Article
Engineering, Electrical & Electronic
Irfan Mulyawan Malik, Anurag Sharma, R. T. Naayagi
Summary: This article proposes a comprehensive three-stage fuzzy logic approach for dissolved gas analysis (DGA) of transformer oil. By utilizing current and historical data, it emulates best practices in transformer health analysis, achieving accurate fault identification with the added benefits of time and cost savings.
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION
(2023)
Article
Engineering, Electrical & Electronic
T. Manoj, C. Ranga, Sherif S. M. Ghoneim, U. Mohan Rao, Saad A. Mohamed Abdelwahab
Summary: Various fault diagnosis techniques in oil immersed power transformers have been studied for the past two decades and are well documented in the literature. Among these techniques, the Duval triangle method (DTM) is reported to be the most prominent. In this study, a new approach combining three Duval triangles with triangular membership functions (MFs) is proposed for fault diagnosis.
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION
(2023)
Article
Computer Science, Information Systems
Osama E. Gouda, Salah Hamdy El-Hoshy, Sherif S. M. Ghoneim
Summary: This study implemented artificial intelligence methods such as fuzzy logic and artificial neural networks to enhance the diagnostic accuracy of conventional DGA techniques. The results showed that the use of artificial intelligence improved the diagnostic accuracy of DGA methods significantly.
Article
Engineering, Electrical & Electronic
Seyed-Alireza Ahmadi, Majid Sanaye-Pasand
Summary: In this paper, a robust multi-layer framework is proposed for online continuous monitoring of dissolved gasses in transformer oil and fault diagnosis. The framework handles measurement uncertainties and fuses the results of independent DGA methods, while improving the accuracy of the diagnosis results using an artificial neural network-based approach.
IEEE TRANSACTIONS ON POWER DELIVERY
(2022)
Article
Computer Science, Information Systems
Chirag Joshi, Ranjeet Kumar Ranjan, Vishal Bharti
Summary: This paper proposes a fuzzy logic-based feature engineering method for the detection and classification of Botnet. The method shows high accuracy on the CTU-13 dataset, but further testing and improvement on different datasets are needed.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Engineering, Electrical & Electronic
Michel Duval, Jerzy Buchacz
Summary: The new sub-zones of Duval Pentagons 1 and 2 allow for the detection of dangerous arcing faults in the paper insulation of transformers and distinguishing them from arcing faults in oil.
IEEE ELECTRICAL INSULATION MAGAZINE
(2022)
Article
Multidisciplinary Sciences
Md. Manzar Nezami, Md. Danish Equbal, Shakeb A. Khan, Shiraz Sohail
Summary: This work presents a fine correlation among destructive and diagnostic parameters of transformer's paper insulation, using an Adaptive Neuro Fuzzy Inference System (ANFIS) to estimate the value of degree of polymerization (DP) as a function of diagnostic parameters. The ANFIS model does not require destructive tests to diagnose the health of solid insulation and achieves greater accuracy in determining DP values compared to a fuzzy inference system (FIS) model.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Haw Jia Yong, Mohd Fairouz Mohd Yousof, Rahisham Abd Rahman, Mohd Aizam Talib, Norhafiz Azis
Summary: An oil-filled transformer requires proper maintenance for long-term operation. Dissolved gas analysis (DGA) is the best diagnostic method for assessing the condition of oil-immersed transformers. Machine learning algorithms can classify DGA data into normal and faulty conditions, based on IEEE limits and the Duval pentagon method. The use of data resampling techniques improves the accuracy of predictions for imbalanced data.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Teruvai Manoj, Chilaka Ranga, U. Mohan Rao
Summary: A new multi-criterion-based fuzzy logic model has been proposed to determine the health index and health status of power transformers. The study shows that the model is accurate and reliable.
ELECTRICAL ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Kandala N. V. P. S. Rajesh, U. Mohan Rao, I. Fofana, P. Rozga, Ashish Paramane
Summary: This article investigates the influence of data balancing approaches on transformer DGA fault classification, highlighting the importance of selecting suitable data sampling methods and machine learning algorithms for efficient classification.
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION
(2023)
Article
Engineering, Electrical & Electronic
Abraao G. C. Menezes, Mateus M. Araujo, Otacilio M. Almeida, Fabio R. Barbosa, Arthur P. S. Braga
Summary: This article introduces the use of a decision tree approach based on computational intelligence for analyzing and diagnosing incipient faults in power transformers. The method relies on measuring the concentration of combustible gas in the insulating oil. By using the gain ratio as an attribute selection metric, the decision tree algorithm is able to extract maximum information from each class and provide a solution for unsolved cases. Overall, the decision tree plays a significant role in improving the performance of dissolved gas analysis and can be combined with other traditional techniques.
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION
(2022)
Review
Energy & Fuels
Alcebiades Rangel Bessa, Jussara Farias Fardin, Patrick Marques Ciarelli, Lucas Frizera Encarnacao
Summary: This study reviewed the conventional techniques and failure analysis tendency of Dissolved Gas Analysis (DGA) based on the norms IEC 60599 and IEEE Std C57.104, and analyzed the performance of various techniques using the IEC TC10 database. It aimed to provide relevant information to support students and professionals in the field of failure analysis and assist in the development of new tools in the DGA field.
