IEEE Transactions on Sustainable Energy最新文献

Online Optimization of Power Response and Efficiency of Contra-Rotating Turbines Using Nonlinear Model Predictive Control 基于非线性模型预测控制的对转汽轮机功率响应和效率在线优化

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-01-12 DOI: 10.1109/TSTE.2026.3652790

Daan P. K. Truijen;Babak Mehdizadeh Gavgani;Thomas Neve;Kurt Stockman;Jeroen D. M. De Kooning

{"title":"Online Optimization of Power Response and Efficiency of Contra-Rotating Turbines Using Nonlinear Model Predictive Control","authors":"Daan P. K. Truijen;Babak Mehdizadeh Gavgani;Thomas Neve;Kurt Stockman;Jeroen D. M. De Kooning","doi":"10.1109/TSTE.2026.3652790","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3652790","url":null,"abstract":"This paper presents a nonlinear model predictive control (MPC) architecture for low-head contra-rotating reversible pump-turbines (CR RPTs) in turbine mode. The developed MPC is compared with a baseline feedback controller in a frequency containment reserve (FCR) application. The MPC is designed to optimize the power response and efficiency online, with the former prioritized. A nonuniform time discretization and increasing weighting factors over the prediction horizon are implemented to reduce computational load and emphasize long-term optimality, respectively. Full reserve power step simulations on a 10 MW system demonstrate that the MPC reduces the rise and settling time by an average of 32% and 23%, respectively. The improved performance is achieved with minimal efficiency compromise, with the deficit becoming less than 0.1% within 8.5 s after reaching the setpoint. In FCR scenarios, the root mean square power tracking error is reduced by an average of 27% across various frequency datasets with a negligible reduction in efficiency. The MPC is experimentally validated on a reduced-scale hardware-in-the-loop setup, confirming the improved performance in a physical environment. The results show that the developed MPC enhances the dynamic power response of CR RPTs for grid support applications in low-head pumped hydropower storage systems.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2530-2542"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148515612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hierarchical Optimal Continuous Fault Ride-through Control Scheme for Heterogeneous Wind Farm With Grid-Forming and Grid-Following Wind Turbines 成网随网风力机异质风电场分层最优连续故障穿越控制方案

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-12-17 DOI: 10.1109/TSTE.2025.3645462

Lai Wei;Juan Wei;Sheng Huang;Canbing Li;Lin Zhu;Kerui Chen;Shuaifeng Wang;Luobin Wang

{"title":"Hierarchical Optimal Continuous Fault Ride-through Control Scheme for Heterogeneous Wind Farm With Grid-Forming and Grid-Following Wind Turbines","authors":"Lai Wei;Juan Wei;Sheng Huang;Canbing Li;Lin Zhu;Kerui Chen;Shuaifeng Wang;Luobin Wang","doi":"10.1109/TSTE.2025.3645462","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3645462","url":null,"abstract":"The heterogeneous wind farms (WFs) will face serious output frequency fluctuations, huge terminal voltage deviations and insufficient voltage support capacity during continuous fault ride-through (CFR) periods. To solve above issues, this article proposes a hierarchical optimal CFR control (HOCFR) scheme to improve the CFR capability for heterogeneous WFs. Considering the difference in CFR response between GFL and GFM WTs, a hierarchical CFR controller is designed to achieve optimal CRT performance by enhancing the CFR capability of GFL and GFM WTs. In the first-layer controller, the output power reference is optimized to suppresses the terminal voltage fluctuation of WTs, which is used as input to the second-layer controller. In the second-layer controller, the virtual impedance, virtual inertia, voltage loop integral parameters, and weak magnetic current (WMC) are regulated to suppress output frequency fluctuations and improve the voltage support capacity by fully utilizing the kinetic energy storage capability for GFM WTs. For GFL WTs, active power, reactive power (Var), and WMC are regulated optimized to minimizing the voltage deviation while fully utilizing the kinetic energy storage capability. The simulations in MATLAB prove the superiority of the proposed HOCFR method than other existing control schemes.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2233-2248"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148517185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Almost Globally Stable GFL Inverter Control Scheme Based on Current Control Synchronization 基于电流控制同步的GFL逆变器几乎全局稳定控制方案

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-09 DOI: 10.1109/TSTE.2026.3662805

