystem. Energy from the energy source is stored in the pump-energy storage subsystem. One or more processors are used to calculate a valve-based flow control setting for recovering energy from the pump-energy storage subsystem. One or more valves in the pump-energy management system are energized, wherein the energizing enables energy recovery. Energy is recovered from the pump-energy storage subsystem using a pump-turbine recovery subsystem enabled by the one or more valves that were energized. Waste heat is recovered through a waste-heat recovery subsystem which includes water heat exchangers or a fluid spray. The water from the water heat exchangers can be used to make steam or ice.

Energy storage and management using pumping

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

Disclosed techniques include energy management with multiple pressurized storage elements. Energy is obtained from one or more energy sources. Energy requirements are modeled over a first time period and a second time period. A first subset of the energy that was obtained is allocated for storage in a first energy store based on the modeling. A second subset of the energy that was obtained is allocated for storage in a second energy store based on the modeling, where the second energy store comprises a pressurized storage element. Energy is routed to the first energy store from the second energy store based on the modeling. Recovering energy further includes using the energy routed to the first energy store or the second energy store, based on the modeling.

Growing community of inventors

Saratoga, CA, United States of America

Shankar Ramamurthy