scholarly journals Towards Efficient Building Designing: Heating and Cooling Load Prediction via Multi-Output Model

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6419
Author(s):  
Muhammad Sajjad ◽  
Samee Ullah Khan ◽  
Noman Khan ◽  
Ijaz Ul Haq ◽  
Amin Ullah ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Residential Buildings ◽  
Cooling Load ◽  
Load Prediction ◽  
Unified Framework ◽  
Single Output ◽  
Heating And Cooling ◽  
Low Performance ◽  
High Level

In the current technological era, energy-efficient buildings have a significant research body due to increasing concerns about energy consumption and its environmental impact. Designing an appropriate energy-efficient building depends on its layout, such as relative compactness, overall area, height, orientation, and distribution of the glazing area. These factors directly influence the cooling load (CL) and heating load (HL) of residential buildings. An accurate prediction of these load facilitates a better management of energy consumption and enhances the living standards of inhabitants. Most of the traditional machine learning (ML)-based approaches are designed for single-output (SO) prediction, which is a tedious task due to separate training processes for each output with low performance. In addition, these approaches have a high level of nonlinearity between input and output, which need more enhancement in terms of robustness, predictability, and generalization. To tackle these issues, we propose a novel framework based on gated recurrent unit (GRU) that reliably predicts the CL and HL concurrently. To the best of our knowledge, we are the first to propose a multi-output (MO) sequential learning model followed by utility preprocessing under the umbrella of a unified framework. A comprehensive set of ablation studies on ML and deep learning (DL) techniques is done over an energy efficiency dataset, where the proposed model reveals an incredible performance as compared to other existing models.

Prediction and Analysis of Building Energy Efficiency Using Artificial Neural Network and Design of Experiments

2016 ◽  
Vol 819 ◽  
pp. 541-545 ◽  
Author(s):  
Sholahudin ◽  
Azimil Gani Alam ◽  
Chang In Baek ◽  
Hwataik Han
Keyword(s):  
Neural Network ◽  
Energy Efficient ◽  
Residential Buildings ◽  
Building Energy ◽  
Cooling Load ◽  
Simulation Data ◽  
Heating And Cooling ◽  
Heating Load ◽  
Input Variables ◽  
Cooling Loads

Energy consumption of buildings is increasing steadily and occupying approximately 30-40% of total energy use. It is important to predict heating and cooling loads of a building in the initial stage of design to find out optimal solutions among various design options, as well as in the operating stage after the building has been completed for energy efficient operation. In this paper, an artificial neural network model has been developed to predict heating and cooling loads of a building based on simulation data for building energy performance. The input variables include relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution of a building, and the output variables include heating load (HL) and cooling load (CL) of the building. The simulation data used for training are the data published in the literature for various 768 residential buildings. ANNs have a merit in estimating output values for given input values satisfactorily, but it has a limitation in acquiring the effects of input variables individually. In order to analyze the effects of the variables, we used a method for design of experiment and conducted ANOVA analysis. The sensitivities of individual variables have been investigated and the most energy efficient solution has been estimated under given conditions. Discussions are included in the paper regarding the variables affecting heating load and cooling load significantly and the effects on heating and cooling loads of residential buildings.

scholarly journals Performance Evaluation of Two Machine Learning Techniques in Heating and Cooling Loads Forecasting of Residential Buildings

2020 ◽  
Vol 10 (11) ◽  
pp. 3829 ◽  
Author(s):  
Arash Moradzadeh ◽  
Amin Mansour-Saatloo ◽  
Behnam Mohammadi-Ivatloo ◽  
Amjad Anvari-Moghaddam
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Residential Buildings ◽  
Load Forecasting ◽  
Training Data ◽  
Support Vector ◽  
Cooling Load ◽  
Heating And Cooling ◽  
Cooling Loads ◽  
Heating And Cooling Load

