scholarly journals Variant Developments of Typical Meteorological Years (TMYs) for Seeb, Oman and their Impact on Energy Simulation of Residential Buildings

2018 ◽  
Vol 15 (2) ◽  
pp. 29 ◽  
Author(s):  
Nasser Al-Azri ◽  
Saleh Al-Saadi

Typical meteorological years (TMYs) are widely used for the analysis and simulation of energy-intensive systems. The reliability of a developed typical year depends on the accuracy of the historical record of weather data as well as the fitness of the developed approach to the application. In this work, a TMY for Seeb area in the Muscat Governorate, Oman was developed using different approaches. The developed TMYs are compared to the current commonly used TMY which is based on 1985-2001 records that have many gaps and anomalies and hence have intensive interpolation treatment. The different TMYs were compared by simulating energy consumption of a typical residential building and also by studying applicability of passive cooling strategies. The findings showed that the variation in energy consumption is minimal for the different TMY development approaches for the same set of historical records but the difference is very significant when the comparison is based on the two sets from the two periods of records.

2018 ◽  
Vol 15 (2) ◽  
pp. 129
Author(s):  
Nasser Al-Azri ◽  
Saleh Al-Saadi

Typical meteorological years (TMYs) are widely used for the analysis and simulation of energy-intensive systems. The reliability of a developed typical year depends on the accuracy of the historical record of weather data as well as the fitness of the developed approach to the application. In this work, a TMY for Seeb area in the Muscat Governorate, Oman was developed using different approaches. The developed TMYs are compared to the current commonly used TMY which is based on 1985-2001 records that have many gaps and anomalies and hence have intensive interpolation treatment. The different TMYs were compared by simulating energy consumption of a typical residential building and also by studying applicability of passive cooling strategies. The findings showed that the variation in energy consumption is minimal for the different TMY development approaches for the same set of historical records but the difference is very significant when the comparison is based on the two sets from the two periods of records.


2020 ◽  
Vol 15 (4) ◽  
pp. 555-564
Author(s):  
Laila Amer Hashem Al-Qahtani ◽  
Lamis Saad Eldeen Elgizawi

Abstract Around the world, most energy is consumed by buildings; residential buildings consume 40% of energy globally. In the Kingdom of Saudi Arabia (KSA), buildings consume 50% of all energy, and 70% of the buildings in the KSA are not insulated well. Creating an envelope is a key to decreasing energy consumption and providing thermal comfort and healthy internal spaces. Thus, the main aim of this study is to test the effect of selected passive cooling strategies by using a simulation program to evaluate a variety of envelope (floor, external and internal walls and roofs) thermal characteristic proposals to create an eco-interior space, to provide the most comfortable conditions for users and to save energy in buildings in hot climates in Riyadh, Saudi Arabia. One residential building case was selected, and some of the passive cooling strategies were tested. Simulation software—Design Builder—was used to calculate the total energy consumption in 1 year and compare the results before and after applying these strategies to the selected residential building.


Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4115 ◽  
Author(s):  
Vincenzo Costanzo ◽  
Gianpiero Evola ◽  
Marco Infantone ◽  
Luigi Marletta

Building energy simulations are normally run through Typical Weather Years (TWYs) that reflect the average trend of local long-term weather data. This paper presents a research aimed at generating updated typical weather files for the city of Catania (Italy), based on 18 years of records (2002–2019) from a local weather station. The paper reports on the statistical analysis of the main recorded variables, and discusses the difference with the data included in a weather file currently available for the same location based on measurements taken before the 1970s but still used in dynamic energy simulation tools. The discussion also includes a further weather file, made available by the Italian Thermotechnical Committee (CTI) in 2015 and built upon the data registered by the same weather station but covering a much shorter period. Three new TWYs are then developed starting from the recent data, according to well-established procedures reported by ASHRAE and ISO standards. The paper discusses the influence of the updated TWYs on the results of building energy simulations for a typical residential building, showing that the cooling and heating demand can differ by 50% or even 65% from the simulations based on the outdated weather file.


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 (8) ◽  
pp. 4099
Author(s):  
Ann-Kristin Mühlbach ◽  
Olaf Mumm ◽  
Ryan Zeringue ◽  
Oskars Redbergs ◽  
Elisabeth Endres ◽  
...  

