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  • Open Access


    Modeling Energy Consumption in the Production Processes of Industrial Units Based on Load Response Programs in the Energy Market

    Baodong Li*

    Energy Engineering, Vol.120, No.2, pp. 461-481, 2023, DOI:10.32604/ee.2022.021877

    Abstract The optimal operation of microgrids is of great significance for the sake of efficient and economical management of its energy resources. The microgrid energy management system should plan to operate the microgrid while simultaneously considering the electric and thermal load. The present study proposes energy management to minimize the costs of operating an industrial microgrid. In fact, planning for energy supply is among the critical issues that distribution companies deal with daily in the competitive environment. A distribution company usually meets customer (end customer) demands by purchasing energy from a wholesale market. Given the load curtailment, distribution companies have more… More >

  • Open Access


    Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

    Manar Ahmed Hamza1,2,*, Aisha Hassan Abdalla Hashim1, Dalia H. Elkamchouchi3, Nadhem Nemri4, Jaber S. Alzahrani5, Amira Sayed A. Aziz6, Mnahel Ahmed Ibrahim7, Abdelwahed Motwakel2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1711-1726, 2023, DOI:10.32604/csse.2023.031467

    Abstract Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in large-scale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads… More >

  • Open Access


    Energy Proficient Reduced Coverage Set with Particle Swarm Optimization for Distributed Sensor Network

    T. V. Chithra1,*, A. Milton2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1611-1623, 2023, DOI:10.32604/csse.2023.026561

    Abstract Retransmission avoidance is an essential need for any type of wireless communication. As retransmissions induce the unnecessary presence of redundant data in every accessible node. As storage capacity is symmetrical to the size of the memory, less storage capacity is experienced due to the restricted size of the respective node. In this proposed work, we have discussed the integration of the Energy Proficient Reduced Coverage Set with Particle Swarm Optimization (PSO). PSO is a metaheuristic global search enhancement technique that promotes the searching of the best nodes in the search space. PSO is integrated with a Reduced Coverage Set, to… More >

  • Open Access


    Life Cycle Assessment Introduced by Using Nanorefrigerant of Organic Rankine Cycle System for Waste Heat Recovery

    Yuchen Yang1,2, Lin Ma1,2,*, Jie Yu1,2, Zewen Zhao1,2, Pengfei You1,2

    Journal of Renewable Materials, Vol.11, No.3, pp. 1153-1179, 2023, DOI:10.32604/jrm.2022.022719

    Abstract The use of nanorefrigerants in Organic Rankine Cycle (ORC) units is believed to affect the cycle environment performance, but backed with very few relevant studies. For this purpose, a life cycle assessment (LCA) has been performed for the ORC system using nanorefrigerant, the material and energy input, characteristic indicators and comprehensive index of environmental impact, total energy consumption and energy payback time (BPBT) of the whole life cycle of ORC system using Al2O3/R141b nanorefrigerant were calculated. Total environmental comprehensive indexes reveal that ECER-135 index decrease by 1.5% after adding 0.2% Al2O3 nanoparticles to R141b. Based on the contribution analysis and… More >

  • Open Access


    Energy Consumption Analysis and Characterization of Aerospace Manufacturing Facilities in the United States–A Step towards Sustainable Development

    Khaled Bawaneh1,*, Bradley Deken2, Amin Esmaeili3

    Energy Engineering, Vol.120, No.1, pp. 23-34, 2023, DOI:10.32604/ee.2023.019813

    Abstract In this study, information on energy usage in the United States (U.S.) aerospace manufacturing sector has been analyzed and then represented as energy intensities (kWh/m2) to establish benchmark data and to compare facilities of varying sizes. First, public sources were identified and the data from these previously published sources were aggregated to determine the energy usage of aerospace manufacturing facilities within the U.S. From this dataset, a sample of 28 buildings were selected and the energy intensity for each building was estimated from the data. Next, as a part of this study the energy data for three additional aerospace manufacturing… More >

