Saving power in data centers is a high priority for data center operators and consumers of data center services, as well as utilities, government regulators, and electricity consumers because of the significant and growing economic and environmental costs associated with the increasing demand and energy consumption.

According to the Lawrence Berkeley National Laboratory 2008 report, in 2005 the direct electricity used by information technology equipment in data centers represented about 0.5% of total world electricity consumption. When electricity for cooling and power distribution is included, that figure is about 1%. To date data centers consume about 2 percent of the world's electricity.

According to the latest available report from the U.S. Environmental Protection Agency (EPA 2007) this sector consumed about 61 billion kilowatt-hours (kWh) in 2006 (1.5 percent of total U.S. electricity consumption) for a total electricity cost of about $4.5 billion. Federal servers and data centers alone account for approximately 6 billion kWh (10 percent) of this electricity use, for total electricity cost to U.S. taxpayers of approximately $450 million annually. Data centers use 150-750 W/ft2, corresponding to 2.5% of current US electricity consumption

The project aim is to demonstrate the feasibility of deploying a network of Performance Optimized Datacenters (PODs), geographically distributed to exploit the availability of renewable energy for their operation. Such a distributed system has the potential to significantly enhance the energy efficiency, reliability, security, and overall performance of the data center by several means, including optimizing the utilization of the available renewable power for computing by intelligently redistributing computational load depending on the availability of renewable energy and minimizing losses associated with power transmission by placing the PODs near the power source. This concept provides data center operators the means to avoid performing expensive utility upgrades as the availability of wind power through New York State and other states grows, keeping the infrastructure and Transmission & Distribution (T&D) costs low, thus making it possible to use the wind power that is currently stranded, i.e. not-delivered to the grid due to the T&D constraints.

During this demonstration project, Clarkson University in partnership with Advanced Micro Devices (AMD) will demonstrate the feasibility of deploying a network of Performance Optimized Datacenters (PODs), geographically distributed to exploit the availability of renewable energy for its operation. Such a distributed system has the potential to significantly enhance the energy efficiency, reliability, security, and overall performance of the data center by several means:

1. Optimizing the utilization of the available renewable power for computing by intelligently redistributing computational load depending on the availability of renewable energy;
2. Minimizing losses associated with power transmission by placing the PODs near the power source;

This concept provides data center operators the means to avoid performing expensive utility upgrades as the availability of wind power through New York State and other states grows, keeping the infrastructure and Transmission & Distribution (T&D) costs low, thus making it possible to use the wind power that is currently stranded, i.e. not-delivered to the grid due to the T&D constraints.

Optimizing compute load shifting in this manner has the potential to generate significant efficiencies for the utilization of renewable energy sources and data center operations and potentially create a new economic model for both renewable energy and data centers. Under this new model, the high costs associated with transmission infrastructure for renewable energy is replaced by relatively low cost and highly efficient data transmission infrastructure.

The main technological benefit of the proposed project is the development of a distributed POD network that can be powered from renewable energy, primarily wind, potentially consuming a significant amount of constrained power that is not otherwise beneficially utilized