Efficient design of residential buildings geometry to optimize photovoltaic energy generation and energy demand in a warm Mediterranean climate

The buildings sector is one of the least sustainable activities in the world, accounting for around 40% of the total global energy demand. With the aim to reduce the environmental impact of this sector, the use of renewable energy sources coupled with energy storage systems in buildings has been investigated in recent years. Innovative solutions for cooling, heating, and domestic hot water in buildings can contribute to the buildings’ decarbonization by achieving a reduction of building electrical consumption needed to keep comfortable conditions. However, the environmental impact of a new system is not only related to its electrical consumption from the grid, but also to the environmental load produced in the manufacturing and disposal stages of system components. This study investigates the environmental impact of an innovative system proposed for residential buildings in Mediterranean climate through a life cycle assessment. The results show that, due to the complexity of the system, the manufacturing and disposal stages have a high environmental impact, which is not compensated by the reduction of the impact during the operational stage. A parametric study was also performed to investigate the effect of the design of the storage system on the overall system impact.

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Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate

Applied Sciences ◽

10.3390/app11093972 ◽

2021 ◽

Vol 11 (9) ◽

pp. 3972

Author(s):

Azin Velashjerdi Farahani ◽

Juha Jokisalo ◽

Natalia Korhonen ◽

Kirsti Jylhä ◽

Kimmo Ruosteenoja ◽

...

Keyword(s):

Climate Change ◽

Energy Demand ◽

Energy Use ◽

Residential Buildings ◽

Weather Conditions ◽

Extreme Weather ◽

Living Room ◽

Extra Energy ◽

Cooling Unit ◽

Indoor Conditions

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.

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Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽

10.3390/en14154649 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4649

Author(s):

İsmail Hakkı ÇAVDAR ◽

Vahit FERYAD

Keyword(s):

Smart Grids ◽

Energy Demand ◽

Optimization Technique ◽

Cost Effective ◽

Optimization Method ◽

Long Term Memory ◽

Successful Implementation ◽

Efficient Design ◽

Energy Disaggregation ◽

Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

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Saving energy in residential buildings: the role of energy pricing

Climatic Change ◽

10.1007/s10584-021-03164-3 ◽

2021 ◽

Vol 167 (1-2) ◽

Author(s):

Jens Ewald ◽

Thomas Sterner ◽

Eoin Ó Broin ◽

Érika Mata

Keyword(s):

Energy Demand ◽

Income Elasticity ◽

Residential Buildings ◽

Policy Framework ◽

Energy Prices ◽

Residential Energy ◽

Residential Energy Demand ◽

Long Run ◽

Zero Carbon

AbstractA zero-carbon society requires dramatic change everywhere including in buildings, a large and politically sensitive sector. Technical possibilities exist but implementation is slow. Policies include many hard-to-evaluate regulations and may suffer from rebound mechanisms. We use dynamic econometric analysis of European macro data for the period 1990–2018 to systematically examine the importance of changes in energy prices and income on residential energy demand. We find a long-run price elasticity of −0.5. The total long-run income elasticity is around 0.9, but if we control for the increase in income that goes towards larger homes and other factors, the income elasticity is 0.2. These findings have practical implications for climate policy and the EU buildings and energy policy framework.

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Heating and Cooling Degree-Days Climate Change Projections for Portugal

Atmosphere ◽

10.3390/atmos12060715 ◽

2021 ◽

Vol 12 (6) ◽

pp. 715

Author(s):

Cristina Andrade ◽

Sandra Mourato ◽

João Ramos

Keyword(s):

Climate Change ◽

High Resolution ◽

Thermal Comfort ◽

Energy Demand ◽

Residential Buildings ◽

Degree Days ◽

Climate Change Projections ◽

Heating And Cooling ◽

Cooling Degree Days ◽

Heating Energy Demand

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating (HDD) and cooling (CDD) degree-days along with HDD + CDD were computed from an ensemble of seven high-resolution bias-corrected simulations attained from EURO-CORDEX under two Representative Concentration Pathways (RCP4.5 and RCP8.5). These three indicators were analyzed for 1971–2000 (from E-OBS) and 2011–2040, and 2041–2070, under both RCPs. Results predict a decrease in HDDs most significant under RCP8.5. Conversely, it is projected an increase of CDD values for both scenarios. The decrease in HDDs is projected to be higher than the increase in CDDs hinting to an increase in the energy demand to cool internal environments in Portugal. Statistically significant linear CDD trends were only found for 2041–2070 under RCP4.5. Towards 2070, higher(lower) CDD (HDD and HDD + CDD) anomaly amplitudes are depicted, mainly under RCP8.5. Within the five NUTS II

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Optimization of Costs and Self-Sufficiency for Roof Integrated Photovoltaic Technologies on Residential Buildings

Energies ◽

10.3390/en14134018 ◽

2021 ◽

Vol 14 (13) ◽

pp. 4018

Author(s):

Guglielmina Mutani ◽

Valeria Todeschi

Keyword(s):

Solar Energy ◽

Energy Security ◽

Energy Demand ◽

Residential Buildings ◽

Maximum Level ◽

Economic Incentives ◽

Economic Benefits ◽

The South ◽

Self Sufficiency ◽

Photovoltaic Technologies

It is common practice, in the production of photovoltaic energy to only use the south-exposed roof surface of a building, in order to achieve the maximum production of solar energy while lowering the costs of the energy and the solar technologies. However, using the south-exposed surface of a roof only allows a small quota of the energy demand to be covered. Roof surfaces oriented in other directions could also be used to better cover the energy load profile. The aim of this work is to investigate the benefits, in terms of costs, self-sufficiency and self-consumption, of roof integrated photovoltaic technologies on residential buildings with different orientations. A cost-optimal analysis has been carried out taking into account the economic incentives for a collective self-consumer configuration. It has emerged, from this analysis, that the better the orientation is, the higher the energy security and the lower the energy costs and those for the installation of photovoltaic technologies. In general, the use of south-facing and north-facing roof surfaces for solar energy production has both economic and energy benefits. The self-sufficiency index can on average be increased by 8.5% through the use of photovoltaic installations in two directions on gable roofs, and the maximum level that can be achieved was on average 41.8, 41.5 and 35.7% for small, medium and large condominiums, respectively. Therefore, it could be convenient to exploit all the potential orientations of photovoltaic panels in cities to improve energy security and to provide significant economic benefits for the residential users.

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