A Study on the Implementation of Economic Zero Energy Building according to Korea’s Renewable Energy Support Policies and Energy Consumption Patterns

Author(s):  
Cheol-Ho Shin ◽  
SekJin Lee ◽  
JaeYoung Kim ◽  
Hong-soon Nam ◽  
Youn Kwae Jeong
Author(s):  
Mostafa Esmaeili Shayan

The Net Zero Energy Building is generally described as an extremely energy-efficient building in which the residual electricity demand is provided by renewable energy. Solar power is also regarded to be the most readily available and usable form of renewable electricity produced at the building site. In contrast, energy conservation is viewed as an influential national for achieving a building’s net zero energy status. This chapter aims to show the value of the synergy between energy conservation and solar energy transfer to NZEBs at the global and regional levels. To achieve these goals, both energy demand building and the potential supply of solar energy in buildings have been forecasted in various regions, climatic conditions, and types of buildings. Building energy consumption was evaluated based on a bottom-up energy model developed by 3CSEP and data inputs from the Bottom-Up Energy Analysis System (BUENAS) model under two scenarios of differing degrees of energy efficiency intention. The study results indicate that the acquisition of sustainable energy consumption is critical for solar-powered net zero energy buildings in various building styles and environments. The chapter calls for the value of government measures that incorporate energy conservation and renewable energy.


2021 ◽  
Vol 25 (1) ◽  
pp. 990-1002
Author(s):  
Danyal Shuja ◽  
Syed Shujaa Safdar Gardezi ◽  
Muhammad Rashid Idrees

Abstract Energy crises has been a serious concern for economies especially for developing ones. The building stocks developed through conventional methods pose serious barriers towards sustainable energy consumption patterns. The transformation of such existing facilities into Net Zero Energy Buildings (NZEB) can offer a valuable opportunity to manage the challenging energy loads. However, cost aspect of such transformations remains the key and explored in current study to assess a breakeven point with the energy conservations. Four commercial buildings, three and four story, were selected as case studies. 3D digital models were developed for energy analysis through cloud computing. Comparative analysis for energy consumption patterns was performed in four phases. For conventional approach, the annual consumptions ranged from 310 kWh/m2/yr to 563 kWh/m2/yr. Based upon the local conditions, roof insulation and PV were adopted as NZEB parameters. This resulted a maximum energy saving of 6 %. The corresponding cost analysis observed an addition expense of almost 11 % for such incorporation with an average payback period of 4.5 years.


Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3252 ◽  
Author(s):  
Xiaolong Xu ◽  
Guohui Feng ◽  
Dandan Chi ◽  
Ming Liu ◽  
Baoyue Dou

Optimizing key parameters with energy consumption as the control target can minimize the heating and cooling needs of buildings. In this paper we focus on the optimization of performance parameters design and the prediction of energy consumption for nearly Zero Energy Buildings (nZEB). The optimal combination of various performance parameters and the Energy Saving Ratio (ESR)are studied by using a large volume of simulation data. Artificial neural networks (ANNs) are applied for the prediction of annual electrical energy consumption in a nearly Zero Energy Building designs located in Shenyang (China). The data of the energy demand for our test is obtained by using building simulation techniques. The results demonstrate that the heating energy demand for our test nearly Zero Energy Building is 17.42 KW·h/(m2·a). The Energy Saving Ratio of window-to-wall ratios optimization is the most obvious, followed by thermal performance parameters of the window, and finally the insulation thickness. The maximum relative error of building energy consumption prediction is 6.46% when using the artificial neural network model to predict energy consumption. The establishment of this prediction method enables architects to easily and accurately obtain the energy consumption of buildings during the design phase.


Author(s):  
Aristeidis Karananos ◽  
Asimina Dimara ◽  
Konstantinos Arvanitis ◽  
Christos Timplalexis ◽  
Stelios Krinidis ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7591
Author(s):  
Wojciech Cieslik ◽  
Filip Szwajca ◽  
Jedrzej Zawartowski ◽  
Katarzyna Pietrzak ◽  
Slawomir Rosolski ◽  
...  

The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluating the energy consumption of a modern public building–electric vehicle system within a specific location. The original methodology developed includes surveys that demonstrate the required mobility range to be provided to occupants of the building under consideration. In the next step, an energy balance was performed for a novel near-zero energy building equipped with a 199.8 kWp photovoltaic installation, the energy from which can be used to charge an electric vehicle. The analysis considered the variation in vehicle energy consumption by season (winter/summer), the actual charging profile of the vehicle, and the parking periods required to achieve the target range for the user.


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