IEEE Transactions on Sustainable Energy最新文献_第6页

IEEE Transactions on Sustainable Energy Publication Information IEEE可持续能源学报出版信息

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-06-22 DOI: 10.1109/TSTE.2026.3699263

引用次数: 0

Accurate and Computationally Efficient Aggregated Modeling of Offshore Wind Farms for Grid Compliance 海上风电场网格合规性的精确和计算效率聚合建模

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-18 DOI: 10.1109/TSTE.2026.3666091

Muhammad Helal Uddin;Junaid Khalid;Michael Smailes;Jun Liang;Sheng Wang

{"title":"Accurate and Computationally Efficient Aggregated Modeling of Offshore Wind Farms for Grid Compliance","authors":"Muhammad Helal Uddin;Junaid Khalid;Michael Smailes;Jun Liang;Sheng Wang","doi":"10.1109/TSTE.2026.3666091","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3666091","url":null,"abstract":"Detailed electromagnetic transient models of offshore wind farms incorporate the individual wind turbine dynamics and controls of many wind turbines (WTs), resulting in substantial computational burdens. This limits their practicality for large-scale system studies. While aggregation techniques reduce this burden, they often compromise accuracy, particularly in capturing dynamic behaviour during power system disturbances. To overcome this challenge, this paper proposes a gaussian mixture model clustering with information-theoretic averaging to group similar WTs and derive representative aggregated models. A structured eigenvalue sensitivity analysis is conducted to identify the control parameters that have the greatest impact on system dynamics, reducing the dimensionality of the parameter space. Additionally, an improved multi-objective gradient descent optimisation strategy is developed to identify and provide optimal values of system and control parameters under varying wind conditions and fault scenarios to ensure accuracy. The proposed modeling applicability is further demonstrated through assessment on an HVDC connected offshore wind farm under large disturbance and weak grid conditions in the time and frequency domains. Finally, the aggregated model's performance is validated against the detailed benchmark to ensure U.K.’s grid compliance on modeling, confirming its ability to replicate key dynamic and steady-state characteristics with substantially reduced computational effort.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3138-3154"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443063","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

Unified Transmission-Distribution Coordination for Secure and Economical Frequency Support From Distributed Energy Resources 分布式能源安全经济频率保障的统一输配协调

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-27 DOI: 10.1109/TSTE.2026.3668374

Rushuai Han;Qinran Hu;Mengtong Chen;Yuanshi Zhang;Tao Qian;Zaijun Wu

{"title":"Unified Transmission-Distribution Coordination for Secure and Economical Frequency Support From Distributed Energy Resources","authors":"Rushuai Han;Qinran Hu;Mengtong Chen;Yuanshi Zhang;Tao Qian;Zaijun Wu","doi":"10.1109/TSTE.2026.3668374","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3668374","url":null,"abstract":"Utilizing numerous distributed energy resources (DERs) for frequency regulation is a promising pathway to enhance the security and economy offuture power systems. However, a fundamental challenge arises from the emergent collective behavior of these resources: their aggregated response, intended to support macro-level system frequency, can jeopardize micro-level local voltage security within distribution networks. To this end, this paper proposes a unified hierarchical framework based on the principle of synergistic co-design. The framework employs a stage-dependent architecture that systematically integrates distinct control strategies for different regulation stages. For security-critical response, it utilizes a novel stage-aware adaptive virtual synchronous generator (VSG) control method with stability formally proven by Lyapunov analysis, while for economic efficiency, it transitions to a distributed control method for cost-optimal restoration. The entire process is underpinned by a proactive voltage security management strategy that enforces micro-level safety. To enable efficient analysis of these complex dynamics, a dual time-scale information interaction mechanism is designed to accelerate the transmission-distribution (T&D) co-simulation process. Simulations on a hybrid transmission-distribution test system validate the framework's effectiveness, demonstrating that the proposed approach enables scalable, secure, and economical frequency support while effectively managing the emergent voltage challenges from collective DER control.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3155-3171"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443084","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}

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IEEE Transactions on Sustainable Energy Information for Authors IEEE可持续能源信息汇刊

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-06-22 DOI: 10.1109/TSTE.2026.3699287

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Fast Active Power Reduction Based Fault Ride-Through Control Strategy for VSC-HVDC Integrating Offshore Wind Farm Under Onshore Fault 陆上故障下基于快速有功降功率的VSC-HVDC集成海上风电场故障穿越控制策略

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-13 DOI: 10.1109/TSTE.2026.3664471

