Article
Construction & Building Technology
Yun-Hao Dong, Fang-Le Peng, Bing-Hao Zha, Yong-Kang Qiao, Hu Li
Summary: This study presents an intelligent layout planning model based on NSGA-II algorithm to optimize the planning scheme for underground space surrounding metro stations. It successfully converts the layout planning issue into a multi-objective optimization problem and develops a decision-making method for planning scheme selection. The proposed model is effectively applied in case studies in Shanghai and Qingdao to improve the rational use of underground space.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Materials Science, Multidisciplinary
Abdul Faheem, Faisal Hasan, Abid Ali Khan, Bharat Singh, Md Ayaz, Farhan Shamim, Kuldeep K. Saxena, Sayed M. Eldin
Summary: Nickel-Titanium based shape memory alloys (SMAs) are unique smart materials with remarkable properties that make them suitable for various applications. This study investigated the machinability of Ni55.65Ti-SMAs using non-traditional electric discharge machining process. The effects of input process parameters on surface roughness and material removal rate were studied, and optimal results were obtained using NSGA-II and TOPSIS methods.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2023)
Article
Chemistry, Multidisciplinary
Dongyi Wang, Guoli Wang, Hang Wang
Summary: Autonomous lane changing is an important application scenario in autonomous driving technologies, as it can reduce traffic congestion and improve road safety. However, determining the weight of the objective function for the multi-objective optimization problem of lane changing trajectory is still uncertain. Therefore, this paper proposes an optimization method based on the combination of NSGA-II and TOPSIS, which provides a new idea for solving the lane change trajectory algorithm's multi-objective optimization problem. Simulations show that the proposed method can generate satisfactory trajectory for automatic lane changing actions.
APPLIED SCIENCES-BASEL
(2023)
Article
Thermodynamics
Aminu Yusuf, Nevra Bayhan, Hasan Tiryaki, Bejan Hamawandi, Muhammet S. Toprak, Sedat Ballikaya
Summary: This study examines the output performances of different equations in a hybrid system combining thermoelectric generators with concentrated photovoltaic cells, utilizing nanostructured thermoelectric materials. By optimizing parameters and selecting appropriate models, it was found that the system performs best when the load resistance is less than the internal resistance of the TEG.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Thermodynamics
Ruitian Yu, Huaizhi Han, Chengang Yang, Wen Luo
Summary: A new concept of cooling channels design with hybrid ribs is proposed in this study, which utilizes response surface methodology and non-dominated sorting genetic algorithm II to optimize design variables for optimal heat transfer and flow performance. Surrogate models in quadratic polynomial forms are utilized to assess the statistical significance of each term, resulting in the determination of the best design solution with guiding significance for cooling channels optimization.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2022)
Article
Agronomy
Yuyang Shan, Ge Li, Shuai Tan, Lijun Su, Yan Sun, Weiyi Mu, Quanjiu Wang
Summary: The contradiction between water demand and water supply in the Yellow River Delta restricts corn yield in the region. It is of great significance to formulate reasonable irrigation strategies to alleviate regional water use and improve corn yield.
Article
Computer Science, Artificial Intelligence
Na Sun, Shuai Zhang, Puhang Jin, Nan Li, Siyuan Yang, Zijian Li, Ke Wang, Xiangmiao Hao, Fan Zhao
Summary: This paper develops an intelligent plate fin-and-tube heat exchanger design system that is entirely self-programming, aiming to achieve quick design. The system consists of four modules: formulation, optimization, post-processing, and decision-making. It is implemented and validated with the optimization of ellipse tubes in a plate-fin heat exchanger, showing its ability to quickly design and reduce computation time.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Tobias Glasmachers, Oswin Krause
Summary: This article introduces the characteristics and performance of the class of algorithms called Hessian Estimation Evolution Strategies (HE-ESs), and provides two strong guarantees for the (1 + 4)-HE-ES algorithm: stability of covariance matrix update and linear convergence on all convex quadratic problems, regardless of the problem instance.
EVOLUTIONARY COMPUTATION
(2022)
Article
Thermodynamics
Ananta Kumar Das, Somashekhar S. Hiremath
Summary: A novel butterfly-wing vortex generator was fabricated inside a microchannel by micro milling process and validated by experiments. Numerical simulation and optimization were used to study the thermo-hydraulic performance and entropy-generation in the microchannel. Response surface method and multi-objective optimization were applied to find the optimal input parameters and maximize the performance factor while minimizing the augmentation entropy-generation number.
