IEEE Transactions on Sustainable Energy最新文献_第7页

Stability Boundary Analysis for Grid-Following and Grid-Forming Inverters 随网与成网逆变器的稳定性边界分析

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-16 DOI: 10.1109/TSTE.2026.3665371

Xi Luo;Efstratios Batzelis;Abhinav Kumar Singh

{"title":"Stability Boundary Analysis for Grid-Following and Grid-Forming Inverters","authors":"Xi Luo;Efstratios Batzelis;Abhinav Kumar Singh","doi":"10.1109/TSTE.2026.3665371","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3665371","url":null,"abstract":"Studying the dynamics and stability of inverter-driven power systems has become a top priority for grid operators in view of the massive renewable energy deployment. The simplest and most widely used model for stability analysis for such networks is the single-inverter single-bus (SISB) equivalent model. Although quite insightful, SISB models with an L-filter for the inverter suffer from implementation difficulties due to algebraic loops. This paper develops a closed-form SISB model for grid-following (GFL) and grid-forming (GFM) inverters and derives symbolic formulation for the linearized system, which resolves algebraic loops and obtains fast results with uncompromised precision. This model is then used in an N-Dimensional Stability Boundary Tracking (ND-SBT) algorithm, which identifies the stability boundary for GFL and GFM inverters. This is the first method to infer the stability region for an arbitrary number of dimensions in a computationally efficient and software-agnostic manner while preserving accuracy. A detailed sensitivity analysis yields useful findings on the stability impact of individual parameters, while the results are validated using the IEEE 14-bus system.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"3080-3093"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443286","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

Central Controller for Photovoltaic Power Plants With Hybrid Energy Storage Systems Providing Automatic Frequency Restoration Reserve 具有自动频率恢复储备的混合储能光伏电站中央控制器

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-01-14 DOI: 10.1109/TSTE.2026.3653342

Juan Diego Rios-Peñaloza;Andrea Prevedi;Milan Prodanović;Javier Roldán-Pérez

{"title":"Central Controller for Photovoltaic Power Plants With Hybrid Energy Storage Systems Providing Automatic Frequency Restoration Reserve","authors":"Juan Diego Rios-Peñaloza;Andrea Prevedi;Milan Prodanović;Javier Roldán-Pérez","doi":"10.1109/TSTE.2026.3653342","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3653342","url":null,"abstract":"Large-scale photovoltaic (PV) power plants have been increasingly used in ancillary service markets, providing services at significantly different time scales. These plants require additional flexibility to provide different services simultaneously and the solution is often sought in application of hybrid energy storage systems (HESSs). In HESSs, the power demand is shared between the storage units to maximise their performance and lifetime. However, this requires a detailed model of all storage elements that must be taken into account by the central controller of the PV plant. This aspect has not been yet studied in detail in the literature. In this paper, a central controller is proposed for a PV power plant with a HESS. This controller allows the PV plant to participate simultaneously in the day-ahead and the secondary reserve markets, providing both energy and power reserve services. First, the assets are scheduled in an optimal way, considering a horizon of 24 hours and taking into consideration weather forecasts and the expected balancing energy requests. Then, a short-term rolling-horizon optimisation with a time horizon of 30 minutes is used to consider the real operating conditions of the PV power plant and state of the storage units. The efficiency of each of the storage elements is modelled in detail for the short-term optimisation. The proposed controller is applied to a test case consisting of a 20 MW PV power plant with a HESS based on a lithium-ion battery and a redox-flow battery, each with 5 MW power and 10 MWh capacity. The main contributions are verified by using numerical simulations performed in MATLAB/Simulink for the electrical system and Gurobi for the optimisation procedures.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2543-2557"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11353033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated SOFC-GT Generation System: Modeling, Analysis, and Grid Forming Control 集成SOFC-GT生成系统：建模，分析和网格成形控制

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-12-18 DOI: 10.1109/TSTE.2025.3645561

