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  • Open Access

    ARTICLE

    Research on Grid-Connected Control Strategy of Distributed Generator Based on Improved Linear Active Disturbance Rejection Control

    Xin Mao*, Hongsheng Su, Jingxiu Li

    Energy Engineering, Vol.121, No.12, pp. 3929-3951, 2024, DOI:10.32604/ee.2024.057106 - 22 November 2024

    Abstract The virtual synchronous generator (VSG) technology has been proposed to address the problem of system frequency and active power oscillation caused by grid-connected new energy power sources. However, the traditional voltage-current double-closed-loop control used in VSG has the disadvantages of poor disturbance immunity and insufficient dynamic response. In light of the issues above, a virtual synchronous generator voltage outer-loop control strategy based on improved linear autonomous disturbance rejection control (ILADRC) is put forth for consideration. Firstly, an improved first-order linear self-immunity control structure is established for the characteristics of the voltage outer loop; then, the… More >

  • Open Access

    ARTICLE

    Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

    Li Wang1,*, Xiaoyong Wang2

    Energy Engineering, Vol.121, No.12, pp. 3953-3979, 2024, DOI:10.32604/ee.2024.056705 - 22 November 2024

    Abstract Plug-in Hybrid Electric Vehicles (PHEVs) represent an innovative breed of transportation, harnessing diverse power sources for enhanced performance. Energy management strategies (EMSs) that coordinate and control different energy sources is a critical component of PHEV control technology, directly impacting overall vehicle performance. This study proposes an improved deep reinforcement learning (DRL)-based EMS that optimizes real-time energy allocation and coordinates the operation of multiple power sources. Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces. They often fail to strike an optimal balance between exploration and exploitation, and… More >

  • Open Access

    ARTICLE

    The Hydraulic Fracturing Optimization for Stacked Tight Gas Reservoirs Using Multilayers and Multiwells Fracturing Strategies

    Yuanyuan Yang1, Xian Shi1,2,*, Cheng Ji3, Yujie Yan3, Na An3, Teng Zhang4

    Energy Engineering, Vol.121, No.12, pp. 3667-3688, 2024, DOI:10.32604/ee.2024.056266 - 22 November 2024

    Abstract Based on a geology-engineering sweet spot evaluation, the high-quality reservoir zones and horizontal well landing points were determined. Subsequently, fracture propagation and production were simulated with a multilayer fracturing scenario. The optimal hydraulic fracturing strategy for the multilayer fracturing network was determined by introducing a vertical asymmetry factor. This strategy aimed to minimize stress shadowing effects in the vertical direction while maximizing the stimulated reservoir volume (SRV). The study found that the small vertical layer spacing of high-quality reservoirs and the presence of stress-masking layers (with a stress difference of approximately 3~8 MPa) indicate that… More > Graphic Abstract

    The Hydraulic Fracturing Optimization for Stacked Tight Gas Reservoirs Using Multilayers and Multiwells Fracturing Strategies

  • Open Access

    ARTICLE

    Rapid Parameter-Optimizing Strategy for Plug-and-Play Devices in DC Distribution Systems under the Background of Digital Transformation

    Zhi Li1, Yufei Zhao2, Yueming Ji2, Hanwen Gu2, Zaibin Jiao2,*

    Energy Engineering, Vol.121, No.12, pp. 3899-3927, 2024, DOI:10.32604/ee.2024.055899 - 22 November 2024

    Abstract By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement, information communication, and other fields, the digital DC distribution network can efficiently and reliably access Distributed Generator (DG) and Energy Storage Systems (ESS), exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play (PnP) operations. However, during device plug-in and -out processes, improper system parameters may lead to small-signal stability issues. Therefore, before executing PnP operations, conducting stability analysis and adjusting parameters swiftly is crucial. This study introduces a four-stage strategy for parameter optimization to enhance… More >

  • Open Access

    ARTICLE

    Combined Wind-Storage Frequency Modulation Control Strategy Based on Fuzzy Prediction and Dynamic Control

    Weiru Wang1, Yulong Cao1,*, Yanxu Wang1, Jiale You1, Guangnan Zhang1, Yu Xiao2

    Energy Engineering, Vol.121, No.12, pp. 3801-3823, 2024, DOI:10.32604/ee.2024.055398 - 22 November 2024

