scholarly journals Investigating Thermal Performance of Residential Buildings in Marmari Region, South Evia, Greece

Challenges ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 5
Author(s):  
Alkistis E. Kanteraki ◽  
Grigorios L. Kyriakopoulos ◽  
Miltiadis Zamparas ◽  
Vasilis C. Kapsalis ◽  
Sofoklis S. Makridis ◽  
...  

In recent decades, the steady increase of energy consumption from building construction and operations cause atmospheric pollution and significant financial burden, mainly due to the high costs imposed from energy production. This study examines ways under which modern designs of a building can be applied on construction and domestication while following conventional methods of construction, compared to a building that has been constructed and domesticated under bioclimatic architecture. Particularly, two buildings were investigated in terms of the energy consumption incurred, being built on the same seaside area and period of construction and at adjacent plots of the same distance from sea for ease of comparison. The first building (A1) was constructed under the principles of bioclimatic architecture, being also facilitated with green and smart technologies. The second building (A2) was constructed under conventional construction techniques. The energy efficiency of both buildings was calculated by the “TEE KENAK” software, while specific parameters were recorded. Energy classifications of both buildings were valued and a proposed scenario and interventions unveiled the energy classification upgrading from A2 to A1. Our analysis revealed, as also found in the literature, that during thermal energy oscillating conditions, corresponding relative humidity stresses were observed, indicating that the vapor pressure handling should be taken into account towards comfort. The preliminary incremental cost evaluation and comparison of A1 and A2 energy upgrading under the criterion of simple payback period were critically discussed.

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Milad Ghanbari ◽  
Armin Monir Abbasi ◽  
Mehdi Ravanshadnia

Steady increase in overexploitation of stone quarries, generation of construction and demolition waste, and costs of preparing extra landfill space have become environmental and waste management challenges in metropolises. In this paper, aggregate production is studied in two scenarios: scenario 1 representing the production of natural aggregates (NA) and scenario 2 representing the production of recycled aggregates (RA). This study consists of two parts. In the first part, the objective is the environmental assessment (energy consumption and CO2 emission) and economic (cost) evaluation of these two scenarios, which is pursued by life-cycle assessment (LCA) method. In the second part, the results of the first part are used to estimate the optimal combination of production of NA and RA and thereby find an optimal solution (scenario) for a more eco-friendly aggregate production. The defined formulas and relationship are used to develop a model. The results of model validation show that the optimal ratio, in optimal scenario, is 50%. The results show that, compared to scenario 1, optimal scenario improves the energy consumption, CO2 emissions, and production cost by, respectively, 30%, 36%, and 31%, which demonstrate the effectiveness of this optimization.


Author(s):  
Junaidah Jailani ◽  
◽  
Norsyalifa Mohamad ◽  
Muhammad Amirul Omar ◽  
Hauashdh Ali ◽  
...  

According to the National Energy Balance report released by the Energy Commission of Malaysia in 2016, the residential sector uses 21.6% of the total energy in Malaysia. Residents waste energy through inefficient energy consumption and a lack of awareness. Building occupants are considered the main factor that influences energy consumption in buildings, and to change energy consumption on an overall scale, it is crucial to change individual behaviour. Therefore, this study focused on analysing the energy consumption pattern and the behaviour of consumers towards energy consumption in their homes in the residential area of Batu Pahat, Johor. A self-administrated questionnaire approach was employed in this study. The findings of this study showed that the excessive use of air conditioners was a significant factor in the increasing electricity bills of homeowners as well as the inefficient use of electrical appliances. Also, this study determined the effect of awareness on consumer behaviour. This study recommends ways to help minimise energy consumption in the residential area.


Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 405
Author(s):  
Anam Nawaz Khan ◽  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Do-Hyeun Kim

With the development of modern power systems (smart grid), energy consumption prediction becomes an essential aspect of resource planning and operations. In the last few decades, industrial and commercial buildings have thoroughly been investigated for consumption patterns. However, due to the unavailability of data, the residential buildings could not get much attention. During the last few years, many solutions have been devised for predicting electric consumption; however, it remains a challenging task due to the dynamic nature of residential consumption patterns. Therefore, a more robust solution is required to improve the model performance and achieve a better prediction accuracy. This paper presents an ensemble approach based on learning to a statistical model to predict the short-term energy consumption of a multifamily residential building. Our proposed approach utilizes Long Short-Term Memory (LSTM) and Kalman Filter (KF) to build an ensemble prediction model to predict short term energy demands of multifamily residential buildings. The proposed approach uses real energy data acquired from the multifamily residential building, South Korea. Different statistical measures are used, such as mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and R2 score, to evaluate the performance of the proposed approach and compare it with existing models. The experimental results reveal that the proposed approach predicts accurately and outperforms the existing models. Furthermore, a comparative analysis is performed to evaluate and compare the proposed model with conventional machine learning models. The experimental results show the effectiveness and significance of the proposed approach compared to existing energy prediction models. The proposed approach will support energy management to effectively plan and manage the energy supply and demands of multifamily residential buildings.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.


