A Zero-Energy Consumption Scheme for System Suspend to Limited NVM

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.

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Data on energy consumption and Nearly zero energy buildings (NZEBs) in Europe

Data in Brief ◽

10.1016/j.dib.2018.11.094 ◽

2018 ◽

Vol 21 ◽

pp. 2470-2474 ◽

Cited By ~ 7

Author(s):

Delia D'Agostino ◽

Livio Mazzarella

Keyword(s):

Energy Consumption ◽

Zero Energy ◽

Zero Energy Buildings

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

2018 International Conference on Information and Communication Technology Convergence (ICTC) ◽

10.1109/ictc.2018.8539571 ◽

2018 ◽

Cited By ~ 1

Author(s):

Cheol-Ho Shin ◽

SekJin Lee ◽

JaeYoung Kim ◽

Hong-soon Nam ◽

Youn Kwae Jeong

Keyword(s):

Renewable Energy ◽

Energy Consumption ◽

Consumption Patterns ◽

Zero Energy ◽

Zero Energy Building ◽

Energy Consumption Patterns

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Building Rehabilitation through nearly Zero Energy Consumption: A Case Study

American Journal of Civil Engineering and Architecture ◽

10.12691/ajcea-9-5-1 ◽

2021 ◽

Vol 9 (5) ◽

pp. 171-180

Author(s):

José Coimbra

Keyword(s):

Energy Consumption ◽

Zero Energy

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Capabilities of Nearly Zero Energy Building (nZEB) Electricity Generation to Charge Electric Vehicle (EV) Operating in Real Driving Conditions (RDC)

Energies ◽

10.3390/en14227591 ◽

2021 ◽

Vol 14 (22) ◽

pp. 7591

Author(s):

Wojciech Cieslik ◽

Filip Szwajca ◽

Jedrzej Zawartowski ◽

Katarzyna Pietrzak ◽

Slawomir Rosolski ◽

...

Keyword(s):

Energy Consumption ◽

Electric Vehicle ◽

Electric Vehicles ◽

Renewable Energy Sources ◽

Energy Transition ◽

Target Range ◽

Zero Energy ◽

Zero Energy Building ◽

Driving Conditions ◽

Almost All

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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