    Abstract To ensure frequency stability in power systems with high wind penetration, the doubly-fed induction generator (DFIG) is often used with the frequency fast response control (FFRC) to participate in frequency response. However, a certain output power suppression amount (OPSA) is generated during frequency support, resulting in the frequency modulation (FM) capability of DFIG not being fully utilised, and the system’s unbalanced power will be increased during speed recovery, resulting in a second frequency drop (SFD) in the system. Firstly, the frequency response characteristics of the power system with DFIG containing FFRC are analysed. Then, based… More >

  • Open Access

    ARTICLE

    Modeling, Simulation, and Risk Analysis of Battery Energy Storage Systems in New Energy Grid Integration Scenarios

    Xiaohui Ye1,*, Fucheng Tan1, Xinli Song2, Hanyang Dai2, Xia Li2, Shixia Mu2, Shaohang Hao2

    Energy Engineering, Vol.121, No.12, pp. 3689-3710, 2024, DOI:10.32604/ee.2024.055200 - 22 November 2024

    Abstract Energy storage batteries can smooth the volatility of renewable energy sources. The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system (BESS). However, the current modeling of grid-connected BESS is overly simplistic, typically only considering state of charge (SOC) and power constraints. Detailed lithium (Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions. Additionally, there is a lack of real-time batteries risk assessment frameworks. To address these issues, in this… More >

  • Open Access

    ARTICLE

    Improving Smart Home Security via MQTT: Maximizing Data Privacy and Device Authentication Using Elliptic Curve Cryptography

    Zainatul Yushaniza Mohamed Yusoff1, Mohamad Khairi Ishak2,*, Lukman A. B. Rahim3, Mohd Shahrimie Mohd Asaari1

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1669-1697, 2024, DOI:10.32604/csse.2024.056741 - 22 November 2024

    Abstract The rapid adoption of Internet of Things (IoT) technologies has introduced significant security challenges across the physical, network, and application layers, particularly with the widespread use of the Message Queue Telemetry Transport (MQTT) protocol, which, while efficient in bandwidth consumption, lacks inherent security features, making it vulnerable to various cyber threats. This research addresses these challenges by presenting a secure, lightweight communication proxy that enhances the scalability and security of MQTT-based Internet of Things (IoT) networks. The proposed solution builds upon the Dang-Scheme, a mutual authentication protocol designed explicitly for resource-constrained environments and enhances it… More >

  • Open Access

    REVIEW

    AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice

    Mitra Madanchian1,*, Hamed Taherdoost1,2,3,4

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2133-2159, 2024, DOI:10.32604/cmc.2024.057094 - 18 November 2024

    Abstract This comparative review explores the dynamic and evolving landscape of artificial intelligence (AI)-powered innovations within high-tech research and development (R&D). It delves into both theoretical models and practical applications across a broad range of industries, including biotechnology, automotive, aerospace, and telecommunications. By examining critical advancements in AI algorithms, machine learning, deep learning models, simulations, and predictive analytics, the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies. The review integrates both qualitative and quantitative data derived from academic studies, industry reports, and real-world case studies to showcase the… More >

  • Open Access

    REVIEW

    A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning

    Jingbo Zhang1, Qiong Wu1,*, Pingyi Fan2, Qiang Fan3

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1953-1998, 2024, DOI:10.32604/cmc.2024.057006 - 18 November 2024

    Abstract Federated Edge Learning (FEL), an emerging distributed Machine Learning (ML) paradigm, enables model training in a distributed environment while ensuring user privacy by using physical separation for each user’s data. However, with the development of complex application scenarios such as the Internet of Things (IoT) and Smart Earth, the conventional resource allocation schemes can no longer effectively support these growing computational and communication demands. Therefore, joint resource optimization may be the key solution to the scaling problem. This paper simultaneously addresses the multifaceted challenges of computation and communication, with the growing multiple resource demands. We… More >

  • Open Access

    ARTICLE

    An Adaptive Congestion Control Optimization Strategy in SDN-Based Data Centers

    Jinlin Xu1,2, Wansu Pan1,*, Haibo Tan1,2, Longle Cheng1, Xiaofeng Li1,2

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2709-2726, 2024, DOI:10.32604/cmc.2024.056925 - 18 November 2024

    Abstract The traffic within data centers exhibits bursts and unpredictable patterns. This rapid growth in network traffic has two consequences: it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load. Consequently, persistent overload situations eventually result in network congestion. The Software Defined Network (SDN) technology is employed in data centers as a network architecture to enhance performance. This paper introduces an adaptive congestion control strategy, named DA-DCTCP, for SDN-based Data Centers. It incorporates Explicit Congestion Notification (ECN) and Round-Trip Time (RTT) to establish congestion awareness and an ECN marking model.… More >

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