The METAPOLIS as the polycentric network of urban–rural settlement is undergoing constant transformation and urbanization processes. In particular, the associated imbalance of the shrinkage and growth of different settlement types in relative geographical proximity causes negative effects, such as urban sprawl and the divergence of urban–rural lifestyles with their related resource, land and energy consumption. Implicitly related to these developments, national and global sustainable development goals for the building sector lead to the question of how a region can be assessed without detailed research and surveys to identify critical areas with high potential for sustainable development. In this study, the TOPOI method is used. It classifies settlement units and their interconnections along the urban–rural gradient, in order to quantify and assess the land-uptake and global warming potential driven by residential developments. Applying standard planning parameters in combination with key data from a comprehensive life cycle assessment of the residential building stock, a detailed understanding of different settlement types and their associated resource and energy consumption is achieved.


Author(s):  
Jerzy Sowa ◽  
Maciej Mijakowski

A humidity-sensitive demand-controlled ventilation system is known for many years. It has been developed and commonly applied in regions with an oceanic climate. Some attempts were made to introduce this solution in Poland in a much severe continental climate. The article evaluates this system's performance and energy consumption applied in an 8-floor multi-unit residential building, virtual reference building described by the National Energy Conservation Agency NAPE, Poland. The simulations using the computer program CONTAM were performed for the whole hating season for Warsaw's climate. Besides passive stack ventilation that worked as a reference, two versions of humidity-sensitive demand-controlled ventilation were checked. The difference between them lies in applying the additional roof fans that convert the system to hybrid. The study confirmed that the application of demand-controlled ventilation in multi-unit residential buildings in a continental climate with warm summer (Dfb) leads to significant energy savings. However, the efforts to ensure acceptable indoor air quality require hybrid ventilation, which reduces the energy benefits. It is especially visible when primary energy use is analyzed.


Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 237 ◽  
Author(s):  
S. Soutullo ◽  
E. Giancola ◽  
M. J. Jiménez ◽  
J. A. Ferrer ◽  
M. N. Sánchez

Based on the European energy directives, the building sector has to provide comfortable levels for occupants with minimum energy consumption as well as to reduce greenhouse gas emissions. This paper aims to compare the impact of climate change on the energy performance of residential buildings in order to derive potential design strategies. Different climate file inputs of Madrid have been used to quantify comparatively the thermal needs of two reference residential buildings located in this city. One of them represents buildings older than 40 years built according to the applicable Spanish regulations prior to 1979. The other refers to buildings erected in the last decade under more energy-restrictive constructive regulations. Three different climate databases of Madrid have been used to assess the impact of the evolution of the climate in recent years on the thermal demands of these two reference buildings. Two of them are typical meteorological years (TMY) derived from weather data measured before 2000. On the contrary, the third one is an experimental file representing the average values of the meteorological variables registered in Madrid during the last decade. Annual and monthly comparisons are done between the three climate databases assessing the climate changes. Compared to the TMYs databases, the experimental one records an average air temperature of 1.8 °C higher and an average value of relative humidity that is 9% lower.


Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3038 ◽  
Author(s):  
José Sánchez Ramos ◽  
MCarmen Guerrero Delgado ◽  
Servando Álvarez Domínguez ◽  
José Luis Molina Félix ◽  
Francisco José Sánchez de la Flor ◽  
...  

The reduction of energy consumption in the residential sector presents substantial potential through the implementation of energy efficiency improvement measures. Current trends involve the use of simulation tools which obtain the buildings’ energy performance to support the development of possible solutions to help reduce energy consumption. However, simulation tools demand considerable amounts of data regarding the buildings’ geometry, construction, and frequency of use. Additionally, the measured values tend to be different from the estimated values obtained with the use of energy simulation programs, an issue known as the ‘performance gap’. The proposed methodology provides a solution for both of the aforementioned problems, since the amount of data needed is considerably reduced and the results are calibrated using measured values. This new approach allows to find an optimal retrofitting project by life cycle energy assessment, in terms of cost and energy savings, for individual buildings as well as several blocks of buildings. Furthermore, the potential for implementation of the methodology is proven by obtaining a comprehensive energy rehabilitation plan for a residential building. The developed methodology provides highly accurate estimates of energy savings, directly linked to the buildings’ real energy needs, reducing the difference between the consumption measured and the predictions.


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