Aizuo Chen;Yue Zhu;Hang Zhao

{"title":"Almost Globally Stable GFL Inverter Control Scheme Based on Current Control Synchronization","authors":"Aizuo Chen;Yue Zhu;Hang Zhao","doi":"10.1109/TSTE.2026.3662805","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3662805","url":null,"abstract":"Various control strategies have been proposed to enhance the transient stability of grid-following (GFL) inverters. However, most existing approaches are tailored to specific operating conditions and often lack theoretical guarantees, limiting their adaptability. Furthermore, these methods tend to complicate the controller design and parameter tuning. To address these limitations, this paper introduces a novel current control synchronization (CCS)-based control strategy for GFL inverters. The stability of the CCS-based control scheme is rigorously verified using the qualitative theory of differential equations and phase portrait analysis, establishing almost global asymptotic stability. Moreover, the controller parameters can be tuned with exceptional simplicity, greatly streamlining the design process. The performance of the CCS-based approach is validated through electromagnetic transient (EMT) simulations and controller hardware-in-the-loop (CHIL) experiments conducted on the StarSim platform. The results show that the proposed method matches phase-locked loop-based schemes in power tracking and frequency synchronization, while significantly outperforming them in transient stability. These findings further underscore the enhanced adaptability and practical feasibility of the proposed method.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2926-2938"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Predictive Control Method for an Integrated Community Energy System Based on a GRU-Driven Dynamic Energy Hub 基于gru驱动动态能源枢纽的综合社区能源系统模型预测控制方法

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-01-12 DOI: 10.1109/TSTE.2026.3651984

Yanze Xu;Yunfei Mu;Hongjie Jia;Jiarui Zhang;Xiaolong Jin;Zeqing Wu

{"title":"Model Predictive Control Method for an Integrated Community Energy System Based on a GRU-Driven Dynamic Energy Hub","authors":"Yanze Xu;Yunfei Mu;Hongjie Jia;Jiarui Zhang;Xiaolong Jin;Zeqing Wu","doi":"10.1109/TSTE.2026.3651984","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3651984","url":null,"abstract":"In integrated community energy systems (ICESs), the efficiency parameters of energy conversion devices are influenced not only by current operating conditions (e.g., device load rate, temperature, and atmospheric pressure) but also by the dynamic characteristics of historical operating conditions. Neglecting the nonlinear dynamic relationship between the efficiency parameters and time series operating conditions can notably reduce the prediction accuracy for the efficiency parameters, thereby disrupting the energy supply-demand balance and reducing the economic performance of the ICES. To address this issue, a model predictive control (MPC) method is proposed for an ICES based on a gated recurrent unit (GRU)-driven dynamic energy hub (G-DEH). First, a G-DEH model is developed to capture the time series correlations in the operating conditions of the ICES, thereby accurately modeling the nonlinear and time-varying relationships between the efficiency parameters and these conditions. On this basis, an optimal scheduling model for the ICES, focused on enhancing the economic performance, is developed via the G-DEH model. The model is subjected to iterative rolling calibration through the MPC strategy, dynamically adjusting the degree of matching between the operating conditions and efficiency parameters, thereby enhancing the adaptability of the scheduling model to complex and dynamic operating conditions. The simulation results from a case study demonstrate that the proposed method significantly outperforms traditional methods in terms of the prediction accuracy for the efficiency parameters and the economic performance of the ICES. This confirms the significant value of the method in reducing operating costs and enhancing dynamic adaptability.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2460-2471"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Bayesian Transfer Learning-Based PV-Load Decomposition Method for Behind-The-Meter Systems Utilizing Small User Sample Datasets 利用小用户样本数据集的基于贝叶斯迁移学习的电力负荷分解方法

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-12-17 DOI: 10.1109/TSTE.2025.3645280

Haotian Ma;Wanxing Sheng;Siyi Wang;Qing Duan

{"title":"A Bayesian Transfer Learning-Based PV-Load Decomposition Method for Behind-The-Meter Systems Utilizing Small User Sample Datasets","authors":"Haotian Ma;Wanxing Sheng;Siyi Wang;Qing Duan","doi":"10.1109/TSTE.2025.3645280","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3645280","url":null,"abstract":"Most distributed photovoltaics (PVs) are installed behind-the-meter (BTM) and measured together with user loads, making the specific PV generation and native load invisible. Existing methods typically learn patterns from detailed data collected at fully observable users, modeling PV generation and native load separately, and then developing net load decomposition algorithms. However, these algorithms require substantial amounts of data, and their accuracy decreases when the total number of users is insufficient or when the observation rate is low. To this end, a novel Bayesian Transfer Learning (BTL) based PV-load decomposition strategy for the BTM system is proposed in this paper. First, feature extraction and clustering are performed on the net load nighttime sequence data based on their characteristics, while a data augmentation algorithm is used to expand the user dataset. Second, a two-layer Bayesian network model is designed, where the outer layer learns common features from all user data, and a parameter transfer strategy is employed to transfer the posterior distribution to the inner layer for learning the individual characteristics of data within each cluster. Finally, the trained BTL model is used to separate the PV generation and native load from the unobservable user net load. The effectiveness of the proposed method is validated across datasets from various user cases.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2206-2218"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Reachability Analysis for VSC-MTDC Integrated Offshore Wind Farms Based on Adaptive Parameter Optimization 基于自适应参数优化的VSC-MTDC集成海上风电场可达性改进分析