Nowadays, since energy management of buildings contributes to the operation cost, many efforts are made to optimize the energy consumption of buildings. In addition, the most consumed energy in the buildings is assigned to the indoor heating and cooling comforts. In this regard, this paper proposes a heating and cooling load forecasting methodology, which by taking this methodology into the account energy consumption of the buildings can be optimized. Multilayer perceptron (MLP) and support vector regression (SVR) for the heating and cooling load forecasting of residential buildings are employed. MLP and SVR are the applications of artificial neural networks and machine learning, respectively. These methods commonly are used for modeling and regression and produce a linear mapping between input and output variables. Proposed methods are taught using training data pertaining to the characteristics of each sample in the dataset. To apply the proposed methods, a simulated dataset will be used, in which the technical parameters of the building are used as input variables and heating and cooling loads are selected as output variables for each network. Finally, the simulation and numerical results illustrates the effectiveness of the proposed methodologies.

scholarly journals Modeling and Simulation Performance Evaluation of a Proposed Calorimeter for Testing a Heat Pump System

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4589 ◽  
Author(s):  
Amoabeng ◽  
Lee ◽  
Choi
Keyword(s):  
Energy Consumption ◽  
Modeling And Simulation ◽  
Heat Pump ◽  
Energy Efficient ◽  
Residential Buildings ◽  
Test Chamber ◽  
High Energy ◽  
Heat Pumps ◽  
Pump System ◽  
Heating And Cooling

The energy consumption for heating and cooling in the building sector accounts for more than one-third of total energy used worldwide. In view of that, it is important to develop energy efficient cooling and heating systems in order to conserve energy in buildings as well as reduce greenhouse gas emissions. In both commercial and residential buildings, the heat pump has been adopted as an energy efficient technology for space heating and cooling purposes as compared to conventional air conditioning systems. However, heat pumps undergo standard testing, rating, and certification procedures to ascertain their system performance. Essentially, the calorimeter for testing heat pumps has two test chambers to serve as a heat source and heat sink to control and maintain the test conditions required to simulate the heat pump indoor and outdoor units, simultaneously. In air-to-air heat pump units, the conventional calorimeter controls the air temperature and humidity conditions in each test chamber with separate air handling units consisting of a refrigerator, heater, humidifier, and supply fan, which results in high energy consumption. In this study, using dynamic modeling and simulation, a new calorimeter for controlling air conditions in each test chamber is proposed. The performance analysis based on simulation results showed that the newly proposed calorimeter predicted at least 43% energy savings with the use of a heat recovery unit and small refrigerator capacity as compared to the conventional calorimeter that utilized a large refrigerator capacity for all the weather conditions and load capacities that we investigated.

scholarly journals ANALYSIS OF ENERGY-EFFICIENT HOUSE LAYOUT DESIGN IN TROPICAL CLIMATE

2021 ◽  
Vol 47 (1) ◽  
pp. 11-18
Author(s):  
Aisyah Zakiah
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Residential Buildings ◽  
Weather Data ◽  
Cooling Load ◽  
City Development ◽  
Total Energy Consumption ◽  
Wall Area ◽  
Consumption Energy ◽  
Cooling Loads

Energy-efficient residential provision is an essential concern for the present and future city development. Currently, the residential buildings contribute approximately 37.5% to significant energy consumption and carbon emissions, which mainly used for cooling. This research aims to study the house layout arrangement to minimise cooling loads and further reduce energy consumption. Energy efficiency analysis is performed by comparing the cooling load and total energy consumption from variations of the hypothetical design of detached or semi-detached housing layouts commonly built in Indonesia. The calculation of cooling loads and energy consumption is performed by simulation in Energy Plus 8.4 with Jakarta weather data. The results show that the arrangement of the house layout may reduce the cooling load up to 24%. The total conditioned wall area that varies due to the variations of house layouts are found to affect the cooling loads.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

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.

