Computers & Electrical Engineering最新文献

{"title":"Novel cascaded tilt fractional-order integral derivative with a proportional integral for harmonics mitigation in 31-level multi-level inverter","authors":"P V V Raghava Sharma ,&nbsp;Neelshetty K","doi":"10.1016/j.compeleceng.2025.110280","DOIUrl":"10.1016/j.compeleceng.2025.110280","url":null,"abstract":"<div><div>Alternate current (AC) motor drives and distributed power generation systems often use inverters, which are also known as DC-to-AC power converters. Multi-Level Inverters (MLIs) have emerged as the preferred inverter technology due to their benefits of lower switching losses and improved harmonic profile. In this article, an innovative controller topology for reducing total harmonic distortion (THD) in the 31-level MLI is proposed. A cascaded controller consisting of tilt fractional order integral derivative with proportional integral controller (C-TFOID-PI) is proposed for optimizing the switching angles of the MLI. Green anaconda optimization algorithm (GAOA) is included in this work to select the optimal gain parameters in the novel controller with minimum error. A single-phase 31-level asymmetrical cascaded MLI is utilized in this work to validate the proposed controller with the optimization method. By simulating the entire procedure with MATLAB/Simulink, the control performance of the proposed system is verified. In order to demonstrate the superior performance of the proposed C-TFOID-PI controller and optimization method, its performance is contrasted with that of other controllers. The proposed controller topology effectively lowers the THD to 0.41 %, which is 2 % better than a fuzzy logic controller. Also, the proposed inverter topology improves efficiency by 3.9 % and reduces losses by 1.02 % when compared with other controllers.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110280"},"PeriodicalIF":4.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain-Based peer-to-peer energy trading: A decentralized and innovative approach for sustainable local markets","authors":"Tao Shen ,&nbsp;Xiufang Ou ,&nbsp;Bingbin Chen","doi":"10.1016/j.compeleceng.2025.110281","DOIUrl":"10.1016/j.compeleceng.2025.110281","url":null,"abstract":"<div><div>This study presents an innovative approach to local energy generation and peer-to-peer energy trading (P2PET) through the use of blockchain technology, with a focus on decentralization and trustlessness. The primary objectives are to reduce energy costs and address privacy concerns in P2PET transactions. To facilitate this, the paper proposes three key smart contracts: one for member registration and data storage, another for managing P2PET transactions, and a third for regulating customer interactions with the main energy network. The objectives of this study go beyond technical implementation, focusing on establishing an efficient energy trading market, reducing costs, and balancing load ratios. Simulation results indicate a potential monthly cost reduction of 514 Euros per consumer. The decentralized blockchain system offers both cost-effectiveness and flexibility, enhancing network sustainability and reliability. This research examines the integration of blockchain and smart contracts in transforming energy markets, highlighting their significant impact on local energy trading and broader environmental objectives.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110281"},"PeriodicalIF":4.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-term optimal operation of phase shifting soft open point with high accuracy loss model in unbalanced distribution networks","authors":"Amir Mohammad Ayazi ,&nbsp;Mahmoud Reza Shakarami ,&nbsp;Meysam Doostizadeh ,&nbsp;Farhad Namdari ,&nbsp;Mohammad Reza Nikzad","doi":"10.1016/j.compeleceng.2025.110284","DOIUrl":"10.1016/j.compeleceng.2025.110284","url":null,"abstract":"<div><div>This paper examines the issues associated with unbalanced operations in distribution networks (DNs), which arise from inconsistencies in loads, resources, and configurations. This is particularly relevant in the context of peer-to-peer (P2P) trading, which may introduce security vulnerabilities and exacerbate existing imbalances. To improve the secure and efficient operation of DNs, we propose a short-term optimal operation model that integrates P2P transactions and emphasizes the physical layer of trading. The study assesses the effectiveness of a developed phase shifting-soft open point (PS-SOP) in enhancing operational flexibility and quantifies the related losses, including conduction and switching losses associated with semiconductor switches. By employing a deep neural network (DNN), these losses are converted