scholarly journals Energy Use in Residential Buildings: Characterisation for Identifying Flexible Loads by Means of a Questionnaire Survey

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2055 ◽  
Author(s):  
Francesco Mancini ◽  
Gianluigi Lo Basso ◽  
Livio De Santoli
Keyword(s):  
Data Analysis ◽  
Energy Use ◽  
Residential Buildings ◽  
Automation System ◽  
Research Activity ◽  
Flexible Loads ◽  
On Line ◽  
House Floor ◽  
Statistical Sample

This work shows the outcomes of a research activity aimed at the energy characterization of residential users. Specifically, by data analysis related to the real energy consumption of sample buildings, the flexible loads amount has been identified so as to investigate on the opportunity to implement a demand/response (DR) program. The most meaningful input data have been collected by an on-line questionnaire created within an Excel spreadsheet allowing one to simulate and compare the calculations with the actual dwellings’ consumption; 412 questionnaires have been used as statistical sample and simulations have been performed based on single-zone dynamic model. Additionally, once the energy consumptions have been sorted by the different services, reference key performance indicators (KPIs) have been also calculated normalising those ones by people and house floor surface. From data analysis, it emerges how the Italian residential users are not very electrified. Furthermore, the flexible loads are low and, implementing minor maintenance interventions, the potential of flexibility can decrease up to 20%. For that reason, the current research can be further developed by investigating on suitable flexibility extensions as well as on the automation system requirements which is needed managing the flexible loads.

scholarly journals Energy Use in Residential Buildings: Impact of Building Automation Control Systems on Energy Performance and Flexibility

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2896 ◽  
Author(s):  
Francesco Mancini ◽  
Gianluigi Lo Basso ◽  
Livio de Santoli
Keyword(s):  
Control Systems ◽  
Energy Use ◽  
Financial Analysis ◽  
Residential Buildings ◽  
Energy Performance ◽  
Automation System ◽  
Research Activity ◽  
Demand Response Program ◽  
Automation Control ◽  
Simple Activity

This work shows the results of a research activity aimed at characterizing the energy habits of Italian residential users. In detail, by the energy simulation of a buildings sample, the opportunity to implement a demand/response program (DR) has been investigated. Italian residential utilities are poorly electrified and flexible loads are low. The presence of an automation system is an essential requirement for participating in a DR program and, in addition, it can allow important reductions in energy consumption. In this work the characteristics of three control systems have been defined, based on the services incidence on energy consumptions along with a sensitivity analysis on some energy drivers. Using the procedure established by the European Standard EN 15232, the achievable energy and economic savings have been evaluated. Finally, a financial analysis of the investments has been carried out, considering also the incentives provided by the Italian regulations. The payback time is generally not very long: depending on the control system features it varies from 7 to 10 years; moreover, the automation system installation within dwellings is a relatively simple activity, which is characterized by a limited execution times and by an initial expenditure ranging in 1000 € to 4000 €, related to the three sample systems.

scholarly journals Baseline Energy Use Modeling and Characterization in Tertiary Buildings Using an Interpretable Bayesian Linear Regression Methodology

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5556
Author(s):  
Benedetto Grillone ◽  
Gerard Mor ◽  
Stoyan Danov ◽  
Jordi Cipriano ◽  
Florencia Lazzari ◽  
...  
Keyword(s):  
Linear Regression ◽  
Energy Use ◽  
Residential Buildings ◽  
Data Driven ◽  
Multilevel Regression ◽  
Measurement And Verification ◽  
Bayesian Linear Regression ◽  
Bayesian Methodologies ◽  
Posterior Estimation

Interpretable and scalable data-driven methodologies providing high granularity baseline predictions of energy use in buildings are essential for the accurate measurement and verification of energy renovation projects and have the potential of unlocking considerable investments in energy efficiency worldwide. Bayesian methodologies have been demonstrated to hold great potential for energy baseline modelling, by providing richer and more valuable information using intuitive mathematics. This paper proposes a Bayesian linear regression methodology for hourly baseline energy consumption predictions in commercial buildings. The methodology also enables a detailed characterization of the analyzed buildings through the detection of typical electricity usage profiles and the estimation of the weather dependence. The effects of different Bayesian model specifications were tested, including the use of different prior distributions, predictor variables, posterior estimation techniques, and the implementation of multilevel regression. The approach was tested on an open dataset containing two years of electricity meter readings at an hourly frequency for 1578 non-residential buildings. The best performing model specifications were identified, among the ones tested. The results show that the methodology developed is able to provide accurate high granularity baseline predictions, while also being intuitive and explainable. The building consumption characterization provides actionable information that can be used by energy managers to improve the performance of the analyzed facilities.

scholarly journals System characterization of dynamic biological systems through improved data analysis.

