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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization *** past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer ***,it is hard to traverse the huge search space within reasonable resource as problem dimension *** evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory *** reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent *** there lacks a thorough review of the state of the art in this specific and important *** paper provides a comprehensive survey of these evolutionary algorithms for *** start with a brief introduction to the research status and the basic concepts of ***,we present surrogate-assisted evolutionary algorithms for HEPs from four main *** also give comparative results of some representative algorithms and application ***,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Digital Twin and TD3-Enabled Optimization of xEV energy Management in Vehicle-to-Grid Networks

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IEEE Access 2025年 13卷 92495-92506页

作者： Saba, Irum Alobaidi, Abdulraheem H. Alghamdi, Sultan Tariq, Muhammad National University of Computer & Emerging Sciences Department of Electrical Engineering Islamabad44000 Pakistan King Abdulaziz University Faculty of Engineering Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia King Abdulaziz University Center of Research Excellence in Renewable Energy and Power Systems Jeddah21589 Saudi Arabia Princeton University Department of Electrical and Computer Engineering PrincetonNJ United States

The rapid expansion of extended electric vehicle (xEV) adoption necessitates optimizing energy storage systems (ESS) management for enhanced performance, longevity, and reliability. However, traditional ESS management approaches struggle with real-time state estimation, energy optimization, and predictive maintenance, leading to inefficiencies in battery utilization and sustainability. This paper addresses these challenges by proposing an advanced ESS framework that integrates digital twin (DT) technology with the twin-delayed deep deterministic policy gradient (TD3) algorithm, a state-of-the-art reinforcement learning method derived from the deep deterministic policy gradient (DDPG). This integration enables precise real-time estimation of critical ESS states, including state of charge (SoC), state of health (SoH), state of energy (SoE), and remaining useful life (RUL), thereby enhancing predictive maintenance and operational efficiency. The proposed framework facilitates proactive battery health monitoring, generates early warnings for potential failures, and enables intelligent battery swapping via DT-driven ESS control. By dynamically adapting ESS control strategies, the TD3 algorithm optimizes energy distribution, reduces energy consumption, and improves overall vehicle performance. With a prediction accuracy of 99.8% for SoC, SoH, and SoE, the proposed approach effectively addresses key challenges in xEV ESS management like cell balancing, dynamic charging rate adjustment, battery swapping decisions, and energy optimization, contributing to a more sustainable and efficient EV ecosystem. © 2013 IEEE.

关键词： Battery management systems

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Synergistic frameworks for sensor fault isolation and accommodation in grid-side converters

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Journal of Automation and Intelligence 2024年第4期3卷 202-218页

作者： Faizan Mehmood Lenos Hadjidemetriou Panayiotis M.Papadopoulos Marios M.Polycarpou KIOS Research and Innovation Center of Excellence and the Department of Electrical and Computer EngineeringUniversity of CyprusNicosia2109Cyprus Energy EnvironmentWater Research CenterThe Cyprus InstituteAglantziaNicosia2121Cyprus

The stable and reliable operation of grid-integrated renewable energy systems requires advanced control and coordination of grid-side converters(GSCs),utilizing the feedback measurements of voltage and current sensors from both the direct current(DC)and alternating current(AC)sides of the ***,the effective operation of the converter is susceptible to sensor failures or divergence from their proper *** sensor fault detection algorithms are usually effective under abrupt faults,the fault propagation effect caused by the physical interconnection between the DC and AC sides of the converter may limit the performance of the sensor fault isolation process in revealing the exact location of a potential faulty ***,this work proposes a robust,model-based fault isolation and accommodation ***,a synergistic sensor fault isolation framework based on adaptive estimation schemes is proposed for both single and multiple faults in the DC voltage and AC current sensors,considering modeling uncertainty and measurement *** performance analysis in terms of stability,learning capability,and fault isolability is rigorously *** accommodation scheme based on a virtual sensor utilizing dynamic sensor fault estimation with realtime learning capabilities is applied to a ***,the performance of the proposed fault isolation and accommodation scheme is evaluated through simulation analysis under several scenarios involving single and multiple sensor faults.

关键词： Fault accommodation Fault detection Fault isolation Grid-side converter Nonlinear system Sensor faults

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"Fiction to Function"Shaping Renewable energy Education with MATLAB and ChatGPT-Driven Environments 21

"Fiction to Function"Shaping Renewable Energy Education with...

