Fabien Mukundufite^1,*, Jean Marie Vianney Bikorimana¹, Alexander Kyaruzi Lugatona²

Energy Engineering, Vol.121, No.7, pp. 1805-1821, 2024, DOI:10.32604/ee.2024.051398

Abstract The governmental electric utility and the private sector are joining hands to meet the target of electrifying all households by 2024. However, the aforementioned goal is challenged by households that are scattered in remote areas. So far, Solar Home Systems (SHS) have mostly been applied to increase electricity access in rural areas. SHSs have continuous constraints to meet electricity demands and cannot run income-generating activities. The current research presents the feasibility study of electrifying Remera village with the smart microgrid as a case study. The renewable energy resources available in Remera are the key sources… More >

Hao Qi¹, Mohamed Sharaf², Andres Annuk³, Adrian Ilinca⁴, Mohamed A. Mohamed^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1387-1404, 2024, DOI:10.32604/cmes.2024.048672

Abstract Hot dry rock (HDR) is rich in reserve, widely distributed, green, low-carbon, and has broad development potential and prospects. In this paper, a distributionally robust optimization (DRO) scheduling model for a regionally integrated energy system (RIES) considering HDR co-generation is proposed. First, the HDR-enhanced geothermal system (HDR-EGS) is introduced into the RIES. HDR-EGS realizes the thermoelectric decoupling of combined heat and power (CHP) through coordinated operation with the regional power grid and the regional heat grid, which enhances the system wind power (WP) feed-in space. Secondly, peak-hour loads are shifted using price demand response guidance More >

Biswajit De^*, Rajsekhar Panua

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-4, 2014, DOI:10.5098/hmt.5.10

Abstract As the world is facing crisis due to the dwindling resources of fossil fuels, rapid depletion of conventional energy is a matter of serious concern for the mankind. So there is a necessity to find alternate fuels. Vegetable oils, because of their agricultural origin, due to less carbon content compared to mineral diesel are producing less CO₂ emissions to the atmosphere is used as an alternate fuel in substitute to diesel fuel. In the present study optimum compression ratio for VCR diesel engine fuelled with Jatropha oil blends with diesel (30%) has been determined at 203 More >

Billel Meghni¹, Afaf Benamor², Oussama Hachana³, Ahmad Taher Azar^4,5,*, Amira Boulmaiz⁶, Salah Saad¹, El-Sayed M. El-kenawy^7,8, Nashwa Ahmad Kamal⁹, Suliman Mohamed Fati⁵, Naglaa K. Bahgaat¹⁰

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3977-3996, 2023, DOI:10.32604/cmc.2023.029838

Abstract The integration of wind turbines (WTs) in variable speed drive systems belongs to the main factors causing low stability in electrical networks. Therefore, in order to avoid this issue, WTs hybridization with a storage system is a mandatory. This paper investigates WT system operating at variable speed. The system contains of a permanent magnet synchronous generator (PMSG) supported by a battery storage system (BSS). To enhance the quality of active and reactive power injected into the network, direct power control (DPC) scheme utilizing space-vector modulation (SVM) technique based on proportional-integral (PI) control is proposed. Meanwhile, More >

Shafaq Abbas¹, Muhammad Attique Khan¹, Majed Alhaisoni², Usman Tariq³, Ammar Armghan⁴, Fayadh Alenezi⁴, Arnab Majumdar⁵, Orawit Thinnukool^6,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1139-1159, 2023, DOI:10.32604/cmc.2023.028824

Abstract Manual diagnosis of crops diseases is not an easy process; thus, a computerized method is widely used. From a couple of years, advancements in the domain of machine learning, such as deep learning, have shown substantial success. However, they still faced some challenges such as similarity in disease symptoms and irrelevant features extraction. In this article, we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases recognition. The proposed architecture consists of five steps. In the first step, data augmentation is performed to increase the numbers of training samples.… More >

Ngoc Thai Huynh¹, Tien V. T. Nguyen², Quoc Manh Nguyen^3,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5961-5983, 2022, DOI:10.32604/cmc.2022.029484

Abstract To achieve high work performance for compliant mechanisms of motion scope, continuous work condition, and high frequency, we propose a new hybrid algorithm that could be applied to multi-objective optimum design. In this investigation, we use the tools of finite element analysis (FEA) for a magnification mechanism to find out the effects of design variables on the magnification ratio of the mechanism and then select an optimal mechanism that could meet design requirements. A poly-algorithm including the Grey-Taguchi method, fuzzy logic system, and adaptive neuro-fuzzy inference system (ANFIS) algorithm, was utilized mainly in this study.… More >

A. Arunkumar^1,*, S. Ramabalan¹, D. Elayaraja²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1229-1244, 2023, DOI:10.32604/iasc.2023.027388

Abstract Environmental issues like pollution are major threats to human health. Many systems are developed to reduce pollution. In this paper, an optimal mobile robot design to reduce pollution in Green supply chain management system. Green supply chain management involves as similating environmentally and economically feasible solutions into the supply chain life-cycle. Smartness, advanced technologies, and advanced networks are becoming pillars of a sustainable supply chain management system. At the same time, there is much change happening in the logistics industry. They are moving towards a new logistics model. In the new model, robotic logistics has… More >

Xiaoyong Wang^*

Journal of Renewable Materials, Vol.10, No.9, pp. 2431-2450, 2022, DOI:10.32604/jrm.2022.020829

Abstract Metakaolin is a highly reactive pozzolanic material that is widely utilized for enhancing the performance of concrete. This study offers a framework for the mixture design of sustainable metakaolin-modified concrete with low CO₂ emissions and low costs. Different design strengths after 28 days are first formulated, with values such as 30, 40, 50, and 60 MPa. A genetic algorithm is then used to determine the optimal mixtures. Minimized CO₂ and cost are set as the aims of the genetic algorithm. The strength of the concrete, its workability (slump), and carbonation service life with climate change are set… More >

M. Nisha^1,*, M. Germin Nisha²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1399-1413, 2022, DOI:10.32604/iasc.2022.024482

Abstract A new methodology is used in this paper, for the optimal tuning of Photovoltaic (PV) by integrating the hybrid Maximum Power Point Tracking (MPPT) algorithms is proposed. The suggested hybrid MPPT algorithms can raise the performance of PV systems under partial shade conditions. It attempts to address the primary research issues in partial shading conditions in PV systems caused by clouds, trees, dirt, and dust. The proposed system computes MPPT utilizing an innovative adaptive model-based approach. In order to manage the input voltage at the Maximum PowerPoint, the MPPT algorithm changes the duty cycle of… More >

Muhammad Asif Saleem¹, Muhammad Aamir^{1,2, * ,*}, Rosziati Ibrahim¹, Norhalina Senan¹, Tahir Alyas³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6053-6067, 2022, DOI:10.32604/cmc.2022.022215

Abstract Plant disease classification based on digital pictures is challenging. Machine learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize, identify, and diagnose plant diseases in the previous decade. Increasing the yield quantity and quality of rice forming is an important cause for the paddy production countries. However, some diseases that are blocking the improvement in paddy production are considered as an ominous threat. Convolution Neural Network (CNN) has shown a remarkable performance in solving the early detection of paddy leaf diseases based on its images in the fast-growing More >