scholarly journals Using Building Energy and Smart Thermostat Data to Evaluate Indoor Ultrafine Particle Source and Loss Processes in a Net-Zero Energy House

2021 ◽  
Vol 1 (4) ◽  
pp. 780-793
Author(s):  
Jinglin Jiang ◽  
Nusrat Jung ◽  
Brandon E. Boor
Keyword(s):  
Ultrafine Particle ◽  
Building Energy ◽  
Zero Energy ◽  
Particle Source ◽  
Net Zero Energy ◽  
Net Zero ◽  
Smart Thermostat

Cost Optimization of Net-Zero Energy House

2007 ◽  
Author(s):  
George A. Mertz ◽  
Gregory S. Raffio ◽  
Kelly Kissock
Keyword(s):  
Energy Use ◽  
Cost Optimization ◽  
Building Design ◽  
Building Energy ◽  
Zero Energy ◽  
Resource Limitations ◽  
Net Zero Energy ◽  
Net Zero ◽  
Building Energy Use ◽  
The Cost

Environmental and resource limitations provide increased motivation for design of net-zero energy or net-zero CO2 buildings. The optimum building design will have the lowest lifecycle cost. This paper describes a method of performing and comparing lifecycle costs for standard, CO2-neutral and net-zero energy buildings. Costs of source energy are calculated based on the cost of photovoltaic systems, tradable renewable certificates, CO2 credits and conventional energy. Building energy simulation is used to determine building energy use. A case study is conducted on a proposed net-zero energy house. The paper identifies the least-cost net-zero energy house, the least-cost CO2 neutral house, and the overall least-cost house. The methodology can be generalized to different climates and buildings. The method and results may be of interest to builders, developers, city planners, or organizations managing multiple buildings.

scholarly journals Spatial and Behavioral Thermal Adaptation in Net Zero Energy Buildings: An Exploratory Investigation

2020 ◽  
Vol 12 (19) ◽  
pp. 7961 ◽  
Author(s):  
Shady Attia
Keyword(s):  
Energy Efficiency ◽  
Thermal Comfort ◽  
Energy Use ◽  
Thermal Adaptation ◽  
Building Energy ◽  
Building Energy Efficiency ◽  
Zero Energy ◽  
Net Zero Energy ◽  
Net Zero ◽  
Energy Efficiency Standards

Climate responsive design can amplify the positive environmental effects necessary for human habitation and constructively engage and reduce the energy use of existing buildings. This paper aims to assess the role of the thermal adaptation design strategy on thermal comfort perception, occupant behavior, and building energy use in twelve high-performance Belgian households. Thermal adaptation involves thermal zoning and behavioral adaptation to achieve thermal comfort and reduce energy use in homes. Based on quantitative and qualitative fieldwork and in-depth interviews conducted in Brussels, the paper provides insights on the impact of using mechanical systems in twelve newly renovated nearly- and net-zero energy households. The article calls for embracing thermal adaptation as a crucial design principle in future energy efficiency standards and codes. Results confirm the rebound effect in nearly zero energy buildings and the limitation of the current building energy efficiency standards. The paper offers a fresh perspective to the field of building energy efficiency that will appeal to researchers and architects, as well as policymakers.

scholarly journals flEECe, an energy use and occupant behavior dataset for net-zero energy affordable senior residential buildings

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Frederick Paige ◽  
Philip Agee ◽  
Farrokh Jazizadeh
Keyword(s):  
Affordable Housing ◽  
Energy Use ◽  
Residential Buildings ◽  
Building Energy ◽  
Hot Water ◽  
Occupant Behavior ◽  
Zero Energy ◽  
Net Zero Energy ◽  
Net Zero ◽  
Building Energy Use

AbstractThe behaviors of building occupants have continued to perplex scholars for years in our attempts to develop models for energy efficient housing. Building simulations, project delivery approaches, policies, and more have fell short of their optimistic goals due to the complexity of human behavior. As a part of a multiphase longitudinal affordable housing study, this dataset represents energy and occupant behavior attributes for 6 affordable housing units over nine months in Virginia, USA which are not performing to the net-zero energy standard they were designed for. This dataset provides researchers the ability to analyze the following variables: energy performance, occupant behaviors, energy literacy, and ecological perceptions. Energy data is provided at a 1 Hz sampling rate for four circuits: main, hot water heater, dryer, and HVAC. Building specifications, occupancy, weather data, and neighboring building energy use data are provided to add depth to the dataset. This dataset can be used to update building energy use models, predictive maintenance, policy frameworks, construction risk models, economic models, and more.

Investigating the probability of designing net-zero energy buildings with consideration of electric vehicles and renewable energy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Seyed Sajad Rezaei Nasab ◽  
Abbasali Tayefi Nasrabadi ◽  
Somayeh Asadi ◽  
Seiyed Ali Haj Seiyed Taghia
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Building Energy ◽  
Energy Performance ◽  
Zero Energy ◽  
Content Type ◽  
Building Energy Performance ◽  
Net Zero Energy ◽  
Net Zero ◽  
Net Zero Energy Buildings

PurposeDue to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.Design/methodology/approachFirst, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.FindingsThe results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.Originality/valueConsidering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

scholarly journals Forecasting of Three Components of Solar irradiation for Building Applications

2019 ◽  
Vol 111 ◽  
pp. 05012
Author(s):  
Gilles Notton ◽  
Cyril Voyant ◽  
Alexis Fouilloy ◽  
Jean Laurent Duchaud ◽  
Marie Laure Nivet
Keyword(s):  
Random Forest ◽  
Weather Forecast ◽  
Building Energy ◽  
Solar Irradiation ◽  
Zero Energy ◽  
Building Model ◽  
Net Zero Energy ◽  
Net Zero ◽  
Net Zero Energy Buildings ◽  
Three Components

Solar energy and the concept of passive architecture and Net Zero Energy buildings are being increased. For an optimal management of the building energy, a Model Predictive Control is generally used but requires an accurate building model and weather forecast. For a more reliable modelling, the knowledge of the global solar irradiation is not sufficient; three methods, smart persistence, artificial neural network and random forest, are compared to forecast the three components of solar irradiation measured on the site with a high meteorological variability. Hourly solar irradiations are forecasted for time horizons from h+1 to h+6. The random forest method (RF) is the most efficient and the accuracy of forecasts are in term of nRMSE, from 19.65% for h+1 to 27.78% for h+6 for global horizontal irradiation, from 34.11% for h+1 to 49.08% for h+6 for beam normal irradiation, from 35.08% for h+1 to 49.14% for h+6 for diffuse horizontal irradiation. The improvement brought by the use of RF compared to the two other methods increases with the forecasting horizon. A seasonal study is realized and shows that the forecasting during spring and autumn is less reliable than during winter and summer due to a higher meteorological variability.

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