Changyue Li;Hanbin Dang;Tianyu Yang;Yuhua Du;Zhipeng Li;Yigeng Huangfu

{"title":"Integrated SOFC-GT Generation System: Modeling, Analysis, and Grid Forming Control","authors":"Changyue Li;Hanbin Dang;Tianyu Yang;Yuhua Du;Zhipeng Li;Yigeng Huangfu","doi":"10.1109/TSTE.2025.3645561","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3645561","url":null,"abstract":"By incorporating the multi-energy interconversion among electrical, gas, and heat, a combination of solid oxide fuel cell (SOFC) and gas turbine (GT) represents advanced performance in efficiency, dispatchability, and service life. In this paper, an integrated control strategy is proposed to enhance the operating principle of the integrated SOFC-GT generation system (ISGS) with droop characteristics, thereby enabling the system to possess grid-forming (GFM) capability. Compared with the conventional GFM units that are based on battery energy storage systems (BESS), the proposed ISGS represents extended operational lifespan, increased power capacity, and inherent mechanical inertia. Compared with the state-of-the-art techniques that also adopt SOFC-GT configuration, the developed method achieves enhanced GFM capabilities. A comprehensive operational framework for the ISGS is developed that explicitly addresses the dynamic coupling and real-time interconversion among electricity, chemical gas, and thermal energy flows. Furthermore, through the Controller Hardware-in-the-Loop (C-HIL) testing platform, the effectiveness of the proposed GFM control method has been validated considering various system configurations, different load disturbances, and unexpected generation failures.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2249-2266"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518568","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

RoCoF Constrained Regional Inertia Security Region: Formulation and Application RoCoF约束区域惯性安全区域：构建与应用

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.2026.3652737

Jiahao Liu;Cheng Wang;Tianshu Bi

引用次数: 0

Analytical Globally Optimal Solution for Multiperiod Self-Scheduling of Energy Storage via Parametric Dynamic Programming 基于参数动态规划的多周期储能自调度全局解析最优解

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-12-10 DOI: 10.1109/TSTE.2025.3642273

Hongyuan Liang;Zhigang Li;Qi Wang;Ye Guo;Xiongming Tao;J. H. Zheng

引用次数: 0

CDT-RiskNet: A Risk-Aware Copula-Diffusion-Transformer Network for Stochastic EV Charging Station Optimization in Energy Market CDT-RiskNet：能源市场中随机电动汽车充电站优化的风险感知联合扩散变压器网络

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2026-02-10 DOI: 10.1109/TSTE.2026.3663278

Xihao Wang;Xiaojun Wang;Zhao Liu;Jianzhong Wu;Jinghan He

引用次数: 0

Optimal Primary Frequency Regulation Provision Based on Demand-Side Resource Complementarity: A Spatial-Temporal Coordination Framework 基于需求侧资源互补的最优一次频率调节：一个时空协调框架

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-11-21 DOI: 10.1109/TSTE.2025.3635657

Songyan Zhang;Di Liu;Peixuan Wu;Chao Lu

{"title":"Optimal Primary Frequency Regulation Provision Based on Demand-Side Resource Complementarity: A Spatial-Temporal Coordination Framework","authors":"Songyan Zhang;Di Liu;Peixuan Wu;Chao Lu","doi":"10.1109/TSTE.2025.3635657","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3635657","url":null,"abstract":"To facilitate the provision of primary frequency regulation (PFR) from active distribution networks (ADNs), this paper proposes a spatial–temporal coordination framework, where up-regulation (UR), down-regulation (DR) and voltage/var control (VVC) tasks are strategically allocated to electric vehicle (EV) clusters and distributed photovoltaics (DPVs) through a three-stage implementation. In node-level assessment stage, node controllers assess the PFR and VVC capabilities of resources in parallel, with special attention to DPV generation uncertainty and time-coupled EV charging demand. In ADN-level dispatch stage, the distribution system operator (DSO) controller co-optimizes PFR scheme and VVC policy to assess the ADN’s aggregate frequency support capability (FSC) and then optimally execute the assigned PFR task with voltage security guarantee. In online deployment stage, resources perform dispatched PFR scheme and suppress the PFR-induced voltage fluctuations with only local measurement. Simulation results indicate that the proposed framework can achieve economical and continuous demand-side PFR provision while reducing the negative impact of PFR service on the voltage quality of the ADNs.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"1952-1966"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148515406","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

Privacy-Preserving Distributed Optimal Dispatch of Shared Energy Storage Considering Battery Degradation Cost 考虑电池退化成本的共享储能保护分布式最优调度

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-12-18 DOI: 10.1109/TSTE.2025.3646082

Mohamed Elimam;Mohamed Shawky El Moursi;Tarek H. M. EL-Fouly;Ahmed Al-Durra;Khalifa Hassan Al Hosani