2021 ◽  
Vol 13 (15) ◽  
pp. 8595
Author(s):  
Lindita Bande ◽  
Abeer Alshamsi ◽  
Anoud Alhefeiti ◽  
Sarah Alderei ◽  
Sebah Shaban ◽  
...  

The city of Al Ain (Abu Dhabi, UAE) has a mainly low rise residential buildings. Villas as part of a compound or separate units represent the majority of the residential areas in the city. Due to the harsh hot arid climate of Al Ain, the energy demand for the cooling load is quite high. Therefore, it is relevant finding new retrofit strategies that are efficient in reducing the cooling load of the villas. The aim of this study is to analyze one particular strategy (parametric shading structure) in terms of design, construction, cost, energy impact on the selected villa. The main data for this study is taken from the local sources. There are six steps followed in this analysis: case study analysis; climate analysis; parametric structure and PV panels; building energy consumption and outdoor thermal comfort; modelling, simulation, and validation; materials, construction, and cost evaluation. The model of the villa was validated for the full year 2020 based on the electricity bills obtained. After adding the parametric design structure, the reduction after shading is approximately 10%. Meanwhile the UTCI (Universal Thermal Climate Index) dropped from extreme heat stress to strong heat stress (average for the month of March and September). These findings are promising in the retrofit industry due to the advanced calculations used to optimize the parametric design structure.


2020 ◽  
Vol 12 (24) ◽  
pp. 10344
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Mohammed Itma

This paper targets the future energy sustainability and aims to estimate the potential energy production from installing photovoltaic (PV) systems on the rooftop of apartment’s residential buildings, which represent the largest building sector. Analysis of the residential building typologies was carried out to select the most used residential building types in terms of building roof area, number of floors, and the number of apartments on each floor. A computer simulation tool has been used to calculate the electricity production for each building type, for three different tilt angles to estimate the electricity production. Tilt angle, spacing between the arrays, the building shape, shading from PV arrays, and other roof elements were analyzed for optimum and maximum electricity production. The electricity production for each household has been compared to typical household electricity consumption and its future consumption in 2030. The results show that installing PV systems on residential buildings can speed the transition to renewable energy and energy sustainability. The electricity production for building types with 2–4 residential units can surplus their estimated future consumption. Building types with 4–8 residential units can produce their electricity consumption in 2030. Building types of 12–24 residential units can produce more than half of their 2030 future consumption.


2021 ◽  
pp. 1420326X2110130
Author(s):  
Manta Marcelinus Dakyen ◽  
Mustafa Dagbasi ◽  
Murat Özdenefe

Ambitious energy efficiency goals constitute an important roadmap towards attaining a low-carbon society. Thus, various building-related stakeholders have introduced regulations targeting the energy efficiency of buildings. However, some countries still lack such policies. This paper is an effort to help bridge this gap for Northern Cyprus, a country devoid of building energy regulations that still experiences electrical energy production and distribution challenges, principally by establishing reference residential buildings which can be the cornerstone for prospective building regulations. Statistical analysis of available building stock data was performed to determine existing residential reference buildings. Five residential reference buildings with distinct configurations that constituted over 75% floor area share of the sampled data emerged, with floor areas varying from 191 to 1006 m2. EnergyPlus models were developed and calibrated for five residential reference buildings against yearly measured electricity consumption. Values of Mean Bias Error (MBE) and Cumulative Variation of Root Mean Squared Error CV(RMSE) between the models’ energy consumption and real energy consumption on monthly based analysis varied within the following ranges: (MBE)monthly from –0.12% to 2.01% and CV(RMSE)monthly from 1.35% to 2.96%. Thermal energy required to maintain the models' setpoint temperatures for cooling and heating varied from 6,134 to 11,451 kWh/year.


Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2538
Author(s):  
Praveen K. Cheekatamarla

Electrical and thermal loads of residential buildings present a unique opportunity for onsite power generation, and concomitant thermal energy generation, storage, and utilization, to decrease primary energy consumption and carbon dioxide intensity. This approach also improves resiliency and ability to address peak load burden effectively. Demand response programs and grid-interactive buildings are also essential to meet the energy needs of the 21st century while addressing climate impact. Given the significance of the scale of building energy consumption, this study investigates how cogeneration systems influence the primary energy consumption and carbon footprint in residential buildings. The impact of onsite power generation capacity, its electrical and thermal efficiency, and its cost, on total primary energy consumption, equivalent carbon dioxide emissions, operating expenditure, and, most importantly, thermal and electrical energy balance, is presented. The conditions at which a cogeneration approach loses its advantage as an energy efficient residential resource are identified as a function of electrical grid’s carbon footprint and primary energy efficiency. Compared to a heat pump heating system with a coefficient of performance (COP) of three, a 0.5 kW cogeneration system with 40% electrical efficiency is shown to lose its environmental benefit if the electrical grid’s carbon dioxide intensity falls below 0.4 kg CO2 per kWh electricity.


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