IEEE Transactions on Sustainable Energy最新文献_第5页

Analysis and Suppression for Temporary Overvoltage Considering Dynamic Interactions Between LCC-HVDC and Renewable Energy Plants 考虑LCC-HVDC与可再生能源电厂动态相互作用的暂态过电压分析与抑制

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-02-05 DOI: 10.1109/TSTE.2025.3538682

Xinyu Liu;Jierui Huang;Di Zheng;Huanhai Xin;Tianshu Bi

{"title":"Analysis and Suppression for Temporary Overvoltage Considering Dynamic Interactions Between LCC-HVDC and Renewable Energy Plants","authors":"Xinyu Liu;Jierui Huang;Di Zheng;Huanhai Xin;Tianshu Bi","doi":"10.1109/TSTE.2025.3538682","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3538682","url":null,"abstract":"Temporary overvoltage (TOV) severely restricts the development and utilization of renewable power resources (RPRs), especially when RPRs are delivered through the line commutated converter-based high voltage direct current (LCC-HVDC) system. To reveal the TOV mechanism for the sending system during commutation failures (CFs), the transient process of the system is partitioned into different stages, where the evolution of the system trajectories is analyzed. On this basis, the variation of AC voltage and DC current considering complex dynamic interactions between LCC-HVDC and renewable energy Plants (REPs) during repetitive CFs (RCFs) is clearly quantified. After revealing the impact of control parameters of both REPs and the LCC-HVDC on the TOV during RCFs, a collaborative optimization method for control parameters is proposed for TOV suppression. Moreover, when the blocking after the RCF tends to be inevitable, the optimal blocking moment is determined to inhibit the TOV caused by HVDC blocking. The accuracy and effectiveness of the proposed methods are verified with EMT simulations of a typical benchmark system.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1849-1859"},"PeriodicalIF":8.6,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331631","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

Study on Output Power of Wind Farm Composed of Current-Source Series-Connected Wind Turbines 电流源串联风力机组成的风电场输出功率研究

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-02-03 DOI: 10.1109/TSTE.2025.3537622

Shoji Nishikata;Fujio Tatsuta

引用次数: 0

Ultra-Short-Term Spatio-Temporal Wind Speed Prediction Based on OWT-STGradRAM 基于OWT-STGradRAM的超短期时空风速预测

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-02-03 DOI: 10.1109/TSTE.2025.3534589

Feihu Hu;Xuan Feng;Huaiwen Xu;Xinhao Liang;Xuanyuan Wang

{"title":"Ultra-Short-Term Spatio-Temporal Wind Speed Prediction Based on OWT-STGradRAM","authors":"Feihu Hu;Xuan Feng;Huaiwen Xu;Xinhao Liang;Xuanyuan Wang","doi":"10.1109/TSTE.2025.3534589","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3534589","url":null,"abstract":"Taking into account the orientation and distance characteristics of wind turbine stations in wind farms can improve the accuracy of wind power prediction. This paper proposed a deep learning spatio-temporal prediction method named orthogonal wind direction transformation spatio-temporal gradient Regression Activation Mapping (OWT-STGrad-RAM) for wind speed prediction. The model encodes the wind farm using an image, and each wind turbine is encoded as a point in the image. The spatio-temporal data related to wind turbines, such as wind speed, temperature, and air pressure, are integrated into fusion features through spatio-temporal fusion convolutional networks model for pre training to obtain a feature dataset. OWT is used to eliminate the effects of different prevailing winds, and STGrad-RAM is used to characterize the orientation and distance between wind turbine nodes and make the spatial features interpretable. The feature dataset is used for wind speed prediction. The experimental results show that the proposed method has achieved a significant improvement in wind speed prediction accuracy compared to the comparative models.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1816-1826"},"PeriodicalIF":8.6,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331735","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

Learning a Robust Fuzzy Cognitive Map Based on Bubble Entropy Fusion With SCAD Regularization for Solar Power Generation 基于气泡熵融合和SCAD正则化的太阳能发电鲁棒模糊认知图学习

