Multivariate statistical monitoring of buildings. Case study: Energy monitoring of a social housing building

Burgas, Llorenç; Colomer, Joan; Meléndez, Joaquím; Pous, Carles

doi:10.1016/j.enbuild.2015.06.069

Cited by 13 publications

(7 citation statements)

References 15 publications

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“…With this monitoring system, it is possible to evaluate building energy performance. In the same line, the authors of [19] propose the energy monitoring of a building, using the Unfolding or Multiway Principal Component Analysis. In [20] a load disaggregation algorithm is studied for smart meter sensor data.…”

Section: Monitoring Systemsmentioning

confidence: 99%

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Design Considerations of a Monitoring System of a Farm for Energy Efficiency Purposes

Moposita

Noboa-Lopez

Clairand

et al. 2019

2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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The monitoring of industry processes can optimize the use of resources and improve its efficiency. In dairy farms, several parameters from the processes must be monitored. This paper proposes the design of a monitoring system for a farm that produces dairy products and jams. Several similar studies are analysed. Based on this, and on the farm characteristics, a novel design is developed. The principal benefits of the system are also exposed.

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Section: Monitoring Systemsmentioning

confidence: 99%

“…This work was supported by Universidad de las Américas -Ecuador under project SIS.JCG. 19.01. The authors would like to thank Mónica Guevara, Andrea Maldonado, and Francisca Martínez from Universidad de las Américas -Ecuador for their valuable help and information.…”

Section: Acknowledgementsmentioning

confidence: 99%

Design Considerations of a Monitoring System of a Farm for Energy Efficiency Purposes

Moposita

Noboa-Lopez

Clairand

et al. 2019

2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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show abstract

“…Control chart is a popular statistical process control, SPC, tool used by practitioners to monitor processes with the aim of detecting unfavorable condition in process parameters. Although it was first proposed for manufacturing industry, control charts have now been applied in a wider range of disciplines, including health-care [1]- [3], environment [4]- [6] and general services [6]- [9]. Exponential weighted moving average (EWMA) and multivariate EWMA (MEWMA) are examples of time-weighted moving control charts, that use the weighted average as the location estimator [10].…”

Section: Introductionmentioning

confidence: 99%

New Robust MEWMA Control Chart for Monitoring Contaminated Data

Jamaluddin¹,

Ali²,

Yahaya³

2019

IJITEE

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Multivariate Exponential Weighted Moving Average (MEWMA), E 2 control chart is a popular multivariate control chart for monitoring the stability of time series data (non-random pattern). However, in this paper, we have shown that the existing MEWMA, E 2 control chart is sensitive in contaminated data or in the presence of outliers. To address this problem, this paper proposed an alternative MEWMA E 2 control chart using robust mean vector and covariance matrix instead of the classical mean vector and covariance matrix respectively. The classical mean vector in MEWMA E 2 control chart is replaced by Winsorized Modified One-step M-estimator (WM) while the classical covariance matrix is replaced by the Winsorized covariance matrix. The proposed MEWMA E 2 control chart known as robust MEWMA control chart, denoted as RE2 control chart. The control limit for the RE2 control chart was calculated based on simulated data. The performance of RE2 and existing MEWMA E 2 control charts are based on the false alarm rate. The result revealed that the RE2 control chart is more effective in controlling false alarm rates as compared to the existing MEWMA, E 2 control chart. The zinc-lead flotation data show that the RE2 performs better in application.

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“…In this context, social housing has been at the centre of several studies on the impact of the rehabilitation of residential buildings on energy consumption [22][23][24][25], and the effect of improved energy installations [26][27][28]. Social housing tends to be inhabited by low-income households, and the buildings are often energy-inefficient.…”

Section: Introductionmentioning

confidence: 99%

“…Although it is generally accepted that the accurate identification and evaluation of the causes of energy poverty constitute the first step in solving the problem [8,42,43], no specific multi-criteria methodology for managing social housing has been developed to date. The specialised literature on energy and building has put forward interesting ideas concerning social housing [28,31,34,[44][45][46][47], but an integrated analysis of household energy poverty and the management of social housing is still lacking.…”

Section: Introductionmentioning

confidence: 99%

Energy Vulnerability Composite Index in Social Housing, from a Household Energy Poverty Perspective

et al. 2017

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In Europe, the proportion of social housing is high, and such houses tend to be inhabited by below average-income households, which are particularly vulnerable to energy poverty. This article proposes a new methodological approach for defining an index for household energy vulnerability assessment. This method can be used to improve the management of social housing. After establishing a heuristic framework for household energy poverty-which stems from different causes such as income, the characteristics of the residence, energy installations, and the energy-consumption habits of household members-multi-criteria analytical methods, based on the aggregation of indicators which reveal the conditions leading to energy poverty, have been applied, and effective means of intervention are proposed. The method is also applied to a sample of social houses and thus validated as a useful tool in decision-making processes which concern the management of social housing from a household energy-poverty perspective.

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Multivariate statistical monitoring of buildings. Case study: Energy monitoring of a social housing building

Cited by 13 publications

References 15 publications

Design Considerations of a Monitoring System of a Farm for Energy Efficiency Purposes

Design Considerations of a Monitoring System of a Farm for Energy Efficiency Purposes

New Robust MEWMA Control Chart for Monitoring Contaminated Data

Energy Vulnerability Composite Index in Social Housing, from a Household Energy Poverty Perspective

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