Journal of Engineering Research最新文献

Numerical investigation of CFD parameters: Evaluating height variations on microclimate and crop performance in large-scale soilless greenhouses in northern Tunisia CFD参数的数值研究：评估突尼斯北部大型无土温室小气候和作物生产的高度变化

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2025.02.006

Olfa Zghal , Ahmed Ketata , Hasna Abid , Slim Zouari , Giovanni Gugliuzza , Maroua Mejri , Emilia Arrabito , Saiid Taktak , Zied Driss

This paper examines the climate conditions of a soilless greenhouse using numerical modeling and experimental setups. The objective is to predict the impacts of design parameters on the microclimate, focusing on adjusting the roof height of the soilless tunnel greenhouse in Tunisia. Numerical simulations using the ANSYS FLUENT 16.2 software were employed to account for the dynamic impacts of current tomato and basil crops on airflow and heat exchanges. An experimental study on a prototype soilless greenhouse in Tunis-Manouba validated the proposed Computational Fluid Dynamics model. This research also investigates how changes in greenhouse height affect the flow characteristics and energy dynamics, recommending optimal climate conditions for soilless agriculture. Developed correlations express the average air temperature and air velocity inside the greenhouse as functions of the height and the ambient temperature. Additionally, reducing the greenhouse height by about 35 % can increase the average temperature inside the greenhouse by 2 K. These findings provide valuable insights for designing efficient greenhouses, improving energy management, and optimizing crop yields. The study also establishes relationships between temperature, Vapor Pressure Deficit, meteorological conditions, and roof height, contributing to sustainable agriculture practices and climate-resilient farming.

本文利用数值模拟和实验装置研究了无土温室的气候条件。目的是预测设计参数对小气候的影响，重点是调整突尼斯无土隧道温室的屋顶高度。利用ANSYS FLUENT 16.2软件进行数值模拟，分析了当前番茄和罗勒作物对气流和热交换的动态影响。在突尼斯马努巴的一个无土温室的实验研究验证了所提出的计算流体动力学模型。本研究还探讨了温室高度变化对流动特性和能量动态的影响，为无土农业提出了最佳气候条件。发达的相关关系表示温室内的平均气温和风速作为高度和环境温度的函数。此外，降低温室高度约35% %可使温室内平均温度提高2 K。这些发现为设计高效温室、改善能源管理和优化作物产量提供了有价值的见解。该研究还建立了温度、蒸汽压差、气象条件和屋顶高度之间的关系，有助于可持续农业实践和气候适应型农业。

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引用次数: 0

Evaluation of the interface shear strength of concrete containing treated and untreated reclaimed asphalt pavement aggregates 含处理和未处理再生沥青路面集料混凝土界面抗剪强度评价

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2024.10.007

Dalal I. Almesri, Nawaf K. Alotaibi

Concrete production significantly contributes to carbon emissions and depletes natural resources, promoting increased interest in substituting traditional materials with recycled alternatives. This shift necessitates a thorough examination of recycled materials’ performance in concrete applications. This study aims to provide a better understanding of the shear transfer behavior of concrete containing reclaimed asphalt pavement (RAP) aggregates. To mitigate the potential negative impact of RAP aggregates, mechanical treatment was applied. The effects of RAP inclusion and mechanical treatment on the shear transfer strength of reinforced concrete were investigated. A total of twenty-four push-off specimens were tested to investigate the effects of aggregate replacement and the clamping reinforcement ratio on specimen behavior. Digital image correlation (DIC) was employed to monitor the strains and displacements, allowing for detailed tracking of the interface slip, crack width development, and reinforcement strain. The findings revealed that replacing natural aggregates with RAP aggregates resulted in lower compressive strengths and lower ultimate push-off strengths of the resulting concrete at equivalent effective water-to-cement (w/c) ratios. Specimens with higher reinforcement ratios retained residual strengths up to 77 % of the ultimate strength, even at relatively large slip and crack widths. The clamping reinforcement ratio was identified as the key factor influencing the ultimate and residual strengths for both types of concrete. The experimental results were compared to the strengths calculated by the ACI, PCI, AASHTO, and CSA design equations to evaluate their applicability when different aggregate types are used.