Article
Computer Science, Artificial Intelligence
Song Yu, Weimin Tan, Chengming Zhang, Yun Fang, Chao Tang, Dong Hu
Summary: A hybrid feature selection method based on fuzzy information entropy is proposed for transformer fault diagnosis model, which optimizes reasonable DGA feature parameters to reduce the influence of DGA data uncertainty on diagnostic accuracy. The method shows significant improvement in classifier accuracy compared to common DGA feature combinations.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Jorge Alfredo Ardila-Rey, Matias Patricio Cerda-Luna, Carlos Beltran Munoz, Bruno Albuquerque de Castro, Suganya Govindarajan
Summary: The electricity sector heavily relies on oil-filled electricity equipment，especially power transformers. Many of these assets have surpassed their useful life or are nearing the end of it, raising concerns about their condition. The monitoring and diagnosis of failures in liquid insulation systems play a crucial role in extending the lifespan of these equipment. However, current measurement systems have limitations, leading to the development of new measurement methods that can provide a more accurate diagnosis without technical-economic restrictions. The article introduces a novel system that utilizes an electronic nose equipped with gas sensors to measure dissolved gases in liquid insulation systems. This innovative approach shows great promise for routine monitoring and diagnosis, offering an efficient and cost-effective solution.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Jiefeng Liu, Boshu Song, Enze Zhang, Heng Zhang, Yiyi Zhang, Hui Hwang Goh
Summary: This work proposes a two-stage residual lifespan prediction model for insulating paper based on methanol and furfural indicators. The changes in the contents of methanol and furfural in the oil are examined to determine two demarcation points for dividing the insulation's life into different aging stages. By coupling with the second-order aging kinetic equation, the two-stage residual lifespan model is obtained. The proposed model is proven to be valid with a mean absolute percentage error of 5.6% for insulating paper's residual lifespan when compared to the conventional method of using a single indicator.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Automation & Control Systems
Shatakshi Jha, Bhim Singh, Sukumar Mishra
Summary: This article presents a multiobjective control scheme for a bidirectional interlinking converter of renewable energy based ac-dc hybrid microgrid. The control scheme focuses on power management and prioritizes feeding ac loads and dc loads from ac source and photovoltaic battery energy storage respectively. It utilizes solar power to its maximum capacity and ensures power quality control. The scheme demonstrates superior performance compared to conventional and contemporary techniques under different scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Dhiman Das, Bhim Singh, Sukumar Mishra
Summary: The decrease in solar panel cost over the past decade has led to a greater usage of solar photovoltaic (SPV) in various applications. In this paper, a PV generation with battery energy storage (BES) is used to reduce the impact of energy consumption from the utility grid on air conditioning units. By utilizing VFD technology and an energy management methodology with PV array and BES, the power consumption of the air conditioning unit is reduced and excess PV generation is fed back to the grid with improved power quality.
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
(2023)
Article
Engineering, Multidisciplinary
Shatakshi Jha, Bhim Singh, Sukumar Mishra
Summary: This article discusses the challenges faced by a solar PV-diesel generator-battery storage (PV-DG-BS) based microgrid operating in standalone mode. It proposes a multi-objective and coordinated control system for converters to manage power, optimize the operation of the DG, and handle nonlinear loads. The control system also ensures that the total harmonic distortion of the DG current remains within the limits defined by the IEEE 519 standard. Additionally, it prevents the flow of negative sequence currents during unbalanced faults and regulates the state of charge of the battery storage to avoid overcharging or overdischarging.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Manas Ranjan Mishra, Priyatosh Mahish, Sukumar Mishra
Summary: The gradual increase in the installation of solar photovoltaic inverters (SPVIs) at the low voltage network leads to over-voltage issues at the SPVI-connected point-of-common-couplings (PCCs). This paper proposes an irradiance-driven adaptive PQV droop control technique for the SPVIs to improve voltage regulation in an active distribution system (ADS). A Two-Bit-Priority (TBP) algorithm is also introduced for distributed coordination among the SPVIs. The results show that the proposed method outperforms the IEEE-1547-2020 recommended droop characteristic.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Computer Science, Information Systems
Anubhav Agrawal, Ranbir Singh, Nagendra Kumar, Vijay Prakash Singh, Majed A. Alotaibi, Hasmat Malik, Fausto Pedro Garcia Marquez, Mohammad Asef Hossaini
Summary: Reducing dependence on non-renewable resources is a global concern, and electric vehicles are an important initiative to reduce reliance on fossil fuels. This study proposes a new mathematical model to analyze the performance of electric vehicles under different driving conditions. The research findings suggest that road conditions, tire pressure, velocity of travel, wind velocity, and temperature significantly influence the performance of electric vehicles.
