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Linear Fresnel Reflector Power Plants in Algeria: Energy, Economic, and Environmental Analysis

Journal of Solar Energy Engineering 2025年第3期147卷 031011页

作者： Ghodbane, Mokhtar Boumeddane, Boussad Hussain, Fayaz El-Amarty, Naima Lahrech, Khadija Barbón, Arsenio Department of Mechanical Engineering Faculty of Technology Saad DAHLAB University of Blida 1 Blida09000 Algeria Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam SIGER Laboratory Faculty of Sciences and Technology Sidi Mohamed Ben Abdellah University P.O. Box 2202 Fez30000 Morocco LIPI Laboratory ENS National School of Applied Science ENSA Sidi Mohamed Ben Abdellah University Fez30000 Morocco Department of Electrical Engineering University of Oviedo Gijón33203 Spain

The Algerian government seeks to provide all the resources available to it to exploit every available energy source in all Algerian provinces. Accordingly, this paper aims to present an energy, economic, and environmental study of linear Fresnel reflector solar power plants using the system advisor model in four strategic Algerian regions (Ain Aménas, Gassi-Touil, Hassi R'mel, and El-Oued). The studied solar power plants can produce between 318.75 GWe and 379.29 GWe annually at a levelized cost of electricity ranging between 0.093 $/kWh and 0.11 $/kWh. In addition, the annual avoided CO2 emissions are between 143.41 kt and 170.87 kt, equivalent to 0.473 kg CO2/1 kWh of electricity, meaning that environmental tax savings will range between 2.08 and 2.48 million dollars annually. The results obtained are very encouraging for decision-makers and investors, as the net capital investment (between 642.67 and 642.82 million dollars) can be recovered in less than 10.2 years, with the power plant capable of operating for 25 consecutive years. © 2025 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Solar power plants

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Microstructure, mechanical and physical characteristics analysis of ADC14 hypereutectic AlSi composite reinforced with Al2O3

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Alexandria Engineering Journal 2025年 126卷 303-319页

作者： Bhutto, Aqeel Ahmed Bin Wahab, Saidin Solangi, Faheem Ahmed Hussain, Fayaz Zhou, Ding Khan, T.M. Yunus Shaik, Abdul Saddique Department of Mechanical Engineering MUET SZAB Campus Sindh Khairpur Mirs66020 Pakistan Faculty of Mechanical and Manufacturing Engineering UTHM Johor Parit Raja86400 Malaysia Department of Mechanical Engineering QUEST Sindh NawabShah67450 Pakistan Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Centre of Advanced Materials Department of Mechanical Engineering Faculty of Engineering Universiti Malaya Kuala Lumpur50603 Malaysia Central Labs King Khalid University P.O. Box 960 AlQura'a Abha Saudi Arabia Department of Mechanical Engineering College of Engineering King Khalid University Abha61421 Saudi Arabia

The instigation of primary and eutectic Si has been observed due to the higher content of Si during melting and caused to reduction in the mechanical strength of hypereutectic AlSi alloy. The appropriate mechanism of microstructure and inclusion of strengthening materials can overcome this problem. Thus, in this research work, 5, 10 and 15 wt% of alumina were added in ADC14 hypereutectic AlSi alloy for composite fabrication through stir casting. The microstructure, mechanical and physical characteristics of the AC14 composite were investigated, and the surface response and ANOVA approaches were used to investigate the interaction between variables and responses, and significance of contribution through statistical analysis. The addition of alumina provided better microstructure, and due to it mechanical strengths were improved. The highest value of tensile strength and hardness 85 MPa and 44 VHN respectively were obtained for 15 wt% of alumina. Whereas, the calculated porosity has inverse proportion with the content of alumina. The surface response analysis and ANOVA results showed good interaction between variables and responses, and the contributions were significant. Based on the obtained experimental and statistical results, the addition of alumina provided better mechanical properties and microstructure of the ADC14 composites. © 2025 The Authors

