IEEE Transactions on Sustainable Energy最新文献_第10页

Integrated Driving Method to Optimize Operation of Wind Turbines for Weakening the Wake Effect 为减弱尾流效应优化风力机运行的集成驱动方法

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.2026.3663560

Guan Bai;Ping Bai;Mingcheng Lyu;Qiuhua Chen;Sheng Huang;Luobin Wang;Lin Zhu

{"title":"Integrated Driving Method to Optimize Operation of Wind Turbines for Weakening the Wake Effect","authors":"Guan Bai;Ping Bai;Mingcheng Lyu;Qiuhua Chen;Sheng Huang;Luobin Wang;Lin Zhu","doi":"10.1109/TSTE.2026.3663560","DOIUrl":"https://doi.org/10.1109/TSTE.2026.3663560","url":null,"abstract":"The wake effect in wind farms (WFs) leads to wind energy loss and increases the fatigue load of wind turbines (WTs). In this paper, an integrated driving method (IDM) to optimize operation of wind turbines (WTs) for weakening the wake effect. Considering the wake effect with delayed time, a model predicted control (MPC)-based WT control method is proposed to optimize the dual-parameter, i.e., pitch angle and generator torque, for mitigating fatigue load and increasing power generation. To pursue the better optimization effect, the data-driven method (DDM) is proposed to learn the accurate and complete dataset for eliminating linearization errors in the nonlinear physical of wind turbines and engineering wake models. DDM is designed to capture the nonlinear aerodynamic interactions based on the operational status of WTs in wake-affected WFs. It utilizes a convolutional neural network (CNN)-based encoder and a graph neural network (GNN)-based decoder. Subsequently, an artificial neural network (ANN)-based fusion method is proposed to select the better optimization values of these two methods for improving the prediction reliability and anti-measurement noise interference ability. Finally, the efficacy of the proposed scheme is substantiated through case studies involving a wake-affected WF.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 3","pages":"2981-2993"},"PeriodicalIF":10.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148519320","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 Event-Triggered Control of District Cooling Systems for the Frequency Regulation Service of Islanded Microgrids With Quantization Communication 基于量化通信的孤岛微电网调频服务区域供冷系统分布式事件触发控制

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-09-17 DOI: 10.1109/TSTE.2025.3610706

Jinshuo Su;Peipei Yu;Hongcai Zhang;Hui Liu

{"title":"Distributed Event-Triggered Control of District Cooling Systems for the Frequency Regulation Service of Islanded Microgrids With Quantization Communication","authors":"Jinshuo Su;Peipei Yu;Hongcai Zhang;Hui Liu","doi":"10.1109/TSTE.2025.3610706","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3610706","url":null,"abstract":"District Cooling System (DCS), one of the demand-side loads with significant regulation flexibility, is a promising resource for providing frequency regulation services for islanded microgrids (MGs). However, existing control methods for DCSs have huge communication burdens due to the continuous communication mode and extensive communication data. Besides, fair power participation among DCSs is not ensured. This may worsen the frequency performance because some DCSs prematurely exit the regulation service due to excessive use of their regulation capacities. Therefore, this paper proposes a distributed event-triggered control strategy with quantization communication for DCSs to provide frequency regulation service with reduced communication burdens while guaranteeing fair power participation and user comfort requirements. In the proposed strategy, the event-triggered mechanism only allows each DCS to communicate with its neighbors at triggering events, which can reduce communication frequency. The quantization communication technology only transmits quantized data among DCSs, allowing less communication data. Additionally, fair power participation can be achieved by converging the power-adjusting ratios of DCSs to the reference. Furthermore, the stability of the proposed control strategy is strictly proven, and the proposed communication strategy is free from Zeno behavior. Numerical results on the modified IEEE 34-bus system validate the effectiveness of the proposed strategy.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"1173-1190"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148511408","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

Higher Order Recursive Linearization of Power Systems With Electronic Converters 带电子变流器的电力系统的高阶递归线性化

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-10-13 DOI: 10.1109/TSTE.2025.3621155

Marcos A. Hernández-Ortega;A. R. Messina;C. M. Rergis;Sergio Molina-Pineda;Claudia M. Castro-Arvizu