混凝土生产大大增加了碳排放，消耗了自然资源，促进了人们用可回收的替代品替代传统材料的兴趣。这种转变需要对再生材料在混凝土应用中的性能进行彻底的检查。本研究旨在更好地理解含有再生沥青路面（RAP）骨料的混凝土的剪切传递行为。为了减轻RAP骨料的潜在负面影响，采用了机械处理。研究了RAP夹杂物和力学处理对钢筋混凝土抗剪传递强度的影响。对24个推脱试件进行了试验，研究了骨料置换和夹紧配筋率对试件性能的影响。采用数字图像相关（DIC）监测应变和位移，可以详细跟踪界面滑移、裂缝宽度发展和钢筋应变。研究结果表明，用RAP骨料代替天然骨料会导致混凝土在等效有效水灰比（w/c）下的抗压强度和极限推脱强度降低。即使在相对较大的滑移和裂缝宽度下，配筋率较高的试件的残余强度仍可达极限强度的77 %。确定了夹紧配筋率是影响两种混凝土极限强度和剩余强度的关键因素。将实验结果与ACI、PCI、AASHTO和CSA设计方程计算的强度进行比较，评价其在不同骨料类型下的适用性。

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引用次数: 0

Hybrid cuckoo search-gorilla troops optimizer for optimal parameter estimation in photovoltaic modules 光伏组件最优参数估计的混合布谷鸟搜索-大猩猩部队优化器

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2024.12.009

Abdelmalek Gacem , Ridha Kechida , Youcef Bekakra , Francisco Jurado , Mariam A. Sameh

Photovoltaic (PV) power plants have recently attracted the attention of researchers and power system developers. One of the challenges of PV systems is ensuring an accurate mathematical model of the PV module. Accurate modeling of the behavior of these modules is indispensable for reliable system evaluation, analysis, design, development, and optimization of the performance and efficiency of photovoltaic systems. This paper presents the optimal estimation of the parameters of a mathematical model for a PV cell and module. Moreover, a new hybrid cuckoo search-gorilla troop optimization CS-GTO algorithm is proposed. The performance of the proposed hybrid CS-GTO algorithm is tested and evaluated on standard 23 benchmark functions and several data sets of commercial PV cells and modules. The obtained results were compared with other optimization algorithms mentioned in the literature, the comparative study conclusively demonstrates that the hybrid CS-GTO algorithm consistently outperforms other methods in terms of accuracy and convergence speed towards the global optimal solution, making it a robust tool for a wide range of optimization problems.

光伏电站近年来引起了研究人员和电力系统开发商的关注。光伏系统的挑战之一是确保光伏模块的精确数学模型。这些模块行为的准确建模对于可靠的系统评估、分析、设计、开发和优化光伏系统的性能和效率是必不可少的。本文提出了光伏电池和组件数学模型参数的最优估计。此外，提出了一种新的混合布谷鸟搜索-大猩猩群体优化CS-GTO算法。在23个标准基准函数和多个商用光伏电池和组件数据集上对所提出的混合CS-GTO算法的性能进行了测试和评估。将得到的结果与文献中提到的其他优化算法进行了比较，结果表明，混合CS-GTO算法在全局最优解的精度和收敛速度方面始终优于其他方法，使其成为解决广泛优化问题的鲁棒工具。