The Effects of Window Film on the Performance of Window System

2014 ◽  
Vol 525 ◽  
pp. 408-411
Author(s):  
Min Seon Jang ◽  
Gyeong Seok Choi ◽  
Jae Sik Kang ◽  
Yumin Kim
Keyword(s):  
Energy Consumption ◽  
Cooling Load ◽  
Indoor Temperature ◽  
Heating And Cooling ◽  
Window System ◽  
Window Systems ◽  
Clear Glass ◽  
Window Film ◽  
And Performance ◽  
Heating And Cooling Load

Window film is generally attached the glazing in buildings to improve the thermal performance of the window system by addressing a range of problems such as indoor temperature rise, indoor temperature imbalance, degraded heating and cooling load due to excessive influx of solar radiation. To evaluate the performance of window films, window films are attached to 3mm or 6mm clear glass. However, window films are generally used on existing window systems for reducing the annual energy consumption. Therefore it is necessary to evaluate the performance of window films depending on the performance of glazing such as clear double glazing or low-e double glazing. Thus the purpose of this study is to analyze the performance of window systems when window film is attached. As a result, in the case of applying window films for reducing the SHGC of buildings, it is necessary to select window films suitable for the configuration and performance of the glazing to be installed, considering the SHGC of the entire glazing system.

scholarly journals ENERGY EFFICIENCY IN RESIDENTIAL BUILDINGS, LESS STRAIGHT FORWARD THEN PRESUMED

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Hugo Hens
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Energy Use ◽  
Low Voltage ◽  
Residential Buildings ◽  
Primary Energy ◽  
Heating And Cooling ◽  
Net Zero ◽  
Energy Conserving ◽  
New Construction

Since the 1990s, the successive EU directives and related national or regional legislations require new construction and retrofits to be as much as possible energy-efficient. Several measures that should stepwise minimize the primary energy use for heating and cooling have become mandated as requirement. However, in reality, related predicted savings are not seen in practice. Two effects are responsible for that. The first one refers to dweller habits, which are more energy-conserving than the calculation tools presume. In fact, while in non-energy-efficient ones, habits on average result in up to a 50% lower end energy use for heating than predicted. That percentage drops to zero or it even turns negative in extremely energy-efficient residences. The second effect refers to problems with low-voltage distribution grids not designed to transport the peaks in electricity whensunny in summer. Through that, a part of converters has to be uncoupled now and then, which means less renewable electricity. This is illustrated by examples that in theory should be net-zero buildings due to the measures applied and the presence of enough photovoltaic cells (PV) on each roof. We can conclude that mandating extreme energy efficiency far beyond the present total optimum value for residential buildings looks questionable as a policy. However, despite that, governments and administrations still seem to require even more extreme measurements regarding energy efficiency.

Improving sustainability of residential homes: occupants motivation and behaviour

2014 ◽  
Vol 8 (4) ◽  
pp. 477-491 ◽  
Author(s):  
Patrick X.W. Zou ◽  
Rebecca J. Yang
Keyword(s):  
Energy Efficient ◽  
Online Survey ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Content Type ◽  
South Wales ◽  
Improvement Measures ◽  
Research Findings ◽  
High Level

Purpose – This paper aims to investigate residential occupants’ motivations and behaviour on energy savings. Energy consumption in residential buildings is a major contributor to greenhouse gas emissions. Design/methodology/approach – By using an online survey questionnaire instrument, this research collected 504 sets of responses from households in the state of New South Wales, Australia. Findings – Through statistical analysis of the data collected, this research found that construction cost and government incentive were considered as the major influencing factors on achieving energy-efficient residential building development, and the lower bills resulted from the reduced energy and water consumption were considered as the most important benefits. The research also found that many households exhibited a high level of awareness and had implemented some sustainability improvement measures. It is suggested, based on these research findings, that governments should articulate, by means of education, the rationale and benefits of sustainable home development that are identified in this research and reduce material costs and increase government incentives. Originality/value – A framework on improving residential sustainability was proposed in this paper. Stakeholders in the sustainable home supply chain could use this framework as a reference to pave the way for energy efficient home development from their perspective

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