Energy Science & Engineering最新文献

{"title":"Hybrid Simulation–Machine Learning Surrogates for Coordinate-Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision-Support Tool","authors":"Bassam Musheer Kareem,&nbsp;Abdolsalam Ebrahimpour,&nbsp;Jafar Ghafouri,&nbsp;Roghayyeh Motallebzadeh","doi":"10.1002/ese3.70592","DOIUrl":"https://doi.org/10.1002/ese3.70592","url":null,"abstract":"<p>Driven by the global shift away from fossil fuels, solar and wind resources are increasingly important for sustainable power planning, especially in data-scarce regions. This study proposes a hybrid simulation–machine learning framework to estimate renewable energy yields across Iraq using minimal geographic inputs. Hourly meteorological variables for 2015–2024 (solar radiation, wind speed, temperature, and humidity) were retrieved from the NASA POWER database for ten representative Iraqi cities at a gridded resolution of approximately 0.1°–0.2°. These data were converted to EPW format and used in EnergyPlus to simulate electricity generation from a standardized PV system (20% efficiency, 1 m² area) at three fixed tilt angles (0°, 30°, 60°) and from a 1 kW wind turbine. The resulting EnergyPlus outputs were then used to train two surrogate predictors: a random forest (RF) model for solar yield and a Feedforward Neural Network (FNN) for wind yield. Using an 80/20 split and cross-validation within the simulated dataset, the RF reproduced EnergyPlus-simulated solar energy with strong agreement within the modeled dataset (<i>R</i>² ≈ 0.98, MSE ≈ 1.45), while the FNN showed strong agreement with the simulated wind-energy outputs (<i>R</i>² ≈ 0.97, MSE ≈ 2.36). Feature analysis indicated that PV tilt and seasonal cycles dominate solar yield variability, whereas elevation and seasonality are the primary drivers for wind yield. For practical decision support, the trained models were deployed in a Streamlit web interface that returns monthly and annual kWh estimates from latitude/longitude, elevation, and configuration inputs. Because validation is performed against EnergyPlus simulation outputs (simulation-derived ground truth), reported accuracy should be interpreted as simulation-level fidelity rather than verified predictive performance against measured field generation.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4584-4607"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Probabilistic Fractional Order Physics Informed Mamba Kolmogorov-Arnold Network for State-of-Charge Estimation in Grid-Connected Battery Energy Storage Systems","authors":"Arun Kumar Rawat,&nbsp;Subhash Chandra,&nbsp;Vinay Kumar Deolia","doi":"10.1002/ese3.70606","DOIUrl":"https://doi.org/10.1002/ese3.70606","url":null,"abstract":"<p>Accurate state of charge (SOC) estimation is critical for reliable battery energy storage system (BESS) operation in renewable grids. However, conventional integer-order and deterministic models often fail to capture long-memory electrochemical diffusion or quantify uncertainty under dynamic conditions. To address this, this paper proposes the probabilistic fractional-order Mamba Kolmogorov-Arnold network (PFO-Mam-KAN) framework. This architecture uniquely integrates a linear-complexity temporal Mamba encoder to efficiently model long sequences, a probabilistic KAN decoder for estimating time-varying parameter distributions, and a differentiable fractional-order physics layer using constant phase elements, to capture non-Markovian dynamics. These components are unified via an adaptive Kalman-gated correction mechanism that dynamically modulates reliance on measurements based on propagated uncertainty. Validated on a hybrid AC/DC microgrid using the Sandia database, the framework achieves a superior SOC estimation RMSE of 0.31% and MAE of 0.18%, outperforming contemporary advanced observers. The model demonstrates improved SOC estimation under 3% measurement noise and temperature variations (10°C-40°C), while exhibiting less computation burden.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4734-4751"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70606","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variance-Empirical Mode Decomposition Method for Fault Detection in MMC-HVDC Transmission Lines","authors":"Seyed Amir Hosseini,&nbsp;Behrooz Taheri","doi":"10.1002/ese3.70595","DOIUrl":"https://doi.org/10.1002/ese3.70595","url":null,"abstract":"<p>In this paper, a new method for fast and accurate fault detection in HVDC transmission lines based on modular multilevel converters (MMC HVDC) is presented. The proposed method, named variance-based empirical mode decomposition (VEMD), relies on the statistical analysis of the variance of voltage and current signals measured from one side of the line and their decomposition using the empirical mode decomposition algorithm. As an indicator sensitive to sudden