APPLIED THERMAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Qiang Luo, Qing Fan, Qianwang Deng, Xin Guo, Guiliang Gong, Xiahui Liu
Summary: Previous research has overlooked the arrangement of on-hand inventory saved in the warehouse in the integrated scheduling problems. In this study, we propose a new production-inventory-distribution integrated scheduling problem that considers the production plan, allocation plan of on-hand inventory, and distribution decision simultaneously. We develop a mixed integer linear programming model and a modified NSGA-II algorithm to solve the problem. The proposed integration mode is shown to be effective compared with sequential scheduling methods commonly used in actual production.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Chemical
Xuanxuan Wang, Wujun Ji, Yun Gao
Summary: This study investigates the multi-objective optimization design of hybrid electric vehicles (HEVs) by analyzing the transmission system parameters and using the NSGA-II algorithm. The results show that the optimization algorithm can adjust the engine's working point, improve efficiency by over 10%, reduce fuel consumption by an average of 2.15% for four-gear vehicles, decrease fuel consumption per 100 km by over 3%, achieve a maximum climbing gradient of 33.9%, and increase the power factor of the direct gear by 15%. The proposed multi-objective energy consumption optimization design effectively enhances the economic and dynamic performance of the vehicle and reduces fuel consumption, providing a reference for the optimization of hybrid vehicle transmission systems.
Article
Computer Science, Theory & Methods
Xinmei Zhang, Nannan Liang, Chen Chen
Summary: This study establishes a multi-objective optimization model with a double priority of safety and economy, and utilizes an improved non-dominated sorting genetic algorithm and entropy weight-TOPSIS method for solving, which significantly improves the algorithm performance. The model and algorithm provide decision support for container storage operation and management.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2022)
Article
Thermodynamics
Wu Xiao, Andi Cheng, Shuai Li, Xiaobin Jiang, Xuehua Ruan, Gaohong He
Summary: This work proposes the design and optimization strategy of steam power system to address the standardized discharge of SO2 and NOX, establishes a mathematical model describing the coupling of SPS with desulfurization and denitrification, and uses the NSGA-II algorithm to obtain Pareto optimization curve.
Article
Chemistry, Multidisciplinary
Pericle Varasteanu, Mihaela Kusko
Summary: Modifying surface plasmon resonance sensors with 2D materials can enhance sensitivity but increase complexity. This study used a multi-objective genetic algorithm and transfer matrix method to optimize sensor performance, achieving high sensitivity and low reflectivity.
APPLIED SCIENCES-BASEL
(2021)
Article
Thermodynamics
Min Dai, Han Yang, Fusheng Yang, Zaoxiao Zhang, Yunsong Yu, Guilian Liu, Xiao Feng
Summary: This study proposes a novel Multi-strategy Ensemble Non-dominated Sorting Genetic Algorithm-II (MENSGA-II) for the multi-objective optimization of the IPA/DIPE/Water separation process. The results demonstrate the superiority of the MENSGA-II algorithm in terms of robustness, convergence speed, and distribution of Pareto front, leading to energy saving, emission reduction, and increased profitability.
Article
Engineering, Electrical & Electronic
I. Arul Doss Adaikalam, C. K. Babulal
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING
(2020)
Article
Engineering, Electrical & Electronic
Jain B. Marshel, C. K. Babulal
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2020)
Article
Acoustics
Bakrutheen Moosasait, Willjuice Iruthayarajan Maria Siluvairaj
Summary: The study demonstrates that ultrasonic treatment can significantly reduce the pour point of vegetable oils, meeting the standard value for liquid insulation and providing a new pathway for the application of low pour point vegetable oils as liquid insulation in power transformers in cold climate areas.
ULTRASONICS SONOCHEMISTRY
(2021)
Article
Engineering, Electrical & Electronic
Bakrutheen Moosasait, Willjuice Iruthayarajan Maria Siluvairaj, Ramachandran Eswaran
Summary: This study proposes the development of low viscous vegetable oil based liquids for insulating power transformers, achieved through processing natural esters with different levels of aromatic solvent benzyl benzoate. The inclusion of benzyl benzoate has shown considerable reduction in viscosity of vegetable oil based liquids, encouraging their application in high voltage power transformers.
IET SCIENCE MEASUREMENT & TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
M. P. E. Rajamani, R. Rajesh, M. Willjuice Iruthayarajan
Summary: This paper investigates the control problem of dynamic behavior in a Buck converter and proposes an improved optimization algorithm. By considering the PID controller gain values and capacitance selection, better performance is achieved. The research results compare the performance of different algorithms in terms of time-domain specifications and ripple voltage.
