Balancing the Power Grid

01/06/2016 |

Strategy to increase coordination, reliability of energy resources

Power lines

A new plan to balance power grid operation and improve its resiliency has been outlined by scientists at Pacific Northwest National Laboratory (PNNL). The project will allow power plants to make smart decisions on a second-by-second basis, taking on or shedding electricity to improve quality and reliability.

The plan, which has been funded by the DOE’s Advanced Research Projects Agency-Energy (ARPA-E), will involve providing incentives for owners of distributed resources such as batteries, smart appliances, rooftop solar systems, and smart HVAC systems to enroll their devices in a reporting system. The system would involve installing sensors and controls on resources to allow changes and performance monitoring to be performed automatically, within limits set by the device owner. The network of sensors and controls is designed to create a decision-making platform based on cooperation that can intelligently manage the needs of the grid with available energy resources.

The new PNNL project would also create a new organization called distribution reliability coordinator that would ensure the new coordinated system provided fast-acting and effective emergency response to major events, fast balancing between power supply and demand, and effectiveness at smoothing the transition to changes in power demand.

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Data Aire understands how digital technology and data gravity is rapidly impacting and transforming businesses. That’s why they developed ultra-efficient cooling technology to support the most modern (and not-so-modern) data centers.  Learn how One Wilshire in Los Angeles, one of the most advanced carrier hotels today, is surpassing California's strict energy efficiency requirements with Data Aire’s purpose-built system, which provide full-economization for 260 days – almost 72% of the year. That’s a measurable savings! Furthermore, the projected PUE on an annual basis for a full load is at or below 1.2.


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