Manliang Wang;Zhichao Yang;Bingtuan Gao;Shenkai Pan;Lingzhi Zhu

{"title":"Fast Active Power Reduction Based Fault Ride-Through Control Strategy for VSC-HVDC Integrating Offshore Wind Farm Under Onshore Fault","authors":"Manliang Wang;Zhichao Yang;Bingtuan Gao;Shenkai Pan;Lingzhi Zhu","doi":"10.1109/TSTE.2026.3664471","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3664471","url":null,"abstract":"The voltage source converter-based high voltage direct current (VSC-HVDC) integrating offshore wind farm (OWF) system suffers from direct current (DC) overvoltage under onshore grid fault. The existing methods mainly use DC chopper of VSC-HVDC or voltage drop control of the OWF to mitigate DC overvoltage, which lead to high costs or forced tripping of offshore wind turbine generators (WTGs). To suppress DC overvoltage and promote active power recovery, this paper proposes a two-stage fast active power reduction (FAPR) based fault ride-through control strategy. By mathematically clarifying the FAPR capacity of the WTG, the DC chopper resistances of the WTG and VSC-HVDC are economically designed. Then, during stage 1, a scheme that combines FAPR control of the OWF with DC chopper control of VSC-HVDC is proposed to suppresses DC overvoltage. During stage 2, considering the issue of electromagnetic torque saturation when offshore WTGs undergo fast active power recovery, a fast pitch angle reduction control scheme is proposed to facilitate the active power recovery. Simulations and experiments validate that the proposed method avoids DC overvoltage. Besides, the DC chopper resistors are reduced by 90% and 80% compared with DC chopper-based method and voltage drop-based method, respectively.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3033-3047"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443192","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

Causal Self-Supervised Graph Learning for Robust PV Power Forecasting Against Distribution Shift 基于因果自监督图学习的配电转移鲁棒光伏发电预测

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-01-23 DOI: 10.1109/TSTE.2026.3657360

Pengfei Zhao;Weihao Hu;Di Cao;Zhiping Lin;Zhirong Shen;Qi Huang;Zhe Chen

{"title":"Causal Self-Supervised Graph Learning for Robust PV Power Forecasting Against Distribution Shift","authors":"Pengfei Zhao;Weihao Hu;Di Cao;Zhiping Lin;Zhirong Shen;Qi Huang;Zhe Chen","doi":"10.1109/TSTE.2026.3657360","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3657360","url":null,"abstract":"Due to stochastic weather changes and the increasing frequency of extreme weather events in recent years, photovoltaic (PV) power generation data frequently undergo probability distribution shifts in practice. This poses huge challenges for traditional machine learning-based power forecasting methods that rely on unstable correlations between input and output for predictions. To this end, this paper proposes a causal self-supervised graph learning framework for robust power forecasting of multiple PV sites. Specifically, a structural causal model is first built to describe the PV power generation process, which allows us to distinguish the confounder that causes the failure of prior studies. Then, the spurious correlations caused by the confounder are removed through causality intervention with do-calculus and back-door adjustment, which is further solved by our proposed theoretical solution, termed PV generation environment disentangled adaptation (PV-EDA). After that, a self-supervised multi-view graph neural network is devised to implement PV-EDA in a fidelity way, such that causality intervention is effectively realized within the designed forecasting model. The stable causality improves the generalization ability of the proposed model and allows it to achieve robust forecasting performance under varying distributional shift scenarios. Numerical experiments are conducted on real-world PV power output data to evaluate the model’s day-ahead forecasting performance. The results show that the proposed method consistently outperforms state-of-the-art PV forecasting approaches under various distribution shift scenarios.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2676-2692"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148515449","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

Transforming Oilfields Into Hydrogen Hubs via Interval Optimization With Repurposed Well Infrastructure 利用井基础设施进行井段优化，将油田转变为氢气中心

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.2026.3651891

Yingzhao Tang;Shixing Ding;Zhigang Lu;Shuai Lu;Wei Gu;Jiangfeng Zhang;Xiaoqiang Guo

{"title":"Transforming Oilfields Into Hydrogen Hubs via Interval Optimization With Repurposed Well Infrastructure","authors":"Yingzhao Tang;Shixing Ding;Zhigang Lu;Shuai Lu;Wei Gu;Jiangfeng Zhang;Xiaoqiang Guo","doi":"10.1109/TSTE.2026.3651891","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3651891","url":null,"abstract":"The low-carbon energy transition faces the challenges of uncertainty from high renewable energy penetration and the economic reconstruction of traditional fossil fuel regions. Repurposing abandoned oil wells (AOWs) provides an alternative option to facilitate the low-carbon transition and revitalization of these oilfields. This paper aims to propose a novel hydrogen hub-centered oilfield integrated energy system (HH-OIES) to resolve the aforementioned challenges. Synergistic hydrogen-heat repurposing of AOWs can be achieved through integrated hydrogen production, storage, and multi-pathway utilization across various oilfield zones. Furthermore, a multi-objective transition planning and optimization framework for the HH-OIES is developed to overcome the limitations of relying solely on AOWs for heat supply, which cannot adequately address the intermittency of renewables. To solve the proposed model, we introduce a Global Envelope Interval Optimization method.Its solution space enveloping technique effectively handles the planning and operation of complex, large-scale systems, enabling a synergy between economic and low-carbon objectives under varying risk preferences while significantly reducing computational complexity. Simulation results demonstrate the role of the HH-OIES in advancing oilfield transition and validate the effectiveness of the proposed solution method.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2446-2459"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518847","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