{"title":"Higher Order Recursive Linearization of Power Systems With Electronic Converters","authors":"Marcos A. Hernández-Ortega;A. R. Messina;C. M. Rergis;Sergio Molina-Pineda;Claudia M. Castro-Arvizu","doi":"10.1109/TSTE.2025.3621155","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3621155","url":null,"abstract":"The generation of electrical energy from renewable energy sources (RESs) has increased over the past few decades as part of efforts to reduce humanity’s environmental impact. However, their integration into the power grid through electronic converters (ECs) has introduced several challenges, including reduced global system inertia, diminished stability margins, and issues affecting power system operation, planning, and reliability. Despite these challenges, a comprehensive nonlinear analysis of electric power systems with ECs has not yet been fully addressed. In this article, we analyze the nonlinear model of an electric power system with ECs using recursive linearization to derive higher-order linear models. Our analysis shows that the EC model is transformed into a differential-algebraic equation (DAE) representation, which limits the direct application of nonlinear analysis techniques such as normal forms and perturbed Koopman mode analysis. In contrast, by employing recursive linearization, we derive a Taylor series-based model and an extended Carleman-type model to explore alternative higher-order linear representations. These models are validated using a two-area power system with a wind power plant (WPP) and a 46-machine test system with three WPPs. Additionally, key observations and potential future research directions are discussed.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"1485-1497"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148511884","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 Bilevel Collaborative Planning Framework for Hydrogen Infrastructure Expansion in Offshore and Seaport Energy Systems 海上和海港能源系统中氢基础设施扩展的双层协同规划框架

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-09-05 DOI: 10.1109/TSTE.2025.3606873

Chengzhi Xie;Payman Dehghanian;Abouzar Estebsari;Farid Kochakkashani;Mohannad Alhazmi;David Celeita

{"title":"A Bilevel Collaborative Planning Framework for Hydrogen Infrastructure Expansion in Offshore and Seaport Energy Systems","authors":"Chengzhi Xie;Payman Dehghanian;Abouzar Estebsari;Farid Kochakkashani;Mohannad Alhazmi;David Celeita","doi":"10.1109/TSTE.2025.3606873","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3606873","url":null,"abstract":"Collaborative planning is essential for managing conflict of interests between stakeholders, enabling coordinated decision-making, and ensuring efficient resource allocation. In the pursuit of decarbonization through hydrogen technology expansion, offshore wind power and offshore-produced green hydrogen trades create potential conflicts between offshore wind farm (OWF) owners and seaport power distribution network (PDN) operators, as they face competing interests in energy distribution, infrastructure investments, and market priorities. In the proposed collaborative planning process, the OWF owner, acting as the leader, determines the optimal sizing and deployment of hydrogen technologies to ensure profitability and maximize resource utilization. Meanwhile, the private seaport owner, as the follower, focuses on meeting hydrogen demand by deploying hydrogen technologies, optimizing operational efficiency, and reducing carbon emissions. A conflict arises as the OWF owner seeks to maximize profit by selling more power and hydrogen to the seaport, while the seaport owner aims to minimize operational costs by purchasing less from the OWF while ensuring grid stability. A bilevel collaborative planning model is introduced to formulate the Stackelberg game between the follower and the leader. Karush-Kuhn-Tucker (KKT) conditions are employed to convert the bilevel problem into its single-level counterpart. The binary investment decisions at the lower-level obstruct single-level formulation by violating KKT optimality conditions. To address this, a continuous reformulation of the lower-level problem is developed, ensuring compliance with KKT conditions. The proposed model is validated through three case studies, demonstrating its effectiveness in balancing stakeholder objectives, improving system collaboration, and supporting long-term sustainability goals.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"1090-1103"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512163","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

SolarCrossFormer: Improving Day-Ahead Solar Irradiance Forecasting by Integrating Satellite Imagery and Ground Sensors SolarCrossFormer：通过整合卫星图像和地面传感器改进日前太阳辐照度预报

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-10-22 DOI: 10.1109/TSTE.2025.3624044