into linear constraints suitable for incorporation into the convex optimization framework. An AC optimal power flow model is constructed to identify optimal power transfer sequences, which is framed as a mixed-integer linear programming problem to evaluate the PS-SOP's influence on voltage imbalance reduction, loss minimization, and facilitation of P2P transactions. Numerical simulations are conducted on two IEEE test networks to validate the proposed method's efficacy. For scenarios involving multi-terminal PS-SOP, all P2P transactions are successfully executed in the IEEE 13-bus network, and a 97.55 % authorization rate is achieved in the IEEE 123-bus network. The SOP loss derived from the DNN exhibits a negligible discrepancy of 2.54 % compared to nonlinear loss formulations, underscoring the model's precision and dependability.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110284"},"PeriodicalIF":4.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age of information-aware intelligent resource management in D2D-enabled social IoT networks","authors":"Saurabh Chandra ,&nbsp;Rajeev Arya ,&nbsp;Maheshwari Prasad Singh","doi":"10.1016/j.compeleceng.2025.110295","DOIUrl":"10.1016/j.compeleceng.2025.110295","url":null,"abstract":"<div><div>Due to the increasing number of time-sensitive Internet of Things (IoT) applications, effective time management is crucial for maintaining the freshness of information in dynamic and resource-constrained environments. The age of Information (AoI) metric is adopted to quantify timeliness in urban dynamic environments. Device-to-Device (D2D) communication enhances timely information freshness updates by enabling direct communication. This paper proposes a two-stage auction-based resource and power-driven mechanism for AoI and throughput optimization in Social IoT networks. The first stage employs a time-sensitive auction-based model to ensure efficient resource allocation. The second stage utilizes a fixed-point iteration-based power control scheme to enhance the network performance. Simulation results demonstrate proposed approach achieves an 18.03 % increment in throughput, a 69.69 % reduction in AoI, and a 66.41 % reduction in power consumption compared to benchmark schemes. The proposed algorithm may be utilized as a practical solution in disaster management systems, where timeliness and resource-efficient communication are paramount.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110295"},"PeriodicalIF":4.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hierarchical integrated energy system management considering energy market, demand response and uncertainties: A robust optimization approach","authors":"Saied Iranpour Mobarakeh,&nbsp;Ramtin Sadeghi,&nbsp;Hadi Saghafi,&nbsp;Majid Delshad","doi":"10.1016/j.compeleceng.2025.110138","DOIUrl":"10.1016/j.compeleceng.2025.110138","url":null,"abstract":"<div><div>In this research, optimal hierarchical energy management in an integrated energy system is introduced, considering the variabilities associated with renewable energy resources, uncertain loads like electric vehicles, energy market interaction uncertainties, and a demand response (DR) program that relies on a robust optimization (RO) technique. The energy hub (EH) is distributed in the microgrid (MG) framework, leading to the establishment of the MG/EH configuration. RO methods and the alternating direction method of multipliers are employed for formulating multi-objective functions and problem-solving. The local controller's role involves the optimal distribution of energy in EH by utilizing customer data, power generation units, storage devices, and energy market interactions. Conversely, the central controller within the MG platform is tasked with optimizing energy distribution by considering the DR execution based on loads and price elasticity, which is influenced by the energy carrier price uncertainty. Furthermore, the proposed model aims to minimize the greenhouse gas (GHG) emissions cost. This proposed method is evaluated under two scenarios, with/without DR programs, and is compared with other methodologies. The findings indicate that the suggested approach effectively manages optimal energy distribution, leading to a 15.4 % reduction in operational costs and GHG in the presence of DR programs.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110138"},"PeriodicalIF":4.