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  • Open Access

    ARTICLE

    Deep Learning for Multivariate Prediction of Building Energy Performance of Residential Buildings

    Ibrahim Aliyu1, Tai-Won Um2, Sang-Joon Lee3, Chang Gyoon Lim4,*, Jinsul Kim1,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5947-5964, 2023, DOI:10.32604/cmc.2023.037202 - 29 April 2023

    Abstract In the quest to minimize energy waste, the energy performance of buildings (EPB) has been a focus because building appliances, such as heating, ventilation, and air conditioning, consume the highest energy. Therefore, effective design and planning for estimating heating load (HL) and cooling load (CL) for energy saving have become paramount. In this vein, efforts have been made to predict the HL and CL using a univariate approach. However, this approach necessitates two models for learning HL and CL, requiring more computational time. Moreover, the one-dimensional (1D) convolutional neural network (CNN) has gained popularity due… More >

  • Open Access

    ARTICLE

    Intelligent System Application to Monitor the Smart City Building Lighting

    Tzu-Chia Chen1, Ngakan Ketut Acwin Dwijendra2,*, Saurabh Singhal3, R. Sivaraman4, Amr Mamdouh5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3159-3169, 2023, DOI:10.32604/cmc.2023.035418 - 31 March 2023

    Abstract A smart city incorporates infrastructure methods that are environmentally responsible, such as smart communications, smart grids, smart energy, and smart buildings. The city administration has prioritized the use of cutting-edge technology and informatics as the primary strategy for enhancing service quality, with energy resources taking precedence. To achieve optimal energy management in the multidimensional system of a city tribe, it is necessary not only to identify and study the vast majority of energy elements, but also to define their implicit interdependencies. This is because optimal energy management is required to reach this objective. The lighting… More >

  • Open Access

    ARTICLE

    Efficiency Performances of LVDC Supplies for Residential Building

    Anis Ammous*, Ammar Alsaedi, Ahmed N. M. Alahmadi, Fahad Alharbi, Kaiçar Ammous

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2171-2186, 2023, DOI:10.32604/csse.2023.029389 - 03 November 2022

    Abstract The Low Voltage Direct Current (LVDC) architecture gives higher benefits over the classic low-voltage alternating current (LVAC) supply concept. LVDC has fewer energy conversion stages, is compatible with renewable energy sources, and is easier to integrate with accumulators. In this paper, an LVDC supply concept is proposed and compared with currently used conventional photovoltaic (PV) systems in terms of efficiency. The new LVDC photovoltaic system behavior is validated using LTspice modeling tool. The findings of this work prove that the concept of LVDC supply is highly attractive when the electricity produced by the photovoltaic is… More >

  • Open Access

    ARTICLE

    Energy Efficient Thermal Comfort Control for Residential Building Based on Nonlinear EMPC

    Xucheng Chang1,*, Bing Kong2, Yong Li1, Gaofeng Ren1, Chao Zhang1, Zhenghe Wang1

    Energy Engineering, Vol.119, No.5, pp. 1941-1966, 2022, DOI:10.32604/ee.2022.020698 - 21 July 2022

    Abstract For purpose of achieving the desired thermal comfort level and reducing the economic cost of maintaining the thermal comfort of green residential building, an energy efficient thermal comfort control strategy based on economic model predictive control (EMPC) for green residential buildings which adopts household heat metering is presented. Firstly, the nonlinear thermal comfort model of heating room is analyzed and obtained. A practical nonlinear thermal comfort prediction model is obtained by using an approximation method. Then, the economic cost function and optimization problem of energy-saving under the necessary thermal comfort requirements are constructed to realize… More >

  • Open Access

    ARTICLE

    Prediction of Residential Building’s Solar Installation Energy Demand in Morocco Using Multiple Linear Regression Analysis

    Nada Yamoul1,*, Latifa Dlimi1, Baraka Achraf Chakir2

    Energy Engineering, Vol.119, No.5, pp. 2135-2148, 2022, DOI:10.32604/ee.2022.020005 - 21 July 2022

    Abstract The building sector is one of the main energy-consuming sectors in Morocco. In fact, it accounts for 33% of the final consumption of energy and records a high increase in the annual consumption of energy caused by further planned large-scale projects. Indeed, the energy consumption of the building sector is experiencing a significant acceleration justified by the rapid need for the development of housing stock, wich is estimated at an average increase of 1,5% per year; furthermore, tant is an estimated increase of about 6,4%. In this sense, building constitutes an important potential source for… More >

  • Open Access

    ARTICLE

    Investigation of Plans Shape and Glazing Percentage for the Energy Efficiency of Residential Buildings

    Tayyebeh Yazarlou*, Mohammad Djavad Saghafi

    Energy Engineering, Vol.118, No.6, pp. 1783-1797, 2021, DOI:10.32604/EE.2021.017282 - 10 September 2021

    Abstract The room's plan shape, the area of the window, and the impact of the materials are significant parameters in determining the thermal needs of buildings. In traditional houses of the hot and dry climate of Iran, the plan shape of the room, the ratio of the window area to the floor area, and the comparison between traditional and prevalent materials have been less studied. This study investigated the thermal performance of seven different models of the plan shape, five different ratios of window area to plan area, and three material structures in a selected room… More >

  • Open Access

    ARTICLE

    Energy-Efficiency Model for Residential Buildings Using Supervised Machine Learning Algorithm

    Muhammad Shoukat Aslam1, Taher M. Ghazal2,3, Areej Fatima4, Raed A. Said5, Sagheer Abbas1, Muhammad Adnan Khan6,7,*, Shahan Yamin Siddiqui1,8, Munir Ahmad1

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 881-888, 2021, DOI:10.32604/iasc.2021.017920 - 20 August 2021

    Abstract The real-time management and control of heating-system networks in residential buildings has tremendous energy-saving potential, and accurate load prediction is the basis for system monitoring. In this regard, selecting the appropriate input parameters is the key to accurate heating-load forecasting. In existing models for forecasting heating loads and selecting input parameters, with an increase in the length of the prediction cycle, the heating-load rate gradually decreases, and the influence of the outside temperature gradually increases. In view of different types of solutions for improving buildings’ energy efficiency, this study proposed a Energy-efficiency model for residential More >

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