关键词： Microhardness

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Leveraging machine learning to optimize cooling tower efficiency for sustainable power generation

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Frontiers in Energy Research 2025年 13卷

作者： Mujtaba, M.A. Munir, Muhammad Adeel Akhtar, Muhammad Mahmood, Bilal Ansar, Talha Khawar, Zeeshan Khalid, Shayan Basit, Abdul Jamil, Saud Kalam, M.A. Hussain, Fayaz Bhowmik, Chiranjib Lahore Pakistan Limited Lahore 1180MW CCPP Bhikki Pakistan Harbin Electric Company Limited 1180MW CCPP Bhikki O&M Lahore Pakistan School of Civil and Environmental Engineering Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW Australia Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Mechanical Engineering Techno India University West Bengal India

United Nations Sustainable Development Goal 7 is about ensuring access to clean and affordable energy, which is a key factor in the development of society. The power generation sector majorly consists of thermal power plants. Cooling towers are a significant part of any power plant to cool steam to be reused again. Hence, the efficiency of power plants can be increased by optimizing the performance of cooling towers. This research paper aims to increase the efficiency of cooling towers by investigating the effect of ambient parameters (changing with climate) on the efficiency of cooling towers for the best site selection. Ambient parameters cannot be controlled after the installation of power plants. Therefore, proper site selection, keeping ambient parameters and their expected change before the installation of power plants, effectively increases the efficiency of the cooling tower and, ultimately, the power plant. For this purpose, data is collected from the 1140 MW combined cycle power plant in Sheikhupura, Pakistan district. A machine learning (Ada boost regressor) model has been used to quantify the effect of ambient parameters on cooling tower efficiency. After tuning the hyperparameters, an R-square score of 0.983 and a root mean squared error of 0.57 are achieved. Afterwards, a sensitivity analysis of relative humidity (%), turned out to be the most important feature, with a contribution of 12%. The novelty of this research lies in its mathematical model for power plant site selection, which optimizes cooling tower efficiency, reduces pollution, and promotes environmental sustainability. Copyright © 2025 Mujtaba, Munir, Akhtar, Mahmood, Ansar, Khawar, Khalid, Basit, Jamil, Kalam, Hussain and Bhowmik.

关键词： Cooling towers

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Experimental investigation on the flow mixing and core length of a supersonic multiple jet configuration using cross-wire as vortex generators

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Aerospace Science and Technology 2025年 162卷

作者： Faheem, Mohammed Khan, Sher Afghan Alam, Mohammad Mukhtar Stanislaus Arputharaj, Beena Hussain, Fayaz Al-Mdallal, Qasem M. Department of Mechanical & Aerospace Engineering Faculty of Engineering International Islamic University Malaysia Kuala Lumpur50728 Malaysia Department of Industrial Engineering College of Engineering King Khalid University Abha61421 Saudi Arabia Department of Research and Innovation Saveetha School of Engineering SIMATS Tamil Nadu Chennai602105 India Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Mathematical Sciences United Arab Emirates University P.O. Box 15551 Abu Dhabi Al Ain United Arab Emirates Center for Engineering and Technology Innovations King Khalid University Abha61421 Saudi Arabia

Many Engineering applications use multi-jet systems, such as aircraft propulsion units and spacecraft. A complex aerodynamic flow field occurs when multiple jets are close to each other. This study experimentally examines the supersonic jets' mean flow field and mixing characteristics from one, two, and three different converging-diverging nozzles placed in close vicinity. The cross-wire is used as a passive control technique to investigate the impact of the control on the flow field and the core length. The nozzle is designed for Mach number M = 1.5, with an inter-nozzle positioning equal to twofold the nozzle exit diameter. The typical contact procedure and the triple jet's growth are discussed using cross-sectional contour patterns and transverse pressure profiles. The effect of leading parallel jets on local flow field features, comprising shock wave structure, supersonic core, and jet spread, is observed by measuring pressure beside the jet axes. Similarly, the flow spread rate declines when the quantity of jet flow increases- this is mainly owed to a decrease in attuning;subsequently, the jet decays more slowly, and the core length decreases. Schlieren's pictures of triple, twin, and single jets reveal that the core of the supersonic jet varies in triple and twin jets compared to single jets. © 2025 Elsevier Masson SAS