Baptiste Schubnel;Jelena Simeunović;Corentin Tissier;Pierre-Jean Alet;Rafael E. Carrillo

{"title":"SolarCrossFormer: Improving Day-Ahead Solar Irradiance Forecasting by Integrating Satellite Imagery and Ground Sensors","authors":"Baptiste Schubnel;Jelena Simeunović;Corentin Tissier;Pierre-Jean Alet;Rafael E. Carrillo","doi":"10.1109/TSTE.2025.3624044","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3624044","url":null,"abstract":"Accurate day-ahead forecasts of solar irradiance are required for the large-scale integration of solar photovoltaic (PV) systems into the power grid. However, current forecasting solutions lack the temporal and spatial resolution required by system operators. In this paper, we introduce SolarCrossFormer, a novel deep learning model for day-ahead irradiance forecasting, that combines satellite images and time series from a ground-based network of meteorological stations. SolarCrossFormer uses novel graph neural networks to exploit the inter- and intra-modal correlations of the input data and improve the accuracy and resolution of the forecasts. It generates probabilistic forecasts for any location in Switzerland with a 15-minute resolution for horizons up to 24 hours ahead. One of the key advantages of SolarCrossFormer its robustness in real life operations. It can incorporate new time-series data without retraining the model and, additionally, it can produce forecasts for locations without input data by using only their coordinates. Experimental results over a dataset of one year and 127 locations across Switzerland show that SolarCrossFormer yield a normalized mean absolute error of 6.1 % over the forecasting horizon. The results are competitive with those achieved by a commercial numerical weather prediction service.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"1575-1587"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512569","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

Energy Filtering Using a Generalized Bandwidth-Based Control Scheme for Hybrid Real and Virtual Energy Storage Systems 基于广义带宽控制的实虚拟混合储能系统能量滤波

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-09-01 DOI: 10.1109/TSTE.2025.3604460

Derek Jackson;Yue Cao

{"title":"Energy Filtering Using a Generalized Bandwidth-Based Control Scheme for Hybrid Real and Virtual Energy Storage Systems","authors":"Derek Jackson;Yue Cao","doi":"10.1109/TSTE.2025.3604460","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3604460","url":null,"abstract":"Hybrid energy storage systems (HESS) involve multi-physics real energy storage and possible virtual energy storage, interfacing through power electronics. Such complex energy systems often employ a hierarchical control approach. Higher-level controls consider the energy management within the system and the dispatching of resources, while lower-level controls manage the power flow, voltage regulation, and SOC balancing of connected storage devices, realized through the connected power electronics. This work proposes a generalized bandwidth-based control scheme for HESS in a dc system that addresses the literature gap of filtration-based controls that have previously prevented them from being used in practice and also within hierarchical control strategies. The generalization unifies control objectives that are commonly considered separately for different storage devices. It also provides a flexible control design framework based on a universal energy storage model (UESM) that is applicable to many hybrid systems and storage devices. Using the UESM, control coefficients are algebraically defined by the model parameters, making this control approach suitable for many storage types. The proposed control scheme is validated on a HESS supported dc microgrid, demonstrating its effectiveness in managing the power flow and SOC regulation within the HESS, while also achieving high-level energy management objectives such as preemptive charging and peak load shaving.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"985-1001"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512749","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 Tri-Level Optimal Sizing of Hydrogen Storage for Addressing Long-Term Seasonal Fluctuation of RES 解决可再生能源长期季节性波动的混合三能级最优储氢规模

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-08-19 DOI: 10.1109/TSTE.2025.3600298

Qianwen Hu;Gengfeng Li;Bingkai Huang;Qiming Yang;Siyuan Sun;Zhaohong Bie;Jianzhong Wu;Yue Zhou;Yiheng Bian