Article
Mathematics, Interdisciplinary Applications
Andrew A. Manderson, Robert J. B. Goudie
Summary: A challenge for Bayesian inference practitioners is how to incorporate multiple relevant, heterogeneous data sets into a model. We propose chained Markov melding, an extension of Markov melding, to combine the submodels into a joint model. We address the challenges of capturing prior dependence and reconciling differences in priors between adjacent submodels. Additionally, we describe a sampler that utilizes the chain structure to incorporate information from submodels in multiple stages.
Review
Computer Science, Information Systems
Neha Sharma, Manoj Sharma, Amit Singhal, Ritesh Vyas, Hasmat Malik, Asyraf Afthanorhan, Mohammad Asef Hossaini
Summary: This paper provides a comprehensive review of conventional signal processing and deep learning techniques for BCI MI signal analysis. It presents recent research, current challenges, a new categorization of existing approaches, and the architectures, merits, and demerits of standard deep learning algorithms. Numerical results are provided in tabular representations, along with open research problems and future directions.
Article
Computer Science, Information Systems
Neeraj Shabbiruddin, Neeraj Kanwar, Vinay Kumar Jadoun, N. S. Jayalakshmi, Asyraf Afthanorhan, Nuzhat Fatema, Hasmat Malik, Mohammad Asef Hossaini
Summary: One important topic of concern is the threat posed by the widespread use of single-use plastic items. It is crucial for manufacturers and investors to prioritize environmental preservation. Sustainable manufacturing faces various challenges that need to be addressed, which is alarming.
Article
Engineering, Electrical & Electronic
Utkarsh Kumar, Sukumar Mishra, Kalyan Dash
Summary: This article proposes a low-cost and less data-intensive methodology for detecting, localizing, and classifying faults in solar photovoltaic (SPV) systems. It utilizes a sensorless electronic circuit, an Internet of things (IoT)-based application, and a deep autoencoder-based semi-supervised learning module, followed by a hybrid support vector machine and logistic regression for fault classification. The methodology is validated in a laboratory-scale real-time setup of a grid-connected SPV system.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Vaibhav Nougain, Sukumar Mishra
Summary: This article proposes a novel time-domain-based algorithm for accurately determining fault location in high-voltage direct current (HVdc) systems with hybrid dc transmission corridors. The algorithm offers flexibility to locate faults ranging from homogeneous transmission lines to n-segment hybrid transmission corridors. Power systems computer-aided design/electromagnetic transients including dc (PSCAD/EMTDC)-based simulations are used to validate the algorithm's performance against parameter variations.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Energy & Fuels
Dinanath Prasad, Narendra Kumar, Rakhi Sharma, Hasmat Malik, Fausto Pedro Garcia Marquez, Jesus Maria Pinar-Perez
Summary: This manuscript proposes and discusses an adaptive control approach for a three-phase grid-interfaced solar photovoltaic system using the new Neuro-Fuzzy Inference System with Rain Optimization Algorithm (ANROA) methodology. The proposed method combines an Adaptive Neuro-fuzzy Inference System (ANFIS) with a Rain Optimization Algorithm (ROA). The goal is to avoid power quality problems and achieve zero voltage regulation and unity power factor modes. The simulations show that the suggested strategy can effectively identify the best global solutions compared to alternative approaches. The robustness of the system has been studied using MATLAB/SIMULINK environment and experimental hardware-in-loop (HLL) setup based on Field Programmable Gate Arrays Controller (FPGA).
Article
Green & Sustainable Science & Technology
Abdulaziz Almutairi, Naif Albagami, Sultanh Almesned, Omar Alrumayh, Hasmat Malik
Summary: Electric vehicles (EVs) have the potential to reduce emissions and enhance energy security, but accurately estimating their load is a challenge for optimizing grid management and integration. This study introduces a tailored three-step solution, focusing on Saudi Arabia, to estimate EV load using real survey data and commercially available EV data. The developed load models facilitate load estimations under different scenarios and building types, providing valuable insights for grid operators and policymakers.
Article
Energy & Fuels
Yawar Irshad Badri, Suresh Kumar Sudabattula, Ikhlaq Hussain, Hasmat Malik, Fausto Pedro Garcia Marquez
Summary: This paper presents a method of integrating ultracapacitors with a regenerative braking system for use in electric drive trains. By combining ultracapacitors and batteries, it improves the vehicle's range and enhances speed control response.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Computer Science, Information Systems
Salwan Tajjour, Shyam Singh Chandel, Majed A. Alotaibi, Hasmat Malik, Fausto Pedro Garcia Marquez, Asyraf Afthanorhan
Summary: This study compares the performance of three deep learning techniques for solar irradiance forecasting. The results show that these models have similar accuracy, but differ in training speed and number of parameters. The study is important for reliable solar irradiance forecasting.
Article
Computer Science, Information Systems
Divya Rishi Shrivastava, Shahbaz Ahmed Siddiqui, Kusum Verma, Satyendra Singh, Majed A. Alotaibi, Hasmat Malik, Fausto Pedro Garcia Marquez
Summary: This article proposes a data-driven unified methodology for enhancing grid stability in solar energy-penetrated power network. This methodology incorporates Prompt Instability Evaluation (PIE) and Decision Assisted Adaptive Control (DAAC) to evaluate and correct system transient instability in real-time.
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)