changes, variance highlights the transient characteristics caused by the occurrence of a fault, and the decomposition of the signal into oscillatory intrinsic mode functions allows the extraction of hidden frequency components. The performance of the proposed method has been evaluated through extensive simulation in the PSCAD environment and implementation in MATLAB software, as well as practical testing on a hardware system. The results show that the VEMD method is capable of detecting various types of faults, including high-impedance faults up to 200 Ω, at different locations along the transmission line (25% to 90% of the line length). The fault detection time in noise-free conditions is 12.46 ms on average, and in the presence of measurement noise with a signal-to-noise ratio of 40 dB, it is up to 22.25 ms. These results indicate the high accuracy, reasonable speed, noise immunity, and stable performance of the proposed method and demonstrate that the VEMD method can be used as a practical, reliable, communication-link-free solution for protecting MMC-based HVDC transmission lines.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4626-4640"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70595","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-Economic and Quasi-Dynamic Load Flow Analysis of a Hybrid Renewable Microgrid for Coastal Industrial Loads","authors":"Md. Behesty Hasan Sagor,&nbsp;Md Abdus Samad Kamal,&nbsp;Md. Feroz Ali,&nbsp;Md. Mahedi Hasan,&nbsp;Fahad Saleh Al-Ismail,&nbsp;Md Shafiul Alam,&nbsp;Mohammad Ali","doi":"10.1002/ese3.70601","DOIUrl":"https://doi.org/10.1002/ese3.70601","url":null,"abstract":"<p>This study evaluates the techno-economic feasibility and technical performance of a grid-connected hybrid renewable microgrid for Mongla Port, Bangladesh, using a dual-framework methodology that integrates HOMER Pro–based lifecycle cost optimization with DIgSILENT PowerFactory–based quasi-dynamic load flow analysis. The proposed system combines 250 kW solar photovoltaic, 450 kW wind turbines, and a national grid connection, optimally sized through least-cost optimization across 8760 annual simulation hours. The optimal configuration (Scenario A) achieves a cost of energy of 0.0341 USD/kWh, net present cost of 531,132 USD, renewable fraction of 70.9%, and a simple payback period of 4.86 years, substantially outperforming the grid-only baseline. Quasi-dynamic load flow analysis confirms that renewable integration improves voltage regulation across all seasonal operating conditions, with a critical demand threshold of 350 kW identified beyond which reactive power compensation will be required. Seasonal analysis across representative winter, summer, and monsoon days demonstrates system robustness under the full range of meteorological and demand variability. Sensitivity analysis confirms economic viability under ±40% variations in key meteorological and financial parameters, identifying grid tariff escalation as the dominant risk factor. The findings provide transferable decision-support guidance for coastal industrial microgrids across developing economies in South and Southeast Asia.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4673-4699"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70601","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Algorithm-Driven Analysis of Gravitational Water Vortex Power Plant Runner Performance: A Comparative Study Integrating Experimental and Computational Fluid Dynamics","authors":"Zakaria. A. Mwakitwange,&nbsp;Adam Faraji","doi":"10.1002/ese3.70604","DOIUrl":"https://doi.org/10.1002/ese3.70604","url":null,"abstract":"<p>The gravitational water vortex power plant (GWVPP) has emerged as a promising renewable energy technology, characterized by low investment costs, a simple design, and minimal maintenance requirements. However, its performance has been constrained by suboptimal parameters, particularly in critical components such as the runner. This paper presents a comprehensive exploration of the optimization process for GWVPP runners, using a comparative analysis driven by a genetic algorithm (GA) prediction that integrates experimental data and computational fluid dynamics (CFD) simulations. The investigation focuses on three key performance parameters: power, torque, and efficiency, assessed over a rotational speed range of 1.91–3.26 rad/s. The findings show a consistent trend across all techniques, with performance improving with rotational speed up to an optimal range of around 2.6–2.7 rad/s, after which it declines. There is strong agreement between GA predictions and CFD simulations, demonstrating the GA's ability to capture and optimize system behavior. Experimental results show a similar pattern, but with lower efficiency, particularly at higher rotational speeds, due to practical losses, flow disruptions, and measurement uncertainties that are not fully captured in the numerical models. Sensitivity analysis emphasizes the impact of rotational speed, hub-blade angle, and blade number on system performance. Overall, the findings demonstrate that GA is a reliable and effective approach for improving GWVPP performance, with results consistent with CFD simulations and supported by experimental data. The study emphasizes the viability of GWVPP systems as a long-term energy option for low-head applications.