Distributed Large-Signal Stability Analysis and Parameter Optimization of Offshore Wind Power Transmission Systems 海上风电传输系统分布式大信号稳定性分析及参数优化

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-01-28 DOI: 10.1109/TSTE.2026.3658495

Haihan Ye;Wu Chen;Junyi Zheng

{"title":"Distributed Large-Signal Stability Analysis and Parameter Optimization of Offshore Wind Power Transmission Systems","authors":"Haihan Ye;Wu Chen;Junyi Zheng","doi":"10.1109/TSTE.2026.3658495","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3658495","url":null,"abstract":"The volatility of wind speeds and the random nature of faults require offshore wind power transmission systems to maintain stable operation under large disturbance conditions. Considering the different equilibrium points of wind turbines and the bidirectional power flow of rectifier stations, the dynamic analysis of the entire offshore AC system is extremely complex, posing challenges for large-signal stability control. To address this issue, this paper proposes a distributed large-signal stability optimization method under the framework of passive control, models offshore wind turbines and rectifier stations with mixed potential functions, and ultimately derives the key constraints that strongly affect the entire offshore AC system via <italic>Brayton-Moser</i> criterion. Comparing with the classic method, the proposed method rectifies the unreasonable expansion of the stable region caused by the power balance calculation, and points out the contribution of zero-sequence control in modular multilevel converters to the stable operation under unexpected power change conditions, which are still effective in expanded wind power plants and time-varying transmission line parameters. Finally, the correctness of the theoretical analysis and parameter settings is verified by simulation results.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2740-2758"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518919","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

Multi-Rate Fast Frequency Regulation With High-Fidelity Neural Network Model of the Electrolyzer Process 基于高保真神经网络的电解槽过程多速率快速调频模型

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-03 DOI: 10.1109/TSTE.2026.3660152

S. Gokul Krishnan;Mohd. Asim Aftab;Shehab Ahmed;Charalambos Konstantinou

{"title":"Multi-Rate Fast Frequency Regulation With High-Fidelity Neural Network Model of the Electrolyzer Process","authors":"S. Gokul Krishnan;Mohd. Asim Aftab;Shehab Ahmed;Charalambos Konstantinou","doi":"10.1109/TSTE.2026.3660152","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3660152","url":null,"abstract":"Frequency regulation is crucial for grid stability, especially with the increasing penetration of inverter-based resources (IBRs). Hydrogen electrolyzers, as flexible loads, offer a promising solution by dynamically adjusting power consumption to counteract frequency deviations. While existing studies primarily focus on electrolyzer stacks and power converters, the role of auxiliary process components such as pumps and coolers remains largely unexplored. This paper proposes a multi-rate frequency response (MRFR) model for hydrogen electrolyzer process plants, distinguishing frequency regulation contributions from both the electrolyzer stack and auxiliary components. A high-fidelity neural network (HiFiNN) model is developed using a detailed alkaline water electrolysis (AWE) process model in <monospace>Aspen HYSYS</monospace>, accurately capturing the interactions between electrical and thermodynamic parameters. The HiFiNN model is integrated with a model predictive controller (MPC) to optimize frequency regulation while maintaining process stability. The proposed framework is validated through simulations and real-time controller-hardware-in-the-loop (CHIL) experiment to validate its feasibility for practical deployment. Additionally, its effectiveness is demonstrated under varying IBR penetration levels, highlighting its capability to maintain frequency stability in low-inertia power systems.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2805-2822"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519381","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

Coordinated Fuzzy Active Power Control of Wind Turbines With Load Optimization 风电机组负荷优化模糊有功协调控制

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-11 DOI: 10.1109/TSTE.2026.3663662

Xuguo Jiao;Hao Luo;Lin Wang;Qinmin Yang;Changjiang Zhu;Fangzheng Nie

{"title":"Coordinated Fuzzy Active Power Control of Wind Turbines With Load Optimization","authors":"Xuguo Jiao;Hao Luo;Lin Wang;Qinmin Yang;Changjiang Zhu;Fangzheng Nie","doi":"10.1109/TSTE.2026.3663662","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3663662","url":null,"abstract":"In modern power systems with a high penetration of wind energy, active power control (APC) enables wind turbines to track the power reference set by the control center. However, the rapidity and accuracy requirements of APC mode always lead to large fatigue loads of turbines’ components. This paper proposes a set of fuzzy logic-based APC strategies integrated together to achieve the joint load optimization of key components while reducing power loss. Firstly, a lower bound parameter for pitch range limitation updated by rotor speed is created to realize a dynamic adjustment of the variable-speed range participating in active power tracking, effectively reducing the load of the pitch system. Secondly, a torque acceleration adjustment parameter is updated adaptively through the established fuzzy logic rules to optimize both acceleration and deceleration performance, thereby reducing power production loss when the available wind power is less than the desired reference. Furthermore, we design an upper bound parameter for pitch range limitation to find a load optimization trade-off among the pitch system, the drive train, and the blade root under high wind speed. Finally, the effectiveness of the proposed controllers is validated on a semi-physical hardware testing platform.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2994-3005"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519392","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