关键词： Vortex flow

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Load Frequency Control Design for the Three Areas of Interconnected Thermal Power Plants

Load Frequency Control Design for the Three Areas of Interco...

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International Conference on Advanced Engineering Theory and Applications, AETA 2022

作者： Tuan, Dao Huy Van Huynh, Van Tran, Binh Ngoc Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789819987023

In this paper, the double integral slide combined with extended observer control is developed for three area interconnected thermal power plants due to the uncertainty of the load and the inability to measure system state variables. The proposed control ensures that the load frequency fluctuations reach an allowable limit, and the load frequency can also fluctuate to a small level so as not to affect the power quality in thermal power plants linking with multi areas power systems. The results using Simulink programming of Matlab software performed not only show that the novel control process works efficiently but also resolve the drastic change in power system parameters of the area connected. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Simulink

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Automatic Generation Control Based Sliding Mode Observer Design for Multi-area Multi-source Power Systems

Automatic Generation Control Based Sliding Mode Observer Des...

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International Conference on Advanced Engineering Theory and Applications, AETA 2022

作者： Tran, Phong Thanh Van Huynh, Van Dong, Chau Si Thien Dinh, Bach Hoang Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789819987023

Today, a multi-area power system (MAPS) has been implemented with a variety of power sources, including gas, hydro, thermal and nuclear, which will have an influence on load frequency regulation. Therefore, using the single-phase sliding mode control-based state observer (SPSMCBSO), load frequency control (LFC) of a deregulated two-area gas-hydro-thermal power system (TAGHTPS) is developed. Second, feedback control state variables are estimated using the state observer. Third, to enhance TAGHTPS performance in term of settling time and overshoot, the SPSMCBSO is designed to adjust the fundamental sliding mode control. Additionally, the SPSMCBSO is set up to totally depend on the state observer to resolve the issue with the state variable measurement. Finally, to verify the SPSMCBSO scheme, the results of the MATLAB/SIMULINK simulation are displayed and contrasted with newly established conventional control approaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sliding mode control

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Output single phase variable structure control for mismatched uncertain systems

International Journal of Control and Automation

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International Journal of Control and Automation 2016年第9期9卷 39-50页

作者： Huynh, Van Van Tsai, Yao-Wen Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Mechanical and Automation Engineering Da-Yeh University No. 168 University Rd. Changhua51591 Taiwan

This paper proposes a new single phase variable structure control (SPVSC) for mismatched uncertain systems. A new sliding mode without reaching phase is designed to address two most important problems in the variable structure control area: 1) the system states are in sliding mode at the initial time movement;and 2) using only output variables directly. First, a new sufficient condition in terms of linear matrix inequality is derived such that the existence of a sliding surface guarantees asymptotic stability of the sliding mode dynamics from the initial time instant. Second, a static output feedback SPVSC law is designed to force the system states to stay in the sliding surface from beginning to end. Final, the lateral motion of a B-26 aircraft is simulated to demonstrate the advantages and effectiveness of the proposed SPVSC scheme. © 2016 SERSC.

关键词： Linear matrix inequalities

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Sliding Mode-Based Load Frequency Control of a Power System with Multi-Source Power Generation

Sliding Mode-Based Load Frequency Control of a Power System ...