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-02-03 DOI: 10.1109/TSTE.2025.3537612

Shoujiang Li;Jianzhou Wang;Hui Zhang;Yong Liang

{"title":"Learning a Robust Fuzzy Cognitive Map Based on Bubble Entropy Fusion With SCAD Regularization for Solar Power Generation","authors":"Shoujiang Li;Jianzhou Wang;Hui Zhang;Yong Liang","doi":"10.1109/TSTE.2025.3537612","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3537612","url":null,"abstract":"Accurate and reliable solar photovoltaic (PV) power forecasting are crucial for cost-effective resource planning and stable operation of smart grids. However, current methods are affected by the intermittent, non-stationary and stochastic nature of solar energy and thus cannot satisfy the requirement of high-precision forecasting. To this end, we propose a fuzzy cognitive map (FCM) forecasting method based on bubble entropy and smoothly clipped absolute deviation (SCAD) regularization, called BesFCM. This method first utilizes bubble entropy to fuse two mode decomposition methods to improve the representation of PV data to capture effective features with significant stability and discriminative ability, then employs a FCM with a combination of fuzzy logic, neural networks, and expert systems to model solar PV power generation, and finally develops a high order FCM learning method based on SCAD regularization to alleviate the overfitting problem, enhancing the robustness and generalization ability of forecasting. Experimental results demonstrate that the BesFCM achieves the best overall performance on PV power datasets from multiple sampling intervals in multiple regions of Belgium compared to multiple state-of-the-art baselines, validating the effectiveness for solar power generation forecasting, providing support and reference for improving the quality of smart grid dispatch and reducing spare capacity reserves.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1837-1848"},"PeriodicalIF":8.6,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329500","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 Multi-Objective Bi-Level LVRT Control Strategy for Two-Stage PV Grid-Connected System Under Asymmetrical Faults 非对称故障下两级光伏并网系统多目标双级LVRT控制策略

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-01-30 DOI: 10.1109/TSTE.2025.3536099

Yiqian Wang;Qi Zhao;Wen Zhang;Tingting Zhang;Xianzhuo Sun;Mingkui Wei;Li Shen;Hua Ye

{"title":"A Multi-Objective Bi-Level LVRT Control Strategy for Two-Stage PV Grid-Connected System Under Asymmetrical Faults","authors":"Yiqian Wang;Qi Zhao;Wen Zhang;Tingting Zhang;Xianzhuo Sun;Mingkui Wei;Li Shen;Hua Ye","doi":"10.1109/TSTE.2025.3536099","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3536099","url":null,"abstract":"With the increasing integration of photovoltaics (PV) into power systems, the low-voltage ride-through (LVRT) control of PV grid-connected systems is drawing significant attention. This paper presents a multi-objective bi-level LVRT control strategy for the two-stage PV grid-connected system to maximize the positive and negative sequence voltage support capability while ensuring safe operation under asymmetrical faults. The AC level controls the grid side inverter, while the DC level regulates the boost converter. The grid voltage support control strategy is implemented at the AC level to support the positive and negative sequence voltage of the point of common coupling. Considering there is an inherent contradiction between grid voltage support with the overcurrent of inverter and DC voltage oscillation, the current references are automatically adjusted to facilitate the maximum positive and negative voltage support while limiting the overcurrent and oscillation of DC-link voltage. Based on the power reference shared from the AC level, the DC level regulates the boost converter to stabilize the DC-link voltage speedily by utilizing the compensation current. Finally, simulations and experiments demonstrate the voltage support capability and fast dynamic response characteristics of DC-link voltage in different scenarios.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 2","pages":"1467-1482"},"PeriodicalIF":8.6,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667385","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 Coordinated Adaptive SMC Method for Frequency Regulation Control in Power Systems With Multiple Wind Farms 多风电场电力系统频率调节的协调自适应SMC方法

