Simulation support for internet-based energy services

The rapidly developing Internet broadband network offers new opportunities for deploying a range of energy, environment and health-related services for people in their homes and workplaces. Several of these services can be enabled or enhanced through the application of building simulation. This paper describes the infrastructure for e-services under test within a European research project and shows the potential for simulation support for these services

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

Multifractal analysis of high-frequency temperature time series in the urban environment

Continuous monitoring systems have been regarded as a very useful tool to provide continuous high-frequency measurements of many parameters. Here, we analyze high-frequency time series of air temperature measurements, recorded every 10 min during 2003 in Athens (Greece) by an online monitoring system for the urban environment. We propose a set of time series analysis techniques, where missing data are well respected and information concerning the system's dynamics is preserved. A power spectral density analysis is performed over time scales spanning from 10 min to several days. A scale-invariant behavior of the form E( f ) ≈ f-β is revealed for scales below 9 h. Over this scaling range, we have performed structure functions analysis, and shown that air temperature data exhibit turbulent-like intermittent properties with multi-fractal statistics. The multifractal exponents obtained possess some similarities with passive scalar turbulence results. Although we illustrate the proposed approach using air temperature data, the method can be used as an efficient tool to analyse other environmental parameters monitored in urban environment. © 2018 by the authors

Socio-economic status and residential energy consumption: A latent variable approach.

Income, housing unit size, number of appliances owned and other components of socio-economic status (SES), are variables generally considered to influence residential energy use. Using structural equation modeling of SES indicators from the U.S. residential energy consumption survey (RECS), we provide evidence that SES, usually modeled as a latent construct with effect indicators, is better conceptualized as including at least some causal indicators. We studied the mediating effect of housing unit size and number of owned appliances on the relationship between SES, household size and residential energy consumption (REC). We found that household size was positively associated with REC, as a direct effect. SES had a strong impact on REC, while being mediated by housing unit size and number of appliances owned. In conclusion, research must take the latent nature of SES into account to uncover its total influence on REC. © 2019 Elsevier B.V

Detection of low-dimensional chaos in buildings energy consumption time series

In this paper, nonlinear time series modeling techniques are applied to analyze building energy consumption data. The time series were obtained for the benchmark data set Proben 1, and comes from the first energy prediction contest, the Great Building Energy Predictor Shootout I, organized by ASHRAE. The phase space, which describes the evolution of the behavior of a nonlinear system, is reconstructed using the delay embedding theorem suggested by TAKENS. The embedding parameters, e.g. the delay time and the embedding dimension are estimated using the average mutual information (AMI) of the data and the false nearest neighbor (FNN) algorithm, respectively. Nonlinearity was detected, by applying the surrogate data sets method. Numerically estimated non-integral fractal dimension and a positive Lyapunov exponent are not necessarily sufficient indication of chaos; therefore we apply a more stringent criterion, developed by Gao and Zheng, which is based on the logarithmic displacement of time-dependent exponent curves, and show that these data are chaotic. Based on this analysis and proof, we then calculate the correlation dimension of the resulting attractor and the largest Lyapunov exponent. The correlation dimension 3.47 and largest Lyapunov exponent 0.047 are estimated. These results indicate that chaotic characteristics obviously exist in the specific energy consumption data set, and thus techniques based on phase space dynamics can be used to analyze and predict buildings energy use. © 2009 Elsevier B.V. All rights reserved

Models of behavior change and residential energy use: A review of research directions and findings for behavior-based energy efficiency

Energy efficiency through change of energy-related behavior represents a significant promise in terms of energy savings. Building occupants' behavior has a great influence on final energy consumption, and although behavioral savings potentials were usually omitted, there is, currently, a revitalized research interest in applying social and behavioral science to energy efficiency research. The research focuses mainly on the residential sector, attempting to explore the relationships between energy use, behavioral determinants, and effective strategies to promote more efficient behaviors. While the promise is significant, it is also clear that not only the complexity of behaviors but also our interpretation and elaboration of existing volume of behavior change theory, create a set of challenges that research should overcome, if it is to move towards a more integrated approach. This paper presents a review of literature on energy behavior as a basis to understand how behavior change occurs, what the main determinants of behavior are, how these are related to applied interventions focusing on altering residential energy use, and finally how all these aspects can be evaluated. Issues for further research are identified. © 2013 Taylor & Francis

On the calculation of solar utilizability for south oriented flat plate collectors tilted to an angle equal to the local latitude

The utilizability or φsymbol-curve method is a design method for some types of solar energy systems that use flat-plate solar collectors. It can be a very useful design tool, for the preliminary design or the design of small systems, cases where methods easy to use and apply are required. In this paper, a simple method to calculate monthly average hourly and daily flat plate collector utilizability is presented. It is based on empirical correlation of φsymbol with independent variables that separate meteorological and collector parameters, making possible quick evaluations of changes in collector design and collector inlet temperature. In general, the method reduces the calculations required to determine φsymbol, and gives good results compared to long-term hourly simulations as well as to existing hourly and daily utilizability calculations methods. © 2006 Elsevier Ltd. All rights reserved

Analysis of experimental data on diffuse solar radiation in Athens, Greece, for building applications

Proper design and performance prediction of solar energy systems requires accurate information on the availability of solar radiation. The diffuse-to-total radiation correlation, originally developed by Liu and Jordan, has been extensively used as the technique and provided excellent results, although it was latitude dependent and not universally applicable. Thus, diffuse fraction correlations of this type have been developed by few other authors and for different location. This paper presents an analysis of hourly diffuse radiation on a horizontal surface. Hourly pyranometer data from Athens, Greece, are used to establish relationships between the diffuse fraction and the clearness index kT for hourly and daily values. The results of the proposed equations are then compared with earlier equations. For the urban conditions of Athens the developed correlation fit to the empirical data. © 2003 Taylor & Francis Ltd

A methodology for the determination of indoor environmental quality in residential buildings through the monitoring of fundamental environmental parameters: A proposed Dwelling Environmental Quality Index

This paper presents the methodology for the calculation of an indoor environmental quality indicator for residential buildings. The 'Dwelling Environmental Quality Index' has been developed with the purpose of assisting both households and property managers to identify potential problems with the indoor environment whilst ensuring that indoor environmental quality is not compromised in favour of energy saving. Based on the combined effect of three simple and commonly measured indoor environmental parameters - air temperature, relative humidity and CO2 concentrations; the index reflects in a single value the quality of indoor environmental conditions for the monitored period, in compliance with the European standard EN15251:2007. The application of the Dwelling Environmental Quality Index in single dwellings and in building blocks is demonstrated. The usability of the index as a communication and management tool for individual households and property managers is also demonstrated. © International Society of the Built Environment