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.

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.

Common Characteristics of Zero Energy Buildings in Relation to the Energy Distribution Networks

2013 ◽  
Vol 855 ◽  
pp. 31-34
Author(s):  
Boris Bielek ◽  
Milan Bielek
Keyword(s):  
Energy Balance ◽  
Energy Distribution ◽  
Distribution Networks ◽  
Building Energy ◽  
Building Envelope ◽  
Zero Energy ◽  
Net Zero Energy ◽  
Net Zero ◽  
Net Zero Energy Buildings ◽  
Zero Energy Buildings

Physical quantification of the building envelope. Energy quantification of the building. Energy from fossil sources. Energy from ecologically clean renewable sources. Nearly net zero energy buildings. Net zero energy buildings. Net plus energy buildings. The characteristics of zero energy buildings in relation to the energy distribution networks. Requirements for physical quantification of buildings with a zero energy balance in relation to energy distribution networks.

Comparison of two strategies of reward-penalty mechanism for promoting net zero energy buildings

2021 ◽  
Vol 47 ◽  
pp. 101347
Author(s):  
Yuehong Lu ◽  
Zafar A. Khan ◽  
Hasan Gunduz ◽  
Changlong Wang ◽  
Muhammad Imran ◽  
...  
Keyword(s):  
Zero Energy ◽  
Net Zero Energy ◽  
Net Zero ◽  
Net Zero Energy Buildings ◽  
Zero Energy Buildings

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.

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