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引用次数: 0

Flexible flow shop scheduling problem with removal times 带移除时间的柔性流水车间调度问题

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2025.01.010

Lotfi Hidri

This paper addresses the challenge of incorporating removal times in multi-stage flexible flow shops. The problem exhibits symmetry, meaning the sequencing process remains the same whether we start from the first stage and proceed to the last, or work in reverse. This symmetry allows for a comprehensive investigation of both the original and reverse problems, leading to more robust and high-quality solutions. From a practical perspective, this problem models several real-world manufacturing systems where removal times significantly impact production schedules. Theoretically, this scheduling problem is particularly complex due to its strong NP-hard nature, posing a significant challenge for optimization. To tackle this, we propose an efficient two-phase optimization heuristic, designed to provide near-optimal solutions. In this heuristic, parallel machine scheduling with release dates, removal times, and delivery dates is applied iteratively at each stage of the process. Additionally, new lower bounds are developed to assess the quality of the proposed heuristic. These lower bounds are critical for measuring the relative gap between the heuristic and the optimal solution. In the first type of lower bound, all stages except one are relaxed in terms of capacity. The second is using the polynomial parallel machine problem to estimate the minimum idle time at subsequent stages. Extensive experimental testing on benchmark problems confirms the effectiveness of the proposed methods, demonstrating their suitability for both practical and theoretical scheduling challenges. The results show an average relative gap of 1.05 %.

本文解决了在多阶段柔性流程车间中纳入去除时间的挑战。这个问题表现出对称性，这意味着无论我们从第一阶段开始到最后阶段，还是反过来，排序过程都是一样的。这种对称性允许对原始问题和反向问题进行全面的调查，从而导致更健壮和高质量的解决方案。从实际的角度来看，这个问题模拟了几个现实世界的制造系统，其中移除时间会显著影响生产计划。从理论上讲，这个调度问题特别复杂，因为它具有很强的NP-hard性质，对优化提出了重大挑战。为了解决这个问题，我们提出了一种有效的两阶段优化启发式方法，旨在提供接近最优的解决方案。在这种启发式方法中，在流程的每个阶段迭代地应用具有发布日期、移除时间和交付日期的并行机器调度。此外，开发了新的下界来评估所提出的启发式的质量。这些下界对于测量启发式和最优解之间的相对差距至关重要。在第一类下界中，除一个阶段外，所有阶段在容量方面都是宽松的。第二种是利用多项式并行机问题来估计后续阶段的最小空闲时间。对基准问题的大量实验测试证实了所提出方法的有效性，证明了它们对实际和理论调度挑战的适用性。结果表明，平均相对差距为1.05 %。

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引用次数: 0

Enhancing employee churn prediction with weibull time-to-event modeling 利用威布尔时间到事件模型增强员工流失预测

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2025.03.009

Hafiza Habiba Shabbir , Muhammad Hamza Farooq , Amna Zafar , Beenish Ayesha Akram , Talha Waheed , Muhammad Aslam

A Very common problem of employee attrition that requires precise and fast predictive models in modern business settings. We proposed a novel time-to-event Weibull Time-to-Event Recurrent Neural Network forecasting model in this study. This is cross-verified and validated by conducting an in-depth comparative study regarding the performance of the proposed Weibull Time to Event Recurrent Neural Network model against traditional models used in machine learning. This involved the comparison of a number of the classical models on their ability and performance, noting the strengths and weaknesses of the Weibull Time to Event Recurrent Neural Network improvements realized with long-range dependencies. Application of the HR dataset had shown that, while using the Weibull Time to Event Recurrent Neural Network model, the prediction worked out well as compared to other models. Our model R-squared value is 0.98, with very minimal Mean Squared Error (MSE) of 0.0032. This model makes it easier for human resource (HR) professionals and decision-makers to understand the predictions that it makes, enabling them to develop recruitment and retention strategies better adjusted to the needs of given employees.

一个非常常见的员工流失问题，在现代商业环境中需要精确和快速的预测模型。本文提出了一种新的威布尔时间到事件递归神经网络预测模型。通过对所提出的威布尔时间到事件递归神经网络模型与机器学习中使用的传统模型的性能进行深入的比较研究，这一点得到了交叉验证和验证。这涉及到对一些经典模型的能力和性能的比较，注意到威布尔时间到事件递归神经网络改进的优势和弱点，实现了长期依赖关系。HR数据集的应用表明，与其他模型相比，使用威布尔时间到事件递归神经网络模型的预测效果较好。我们的模型r平方值为0.98，均方误差（MSE）非常小，为0.0032。该模型使人力资源（HR）专业人员和决策者更容易理解它所做的预测，使他们能够制定更好地适应特定员工需求的招聘和保留策略。