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4722-4733"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on Roof-Control Technology for Gob-Side Entry Retaining Under Composite Roofs","authors":"Dong Li,&nbsp;Yujiang Zhang,&nbsp;Yunlou Du,&nbsp;Haodong Zheng,&nbsp;Baoji Yang","doi":"10.1002/ese3.70610","DOIUrl":"https://doi.org/10.1002/ese3.70610","url":null,"abstract":"<p>This paper addresses the challenge of roof control during gob-side entry retaining under a composite roof. Taking the 15210 working face of Hecaogou No. 1 Mine as the engineering background, borehole-camera exploration, numerical simulation, and field measurements are integrated to systematically investigate the mining-induced failure mechanism of roadway surrounding rock and the corresponding stability-control technology. Borehole observations reveal typical damage features of a composite roof, characterized by pervasive fractures and pronounced interlayer separation. FLAC^3D simulations clarify the spatiotemporal evolution of the surrounding-rock plastic zone with face advancement; the whole process is divided into four stages—stable excavation, presplitting-induced expansion, mining-induced expansion, and post-mining stabilization—and the corresponding spatial regions are identified. The results show that: (1) The spatiotemporal evolution law of the plastic zone from excavation to abandonment exhibits a “dynamic–static coupling” mechanism, where the dynamic failure process corresponds to the static damage state. This correspondence provides a key theoretical basis for interpreting roadway deformation mechanisms and designing stage-wise support schemes. (2) By analyzing the stress-field evolution under presplitting and mining disturbance, the mechanical mechanism of asymmetric plastic-zone propagation is revealed. The stress field around the retained entry presents an S-shaped three-zone distribution: mining-influence stable zone, mining-influence zone, and excavation-influence stable zone. This stress evolution is the fundamental reason for asymmetric plastic-zone expansion. (3) The propagation morphology is clarified: during presplitting and mining disturbance, the depth and extent of the plastic zone increase markedly, and roof development is far greater than floor development. Damage and deformation concentrate around the presplitting boreholes and in the roof region extending from the boreholes toward the working face. (4) Based on the above spatiotemporal laws, a targeted reinforcement-support method is proposed. Guided by plastic-zone morphology and field monitoring, the method accurately determines reinforcement locations and parameters, effectively stabilizing surrounding rock and ensuring safe longwall production.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4770-4788"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70610","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Inverters With Dual Switching Frequencies for Switched Reluctance Motors","authors":"Fares S. El-Faouri,&nbsp;Majd G. Batarseh,&nbsp;Hamzeh J. Jaber,&nbsp;Ayman Faza,&nbsp;Wejdan Abu Elhaija","doi":"10.1002/ese3.70617","DOIUrl":"https://doi.org/10.1002/ese3.70617","url":null,"abstract":"<p>This paper proposes a novel inverter topology for driving switched reluctance motors (SRMs), utilizing two conventional three-phase inverters for a total of 12 switches. To reduce cost, only six of these switches are Silicon Carbide (SiC), while the remaining six are more economical insulated gate bipolar transistors (IGBTs). The proposed concept exploits the variable inductance characteristics of SRMs. When the rotor is at a low-inductance, the drive transfers operation to the SiC switches to enable high-frequency switching and precise current control. Conversely, during high-inductance rotor positions, the inverter shifts to IGBT switches, minimizing system cost without compromising performance. The topology and control strategy were validated through multiphysics finite element analysis (FEA) simulations. Key performance metrics, including current waveform, torque, radial force, stator vibration, and acoustic noise were evaluated and compared.