Showing papers in "Energy and Buildings in 2017"

TL;DR: In this article, the authors compared the performance of feed-forward back-propagation artificial neural network (ANN) with random forest (RF), an ensemble-based method gaining popularity in prediction, for predicting the hourly HVAC energy consumption of a hotel in Madrid, Spain.

TL;DR: In this paper, a comprehensive review of the artificial neural network (ANN) based model predictive control (MPC) system design is carried out followed by a case study in which ANN models of a residential house located in Ontario, Canada are developed and calibrated with the data measured from site.

TL;DR: Data filtering to remove non-predictive parameters and feature ranking is discussed to include in energy prediction models and for building performance modeling.

TL;DR: The International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs as mentioned in this paper.

TL;DR: The results show the viability to develop methods based on BIM models for organizing building information used to estimate environmental and energy consumption impacts based on LCA, including: templates and plug-ins for BIM software, and the integration of automated processes combining different data and software.

TL;DR: A review of the recent contributions related to the environmental evaluation of building refurbishment and renovation using the lifecycle assessment (LCA) methodology is presented in this article, where the main barriers found for disseminations are discussed: system boundaries interpretation of EN 15978, functional unit, LCI methods, operational stage and the end-of-life stage definition.

TL;DR: In this article, the authors employed an interdisciplinary approach, integrating building science, architectural engineering, computer modeling and simulation, and social and behavioral science to develop and apply methods to analyze and evaluate the real energy use in buildings considering the six influencing factors.

TL;DR: In this article, the best in class of the building integrated photovoltaic (BIPV) products and their properties along with international guidelines and testing standards are introduced and highlighted.

TL;DR: The IEA EBC Annex 67 (Energy in Buildings and Communities program) as discussed by the authors was started in 2015 to provide an overview and insight into how much Energy Flexibility different building may offer to the future energy systems in the sense of avoiding excess energy production, increase the stability of the energy networks, minimize congestion problems, enhance the efficiency and cost effectiveness of future energy networks.

TL;DR: In this paper, the authors evaluate the current construction industry practice through a review of both academic and professional literature, and through focus groups and interviews with industry experts in the field, and identify the barriers to the effective measurement and reduction of embodied CO2e in practice.

TL;DR: Wang et al. as mentioned in this paper conducted an online survey to study the urban residential energy and usage behavior, and found that the general trend in Chinese urban households is larger unit sizes (on average, 109m2 per household) and smaller families.

TL;DR: In this article, a review of the available research information on synthesis, characterization, properties and applications of microencapsulated phase change materials for thermal energy storage is presented, where the properties of micro-encapped phase change material like physical properties, chemical properties and thermal properties are analyzed.

TL;DR: In this paper, a cross-comparative study of the societal and technical barriers of nZEB implementation in 7 Southern European countries is presented, and the authors provide recommendations for actions to shift the identified gaps into opportunities for future development of climate adaptive high performance buildings.

TL;DR: In this article, the experimental works in the fields of phase change materials (PCMs) in buildings are taken into account, and they are classified based on heating, cooling, and air-conditioning.

TL;DR: In this paper, the authors presented the outcome of a new system architecture and control algorithm that can use both battery storage and manage the temperature of thermal appliances, which is an important part of the smart grid that enables residential customers to execute demand response programs autonomously.

TL;DR: Wang et al. as mentioned in this paper investigated the performance of a representative apartment building in the city of Shanghai and evaluated the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multiorientive optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time

TL;DR: In this paper, the authors presented a more detailed methodology for setting up UBEMs while faced with incomplete information about the buildings, which called for defining unknown or uncertain parameters in archetype descriptions as probability distributions and using measured energy data to update these distributions by Bayesian calibration.

TL;DR: In this article, the effect of four green-roof types on outdoor/indoor temperature and cooling demand under four different climates and three urban densities using co-simulation approach with ENVI-met and EnergyPlus.

TL;DR: Wang et al. as mentioned in this paper presented a year-long survey which was carried out in 505 residential buildings in six cities located in the Hot Summer and Cold Winter (HSCW) zone of China involving 11,524 subjects.

TL;DR: A new pattern-based anomaly classifier is proposed, the collective contextual anomaly detection using sliding window (CCAD-SW) framework, which improved the anomaly detection capacity of the CCAD- SW by 3.6% and reduced false alarm rate by 2.7%.

TL;DR: In this paper, the authors proposed to identify and classify occupants' behavior with direct energy consumption outcomes and energy time use data through unsupervised clustering, based on the American Time Use Survey (ATUS), the proposed approach integrates k-modes clustering and demographic-based probability neural networks and identifies 10 distinctive behavior patterns.

TL;DR: In this paper, the authors evaluate the potential for use of building information modelling (BIM) as a tool to support the visualisation and management of a building's performance; demonstrating a method for the capture, collation and linking of data stored across the currently disparate BIM and building management system (BMS) data environments.

TL;DR: In this article, the authors investigate the underpinnings of green building adoption in the following areas: (1) the critical barriers inhibiting the adoption of GBTs, (2) major drivers for adopting GBTs and (3) important strategies to promote GBTs adoption.

TL;DR: In this article, a real time optimal schedule controller for HEMS is proposed using a new binary backtracking search algorithm (BBSA) to manage the energy consumption, which gives optimal schedule for home devices in order to limit the demand of total load and schedule the operation of home appliances at specific times during the day.

TL;DR: In this paper, the authors present a framework for quantifying the impact of occupant behaviors on energy conservation measures (ECM) energy savings using building performance simulation and a pilot study is performed in a real building to demonstrate the application of the framework.

TL;DR: In this article, the authors review the recent advancements in building predictive control with energy storage system and pay special attention to its limitations and abilities, while considering both loads and renewable energy production.

TL;DR: In this paper, the authors reviewed air temperatures measured in bedroom and the effects of heat and cold exposure on sleep quality, and then proposed five aspects of approaches or technologies that could improve sleeping thermal environment at a low energy consumption.

TL;DR: Different types of optimization problems, constraints and techniques as well as the optimization tools used in district energy systems are discussed.

TL;DR: This proposed clustering method based on k-shape algorithm is a relatively novel method to identify shape patterns in time-series data and can detect building energy usage patterns in different time granularity effectively and proves that the forecasting accuracy of SVR model is significantly improved by utilizing the results of the proposed clustered method.

TL;DR: Wang et al. as mentioned in this paper investigated the relationship between land use/land cover (LULC) types and land surface temperature (LST) patterns in Shenyang, China were investigated using Landsat 8 image.