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-01-27 DOI: 10.1109/TSTE.2025.3535224

Nan Zhang;Zheren Zhang;Zheng Xu

{"title":"A Coordinated Adaptive SMC Method for Frequency Regulation Control in Power Systems With Multiple Wind Farms","authors":"Nan Zhang;Zheren Zhang;Zheng Xu","doi":"10.1109/TSTE.2025.3535224","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3535224","url":null,"abstract":"The extensive integration of renewable energy resources inevitably gives rise to the complex and uncertain power system, where the somber matter of frequency instability becomes apparent. This article presents a coordinated adaptive radial basis function neural network (RBFNN)-based sliding mode control (CAR-SMC) to reduce the frequency deviation and oscillation of the uncertain power system comprising multiple wind farms. Firstly, the SMC is aimed at establishing the upper layer control law of the frequency regulation controllers. Then, the uncertainties are represented with RBFNN, and an adaptive law is employed to estimate the uncertainties online rapidly and realize the free-chattering of SMC. Furthermore, since a single SMC is only capable of handling a single control input system, a power distribution law based on momentum is proposed to implement the multiple control inputs of the AR-SMC, and also coordinate the frequency regulation abilities of wind turbines and energy storage systems (ESSs). Eventually, the proposed CAR-SMC is validated on a modified IEEE 39-bus system. The simulation results demonstrate that CAR-SMC can enhance the frequency stability in the presence of disturbances and uncertainties during steady-state operation, as well as in under-frequency and over-frequency scenarios.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1806-1815"},"PeriodicalIF":8.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502910","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

Customized Mean Field Game Method of Virtual Power Plant for Real-Time Peak Regulation 面向实时调峰的虚拟电厂自定义平均场博弈方法

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-01-27 DOI: 10.1109/TSTE.2025.3533929

Kuan Zhang;Yawen Xie;Nian Liu;Siqi Chen

{"title":"Customized Mean Field Game Method of Virtual Power Plant for Real-Time Peak Regulation","authors":"Kuan Zhang;Yawen Xie;Nian Liu;Siqi Chen","doi":"10.1109/TSTE.2025.3533929","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3533929","url":null,"abstract":"This paper proposes a customized incentive compatible mean field game (MFG) method for virtual power plant (VPP) with a large number of self-interest heterogeneous distributed energy resources (DERs) to participate in the real-time peak regulation. Firstly, an optimal chance-constrained peak-regulation bidding model of VPP considering the stochastic power flexibility is formulated, where inscribed pyramid approximation method is utilized to form a compact and concise dispatch region. Secondly, a customized MFG method with dynamic granulation division is proposed for encouraging very large-scale DERs to spontaneously respond to the peak regulation instructions from VPP while achieving dynamic allocation of peak-regulation revenue. Brouwer fixed-point theorem and contraction mapping theorem are used to prove the existence and uniqueness of the mean field equilibrium (MFE) of the formulated MFG, and ϵ-Nash property of MFE is validated based on the Lipschitz continuity condition. Furthermore, an accelerated decentralized solution algorithm is developed to rapidly search MFE, exhibiting good scalability. Comparative studies have validated the superiority of the proposed methodology on incentive compatibility and decomposition efficiency of the VPP's peak-regulation instructions.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 2","pages":"1453-1466"},"PeriodicalIF":8.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667583","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

Advanced Grid-Forming Undersea Pumped Storage to Enable 100% Renewable Offshore Oilfield Power Systems 先进的海底抽水蓄能系统，可实现100%可再生的海上油田电力系统

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-01-27 DOI: 10.1109/TSTE.2025.3533893