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4856-4865"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70617","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis and Classification of Partial Shading Conditions in Photovoltaic Arrays","authors":"Hamid Reza Parsa,&nbsp;Mohammad Sarvi","doi":"10.1002/ese3.70613","DOIUrl":"https://doi.org/10.1002/ese3.70613","url":null,"abstract":"<p>With the escalating global transition toward renewable energy, ensuring the operational stability and reliability of photovoltaic (PV) systems has become a critical concern. Among the various factors that impair PV system performance, partial shading emerges as a particularly challenging issue. This study conducts an in-depth investigation of partial shading effects by analyzing the power–voltage (P–V) response of PV arrays. A set of novel mathematical formulations is developed to characterize the extremum points on P–V curves under diverse shading scenarios. These formulations offer essential insights into the dynamic behavior of PV arrays subjected to non-uniform irradiance, facilitating accurate detection and classification of partial shading conditions. The proposed approach enhances fault diagnosis and contributes to more effective control strategies for maintaining system performance. Furthermore, four diagnostic features derived from the P–V curve analysis are employed to distinguish between simple and complex shading patterns using two distinct machine learning classifiers. The results confirm that the proposed models reliably discriminate between different levels of shading complexity, even when using a single extracted feature.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4810-4818"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70613","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Camber of S-Series Airfoils on Aerodynamic Performance, Entropy Generation Rate, Irreversibility, and Second Law Efficiency of Horizontal Axis Wind Turbines","authors":"Mitra Yadegari","doi":"10.1002/ese3.70611","DOIUrl":"https://doi.org/10.1002/ese3.70611","url":null,"abstract":"<p>Today, wind turbines play a pivotal role in power generation due to the depletion of nonrenewable resources all over the world. Therefore, it is imperative to enhance their affordability by improving the efficiency and reducing the cost of production. The use of airfoils with high lift-to-drag ratios is one of the effective techniques to increase the power generation in wind turbines, which depends on the attack angle, flow velocity, thickness, camber, and trailing edge angle of the airfoil. Moreover, entropy generation analysis can propose a proper design by reduction of losses and exergy destruction in wind turbines. The present study aims to investigate the influences of camber of S-series airfoils at different angles of attack (0°, 5°, 10°, 15°, and 20°) on aerodynamic performance, entropy generation rate, irreversibility, and second law efficiency of horizontal axis wind turbines in turbulent flow regime to the best of our knowledge is the first time. The results show that camber has a significant impact on the aerodynamic performance of wind turbines. The average second law efficiency increases by 242.86% with an increase in camber, while irreversibility decreases by 18.37%. Moreover, the leading edge accounts for the second largest proportion of local entropy generation, after the wake region.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4789-4809"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models","authors":"Abdoalateef Alzhrani,&nbsp;Abdullahi Abubakar Mas'ud,&nbsp;Mohd Khairul Amri Kamarudin,&nbsp;Firdaus Muhammad-Sukki,&nbsp;Abdullahi Mohammad","doi":"10.1002/ese3.70616","DOIUrl":"https://doi.org/10.1002/ese3.70616","url":null,"abstract":"<p>Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine learning (ML) algorithms, that is, Decision Tree Regression (DTR), Multiple Linear Regression (MLR), Random Forest (RF), k-Nearest Neighbors (kNN), and Extreme Gradient Boosting (XGBoost) for forecasting PV power output in Jazan, Saudi Arabia. Jazan has a tropical desert climate with high humidity, seasonal wind speed variation, and coastal proximity, unlike the arid inland regions typically studied in the KSA. This makes it an ideal testbed for evaluating model robustness under varied meteorological parameters. The models were trained on a 6-year (2017–2022) dataset comprising hourly measurements of four different meteorological parameters and evaluated using coefficient of determination (<i>R</i>²), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Wilcoxon signed-rank test. Among the models used, XGBoost achieved the highest accuracy (<i>R</i>² = 0.93, MAE = 7.3, RMSE = 20.38), outperforming all others. The results highlight the effectiveness of ensemble methods in PV power forecasting and offer valuable guidance for improving forecast accuracy in regions with comparable climates.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 10","pages":"4838-4855"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}