Development of a statistical analysis model to benchmark the energy use intensity of subway stations

Ahn, Jonghoon; Cho, Soolyeon; Chung, Dae Hun

doi:10.1016/j.apenergy.2016.06.065

Cited by 46 publications

(16 citation statements)

References 23 publications

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“…KPIs are often used to monitor energy performance in several industrial applications, e.g. from subway stations [17] to compressed air systems [18]. In the wastewater sector, KPIs have been used to give a general overview of the energy performance of WWTPs [19].…”

Section: Literature Reviewmentioning

confidence: 99%

ENERWATER – A standard method for assessing and improving the energy efficiency of wastewater treatment plants

et al. 2019

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This paper describes the first methodology specifically tailored to estimate energy efficiency at wastewater treatment plants (WWTPs). Inspired by the cycle of continuous improvement, the method i) precisely defines the concept of energy efficiency in WWTPs, ii) proposes systematic and comparable ways to measure it, and iii) allows benchmarking and diagnosing energy hotspots. The methodology delivers an aggregated measure of the WWTP energy efficiency defined as the Water Treatment Energy Index, a single energy label that uses universally known illustrations enabling wide communication of standardized information on the WWTP energy status. The accuracy, reproducibility and generality of the methodology were validated by a widespread energy benchmarking method, and a case study is presented to show its capabilities. By promoting dialogue towards the

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Section: Literature Reviewmentioning

confidence: 99%

ENERWATER – A standard method for assessing and improving the energy efficiency of wastewater treatment plants

et al. 2019

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“…EUI is a measure of the building's energy performance. It is an expression of the total energy consumption as a function of the total size of the site [22,23]. In this study, EUI was calculated by the total energy consumption divided by the total size of site (ft 2 ) at OC and WB separately.…”

Section: Utility Total Sitementioning

confidence: 99%

Greener and Leaner: Lower Energy and Water Consumption, and Reduced Work Orders, in Newly Constructed Boston Public Housing

Brod¹,

Laurent

Kane

et al. 2020

Atmosphere

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The Boston Residential Investigation on Green and Healthy Transitions (BRIGHT) Study is focused on quantifying the effects of redeveloping public housing developments into new buildings with improved energy performance and indoor environmental quality. This report presents an analysis of utility consumption and work order requests at Old Colony and Washington-Beech, two redeveloped housing sites in Boston, Massachusetts. We compare the consumption of electricity, natural gas, and water, as well as work order data, from 2012–2014 to development-wide baseline data from 2006–2009. We found that despite the higher number of electric appliances in the new apartments (e.g., air conditioning and ranges), electricity consumption decreased 46% in Old Colony and nearly 30% in Washington-Beech when compared to the baseline data. Natural gas used for space heating decreased by more than 70% at both sites; and water use decreased by nearly 56% at Old Colony and nearly 30% at Washington-Beech. Work order categories that directly influence the residents’ quality of life, such as pests, mold, windows and plumbing decreased by more than 50% in both renovated sites. In combination with previous documentation of health improvements in the redeveloped sites, these results provide further evidence of the magnitude of benefits from updating public housing infrastructure using green design principles.

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“…Guan et al [12] applied a multivariate linear regression (MLR) model to analyse the contribution of different factors such as floor area of station and passenger volume to the ECMS. Ahn et al [13] built a linear regression model to assess existing subway stations performance and predict energy consumption levels for future expansion. In fact, however, these models would be less likely to achieve a high accuracy in predicting the ECMS, as they may fail to capture the underlying nonlinearity in the relationship between the ECMS and its influencing factors.…”

Section: Introductionmentioning

confidence: 99%

An Estimation Model on Electricity Consumption of New Metro Stations

Zhao

Bai

et al. 2020

Journal of Advanced Transportation

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Electricity consumption of metro stations increases sharply with expansion of a metro network and this has been a growing cause for concern. Based on relevant historical data from existing metro stations, this paper proposes a support vector regression (SVR) model to estimate daily electricity consumption of a newly constructed metro station. The model considers some major factors influencing the electricity consumption of metro station in terms of both the interior design scheme of a station (e.g., layout of the station and allocation of facilities) and external factors (e.g., passenger volume, air temperature and relative humidity). A genetic algorithm with five-fold cross-validation is used to optimize the hyper-parameters of the SVR model in order to improve its accuracy in estimating the electricity consumption of a metro station (ECMS). With the optimized hyper-parameters, results from case studies on the Beijing Subway showed that the estimating accuracy of the proposed SVR model could reach up to 95% and the correlation coefficient was 0.89. It was demonstrated that the proposed model could outperform the traditional methods which use a back-propagation neural network or multivariate linear regression. The method presented in this paper can be an adequate tool for estimating the ECMS and should further assist in the delivery of new, energy-efficient metro stations.

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Development of a statistical analysis model to benchmark the energy use intensity of subway stations

Cited by 46 publications

References 23 publications

ENERWATER – A standard method for assessing and improving the energy efficiency of wastewater treatment plants

ENERWATER – A standard method for assessing and improving the energy efficiency of wastewater treatment plants

Greener and Leaner: Lower Energy and Water Consumption, and Reduced Work Orders, in Newly Constructed Boston Public Housing

An Estimation Model on Electricity Consumption of New Metro Stations

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