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引用次数: 0

Improving energy harvesting by integrating smart materials into road infrastructure 通过将智能材料整合到道路基础设施中来改善能源收集

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2025.01.003

Mouna Ben Zohra , Amine Riad , Essaadia Azelmad , Abdelilah Alhamany

To improve energy harvesting from road surfaces prone to instability and fatigue, this study presents an innovative design that integrates shape memory alloys (SMAs) with piezoelectric materials. Piezoelectric materials convert mechanical vibrations from vehicular motion into electrical energy, but their efficiency is often reduced by irregular pressure fluctuations. In contrast, SMAs possess reversible deformation properties that adapt to stress and temperature changes, making them suitable for stabilizing vibrations and enhancing energy capture. Additionally, SMAs can act as indirect dynamic energy generators through vibration feedback. Therefore, this study presents an innovative design that combines SMAs and piezoelectric materials for energy harvesting on road surfaces. The main objective is to enhance energy production by stabilizing vibrations and increasing the lifespan of the harvesting system. The methodology involves modeling the SMA-piezoelectric system integration and conducting numerical simulations to validate its effectiveness. Findings demonstrate that this hybrid system increases electricity production by 36 % and extends system lifespan by 67 % by mitigating stress fluctuations. Thus, the present work demonstrates promising potential by building on previous literature. It introduces a novel hybrid SMA-piezoelectric system that stabilizes stress, enhances energy conversion efficiency, and extends lifespan, effectively addressing conventional design limitations. Key challenges include the high cost of SMAs and the need for extensive testing under varied conditions. Hence, upcoming study will focus on optimizing cost-effectiveness, exploring alternative materials, assessing long-term performance, and validating simulations through field tests. Additionally, efficient material combinations, long-term durability, and design optimization will be explored.

为了提高从容易不稳定和疲劳的路面上收集能量的能力，本研究提出了一种将形状记忆合金（sma）与压电材料相结合的创新设计。压电材料将车辆运动产生的机械振动转化为电能，但它们的效率经常因不规则的压力波动而降低。相比之下，sma具有适应应力和温度变化的可逆变形特性，使其适合稳定振动和增强能量捕获。此外，sma可以通过振动反馈作为间接的动态能量发生器。因此，本研究提出了一种结合sma和压电材料的创新设计，用于在路面上收集能量。主要目标是通过稳定振动和增加收获系统的寿命来提高能源产量。该方法包括对sma -压电系统集成进行建模并进行数值仿真以验证其有效性。研究结果表明，该混合系统通过减轻应力波动，可将发电量提高36% %，并将系统寿命延长67% %。因此，目前的工作显示出有希望的潜力，建立在以前的文献。它引入了一种新型的混合sma -压电系统，该系统稳定应力，提高能量转换效率，延长寿命，有效地解决了传统设计的局限性。主要挑战包括sma的高成本和需要在各种条件下进行广泛测试。因此，接下来的研究将集中在优化成本效益，探索替代材料，评估长期性能，并通过现场测试验证模拟。此外，高效的材料组合，长期耐用性和设计优化将被探索。

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引用次数: 0

IWOA-PTS: An improved whale optimization algorithm-based PTS technique for PAPR reduction in OFDM systems IWOA-PTS：一种改进的基于鲸鱼优化算法的PTS技术，用于降低OFDM系统中的PAPR

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2025.02.009

Somia Taba, Mohamed Amine Benchana, Salah Redadaa, Samir Ikni

The ordinary partial transmission sequence (OPTS) technique is known as an inherent and accurate peak-to-average power ratio (PAPR) reduction scheme in orthogonal frequency division multiplexing (OFDM). However, it suffers from a major drawback, an exponentially increasing complexity, mainly caused by the exhaustive search for the ideal set of phase factors that effectively reduces PAPR. This work proposes a new PTS scheme based on an improved whale optimization algorithm (IWOA) to search for an appropriate combination of phase factors that mitigates PAPR with much lower complexity. The particular hunting behavior of humpback whales is mimicked, and its mathematical model is used in the PTS technique. The modified mutualism phase in the algorithm balances its exploration-exploitation capabilities, ensuring convergence to the best global solution and avoiding less efficient solutions. The simulation results confirm the superiority of IWOA-PTS in terms of computational load and PAPR reduction

