2014Unpublished venueRequires access

Standby power consumption estimation for energy saving service

Zhen Wei, Yanan Zhang, Feng Jin, Wenjun Yin, Lin Wu

Open publisher page 2 citations

Abstract

Standby power consumption often takes place unnoticeably, the negligence of which often leads to intangible energy waste. Although there have been several studies related to this issue, no method has been developed to estimate the amount of power consumed this way by analyzing users' power consumption data. Therefore, this paper, based on findings of previous researches and users' power consumption data, proposes an innovative model to characterize users' standby power consumption. Firstly, by considering power data as continuous signal, standby power consumption is estimated by using frequency analysis and high frequency denoising model. Furthermore, Signal decomposition analysis has also been implemented as well as the conduction of rigorous mathematical derivation to get the average standby power based on thousands of power consumption data from Chinese users. Finally, results show that this method successfully separates standby power from the whole consumption dataset. Users are divided into four types based on the distribution of standby mode and nominal mode.

About this research paper

What this paper is about

Standby power consumption often takes place unnoticeably, the negligence of which often leads to intangible energy waste. Although there have been several studies related to this issue, no method has been developed to estimate the amount of power consumed this way by analyzing users' power consumption data. Therefore, this paper, based on findings of previous researches and users' power consumption data, proposes an innovative model to characterize users' standby power consumption. Firstly, by considering power data as continuous signal, standby power consumption is estimated by using frequency analysis and high frequency denoising model. Furthermore, Signal decomposition analysis has also been implemented as well as the conduction of rigorous mathematical derivation to get the average standby power based on thousands of power consumption data from Chinese users. Finally, results show that this method successfully separates standby power from the whole consumption dataset. Users are divided into four types based on the distribution of standby mode and nominal mode.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Standby power consumption often takes place unnoticeably, the negligence of which often leads to intangible energy waste. Although there have been several studies related to this issue, no method has been developed to estimate the amount of power consumed this way by analyzing users' power consumption data. Therefore, this paper, based on findings of previous researches and users' power consumption data, proposes an innovative model to characterize users' standby power consumption. Firstly, by considering power data as continuous signal, standby power consumption is estimated by using frequency analysis and high frequency denoising model. Furthermore, Signal decomposition analysis has also been implemented as well as the conduction of rigorous mathematical derivation to get the average standby power based on thousands of power consumption data from Chinese users. Finally, results show that this method successfully separates standby power from the whole consumption dataset. Users are divided into four types based on the distribution of standby mode and nominal mode.

Key concepts: Standby power, Energy consumption, Computer science, Power (physics), Power consumption, Consumption (sociology), Reliability engineering, Real-time computing

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