Towards non-intrusive thermal load Monitoring of buildings: BES calibration

Enríquez, Ricardo; Jiménez, M.J.; Heras, M.R.

doi:10.1016/j.apenergy.2017.01.050

Cited by 33 publications

(13 citation statements)

References 40 publications

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“…For the placement of the devices, the recommendations of ASHRAE 55-2017 were taken as reference [32], except for the common areas, where these were placed 80cm below the roof level, while in the particular areas it was decided to place them on the partitions, away from direct solar radiation and air-conditioning equipment outputs. All this, in order to not obstruct the occupants activities and avoid damage to the sensors [33]. Two reference monitoring campaigns were performed.…”

Section: Equipment and Data Recordingmentioning

confidence: 99%

Indoor Temperature Validation of Low-Income Detached Dwellings under Tropical Weather Conditions

Barrientos-González

Vega-Azamar

Cruz

et al. 2019

Climate

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Urban territorial expansion generated in the last decades has brought a series of consequences, such as the variation between urban and suburban weather conditions affecting indoor temperature and increasing electricity consumption derived from the use of cooling systems. Current approaches of simulation models in residential buildings use indoor environmental data for carrying out validations to propose hygrothermal comfort alternatives for the mitigation of the effects of the external environmental conditions on the interior spaces of dwellings. In this work, an hourly evaluation of both indoor and outdoor environmental parameters of two case studies in a tropical climate was carried out, by means of a whole-building simulation approach tool during a week representative of the warmest period of the year. The integration of the collected environmental data in the theoretical model allowed us to reduce the error range of the estimated indoor temperature with results in normalized mean bias error between 7.10% and −0.74% and in coefficient of variation of the root mean square error between 16.72% and 2.62%, in the different indoor zones of the case studies. At the same time, the energy assessment showed a difference of 33% in Case 1 and −217% in Case 2 for final electricity consumption.

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Section: Equipment and Data Recordingmentioning

confidence: 99%

Indoor Temperature Validation of Low-Income Detached Dwellings under Tropical Weather Conditions

Barrientos-González

Vega-Azamar

Cruz

et al. 2019

Climate

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“…In response to both soaring energy demands and their consequential environmental impacts, the goal of carbon neutrality has been proposed recently to balance the emission and absorption of greenhouse gases [ 1 ]. The building load is the largest energy consumption end, accounting for an average of over 40% electricity in developed countries [ 2 ]. In this regard, building loads such as residential, education, office, healthcare, and industrial loads are emerging as critical consumers in energy consumption sectors [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Non-Intrusive Load Monitoring for Residential Appliances with Ultra-Sparse Sample and Real-Time Computation

Tao

Fan

et al. 2021

Sensors

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To achieve the goal of carbon neutrality, the demand for energy saving by the residential sector has witnessed a soaring increase. As a promising paradigm to monitor and manage residential loads, the existing studies on non-intrusive load monitoring (NILM) either lack the scalability of real-world cases or pay unaffordable attention to identification accuracy. This paper proposes a high accuracy, ultra-sparse sample, and real-time computation based NILM method for residential appliances. The method includes three steps: event detection, feature extraction and load identification. A wavelet decomposition based standard deviation multiple (WDSDM) is first proposed to empower event detection of appliances with complex starting processes. The results indicate a false detection rate of only one out of sixteen samples and a time consumption of only 0.77 s. In addition, an essential feature for NILM is introduced, namely the overshoot multiple (which facilitates an average identification improvement from 82.1% to 100% for similar appliances). Moreover, the combination of modified weighted K-nearest neighbors (KNN) and overshoot multiples achieves 100% appliance identification accuracy under a sampling frequency of 6.25 kHz with only one training sample. The proposed method sheds light on highly efficient, user friendly, scalable, and real-world implementable energy management systems in the expectable future.

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“…The hybrid models use numerical models coupled with statistical models to characterize the energy behavior of buildings. This methodology solves a set of mathematical equations defined by numerical models using real databases as inlet information [14][15]. Asadi et al [16] proposed an optimization technique that makes use of a genetic algorithm and artificial neural networks, with the aim of minimizing the retrofit cost, the energy consumption, and the thermal discomfort hours.…”

Section: Introductionmentioning

confidence: 99%

Relationship between construction parameters and thermal loads in a building without internal gains

Angulo

Soutullo

Giancola

et al. 2021

Rev.Fac.Ing.Univ.Antioquia

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The analysis of building characteristics indicates that there are some uncertainties influencing its energy performance: Environment, volumetry or operating conditions. It is important to have a low-cost system that performs this analysis and energy management by optimizing the coupling between production and consumption. Knowing the relationship between the annual thermal needs with different construction parameters can help to define this system and allow understanding the expected heating and cooling consumption based on easily available information. In this work, a numerical methodology has been applied to estimate the thermal loads of a building without internal gains. For this purpose, a simulation environment has been developed to execute a sensitivity analysis through the interconnection between TRNSYS 16.1 and GenOpt programs. Volumetry, building materials according to Spanish regulations and percentage of external windows are evaluated as analysis variables of the parametric study. Heating, and cooling loads have been calculated to quantify their influence: Older regulations imply higher annual loads; the increase in building height and area reduces the annual thermal loads and higher percentages of glazing on the external façades imply higher annual demands, particularly in the east and west orientations; the variation of the envelope results in the most influential factor. Finally, a statistical study has been performed to assess the annual trends: Heating trends point to more stability with two defined intervals, while cooling trends are more asymmetric.

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Towards non-intrusive thermal load Monitoring of buildings: BES calibration

Cited by 33 publications

References 40 publications

Indoor Temperature Validation of Low-Income Detached Dwellings under Tropical Weather Conditions

Indoor Temperature Validation of Low-Income Detached Dwellings under Tropical Weather Conditions

Non-Intrusive Load Monitoring for Residential Appliances with Ultra-Sparse Sample and Real-Time Computation

Relationship between construction parameters and thermal loads in a building without internal gains

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