普通部分传输序列（OPTS）技术是正交频分复用（OFDM）中固有的、精确的峰均功率比（PAPR）降低方案。然而，它有一个主要缺点，即复杂性呈指数级增长，这主要是由于穷尽搜索有效降低PAPR的理想相位因子集造成的。本文提出了一种新的PTS方案，该方案基于改进的鲸鱼优化算法（IWOA）来搜索相位因子的适当组合，从而以更低的复杂性减轻PAPR。模拟座头鲸的特殊捕猎行为，并将其数学模型用于PTS技术。算法中改进的互惠阶段平衡了其探索-开发能力，确保收敛到最佳全局解决方案并避免效率较低的解决方案。仿真结果证实了IWOA-PTS在计算负荷和PAPR降低方面的优越性

引用次数: 0

Strategic and technological drivers of ambidexterity and sustainability: Impact assessment in UAE project-based public sector organizations 两面性和可持续性的战略和技术驱动因素：阿联酋基于项目的公共部门组织的影响评估

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2024.11.008

Mey Al Leem , Khalil Abdelrazek Khalil , Alaa M. Ubaid

This research aims to propose a framework for applying ambidexterity in the UAE’s public sector project-based organization. The study uses a quantitative research methodology to survey 400 public sector employees to establish the correlation between organizational culture, leadership, technology, and ambidexterity. The study validates these factors' importance to ambidexterity using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The study reveals that a supportive organizational culture and transformational leadership positively influence ambidextrous capabilities, while technology adoption moderates the impact of leadership and culture on ambidexterity. Furthermore, the findings reinforce the hypotheses that human capital and employee flexibility facilitate ambidextrous strategies, mainly when supported by technology. However, the study identifies factors like organizational silos, resistance to change, and resource scarcity, which are the main barriers to ambidexterity. Therefore, the study contributes to the literature by proposing a context-specific framework for ambidexterity in the UAE’s public sector. It offers valuable insights to policymakers and public sector managers about overcoming the challenges inherent in the ambidexterity process. The validated framework provides tangible guidelines for building ambidexterity, especially regarding technology resources, organizational culture, and leadership.

本研究旨在提出在阿联酋公共部门基于项目的组织中应用二元性的框架。本研究采用定量研究方法对400名公共部门雇员进行调查，以建立组织文化、领导力、技术和二元性之间的相关性。本研究利用探索性因子分析（EFA）和验证性因子分析（CFA）验证了这些因素对二元性的重要性。研究发现，支持性组织文化和变革型领导正向影响员工的双灵巧能力，而技术采用会调节领导和文化对双灵巧能力的影响。此外，研究结果强化了人力资本和员工灵活性促进双灵巧战略的假设，主要是在技术支持下。然而，该研究确定了组织孤岛、抗拒变革和资源稀缺等因素，这些因素是双元性的主要障碍。因此，该研究通过为阿联酋公共部门的二元性提出一个具体背景的框架，为文献做出了贡献。它为政策制定者和公共部门管理者提供了宝贵的见解，帮助他们克服两重性过程中固有的挑战。经过验证的框架为构建双灵巧性提供了切实的指导方针，特别是在技术资源、组织文化和领导方面。

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引用次数: 0

Redundancy allocation and optimal buffer size determination in series-parallel production systems: A hybrid approach 串并联生产系统中冗余分配和最优缓冲区大小的确定：一种混合方法

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2025.03.008

Mojtaba Aghaei , Maghsoud Amiri , Mani Sharifi , Seyyed Jalaladdin Hosseini Dehshiri , Mohammad Taghi Taghavifard