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21st International Learning and Technology Conference, L and T 2024

作者： Mohamed, Baher Babiker, Safia Aldybous, Alaa Kabbaj, Narjisse Brahimi, Tayeb Effat University Effat College of Engineering Electrical and Computer Engineering Department Jeddah Saudi Arabia Effat University Effat College of Engineering Energy and Technology Research Center Electrical and Computer Engineering Department Jeddah Saudi Arabia Effat University Natural Science Math and Tech Unit Effat College of Engineering Energy and Technology Research Center Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

Addressing the gap in effective and engaging renewable energy education, this study, 'Fiction to Function,' transitions imaginative frameworks into practical educational tools, focusing on solar and wind energy in line with Sustainable Development Goals (SDGs). The goal is to empower users with deep insights into renewable energy through the novel integration of MATLAB and ChatGPT-driven environments, enhancing the analysis and exploration of these energy sources. The study employs a structured approach using MATLAB App Designer to develop a user-friendly GUI, aligning instructional content with the SDGs and integrating ChatGPT via the OpenAI API for dynamic, interactive learning experiences. This integration provides a multifaceted platform that not only educates but also engages users in practical scenarios, bridging the gap between theoretical knowledge and real-world application. The results demonstrate an enhanced understanding of renewable energy concepts among users, showcasing the efficacy of combining MATLAB's analytical capabilities with ChatGPT's AI-driven guidance. Ultimately, the study highlights the transformative potential of innovative technology in sustainable energy education, setting a precedent for future educational tools in this domain. © 2024 IEEE.

关键词： Integration

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Microgrid energy Management with energy Storage systems:A Review

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CSEE Journal of Power and energy systems 2023年第2期9卷 483-504页

作者： Xiong Liu Tianyang Zhao Hui Deng Peng Wang Jizhen Liu Frede Blaabjerg Energy Electricity Research Center Jinan UniversityZhuhai 519070China School of Electrical and Electronic Engineering Nanyang Technological University639798 Singapore School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Department of Energy Technology at Aalborg University Denmark

Microgrids(MGs)are playing a fundamental role in the transition of energy systems towards a low carbon future due to the advantages of a highly efficient network architecture for flexible integration of various DC/AC loads,distributed renewable energy sources,and energy storage systems,as well as a more resilient and economical on/off-grid control,operation,and energy ***,MGs,as newcomers to the utility grid,are also facing challenges due to economic deregulation of energy systems,restructuring of generation,and marketbased *** paper comprehensively summarizes the published research works in the areas of MGs and related energy management modelling and solution ***,MGs and energy storage systems are classified into multiple branches and typical combinations as the backbone of MG energy ***,energy management models under exogenous and endogenous uncertainties are summarized and extended to transactive energy *** programming,adaptive dynamic programming,and deep reinforcement learning-based solution methods are investigated accordingly,together with their implementation ***,problems for future energy management systems with dynamics-captured critical component models,stability constraints,resilience awareness,market operation,and emerging computational techniques are discussed.

关键词： Architecture energy management energy storage systems microgrids optimization uncertainty models

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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EEG based stress classification by using difference plots of variational modes and machine learning

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16347-16360页

作者： Salankar, Nilima Qaisar, Saeed Mian School of Computer Science University of Petroleum and Energy Studies Dehradun India Persistent System Limited IT Park Maharashtra Nagpur India Department of Electrical and Computer Engineering EFfat University Jeddah22332 Saudi Arabia Communication and Signal Processing Lab Energy and Technology Research Center Effat University Jeddah22332 Saudi Arabia

The recent trend in healthcare is to use the automated biomedical signals processing for an augmented and precise diagnosis. In this context, an original approach is presented for categorization of stress and non-stress classes by processing the multichannel Electroencephalogram (EEG) signals. The EEG signals are decomposed by using the "Empirical Mode Decomposition" (EMD) and "Variational Mode Decomposition" (VMD), respectively render the "Intrinsic Mode Functions" (IMFs) and Modes. The Second Order Difference Plots (SODPs) are traced for each IMF and Mode. Shapes of SODPs are used to discriminate the two intended categories. The feature space includes areas, Central Tendency Measures (CTMs) and means of SODPs. It is derived from first 7 IMFs and Modes. The identification of stress and non-stress categories is performed by using the robust machine learning algorithms namely, the Support Vector Machine (SVM), Boosting with Random Forest (RF) and Multilayer Perceptron Neural Network (MLPNN). The applicability is tested by using a publicly available EEG signals dataset, recorded during mental arithmetic test. A detailed evaluation is carried out at the subset, individual channel and lobes wise. Noteworthy highest accuracies of subset wise 99.89%, channel wise 98.89% and lobe wise 99.99% are obtained respectively. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Empirical mode decomposition