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2023 International Conference on System Science and Engineering, ICSSE 2023

作者： Tran, Phong Thanh Huynh, Van Van Dong, Chau Thien Si Dinh, Bach Hoang Ton Duc Thang University Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ho Chi Minh City Viet Nam International University- Vnuhcmc Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350322941

The chattering phenomena of high-frequency switching make it challenging to perform sliding-mode control (SMC) for load frequency control of power networks. Actuators utilized in power systems are highly vulnerable to this chattering issue in SMC. In this study, a load frequency controller based on decentralized SMC is developed for multi-area multi-source interconnected power systems (MMIPS) with matching uncertainties. To enhance the dynamic performance of the system in achieving intervals, the proportional and integral switching surface is built for each region. In addition to guaranteeing the resilience of the multi-area multi-source power network, the suggested second order sliding mode control (SOSMC) legislation avoids chattering phenomena in control input. The reaching law approach suggests the robust controller to ensure that, following a load and operation point modification, frequency fluctuation converges to zero. Additionally, the simulation report shows that the suggested controller maintains the quality requirement by dealing with operating conditions in a wider range, rejecting disturbance, lowering the transient response of frequency, and removing the overshoot issue. To demonstrate the effectiveness of the suggested decentralized SMC approach, a two-area multi-area multi-source linked power system is explored. The result of the MATLAB/SIMULINK simulation is presented, and its findings are contrasted with recently developed traditional control systems. © 2023 IEEE.

关键词： Sliding mode control

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Glioblastoma multiforme classification on high resolution histology image using deep spatial fusion network ? 5

Glioblastoma multiforme classification on high resolution hi...

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5th International Workshop on Experimental Economics and Machine Learning, EEML 2019

作者： Sumi, P. Sobana Delhibabu, Radhakrishnan School of Computer Science and Engg. Vellore Institute of Technology Vellore India Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Due Thang University Ho Chi Minh City Viet Nam

Brain tumor is a growth of abnormal cells in brain, which can be cancerous or non-cancerous. The Brain tumor have scarce symptoms so it is very difficult to classify. Diagnosing brain tumor with histology images will efficiently helps us to classify brain tumor types. Sometimes, histology based image analysis is not accepted due to its variations in morphological features. Deep learning CNN models helps to overcome this problem by feature extraction and classification. Here proposed a method to classify high resolution histology image. InceptionResNetV2 is an CNN model, which is adopted to extract hierarchical features without any loss of data. Next generated deep spatial fusion network to extract spatial features found in between patches and to predict correct features from unpredictable discriminative features. 10-fold cross-validation is performed on the histology image. This achieves 95.6 percent accuracy on 4-class classification (benign, malignant, Glioblastoma, Oligodendroglioma). Also obtained 99.1 percent accuracy and 99.6 percent AUC on 2-way classification (necrosis and non-necrosis). Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Histology

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Performance Analysis of Distributed Learning in Edge Computing on Handwritten Digits Dataset 9th

Performance Analysis of Distributed Learning in Edge Compu...

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9th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2023

作者： Vo, Tinh Phuc Nguyen, Viet Anh Nguyen, Xuyen Bao Le Dang, Duc Ngoc Minh Tran, Anh Khoa Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Computing Fundamental Department FPT University Ho Chi Minh City Viet Nam

ISBN: (纸本)9783031473586

Deep learning models often consist of millions or even billions of parameters, making it challenging to deploy them on devices with limited resources. Therefore, this study presents scenarios to assess the computational capability of edge devices to provide an evaluation of the learning performance of distributed learning methods. It focuses on using Deep Neural Network and the handwritten digit dataset (MNIST) in edge computing to evaluate the performance of distributed learning methods (no-offloading, full-offloading, split computing, and federated computing) in both ideal and realistic conditions. The performance evaluations are based on Precision, Recall, Accuracy, F1-score, and Estimated time complexity. The findings indicate that the full-offloading method achieved the highest performance in ideal conditions. However, in realistic situations, the split computing and federated computing methods performed better than the others. © 2023, © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Deep neural networks

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