  • Open Access


    Scheduling an Energy-Aware Parallel Machine System with Deteriorating and Learning Effects Considering Multiple Optimization Objectives and Stochastic Processing Time

    Lei Wang1,2,*, Yuxin Qi1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 325-339, 2023, DOI:10.32604/cmes.2022.019730

    Abstract Currently, energy conservation draws wide attention in industrial manufacturing systems. In recent years, many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach. This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects. In it, the real processing time of jobs is calculated by using their processing speed and normal processing time. To describe this problem in a mathematical way, a multi-objective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated. Furthermore, we develop a multi-objective… More >

  • Open Access


    Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique

    Hanadi AlZaabi1, Khaled Shaalan1, Taher M. Ghazal2,3,*, Muhammad A. Khan4,5, Sagheer Abbas6, Beenu Mago7, Mohsen A. A. Tomh6, Munir Ahmad6

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2261-2278, 2023, DOI:10.32604/cmc.2023.031834

    Abstract Energy is essential to practically all exercises and is imperative for the development of personal satisfaction. So, valuable energy has been in great demand for many years, especially for using smart homes and structures, as individuals quickly improve their way of life depending on current innovations. However, there is a shortage of energy, as the energy required is higher than that produced. Many new plans are being designed to meet the consumer’s energy requirements. In many regions, energy utilization in the housing area is 30%–40%. The growth of smart homes has raised the requirement for intelligence in applications such as… More >

  • Open Access


    Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

    Rongxin Zhang1,*, Chengying Yang2,3, Xuetao Li1

    Energy Engineering, Vol.119, No.6, pp. 2489-2511, 2022, DOI:10.32604/ee.2022.021517

    Abstract Buildings are the main energy consumers across the world, especially in urban communities. Building smartization, or the smartification of housing, therefore, is a major step towards energy grid smartization too. By controlling the energy consumption of lighting, heating, and cooling systems, energy consumption can be optimized. All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources (RES), which mitigates environmental impacts and reduces peak demand for electrical energy. In this paper, a new optimization algorithm is applied to solve the optimal energy consumption problem by considering the electric vehicles and demand… More >

  • Open Access


    Data Mining Based Integrated Electric-Gas Energy System Multi-Objective Optimization

    Zhukui Tan1,*, Yongjie Ren1, Hua Li1, Weili Ren2, Xichao Zhou2, Ming Zeng1

    Energy Engineering, Vol.119, No.6, pp. 2607-2619, 2022, DOI:10.32604/ee.2022.019550

    Abstract With the proposal of carbon neutrality, how to improve the proportion of clean energy in energy consumption and reduce carbon dioxide emissions has become the important challenge for the traditional energy industry. Based on the idea of multi-energy complementarity, a typical integrated energy system consisting of electric system and gas system is constructed based on the application of power to gas (P2G) technology and gas turbine in this paper. Furthermore, a multi-objective optimization model with economic improvement, carbon emission reduction and peak-load shifting as objectives is proposed, and solved by BSO algorithm. Finally, a typical power-gas coupling system is selected… More >

  • Open Access


    An Improved Hyperplane Assisted Multiobjective Optimization for Distributed Hybrid Flow Shop Scheduling Problem in Glass Manufacturing Systems

    Yadian Geng1, Junqing Li1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 241-266, 2023, DOI:10.32604/cmes.2022.020307

    Abstract To solve the distributed hybrid flow shop scheduling problem (DHFS) in raw glass manufacturing systems, we investigated an improved hyperplane assisted evolutionary algorithm (IhpaEA). Two objectives are simultaneously considered, namely, the maximum completion time and the total energy consumptions. Firstly, each solution is encoded by a three-dimensional vector, i.e., factory assignment, scheduling, and machine assignment. Subsequently, an efficient initialization strategy embeds two heuristics are developed, which can increase the diversity of the population. Then, to improve the global search abilities, a Pareto-based crossover operator is designed to take more advantage of non-dominated solutions. Furthermore, a local search heuristic based on… More >

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