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A Novel Multiobjective Fireworks Algorithm and Its Applications to Imbalanced Distance Minimization Problems

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1476-1489页

作者： Shoufei Han Kun Zhu MengChu Zhou Xiaojing Liu Haoyue Liu Yusuf Al-Turki Abdullah Abusorrah College of Computer Science and Technology Nanjing University of Aeronautics and Astronauticsand also with the Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjing 211106China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand also with the K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions *** this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision *** first extend a latest single-objective fireworks algorithm to handle *** we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special ***,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization *** results show that the proposed algorithm is superior to compared algorithms in solving ***,its runtime is less than its peers'.

关键词： Adaptive strategy fireworks algorithm multimodal multiobjective optimization problems(MMOP)

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Low-Carbon Dispatching for Virtual Power Plant with Aggregated Distributed energy Storage Considering Spatiotemporal Distribution of Cleanness Value

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Journal of Modern Power systems and Clean energy 2024年第2期12卷 346-358页

作者： Hongchao Gao Tai Jin Guanxiong Wang Qixin Chen Chongqing Kang Jingkai Zhu State Key Laboratory of Power System Operation and Control Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Sichuan Energy Internet Research Institute Tsinghua University Chengdu 200016China Power Dispatching and Control Center of Shanghai Municipal Electric Power Company Shanghai 200122China IEEE

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor *** address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and *** on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system ***,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both *** achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear ***,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and ***,the simulation verification based on the IEEE 33-bus DN is *** simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to ***,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

关键词： Distributed energy storage virtual power plant(VPP) spatiotemporal distribution low-carbon dispatching

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Isolation Enhancement in a Compact Four-Element MIMO Antenna for Ultra-Wideband Applications

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computers, Materials & Continua 2023年第4期75卷 911-925页

作者： Awais Khan Shahid Bashir Salman Ghafoor Hatem Rmili Jawad Mirza Ammar Ahmad Department of Electrical Engineering University of Engineering and TechnologyPeshawar25000Pakistan Department of Electrical Engineering University of Science and TechnologyBannu28100Pakistan School of Electrical Engineering and Computer Science(SEECS) National University of Sciences and Technology(NUST)Islamabad44000Pakistan Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589Saudi Arabia SEECS Photonic Research Group National University of Sciences and TechnologyIslamabad44000Pakistan

Mutual coupling reduction or isolation enhancement in antenna arrays is an important area of research as it severely affects the performance of an *** this paper,a new type of compact and highly isolated Multiple-Input-Multiple-Output(MIMO)antenna for ultra-wideband(UWB)applications is *** design consists of four radiators that are orthogonally positioned and confined to a compact 40×40×0.8 mm3 *** final antenna design uses an inverted L shape partial ground to produce an acceptable reflection coefficient(S11<−10 dB)in an entire UWB band(3.1–10.6)giga hertz(GHz).Moreover,the inter-element isolation has also been enhanced to>20 db for majority of the UWB *** antenna was fabricated and tested with the vector network analyzer(VNA)and in an anechoic chamber for scattering parameters and radiation ***,different MIMO diversity performance metrics are also measured to validate the proposed *** simulation results and the experimental results from the constructed model agree quite *** proposed antenna is compared with similar designs in recently published literature for various performance *** of its low envelope correlation coefficient(ECC<0.1),high diversity gain(DG>9.99 dB),peak gain of 4.6 dB,reduced channel capacity loss(CCL<0.4 b/s/Hz),and average radiation efficiency of over 85%,the proposed MIMO antenna is ideally suited for practical UWB applications.

关键词： Multiple input multiple output antennas envelope correlation coefficient defected ground structure ultra wide band diversity gain

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