{"title":"Hybrid Tri-Level Optimal Sizing of Hydrogen Storage for Addressing Long-Term Seasonal Fluctuation of RES","authors":"Qianwen Hu;Gengfeng Li;Bingkai Huang;Qiming Yang;Siyuan Sun;Zhaohong Bie;Jianzhong Wu;Yue Zhou;Yiheng Bian","doi":"10.1109/TSTE.2025.3600298","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3600298","url":null,"abstract":"Time-varying renewable energy sources (RES), influenced by climate conditions, create seasonal power mismatches. Allocation of hydrogen energy storage (HES) can mitigate long-duration seasonal power mismatch caused by load variation, climate variability and seasonal meteorological conditions. However, one single uncertainty set cannot well consider the characteristics of RES uncertainty in different seasons impacted by long-term climate conditions. To address the above challenges and optimally size and allocate HES in power systems, this paper proposes a hybrid tri-level planning framework that integrates RES interannual long-term and seasonal fluctuation, using a combination of distributionally robust optimization (DRO) and adaptive robust optimization (ARO). Specifically, a RES probability distribution ambiguity set under typical climate conditions is constructed using norm constraints, and data-driven DRO is introduced to address RES long-term uncertainty. RES seasonal uncertainty is then adaptively modelled using multiple uncertainty sets based on the seasonal meteorological characteristics of RES, and ARO is proposed to reformulate the lower-level problem for the worst-case scenarios. The proposed framework is solved using the improved column and constraint generation algorithm (C&CG) with duality-free decomposition. Simulations on IEEE 39-bus system and IEEE 118-bus system confirm the effectiveness of the proposed planning framework and solution algorithm.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"883-896"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148506166","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

Enhanced Co-Simulation of Wind Energy Conversion Systems: A Mechanically Equivalent Interfacing Method 风能转换系统的增强联合仿真：一种机械等效接口方法

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-08-14 DOI: 10.1109/TSTE.2025.3599154

Bing Li;Haoran Zhao;Yibao Jiang;Changwang Zhao

{"title":"Enhanced Co-Simulation of Wind Energy Conversion Systems: A Mechanically Equivalent Interfacing Method","authors":"Bing Li;Haoran Zhao;Yibao Jiang;Changwang Zhao","doi":"10.1109/TSTE.2025.3599154","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3599154","url":null,"abstract":"Co-simulation of mechanical subsystems (MSs) and electrical subsystems (ESs) is crucial for the efficient design and analysis of wind energy conversion systems (WECSs). The interfacing method is critical to affect the accuracy of such multi-rate co-simulations, due to the inherent multi-timescale nature of WECSs. Existing studies primarily utilize the zero-order-hold (ZOH)-based interfacing method, introducing the stepwise approximation errors for updating interfacing variables. Enhancing co-simulation accuracy via an effective interfacing method remains an open research challenge. This paper proposes a mechanically equivalent interfacing method that accurately predicts interfacing variables, thereby enhancing co-simulation accuracy. A frequency-dependent equivalent model is derived based on the frequency-domain response of the MS. A parameter-free nonlinear identification algorithm is proposed, operating independently of prior MS parameters knowledge to improve generality. Moreover, a linear parameter-varying (LPV) model is introduced to capture nonlinear behavior across the global operating region of the MS. The proposed frequency-dependent equivalent model is verified in both the frequency and time domains using the 5 MW and 10 MW WECSs. Furthermore, the interfacing method is compared with the ZOH-based, higher-order extrapolation interpolation-based, and waveform relaxation-based methods under both normal and fault operating conditions in offline and real-time co-simulations. Simulation results confirm the accuracy advantages of the proposed method for multi-rate co-simulation of WECSs.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"834-853"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148508466","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

Coordination of Power and Transportation Networks With Integrated Electricity-Hydrogen Stations: A Reinforcement Learning Approach Considering Delayed Reward 集成电氢站的电力和交通网络协调：考虑延迟奖励的强化学习方法

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-10-08 DOI: 10.1109/TSTE.2025.3619196