2021 ◽  
Author(s):  
Gerben R Stouten ◽  
Sieze Douwenga ◽  
Carmen Hogendoorn ◽  
Robbert Kleerebezem
Keyword(s):  
Data Analysis ◽  
Process Model ◽  
System Analysis ◽  
Close Monitoring ◽  
Line System ◽  
Wide Range ◽  
System Characterization ◽  
On Line ◽  
Batch Bioreactors

Determining the functional development and dominant competitive strategy in microbial community enrichments is complicated by the extensive measurement campaigns required for off-line system analysis. This study demonstrates that detailed system characterization of aerobic pulse fed enrichments can be established using on-line measurements combined with automated data analysis. By incorporating the physicochemical processes in on-line data processing with a Particle Filter and kinetic process model, an accurate reconstruction of the dominant biological rates can be made. We hereby can differentiate between storage compound production and biomass growth in sequencing batch bioreactors. The method proposed allows for close monitoring of changes in functional behavior of long-running enrichment cultures, without the need for off-line samples, therewith enabling the identification of new insights in process dynamics with a minimal experimental effort. Even though a specific example application of the method proposed is described here, the approach can readily be extended to a wide range of dynamic experimental systems that can be characterized based on on-line measurements.

Generic monitoring tools for water characteristics assessment

2003 ◽  
Vol 3 (1-2) ◽  
pp. 351-357
Author(s):  
S. Le Bonté ◽  
M.-N. Pons ◽  
O. Potier ◽  
S. Chanel ◽  
M. Baklouti
Keyword(s):  
Municipal Wastewater ◽  
Principal Component ◽  
Toxic Substances ◽  
Capacity Curves ◽  
Water Characteristics ◽  
Monitoring Tools ◽  
Visible Spectra ◽  
On Line ◽  
Mining Procedure

An adaptive principal component analysis applied to sets of data provided by global analytical methods (UV-visible spectra, buffer capacity curves, respirometric tests) is proposed as a generic procedure for on-line and fast characterization of wastewater. The data-mining procedure is able to deal with a large amount of information, takes into account the normal variations of wastewater composition related to human activity, and enables a rapid detection of abnormal situations such as the presence of toxic substances by comparison of the actual wastewater state with a continuously updated reference. The procedure has been validated on municipal wastewater.

ON-LINE CHARACTERIZATION OF MAGNETIC NANO PARTICLES - SIMULATION VERSUS EXPERIMENT

2001 ◽  
Vol 32 ◽  
pp. 385-386
Author(s):  
TH. KAUFFELDT ◽  
E. KAUFFELDT ◽  
T. ZARUTSKAYA ◽  
M. SHAPIRO ◽  
A. SCHMIDT-OTT
Keyword(s):  
Nano Particles ◽  
On Line ◽  
Magnetic Nano Particles

scholarly journals Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate

2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Energy Use ◽  
Residential Buildings ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Living Room ◽  
Extra Energy ◽  
Cooling Unit ◽  
Indoor Conditions

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.

scholarly journals Optimal Control Strategies for Switchable Transparent Insulation Systems Applied to Smart Windows for US Residential Buildings

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2917
Author(s):  
Mohammad Dabbagh ◽  
Moncef Krarti
Keyword(s):  
Energy Use ◽  
Control Strategies ◽  
Residential Buildings ◽  
Residential Building ◽  
Optimization Approach ◽  
Optimal Controls ◽  
Peak Demand ◽  
Smart Windows ◽  
Insulation Systems ◽  
Rule Set

This paper evaluates the potential energy use and peak demand savings associated with optimal controls of switchable transparent insulation systems (STIS) applied to smart windows for US residential buildings. The optimal controls are developed based on Genetic Algorithm (GA) to identify the automatic settings of the dynamic shades. First, switchable insulation systems and their operation mechanisms are briefly described when combined with smart windows. Then, the GA-based optimization approach is outlined to operate switchable insulation systems applied to windows for a prototypical US residential building. The optimized controls are implemented to reduce heating and cooling energy end-uses for a house located four US locations, during three representative days of swing, summer, and winter seasons. The performance of optimal controller is compared to that obtained using simplified rule-based control sets to operate the dynamic insulation systems. The analysis results indicate that optimized controls of STISs can save up to 81.8% in daily thermal loads compared to the simplified rule-set especially when dwellings are located in hot climates such as that of Phoenix, AZ. Moreover, optimally controlled STISs can reduce electrical peak demand by up to 49.8% compared to the simplified rule-set, indicating significant energy efficiency and demand response potentials of the SIS technology when applied to US residential buildings.

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