ICT for Energy Efficiency

Assessing the average energy intensity of Internet transmissions is a complex task that has been a controversial subject of discussion. Estimates published over the last decade diverge by up to four orders of magnitude — from 0.0064 kilowatt-hours per gigabyte (kWh/GB) to 136 kWh/GB. This article presents a review of the methodological approaches used so far in such assessments: i) top–down analyses based on estimates of the overall Internet energy consumption and the overall Internet traffic, whereby average energy intensity is calculated by dividing energy by traffic for a given period of time, ii) model-based approaches that model all components needed to sustain an amount of Internet traffic, and iii) bottom–up approaches based on case studies and generalization of the results. Our analysis of the existing studies shows that the large spread of results is mainly caused by two factors: a) the year of reference of the analysis, which has significant influence due to efficiency gains in electronic equipment, and b) whether end devices such as personal computers or servers are included within the system boundary or not. For an overall assessment of the energy needed to perform a specific task involving the Internet, it is necessary to account for the types of end devices needed for the task, while the energy needed for data transmission can be added based on a generic estimate of Internet energy intensity for a given year. Separating the Internet as a data transmission system from the end devices leads to more accurate models and to results that are more informative for decision makers, because end devices and the networking equipment of the Internet usually belong to different spheres of control.

Despite the fact that Information and Communication Technologies (ICTs) are responsible for only a small part of worldwide greenhouse gas emissions–current estimations attribute around 2% of man made emissions to ICT–this sector is the one with the fastest growing emissions. As a result, there is an increasing concern about the environmental impact of ICT, especially the climate change potential induced by ICT related energy consumption.

This introductory chapter provides definitions of sustainability, sustainable development, decoupling, and related terms; gives an overview of existing interdisciplinary research fields related to ICT for Sustainability, including Environmental Informatics, Computational Sustainability, Sustainable HCI, and Green ICT; introduces a conceptual framework to structure the effects of ICT on sustainability; and provides an overview of this book.

For quite some years now, there has been a growing debate under the label of “Green I(C)T” about reducing the energy consumption of ICT equipment. More recently, the discourse started to partly shift towards a novel discussion on using ICT to induce energy savings in sectors other than ICT. Advocates suggest that the cumulated potential for ICT-induced savings is several times larger than the entire energy consumption of ICT itself. Numerous studies on ICT-related energy consumption exist, and also an increasing number of studies looking at ICT-induced energy efficiency. The few studies, however, considering both aspects, typically do so independently, without relating the two aspects. Moreover, in the energy efficiency discourse, ICT is usually treated as a monolithic block of technologies – only the application areas that are expected to benefit from it being differentiated. In this paper, we make the case that ICT energy consumption and ICT’s potential for inducing energy efficiency can – and should – be related to each other. We further argue that this can only be obtained by decomposing the “ICT monolith” and look at its (naturally heterogeneous) parts separately. Based on a first round of expert interviews, we show that it is possible to qualitatively determine for every single technology subsumed under ICT its potential for inducing energy efficiency. We finally argue that only by consequently following low energy consumption targets for technologies with a low energy efficiency potential, while at the same time not suffocating technologies with a high energy efficiency potential through restrictive consumption targets, the full ICT-related energy saving potential can be unleashed.

A simple, generic measurement-based power consumption model is described and is shown to apply to equipment, networks and services. This model is used to construct power consumption estimates for a diverse range of network scenarios including customer premises equipment and access, edge and core networks and services provided over a network.