{"title":"Privacy-Preserving Distributed Optimal Dispatch of Shared Energy Storage Considering Battery Degradation Cost","authors":"Mohamed Elimam;Mohamed Shawky El Moursi;Tarek H. M. EL-Fouly;Ahmed Al-Durra;Khalifa Hassan Al Hosani","doi":"10.1109/TSTE.2025.3646082","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3646082","url":null,"abstract":"Shared energy storage (ES) systems provide a solution for improving the use of intermittent renewable energy while reducing the high capital costs and limited efficiency of individual storage units. This paper proposes a privacy-preserving distributed framework for the optimal operation of a shared ES system collectively owned by multiple microgrids. The proposed framework integrates a novel battery degradation cost model and explicitly accounts for uncertainties in load demand and renewable generation. It consists of two stages: the first stage is a mixed-integer linear programming (MILP) model that minimizes total operational and degradation costs under uncertainty, solved in a distributed manner using Benders decomposition to preserve data privacy. The second stage applies generalized Nash bargaining theory, using ownership percentages as bargaining powers to fairly distribute the benefits among microgrids. Simulation results on a system of four interconnected microgrids demonstrate a 19.2% reduction in total operational cost compared to private storage. Moreover, the cost reduction is consistent across various share distributions.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2279-2292"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148517278","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

Data-Driven Adaptive Control of Distributed PV Clusters in Active Distribution Networks Based on Primal-Dual Transformation 基于原对偶变换的有源配电网分布式光伏集群数据驱动自适应控制

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-07-01 Epub Date: 2025-12-25 DOI: 10.1109/TSTE.2025.3648118

Hao Yu;Yapeng Rong;Haoran Ji;Peng Li;Jiancheng Yu;Guanyu Song;Jinli Zhao;Jianzhong Wu

{"title":"Data-Driven Adaptive Control of Distributed PV Clusters in Active Distribution Networks Based on Primal-Dual Transformation","authors":"Hao Yu;Yapeng Rong;Haoran Ji;Peng Li;Jiancheng Yu;Guanyu Song;Jinli Zhao;Jianzhong Wu","doi":"10.1109/TSTE.2025.3648118","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3648118","url":null,"abstract":"The high penetration of photovoltaic (PV) systems brings significant operational challenges in active distribution networks (ADNs), such as overloads and voltage violations. To address these issues, this paper proposes a data-driven adaptive control method for distributed PV clusters based on primal-dual transformation. The complex physical constraints for PV control are relaxed and decoupled to reduce the problem complexity. A hierarchical coordinated control framework is developed to facilitate data-driven optimization of PV control strategies under fluctuating conditions without requiring accurate ADN parameters. Furthermore, a dynamic coordination approach based on the Gompertz curve model is introduced to manage the active and reactive power of PVs in real time, eliminating the need for prior knowledge of converter reactive power capacity. The proposed method is validated on modified IEEE 33-node and IEEE 123-node test systems. Simulation results demonstrate its effectiveness in mitigating voltage and power violations, confirming its practicality and adaptability in uncertain network conditions.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2350-2364"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518385","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

Photovoltaic Power Prediction Based on Cloud Spatial Position Correction and Occlusion Potential Evaluation 基于云空间位置校正和遮挡势评估的光伏功率预测

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.2025.3645259

Yang Cui;Han Zhu;Jietan Zhang;Guanghui Wang

{"title":"Photovoltaic Power Prediction Based on Cloud Spatial Position Correction and Occlusion Potential Evaluation","authors":"Yang Cui;Han Zhu;Jietan Zhang;Guanghui Wang","doi":"10.1109/TSTE.2025.3645259","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3645259","url":null,"abstract":"Cloud occlusion is the primary factor responsible for photovoltaic (PV) power fluctuations. Existing PV power prediction methods based on satellite observation data face the following challenges: 1) The cloud occlusion model lacks sufficient refinement. 2) Quantifying the degree of interference of cloud in different regions on PV power generation is difficult. To solve these problems, this paper proposes a PV power prediction method based on cloud spatial position correction and occlusion potential evaluation. Initially, satellite-observed cloud height data are introduced, followed by the development of an end-to-end model to predict the spatial distribution of clouds. Next, a cloud spatial position correction model is proposed to adjust the position of clouds in the local spatial coordinate system, enabling the construction of a refined cloud occlusion model. Then, a cloud occlusion potential evaluation model is developed to quantify the degree of cloud occlusion in different regions. Clouds with low-occlusion potential are removed. The remaining clouds form a disordered point cloud set, which is processed by parallel PointNet to extract occlusion features and generate an occlusion factor. This factor, combined with other variables forms a multivariate time series, enabling the accurate power prediction using a neural network. Verification results show that the proposed method can effectively reduce prediction error.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2193-2205"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148518391","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