Peiyue Li;Sheng Chen;Zhinong Wei;Qiuwei Wu;Guoqiang Sun;Jiahui Jin

{"title":"Coordination of Power and Transportation Networks With Integrated Electricity-Hydrogen Stations: A Reinforcement Learning Approach Considering Delayed Reward","authors":"Peiyue Li;Sheng Chen;Zhinong Wei;Qiuwei Wu;Guoqiang Sun;Jiahui Jin","doi":"10.1109/TSTE.2025.3619196","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3619196","url":null,"abstract":"The increasing adoption of electric vehicles (EVs) and fuel cell EVs (FCEVs) has intensified the coupling between urban transportation and energy systems. However, existing approaches lack effective optimization strategies for integrated transportation–energy systems, particularly in managing integrated electricity-hydrogen stations (IEHSs) to maximize revenue while serving various vehicle types, such as EVs and FCEVs. The present work proposes a dynamic optimization strategy for IEHSs that enhances the operation of IEHSs, power distribution networks, and transportation networks by guiding vehicle charging and fueling decisions. The sensitivity of vehicular traffic to system-level decisions is ensured by establishing a mixed dynamic user equilibrium model incorporating EVs, FCEVs, and conventional-fuel vehicles. An IEHS operation framework that integrates discount coupon allocation and hydrogen production/storage strategies is designed with traffic flow feedback and distribution locational marginal pricing. The inherent delayed reward problem in transportation, where the impacts of pricing decisions on station revenue and traffic congestion manifest over extended time horizons, is addressed by applying a multi-agent deep reinforcement learning approach, featuring a dual-critic architecture based on long short-term memory networks under the sequence markov decision process framework, to redistribute delayed rewards. The results of numerical computations involving real-world traffic and power networks demonstrate that the proposed approach improves IEHS profitability, balances charging demand, and alleviates traffic congestion compared with static and semi-dynamic traffic approaches.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"1396-1409"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512196","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

Optimal Investment Portfolio of Thyristor- and IGBT-Based Electrolysis Rectifiers in Utility-Scale Renewable P2H Systems 基于晶闸管和igbt的电解整流器在公用事业规模可再生P2H系统中的最佳投资组合

IF 10.3 1区工程技术

IEEE Transactions on Sustainable Energy Pub Date : 2026-04-01 Epub Date: 2025-08-04 DOI: 10.1109/TSTE.2025.3595150

Yangjun Zeng;Yiwei Qiu;Liuchao Xu;Chenjia Gu;Yi Zhou;Jiarong Li;Shi Chen;Buxiang Zhou

{"title":"Optimal Investment Portfolio of Thyristor- and IGBT-Based Electrolysis Rectifiers in Utility-Scale Renewable P2H Systems","authors":"Yangjun Zeng;Yiwei Qiu;Liuchao Xu;Chenjia Gu;Yi Zhou;Jiarong Li;Shi Chen;Buxiang Zhou","doi":"10.1109/TSTE.2025.3595150","DOIUrl":"https://doi.org/10.1109/TSTE.2025.3595150","url":null,"abstract":"Renewable power-to-hydrogen (ReP2H) systems require rectifiers to supply power to electrolyzers (ELZs). Two main types of rectifiers, insulated-gate bipolar transistor rectifiers (IGBT-Rs) and thyristor rectifiers (TRs), offer distinct tradeoffs. IGBT-Rs provide flexible reactive power control but are costly, whereas TRs are more affordable with lower power loss but consume a large amount of uncontrollable reactive power. A mixed configuration of rectifiers in utility-scale ReP2H systems could achieve a decent tradeoff and increase overall profitability. To explore this potential, this paper proposes an optimal investment portfolio model. First, we model and compare the active and reactive power characteristics of ELZs powered by TRs and IGBT-Rs. Second, we consider the investment of ELZs, rectifiers, and var resources and coordinate the operation of renewables, energy storage, var resources, and the on-off switching and load allocation of multiple ELZs. Subsequently, a two-stage stochastic programming (SP) model based on weighted information gap decision theory (W-IGDT) is developed to address the uncertainties of the renewable power and hydrogen price, and we apply the progressive hedging (PH) algorithm to accelerate its solution. Case studies demonstrate that optimal rectifier configurations increase revenue by at most 13.78% compared with configurations using only TRs or IGBT-Rs, existing project setups, or intuitive designs. Under the optimal portfolio, reactive power compensation investment is nearly eliminated, with a preferred TR-to-IGBT-R ratio of 3:1.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"17 2","pages":"740-755"},"PeriodicalIF":10.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512278","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