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-inspired intrusion detection system for IoT: Security issues and future challenges","authors":"Tariq Ahamed Ahanger ,&nbsp;Imdad Ullah ,&nbsp;Shabbab Ali Algamdi ,&nbsp;Usman Tariq","doi":"10.1016/j.compeleceng.2025.110265","DOIUrl":"10.1016/j.compeleceng.2025.110265","url":null,"abstract":"<div><div>The Internet of Things (IoT) has revolutionized numerous domains, including smart grids, smart cities, healthcare, and business networks, by seamlessly integrating digital and physical systems. However, the rapid proliferation of IoT devices has introduced significant security challenges due to their resource constraints, heterogeneous architectures, and decentralized nature. Traditional security mechanisms, such as firewalls and IDS, often fail to address the unique vulnerabilities of IoT environments. This study provides a comprehensive analysis of the IDS market for IoT devices from 2014 to 2023, focusing on the evolution of deployment methods, emerging trends, and the integration of Artificial Intelligence (AI) strategies to enhance IoT security. The motivation for this research lies in the increasing reliance on IoT systems in critical infrastructures and the corresponding rise in sophisticated cyberattacks. Security breaches in IoT can lead to severe consequences, including data theft, service disruptions, and physical harm. To address these challenges, this study explores AI-driven techniques, such as Machine Learning (ML), Deep Learning (DL), and Federated Learning (FL), for detecting and mitigating complex intrusion patterns in IoT systems. By leveraging bibliographic analysis using VOS viewer, the study identifies key research themes, including blockchain-based security, DDoS mitigation, and cybersecurity for IoT, through keyword co-occurrence analysis with varying levels of overlap (50 to 250 keywords). This research also evaluates various IDS deployment methods, including Host-Based IDS (HIDS), Network-Based IDS (NIDS), and Hybrid IDS, based on metrics such as detection accuracy, resource efficiency, and adaptability to IoT environments. A detailed examination of IoT-specific intrusions, such as Sybil attacks, malicious node attacks, and memory exhaustion (DoS) attacks, is conducted to highlight vulnerabilities and propose AI-enhanced solutions. The novelty of this study lies in its integration of AI strategies into IDS frameworks, comprehensive market analysis over a decade, and systematic evaluation of IDS deployment tailored to IoT systems. The findings reveal that AI-driven IDS can significantly improve intrusion detection capabilities while addressing the resource constraints of IoT devices. This research provides actionable insights for researchers and practitioners, paving the way for the development of more robust and adaptive IDS frameworks to secure the rapidly expanding IoT ecosystem.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110265"},"PeriodicalIF":4.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep learning model based on multi-attention mechanism and gated recurrent unit network for photovoltaic power forecasting","authors":"Kuo Yang,&nbsp;Yanjie Cai,&nbsp;Jinrun Cheng","doi":"10.1016/j.compeleceng.2025.110250","DOIUrl":"10.1016/j.compeleceng.2025.110250","url":null,"abstract":"<div><div>Solar energy plays a crucial role in the power grid due to its clean, stable, and cost-effective nature, as well as its significant storage potential. Accurate short-term photovoltaic (PV) power forecasting is essential for effective grid management and dispatching decisions. This study introduces a hybrid deep learning model integrating multiple attention mechanisms and gated recurrent unit networks to forecast PV output power one day in advance. To address the impact of random weather variations and historical PV power data on forecasting accuracy, the model incorporates an input attention mechanism to process input features. Additionally, temporal and spatial attention mechanisms are embedded within the encoder-decoder framework to enhance prediction performance. These mechanisms effectively capture the relationships between historical PV power output and meteorological variables while identifying crucial time-dependent hidden states. The proposed model is validated on a real-world PV dataset, achieving a mean absolute error of 0.0903 under favorable weather conditions, demonstrating a 22.5 % improvement over traditional forecasting methods across various weather classifications. Comparative analyses with other state-of-the-art models confirm that the proposed approach offers superior predictive accuracy.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110250"},"PeriodicalIF":4.