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  • Open Access

    ARTICLE

    Numerical Study on the Suitability of Passive Solar Heating Technology Based on Differentiated Thermal Comfort Demand

    Xiaona Fan, Qin Zhao, Guochen Sang, Yiyun Zhu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 627-660, 2022, DOI:10.32604/cmes.2022.020507 - 15 June 2022

    Abstract Indoor thermal comfort and passive solar heating technologies have been extensively studied. However, few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfort demands. This work took the rural dwellings in Northwest China as the research object. First, the current indoor and outdoor thermal environment in winter and the mechanism of residents’ differentiated demand for indoor thermal comfort were obtained through tests, questionnaires, and statistical analysis. Second, a comprehensive passive optimized design of existing buildings was conducted, and the validity of the optimized combination scheme was explored using DesignBuilder… More >

  • Open Access

    ARTICLE

    Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response

    Jian Dong, Haixin Wang, Junyou Yang*, Liu Gao, Kang Wang, Xiran Zhou

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 319-340, 2022, DOI:10.32604/cmes.2022.020394 - 02 June 2022

    Abstract Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy. This paper studies an electric-gas-heat integrated energy system, including the carbon capture system, energy coupling equipment, and renewable energy. An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost, carbon emission and enhance the power supply reliability. Firstly, the low-carbon mathematical model of combined thermal and power unit, carbon capture system and power to gas unit (CCP) is established. Subsequently, we establish a low carbon multi-objective optimization model considering system operation cost, carbon emissions cost, integrated demand More >

  • Open Access

    ARTICLE

    A Hybrid Neural Network-based Approach for Forecasting Water Demand

    Al-Batool Al-Ghamdi1,*, Souad Kamel2, Mashael Khayyat3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1365-1383, 2022, DOI:10.32604/cmc.2022.026246 - 18 May 2022

    Abstract Water is a vital resource. It supports a multitude of industries, civilizations, and agriculture. However, climatic conditions impact water availability, particularly in desert areas where the temperature is high, and rain is scarce. Therefore, it is crucial to forecast water demand to provide it to sectors either on regular or emergency days. The study aims to develop an accurate model to forecast daily water demand under the impact of climatic conditions. This forecasting is known as a multivariate time series because it uses both the historical data of water demand and climatic conditions to forecast… More >

  • Open Access

    ARTICLE

    Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

    Muhammad Irfan1, Ali Raza2,*, Faisal Althobiani3, Nasir Ayub4,5, Muhammad Idrees6, Zain Ali7, Kashif Rizwan4, Abdullah Saeed Alwadie1, Saleh Mohammed Ghonaim3, Hesham Abdushkour3, Saifur Rahman1, Omar Alshorman1, Samar Alqhtani8

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4249-4265, 2022, DOI:10.32604/cmc.2022.025863 - 21 April 2022

    Abstract In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and… More >

  • Open Access

    ARTICLE

    How Load Aggregators Avoid Risks in Spot Electricity Market: In the Framework of Power Consumption Right Option Contracts

    Jiacheng Yang1, Xiaohe Zhai1, Zhongfu Tan1,2,*, Zhenghao He1

    Energy Engineering, Vol.119, No.3, pp. 883-906, 2022, DOI:10.32604/ee.2022.018033 - 31 March 2022

    Abstract There is uncertainty in the electricity price of spot electricity market, which makes load aggregators undertake price risks for their agent users. In order to allow load aggregators to reduce the spot market price risk, scholars have proposed many solutions, such as improving the declaration decision-making model, signing power mutual insurance contracts, and adding energy storage and mobilizing demand-side resources to respond. In terms of demand side, calling flexible demand-side resources can be considered as a key solution. The user's power consumption rights (PCRs) are core contents of the demand-side resources. However, there have been… More >

  • Open Access

    ARTICLE

    Dynamic Intelligent Supply-Demand Adaptation Model Towards Intelligent Cloud Manufacturing

    Yanfei Sun1, Feng Qiao2, Wei Wang1, Bin Xu1, Jianming Zhu1, Romany Fouad Mansour3, Jin Qi1,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2825-2843, 2022, DOI:10.32604/cmc.2022.026574 - 29 March 2022

    Abstract As a new mode and means of smart manufacturing, smart cloud manufacturing (SCM) faces great challenges in massive supply and demand, dynamic resource collaboration and intelligent adaptation. To address the problem, this paper proposes an SCM-oriented dynamic supply-demand (S-D) intelligent adaptation model for massive manufacturing services. In this model, a collaborative network model is established based on the properties of both the supply-demand and their relationships; in addition, an algorithm based on deep graph clustering (DGC) and aligned sampling (AS) is used to divide and conquer the large adaptation domain to solve the problem of… More >

  • Open Access

    ARTICLE

    Dynamic Vehicular Clustering Enhancing Video on Demand Services Over Vehicular Ad-hoc Networks

    M. Almutiq1, L. Sellami1,2,*, B. Alaya1,3

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3493-3510, 2022, DOI:10.32604/cmc.2022.024571 - 29 March 2022

    Abstract Nowadays, video streaming applications are becoming one of the tendencies driving vehicular network users. In this work, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks (VANET). The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls, inspired by the different features and the performance of the Long… More >

  • Open Access

    ARTICLE

    An Efficient On-Demand Virtual Machine Migration in Cloud Using Common Deployment Model

    C. Saravanakumar1,*, R. Priscilla1, B. Prabha2, A. Kavitha3, M. Prakash4, C. Arun5

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 245-256, 2022, DOI:10.32604/csse.2022.022122 - 02 December 2021

    Abstract Cloud Computing provides various services to the customer in a flexible and reliable manner. Virtual Machines (VM) are created from physical resources of the data center for handling huge number of requests as a task. These tasks are executed in the VM at the data center which needs excess hosts for satisfying the customer request. The VM migration solves this problem by migrating the VM from one host to another host and makes the resources available at any time. This process is carried out based on various algorithms which follow a predefined capacity of source… More >

  • Open Access

    ARTICLE

    System Dynamics Forecasting on Taiwan Power Supply Chain

    Zhiqiu Yu1,*, Shuo-Yan Chou1, Phan Nguyen Ky Phuc2, Tiffany Hui-Kuang Yu3

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1191-1205, 2022, DOI:10.32604/csse.2022.021239 - 10 November 2021

    Abstract This research aims to study the sustainability of Taiwan power supply chain based on system dynamics forecasting. The paper tries to investigate electricity shortage effects not only on the industrial side, but also from the standpoint of society. In our model, different forecasting methods such as linear regression, time series analysis, and gray forecasting are also considered to predict the parameters. Further tests such as the structure, dimension, historical fit, and sensitivity of the model are also conducted in this paper. Through analysis forecasting result, we believe that the demand for electricity in Taiwan will More >

  • Open Access

    ARTICLE

    Analysis of Inventory Model for Quadratic Demand with Three Levels of Production

    Dharamender Singh1, Majed G. Alharbi2, Anurag Jayswal1, Ali Akbar Shaikh3,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 167-182, 2022, DOI:10.32604/iasc.2022.021815 - 26 October 2021

    Abstract The inventory framework is one of the standards of activity research fundamentals in ventures and business endeavors. Production planning includes all building production plans, including organizing and appointing exercises to every individual, gathering individuals or machines, and mastering work orders in every work environment. Production booking should take care of all issues, for example, limiting client standby time and production time; and viably utilizing the undertaking’s HR. This paper considered three degrees of a production inventory model for a consistent deterioration rate. This model assumes a significant part in the production of the board and… More >

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