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-17 DOI: 10.1109/TSTE.2026.3665816

Wen Gao;Kaishun Xiahou;Yang Liu;Zhigang Li;Chuanyue Li;Jun Liang;Q. H. Wu

{"title":"Improved Reachability Analysis for VSC-MTDC Integrated Offshore Wind Farms Based on Adaptive Parameter Optimization","authors":"Wen Gao;Kaishun Xiahou;Yang Liu;Zhigang Li;Chuanyue Li;Jun Liang;Q. H. Wu","doi":"10.1109/TSTE.2026.3665816","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3665816","url":null,"abstract":"To address the challenges presented by the complex nonlinear dynamics and limited disturbance resilience of offshore wind farms (OWFs) integrated via voltage source converter based multi-terminal high voltage direct current (VSC-MTDC) system under large disturbances, an improved reachability analysis method is proposed to capture dynamic behaviors of the system. The analysis framework encompasses: 1) high-dimensional nonlinear differential and hybrid models of VSC-MTDC integrated OWFs system are constructed based on Kron reduction method to enhance computational efficiency and mitigate the limitations imposed by algebraic constraints; 2) an adaptive time-step optimization algorithm is implemented to further improve computational efficiency while enhancing the capability to capture both transient and steady-state dynamics of hybrid system; 3) the improved reachability algorithm is designed to quantitatively analyze the operational states of VSC-MTDC integrated OWFs system under uncertainties and varying operating conditions. Case studies on VSC-MTDC integrated OWFs system are conducted to demonstrate the effectiveness of the proposed method in revealing complex nonlinear characteristics and safety verification under large disturbances.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3124-3137"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Medium-Frequency Oscillation Analysis and Single-Parameter Feedback Suppression for Full-Size Converter-Based Variable-Speed Pumped Storage and Renewable Energy Combined System 基于全尺寸变流器的变速抽水蓄能与可再生能源联合系统中频振荡分析及单参数反馈抑制

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-16 DOI: 10.1109/TSTE.2026.3665057

Qi Zhang;Junliang Liu;Xiaoming Zou;Chengmao Du;Xiong Du;Bing Chen

{"title":"Medium-Frequency Oscillation Analysis and Single-Parameter Feedback Suppression for Full-Size Converter-Based Variable-Speed Pumped Storage and Renewable Energy Combined System","authors":"Qi Zhang;Junliang Liu;Xiaoming Zou;Chengmao Du;Xiong Du;Bing Chen","doi":"10.1109/TSTE.2026.3665057","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3665057","url":null,"abstract":"The coordinated operation of the full-size converter-based variable-speed pumped storage unit (FSC-VSPSU) and renewable energy station can help smooth the power fluctuations and improve the renewable energy utilization. However, this combined system may encounter instability problem such as medium-frequency oscillation in practical application. The impedance-based analysis method is commonly used for addressing such instability problems. Nevertheless, existing research lacks an impedance model of FSC-VSPSU and does not fully conduct the stability analysis of the system. Hence, this paper develops the impedance model for FSC-VSPSU. By integrating it with the impedance model of renewable energy units, an equivalent impedance model of the entire system is derived. The system stability is then analyzed using the impedance-based analysis method. To address the instability issues, a suppression method based on a single feedback parameter <italic>k</i> is proposed for FSC-VSPSU. This method reshapes the equivalent impedance with minimal complexity, eliminating the need for filters that typically degrade dynamic response performance in existing solutions. Simulation and experimental results are presented to validate the effectiveness of the established impedance model and the proposed control strategy.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3048-3063"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Voltage Deviation and Wideband Oscillation Constrained Stability and Weakness Analysis of Hybrid GFM/GFL Multi-Converter Systems GFM/GFL混合多变换器系统电压偏差与宽带振荡约束稳定性及弱点分析

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-17 DOI: 10.1109/TSTE.2026.3665524