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Irradiance sensorless PSO-based Integral Backstepping and Immersion & invariance algorithm for robust MPPT control with real-climatic microcontroller-in-the-loop experimental validation","authors":"Jian Chen ,&nbsp;Ambe Harrison ,&nbsp;Njimboh Henry Alombah ,&nbsp;Wulfran Fendzi Mbasso ,&nbsp;Reagan Jean Jacques MOLU ,&nbsp;Abdullah M Alharbi ,&nbsp;Pradeep Jangir","doi":"10.1016/j.compeleceng.2025.110279","DOIUrl":"10.1016/j.compeleceng.2025.110279","url":null,"abstract":"<div><div>This paper presents a novel irradiance sensorless Maximum Power Point Tracking (MPPT) controller for photovoltaic (PV) systems using a Particle Swarm Optimization (PSO)-based Integral Backstepping (IBSC) and Immersion &amp; Invariance (I&amp;I) algorithm. The proposed controller addresses the limitations of traditional and contemporary MPPT methods, such as the need for costly irradiance sensors and suboptimal performance under dynamic environmental conditions. The integration of a higher-order sliding mode differentiator (HOSMD) with the IBSC enhances transient response by completely eliminating overshoots, achieving a 0 % overshoot compared to 4.8 % with the conventional IBSC under standard test conditions. The system exhibits rapid tracking convergence with a significantly reduced tracking time of 0.4 ms, approximately seven times faster than the traditional Perturb and Observe (P&amp;O) algorithm's 3 ms. Under real-world conditions, the proposed system's irradiance estimator maintains a mean absolute error below 15 W/m², with a maximum error of 69 W/m² at high irradiance levels. The system achieves an operating efficiency of 99.99 % with peak-to-peak power ripples of just 0.17 % under standard conditions, outperforming eight state-of-the-art MPPT techniques. This robust and efficient MPPT solution is validated through extensive simulations and real-climatic conditions. Additionally, real-climatic experimental implementations are carried out using Microcontroller-in-the-loop (MIL) integration. The acquired experimental results do not only corroborate the simulation outcomes but also endorses the reliability and practical robustness of the proposed MPPT controller</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110279"},"PeriodicalIF":4.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and development of SIW based H-plane horn applicator for sustainable agriculture applications","authors":"Kiran Kumari,&nbsp;Mayank Agarwal,&nbsp;Hari Shankar Singh,&nbsp;Rajesh Khanna","doi":"10.1016/j.compeleceng.2025.110254","DOIUrl":"10.1016/j.compeleceng.2025.110254","url":null,"abstract":"<div><div>Traditional weed control methods often depend on chemical herbicides, raising ecological and health hazards which are introducing unsustainable practices in agriculture. This study explores electromagnetic (EM) wave-based soil sterilization as a sustainable alternative. A substrate-integrated waveguide (SIW) horn applicator, operating at 2.45 GHz, is proposed for efficient weed mitigation. The applicator is designed on an ultrathin substrate with a thickness of λ₀/10 at 2.45 GHz, providing improved gain and maintaining a compact, low-profile design. The proposed antenna incorporates Vivaldi-shaped flaring to enhance radiation performance, specifically in terms of directivity and gain. Further optimizations include the introduction of reflector nails, substrate extension, and refined flaring geometry, which improve EM radiation performance. Experimental validation indicates that with 25 watts of power, the soil temperature can be raised to 68.6°C within 60 min, sufficient to thermally eradicate most weed species. Comprehensive thermal simulations were conducted to assess the antenna's efficacy in diverse soil conditions, such as wet and loamy soils, examining heat distribution by changing loss tangent of soil. The nutrient values such as NPK, PH and electric conductivity of soil also been measured with both controlled and treated soil. Results indicates a promising value across all the measured parameters. These analyses demonstrate the thermal impact of the SIW horn antenna and its potential for localized soil heating. The results provide critical insights into the use of EM waves for soil sterilization, offering a sustainable, non-chemical approach to weed management, with potential implications for both agricultural practices and environmental conservation.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110254"},"PeriodicalIF":4.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introduction to the special section on the role of renewable energies in an efficient electric power system (VSI-irep3)","authors":"Ahmad Harb ,&nbsp;Fernando Tadeo","doi":"10.1016/j.compeleceng.2025.110273","DOIUrl":"10.1016/j.compeleceng.2025.110273","url":null,"abstract":"","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110273"},"PeriodicalIF":4.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}