IETE JOURNAL OF RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Zamrooth Dawood, C. K. Babulal
Summary: The study introduces a novel algorithm for PQD classification combining feature selection and machine learning techniques, utilizing DWT for signal decomposition and PNN-adaptive AABC algorithm for classification. By optimizing feature selection, discarding redundant features and retaining useful ones, improving convergence rate, and enhancing accuracy, among other aspects.
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Ajitha Priyadarsini Sobhanam, Paulraj Melba Mary, Willjuice Iruthayarajan Mariasiluvairaj, Rajeev Davy Wilson
Summary: This paper proposes an improved artificial electric field algorithm (IAEF) for automatic generation control (AGC) in a multi-area power system to minimize area control errors and obtain optimal solutions. The study examines four area AGC systems with PID controllers and obtains an optimal gain value for the PID controller using IAEFA to minimize area control errors. Performance evaluations using nine different test functions and comparisons with other optimization approaches demonstrate that the proposed IAEF-based AGC method achieves better control errors and optimal tuning of the PID controller.
IETE JOURNAL OF RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
B. Vigneshwaran, M. Willjuice Iruthayarajan, R. Maheswari
Summary: Measurement and recognition of partial discharge (PD) is crucial for monitoring and diagnosing faults in high-voltage transformers. Past approaches for PD classification relied on feature extraction by experts and clean PD data in the lab, but real-time circumstances may involve different PD patterns and external interference. The use of deep convolutional neural networks (CNN) for image classification poses challenges in fine-tuning hyperparameters. This study proposes an enhanced particle swarm optimization method for hyperparameter tuning and employs random minority and majority sampling to address imbalanced datasets. Experimental results demonstrate a 7.6% improvement in recognition rate compared to other deep learning methods under noisy conditions.
ELECTRICAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
B. Vigneshwaran, M. Willjuice Iruthayarajan, R. Maheswari
Summary: This paper introduces the use of deep learning (DL) methods and Bayesian optimization (BO) techniques to predict the types of faults occurring in power apparatus and optimize hyperparameters, showing a high recognition rate.
Article
Automation & Control Systems
Preethi Vela Anandam, Shunmugalatha Alagarsamy, Babulal Chittu Kuppusamy
Summary: This article investigates the effects of uncertainties on multi-objective reactive power management and proposes a solution based on ISDE+. The generated non-dominated optimal solutions are evaluated using a hyper-volume indicator, considering real power loss minimization and voltage deviation minimization as the goal functions.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2022)
Article
Engineering, Electrical & Electronic
P. Pon Ragothama Priya, S. Baskar, S. Tamil Selvi, C. K. Babulal
Summary: This paper proposes a new long-term planning methodology for Multi-objective Distributed Generation Placement and Sizing (MO-DGPS) with the aim of optimizing energy loss, CO2 emission, overall cost, system voltage stability, and reliability. The problem is formulated to incorporate uncertainties such as intermittent power generation and forced outages, as well as time-varying loads and load growth. The proposed method is validated using test systems and a fast-elitist Non-dominated Sorting Genetic Algorithm-II. The results show that the combination of biomass and conventional DG units provides better objective values and performance indices, minimizing energy loss and CO2 emission.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Ramaveerapathiran Arun, Rathinam Muniraj, Maria Siluvairaj Willjuice Iruthayarajan
Summary: In this study, the traditional particle swarm optimization technique is used to optimize parameters of PID controllers with and without delayed external reset for the first order plus dead-time process. The performance and robustness of the controllers are compared, showing that the PI controller with delayed external reset outperforms in time delay processes.
REVUE ROUMAINE DES SCIENCES TECHNIQUES-SERIE ELECTROTECHNIQUE ET ENERGETIQUE
(2021)
Article
Automation & Control Systems
Arun R. Pathiran, R. Muniraj, M. Willjuice Iruthayarajan, S. R. Boselin Prabhu, T. Jarin
Summary: This paper analyzes the robustness of the time-delayed PI controller for the First Order plus Dead-Time (FOPDT) process model, and introduces a unified tuning method for processes with different dead-time to time constant ratios. The efficiency of the proposed unified tuning technique is demonstrated through simulation examples and experimental evaluation. Additionally, the applicability of the technique to process models other than FOPDT is shown via simulation examples.
ARCHIVES OF CONTROL SCIENCES
(2021)
Article
Multidisciplinary Sciences
S. Ajmal Ahamed, S. Mohamed Riyaz, A. Mahadevan, J. Mohamed Hathim, M. Bakrutheen, M. Willjuice Iruthayarajan
Summary: This study experimentally analyzed the ability of vegetable oil-based liquid insulation as an alternative medium in moisture-rich environments, and found that the addition of moisture led to a significant reduction in breakdown voltage of the oil samples, possibly due to the influence of moisture on the molecular components of the oil.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