Kaiyuan Su;Xi Wang;Xiaorong Xie

{"title":"Advanced Grid-Forming Undersea Pumped Storage to Enable 100% Renewable Offshore Oilfield Power Systems","authors":"Kaiyuan Su;Xi Wang;Xiaorong Xie","doi":"10.1109/TSTE.2025.3533893","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3533893","url":null,"abstract":"To advance carbon reduction of the offshore oilfield power system (OOPS), the grid-forming undersea pumped storage system (GFM-UPSS) emerges as a promising solution. This paper introduces a novel framework for a 100% renewable OOPS utilizing the GFM-UPSS. Firstly, the control strategy of the GFM-UPSS is presented. It consists of the grid-side converter (GSC), machine-side converter (MSC), and reversible pump-turbine (RPT) to achieve frequency and voltage regulation. A steady-state model is then developed detailing the water head, power, and volume of the spherical shell. In addition, the paper explores the converter parameter impacts on the GFM-UPSS transient model and derives the closed-form solutions. With the steady-state model, an optimal sizing method is presented and economic advantages in the marine environment are studied for the GFM-UPSS. Finally, EMT simulations are conducted to assess the frequency & voltage stabilities and verify the effectiveness of the GFM-UPSS in enabling a 100% renewable OOPS. The optimal sizing results show that construction costs, mainly for OWP, are dominated and are influenced by sphere radius, placement depth, and start-stop cycles, while a 2.5 capacity ratio between OWP and GFM-UPSS consistently emerges as optimal. Moreover, analysis of transient stability shows that it improves with higher frequency & voltage modulation coefficient and lower virtual impedance. The impact of RPT and MSC, mainly on frequency regulation, is determined by the DC droop coefficient and turbine inertia.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1791-1805"},"PeriodicalIF":8.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331701","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

Complex Variable Design for Power Control of Grid-Forming Inverter 成网逆变器功率控制的复杂变量设计

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-01-27 DOI: 10.1109/TSTE.2025.3533971

Xiangjun Quan;Dale Li;Zhixiang Zou;Qinran Hu;Zaijun Wu;Wei Gu;Huiyu Miao

引用次数: 0

Inertia Transmission Control of Full-Power Converter Variable-Speed Pumped Storage System for Grid Frequency Support 电网频率支持下全功率变流器变速抽水蓄能系统的惯性传递控制

IF 8.6 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2025-01-24 DOI: 10.1109/TSTE.2025.3533493

Kaihsun Chuang;Xiongfei Tao;Yihang Luan;Minxuan Peng;Jianjun Sun;Xiaoming Zha

{"title":"Inertia Transmission Control of Full-Power Converter Variable-Speed Pumped Storage System for Grid Frequency Support","authors":"Kaihsun Chuang;Xiongfei Tao;Yihang Luan;Minxuan Peng;Jianjun Sun;Xiaoming Zha","doi":"10.1109/TSTE.2025.3533493","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3533493","url":null,"abstract":"Full-power converter variable-speed pumped storage (FPC-VSPS) is a promising technique for flexible power regulation in small-scale distributed hydroelectric power plants. However, conventional vector control limits the synchronous motor of the FPC-VSPS from providing inertia support to the power grid. To overcome this limitation, this paper introduces an inertia transmission control for FPC-VSPS based on the concept of DC voltage synchronization. Firstly, the control incorporates the DC capacitor power equation into the GSC control. To enable inertia transmission from the FPC-VSPS synchronous machine, the DC capacitor dynamics are fed into both the speed and torque control of the MSC. Secondly, a torsion spring-rigid body equivalent model is introduced based on the inertia transmission process, analyzing the effects of physical parameters, control coefficients, and transmission delays on the inertia transmission performance. Theoretical analysis and simulation results reveal that the inherent physical differences and transmission delay have a negative impact on the effectiveness of the inertia transmission. Consequently, a DC capacitor design method based on inertia matching is proposed, accounting for the constraints of physical inertia matching, system stability, and operational security. Finally, simulations and experiments prove the necessity of inertia matching and verify the effectiveness of the proposed control to cope with frequency fluctuations in both pumping and generating modes.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1776-1790"},"PeriodicalIF":8.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331702","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