Buffer allocation and redundancy allocation problems arose during the design of the production line. This study investigated these two problems as an integer nonlinear multi-objective model. The purposes of the model included maximizing availability and minimizing overall system costs and buffer capacity. Machine failures were divided into preventive and emergency categories, and their costs were factored into the cost goal function. Furthermore, each machine's failures were considered accidental and followed Weibull distribution functions. To solve the problem, a method combining the design of experiments, simulation, neural network, and meta-heuristic algorithm was applied. The system was simulated using the results of designed experiments, and the results in neural networks were analyzed to estimate the functions related to cost and availability purposes. Finally, the neural network's estimated functions, another objective function (buffer capacity), and the problem's constraints were implemented in the meta-heuristic non-dominated sorting genetic algorithm III (NSGA-III) to obtain Pareto sets. The results were compared to the non-dominated sorting genetic algorithm II (NSGA-II) and the Multi-objective particle swarm optimization algorithm (MOPSO). The applicability of the proposed approach was demonstrated using a real case, and the outcomes validated the algorithm's effectiveness.

在生产线设计过程中出现了缓冲区分配和冗余分配问题。本文将这两个问题作为一个整数非线性多目标模型来研究。该模型的目的包括最大化可用性和最小化总体系统成本和缓冲容量。将机器故障分为预防性故障和紧急故障两类，并将其成本计入成本目标函数。此外，每台机器的故障被认为是偶然的，并遵循威布尔分布函数。为了解决这一问题，采用了实验设计、仿真、神经网络和元启发式算法相结合的方法。利用设计的实验结果对系统进行了仿真，并对实验结果进行了神经网络分析，以估算出与成本和可用性相关的函数。最后，利用元启发式非支配排序遗传算法III （NSGA-III）实现神经网络的估计函数、另一个目标函数（缓冲容量）和问题约束，得到Pareto集。将结果与非支配排序遗传算法II （NSGA-II）和多目标粒子群优化算法（MOPSO）进行比较。通过实例验证了所提方法的适用性，结果验证了算法的有效性。

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引用次数: 0

Multi-objective mathematical model for optimal wind turbine placement in wind farm under uncertainty 不确定条件下风电场风力机优化布置的多目标数学模型

IF 2.2 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY

Journal of Engineering Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jer.2024.09.014

Guanting Li , Tzu-Chia Chen

The main objective of this research is to introduce three energy risk management models grounded in optimization techniques for the strategic placement of wind turbines, considering wake effects and uncertainties in wind speed and direction. For this purpose, wind speed and direction data are gathered, and Monte Carlo simulation is employed to model the uncertainties. Subsequently, the risk management models undergo optimization using Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Pareto envelope-based selection algorithm II (PESA-II), and Multi-Objective Particle Swarm Optimization (MOPSO) algorithms. Findings reveal that the wind farm's maximum power output reaches approximately 5.8 megawatts across all three algorithms and optimal turbine placements. A risk assessment was conducted using a tenth percentile criterion, revealing a significant production risk within the study area, with production falling below 1.8 megawatts in 90 % of cases. Regarding the performance evaluation of the algorithms across all three models, superior performance in terms of solution proximity to the ideal solution is exhibited by PESA-II, while enhanced diversity and solution spread compared to the other algorithms are demonstrated by NSGA-II.

本研究的主要目的是介绍三种基于优化技术的能量风险管理模型，用于风力涡轮机的战略布局，考虑尾流效应和风速和风向的不确定性。为此，采集风速和风向数据，并采用蒙特卡罗模拟对不确定性进行建模。随后，采用非支配排序遗传算法II （NSGA-II）、Pareto包络选择算法II （PESA-II）和多目标粒子群优化（MOPSO）算法对风险管理模型进行优化。研究结果显示，在所有三种算法和最佳涡轮机位置下，风电场的最大输出功率约为5.8兆瓦。使用十分之一百分位标准进行风险评估，揭示了研究区域内的重大生产风险，90% %的情况下产量低于1.8兆瓦。对于三种算法的性能评价，PESA-II在解接近理想解方面表现出优越的性能，而NSGA-II在多样性和解扩散方面表现出优于其他算法的性能。

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引用次数: 0