Xuyang Li;Zili Wang;Yandong Chen;Zhiwei Xie;Cong Luo;Boning Sun;Huijie Yu

{"title":"Voltage Deviation and Wideband Oscillation Constrained Stability and Weakness Analysis of Hybrid GFM/GFL Multi-Converter Systems","authors":"Xuyang Li;Zili Wang;Yandong Chen;Zhiwei Xie;Cong Luo;Boning Sun;Huijie Yu","doi":"10.1109/TSTE.2026.3665524","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3665524","url":null,"abstract":"The oscillation risk assessment and oscillation source identification pose significant challenges for heterogeneous multi-converter systems such as hybrid grid-forming and grid-following renewable energy station (GFM/GFL-RES). Furthermore, the theoretical impact of GFM converter capacity and placement on the voltage support strength and resonant modes of each bus remains unexplored. To fill this gap, this paper proposes a stability assessment and weakness location method for hybrid GFM/GFL multi-converter systems. Firstly, a power flow method incorporating the reactive power support capability of the GFM converter and the multiple renewable short-circuit ratio is used to evaluate the voltage support strength at each bus. Then, a <italic>s</i>-domain modal analysis method incorporating frequency-coupling is proposed. This method accurately extracts system resonant modes by combining modal impedance curves and a center-difference Newton-Raphson iterative algorithm. Finally, the steady-state stability region is established by integrating steady-state voltage stability and small-signal stability. The method in this paper is validated through a 16-converter 34-bus GFM/GFL-RES, and the influence of GFM capacity and placement on the steady-state stability region of the system is quantified. The accuracy of the proposed stability analysis method is verified by time-domain simulation.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3094-3107"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Score-Driven Multivariate Probabilistic Forecasting of Correlated PV Generation Using Deep Mixture Density Network 基于深度混合密度网络的混合分数驱动的相关光伏发电多元概率预测

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-03-12 DOI: 10.1109/TSTE.2026.3673563

Zhiqiang He;Can Wan;Kaiming Zhang;Ping Ju

{"title":"Hybrid Score-Driven Multivariate Probabilistic Forecasting of Correlated PV Generation Using Deep Mixture Density Network","authors":"Zhiqiang He;Can Wan;Kaiming Zhang;Ping Ju","doi":"10.1109/TSTE.2026.3673563","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3673563","url":null,"abstract":"With massive integration of photovoltaic (PV) generation in power systems, multivariate probabilistic forecasting (MPF) is essential for analysis and decision-making of power systems, which provides comprehensive information about uncertainty of future PV generation. Traditional MPF methods separate probabilistic forecasting and dependency structure estimation, limiting their ability to generate multivariate distributions in an analytical form. This paper innovatively proposes a hybrid score-driven MPF method to directly generate semi-parametric joint predictive density of correlated PV generation using deep mixture density network. Firstly, an integrated framework of MPF based on multivariate Gaussian mixture models is established to unify the training of probabilistic forecasting and the optimization of conditional correlation modeling. Then, a novel hybrid score-based network loss function with the closed-form expression is meticulously devised for the robust training of MPF. In addition, graph structure learning is incorporated to adaptively capture spatial dependency among correlated PV generation. To address overwhelming parameters of joint distributions, a parameter-reduced structure of covariance matrices using incomplete Cholesky decomposition is formulated, which enhances the tractability of MPF in high-dimensional settings. Comprehensive case studies on three realistic PV power datasets are conducted to validate the superior performance of the proposed method for day-ahead multivariate probabilistic forecasting.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3187-3200"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decentralized Coordination for Offshore Power Systems and UAV-Empowered Coastal Logistics Networks 海上电力系统与无人机沿海物流网络的分散协调

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-01-21 DOI: 10.1109/TSTE.2026.3656461

Yangfan Luo;Ang Xuan;Yunfei Du;Xinwei Shen

{"title":"Decentralized Coordination for Offshore Power Systems and UAV-Empowered Coastal Logistics Networks","authors":"Yangfan Luo;Ang Xuan;Yunfei Du;Xinwei Shen","doi":"10.1109/TSTE.2026.3656461","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3656461","url":null,"abstract":"The burgeoning electric-driven uncrewed aerial vehicle (UAV) technology is reshaping traditional coastal logistics dominated by cargo vessels (CVs). This revolution is catalyzing deep integration between coastal logistics networks (CLNs) and offshore power systems (OPSs) with rich marine renewable energy (MRE), ultimately evolving into sophisticated offshore power-logistics systems (OPLSs). Against such backdrop, this paper proposed a decentralized coordination framework for OPSs and UAV-empowered CLN to step towards a low-carbon and cost-saving OPLS. Firstly, a composite UAV-CV joint delivery model is developed to preciously capture energy- and logistics service-related characteristics of the CLN. Subsequently, by incorporating impacts of marine meteorological uncertainties (e.g., winds, waves and currents) on MRE generation and coastal logistics, a coordinative dispatching model for OPSs and the CLN is formulated to minimize total operational costs while complying with preset carbon emission caps. Finally, a decentralized solution procedure based on two-phase projection is designed for solving the coordination model to ensure decision independence and privacy security of OPSs and the CLN. Numerical studies confirm the effectiveness of proposed approach in MRE utilization, cost-efficiency, and decarbonization capabilities for the OPLS.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2633-2647"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148515374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0