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Summary: In order to understand the electricity use of Internet services, it is important to have accurate estimates for the average electricity intensity of transmitting data through the Internet (measured as kilowatt‐hours per gigabyte [kWh/GB]). This study identifies representative estimates for the average electricity intensity of fixed‐line Internet transmission networks over time and suggests criteria for making accurate estimates in the future. Differences in system boundary, assumptions used, and year to which the data apply significantly affect such estimates. Surprisingly, methodology used is not a major source of error, as has been suggested in the past. This article derives criteria to identify accurate estimates over time and provides a new estimate of 0.06 kWh/GB for 2015. By retroactively applying our criteria to existing studies, we were able to determine that the electricity intensity of data transmission (core and fixed‐line access networks) has decreased by half approximately every 2 years since 2000 (for developed countries), a rate of change comparable to that found in the efficiency of computing more generally. [ABSTRACT FROM AUTHOR]

Data centers are a significant and growing component of electricity demand in the United States. This paper presents a bottom-up model that can be used to estimate total data center electricity demand within a region as well as the potential electricity savings associated with energy efficiency improvements. The model is applied to estimate 2008 U.S. data center electricity demand and the technical potential for electricity savings associated with major measures for IT devices and infrastructure equipment. Results suggest that 2008 demand was approximately 69 billion kilowatt hours (1.8% of 2008 total U.S. electricity sales) and that it may be technically feasible to reduce this demand by up to 80% (to 13 billion kilowatt hours) through aggressive pursuit of energy efficiency measures. Measure-level savings estimates are provided, which shed light on the relative importance of different measures at the national level. Measures applied to servers are found to have the greatest contribution to potential savings. [ABSTRACT FROM PUBLISHER]

The article discusses the financial risks in developing new nuclear power to achieve its cost objectives in the U.S. Reportedly, the U.S. Nuclear Regulatory Commission did not approved the construction of any proposed nuclear reactors since 1978. Factors of the disapproval include the rising and volatile petroleum prices, increasing energy demand from emerging economies, and the potential creation of regional pollutants. The construction of new nuclear power will play a significant role in addressing future energy needs of the country, however, it requires bigger budget for future nuclear energy costs, benefits, and risk. Furthermore, nuclear development and deployment of nuclear technology will mitigate cost that will remain prone to argument between the government.

As information and communications technology matures, the nature of the infrastructure that supports it evolves and specializes. While the telephone infrastructure had been built as a network with central offices acting as hubs, the information and communications technology maintains a similar structure, but instead, has hubs of specialized Internet data centers which house the routers and servers. This paper updates one of the first studies to document the electricity consumption and power distribution within an Internet data center. For this study, electricity billing data, metering data, and facility floor space allocation data were used to calculate computer room, total computer room, and building power densities for July 2002. The results of this 2002 study indicate that although the data center had expanded its operations by roughly 33% from the previous year and increased the electricity demand associated with the computer equipment by 55%, the total computer room power density (which includes cooling and auxiliary equipment) remained the same as the previous year at 355 W/m2. The facility’s efforts to improve energy efficiency offset the energy demand from an increased, electrically active, computer room area. The energy-efficiency measures included better optimization of power distribution units, power management modules, computer room air-conditioning units, alterations to operating conditions, facilitywide reductions in lighting, and improved facility controls. A key recommendation is to expand this research to address the need to develop metrics to capture the energy efficiency of the data network throughput. [ABSTRACT FROM AUTHOR]

The electrical efficiency of computation has doubled roughly every year and a half for more than six decades, a pace of change comparable to that for computer performance and electrical efficiency in the microprocessor era. These efficiency improvements enabled the creation of laptops, smart phones, wireless sensors, and other mobile computing devices, with many more such innovations yet to come. The Web Extra appendix outlines the data and methods used in this study. [ABSTRACT FROM PUBLISHER]