IET Smart Grid最新文献_第7页

IF 2.7

IET Smart Grid Pub Date : 2026-02-12

引用次数: 0

Mobile Microgrids: Concepts, Key Technologies, Business Models, Applications and Prospects 移动微电网：概念，关键技术，商业模式，应用和前景

IF 2.7

IET Smart Grid Pub Date : 2026-02-12 DOI: 10.1049/stg2.70069

Tao Ding, Chenggang Mu, Yujie Ding, Shunqi Wang, Rui Song, Mohammad Shahidehpour

{"title":"Mobile Microgrids: Concepts, Key Technologies, Business Models, Applications and Prospects","authors":"Tao Ding, Chenggang Mu, Yujie Ding, Shunqi Wang, Rui Song, Mohammad Shahidehpour","doi":"10.1049/stg2.70069","DOIUrl":"10.1049/stg2.70069","url":null,"abstract":"The expansion of global energy systems will require a crucial shift towards durable and flexible technologies. The rapid growth of renewable energy sources demands practical solutions to ensure a stable and reliable power supply within the electrical distribution grid. Microgrid technologies, by integrating various energy sources, offer optimised dispatching to enhance the reliability, resilience, economy, security and sustainability of the grid. However, stationary microgrids, which rely on fixed resources and infrastructure, may encounter challenges such as deployment difficulties and limited flexibility under extreme and special conditions. This paper introduces Mobile Microgrids (MMGs) as an agile solution to augment traditional and stationary microgrid systems, enhancing their flexibility and resilience. MMGs integrate renewable energy sources, energy storage systems and advanced communication technologies to provide reliable and flexible power solutions. We systematically review the key technologies behind MMGs, their business models and applications in diverse critical sectors. This work further discusses the strengths and limitations of existing MMG implementations and provides a critical analysis of current research gaps. We emphasise MMGs' pivotal role in improving grid resilience, offering insights into their prospects and proposing directions for further development in mobile energy systems. By synthesising the existing literature, this review aims to contribute a coherent framework for understanding MMGs and their transformative potential in the global energy landscape.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146680402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flexible Operation of High Voltage Distribution Network for Transmission Congestion Mitigation in Urban Power Grid With Spatio-Temporal Load 城市电网时空负荷下高压配电网柔性运行缓解输电拥塞

IF 2.7

IET Smart Grid Pub Date : 2026-02-11 DOI: 10.1049/stg2.70072

Gang Chen, Chengwei Fan, Shudi Liu, Peng Shi, Yang Huang, Zhaoming Guo, Aoyang Jiang, Youbo Liu

{"title":"Flexible Operation of High Voltage Distribution Network for Transmission Congestion Mitigation in Urban Power Grid With Spatio-Temporal Load","authors":"Gang Chen, Chengwei Fan, Shudi Liu, Peng Shi, Yang Huang, Zhaoming Guo, Aoyang Jiang, Youbo Liu","doi":"10.1049/stg2.70072","DOIUrl":"10.1049/stg2.70072","url":null,"abstract":"This paper investigates the integration of high-voltage distribution network (HVDN) load transfer and electric vehicle (EV) rescheduling as a strategy for mitigating transmission congestion in urban power grids (UPGs). To facilitate a simplified network representation, a transformer unit is introduced for modelling the HVDN topology. A comparative analysis of four operational scenarios—namely, the load curtailment scenario, HVDN load transfer scenario, EV rescheduling scenario and combined scenario of EV rescheduling and HVDN load transfer—demonstrates that the proposed combined strategy achieves the minimal levels of load curtailment and HVDN switching operations. These results highlight the synergistic benefits of jointly leveraging supply-side flexibility through network reconfiguration and demand-side flexibility through EV scheduling. The study underscores the importance of co-optimising grid topology and EV charging behaviour to improve the operational efficiency and reliability of UPGs.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.7

IET Smart Grid Pub Date : 2026-02-11

引用次数: 0

A Bilevel Optimisation Model for Distributed Energy Storage Considering Wind-Solar Uncertainty and Carbon Trading 考虑风能-太阳能不确定性和碳交易的分布式储能双层优化模型

IF 2.7

IET Smart Grid Pub Date : 2026-02-10 DOI: 10.1049/stg2.70059

Xiaonan Li, Rongxin Sun, Wenxu Zhang, Zhanhong Wei, Xiping Ma

{"title":"A Bilevel Optimisation Model for Distributed Energy Storage Considering Wind-Solar Uncertainty and Carbon Trading","authors":"Xiaonan Li, Rongxin Sun, Wenxu Zhang, Zhanhong Wei, Xiping Ma","doi":"10.1049/stg2.70059","DOIUrl":"https://doi.org/10.1049/stg2.70059","url":null,"abstract":"To achieve the ‘Dual Carbon’ strategic goals, the integration of a high proportion of renewable energy poses significant challenges to the stability and economic efficiency of power systems. This paper proposes a bilevel optimisation method for distributed energy storage configuration that integrates wind-solar power uncertainty and a carbon trading mechanism. First, a spectral normalisation generative adversarial network (SNGAN) is employed to generate a large number of wind-solar power output scenarios. These scenarios are then reduced using the K-means clustering algorithm to obtain typical representative scenarios, significantly improving the quality of scenario generation. Second, a bilevel optimisation model is constructed for distributed energy storage configuration considering a tiered carbon trading scheme. The upper-level model aims to minimise the total cost, including energy storage investment, grid electricity purchase and carbon trading costs, whereas the lower-level model focuses on minimising power grid vulnerability indices and active power losses. Finally, an improved Osprey Optimisation Algorithm is developed to solve the bilevel model. Simulation results demonstrate that the proposed method reduces annual carbon emissions by 22.6%, daily active power loss by 22.3% and daily electricity purchase cost by 9.2% compared to the case without ESS and carbon trading while significantly enhancing overall power system performance.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Overcurrent Suppression Strategy for Distributed Photovoltaic Inverters Under Unbalanced Faults Based on Adaptive Linear Active Disturbance Rejection Control 基于自适应线性自抗扰控制的分布式光伏逆变器不平衡故障过流抑制策略

IF 3.1

IET Smart Grid Pub Date : 2026-01-31 DOI: 10.1049/stg2.70060

Dandan Zhu, Qian Zhou, Yongyong Jia, Dajiang Wang, Jianhui Meng, Xintong Dong, Junyuan Zhang

{"title":"An Overcurrent Suppression Strategy for Distributed Photovoltaic Inverters Under Unbalanced Faults Based on Adaptive Linear Active Disturbance Rejection Control","authors":"Dandan Zhu, Qian Zhou, Yongyong Jia, Dajiang Wang, Jianhui Meng, Xintong Dong, Junyuan Zhang","doi":"10.1049/stg2.70060","DOIUrl":"10.1049/stg2.70060","url":null,"abstract":"After distributed photovoltaic (PV) systems are connected to the distribution network, the overcurrent problem caused by transient faults instantaneously threatens the safety of PV inverters and other equipment. This paper proposes a comprehensive control method that combines active-loop adaptive linear active disturbance rejection control (A-LADRC) with fault voltage adaptation and reactive-loop smooth switching to address the transient overcurrent issue of inverters under unbalanced faults. Firstly, the low-voltage ride-through (LVRT) control principle of distributed PV systems and the mechanism of overcurrent generation under unbalanced faults in the distribution network are elaborated, the phenomenon of grid-connected current exceeding the rated threshold due to fault voltage is analysed. Secondly, a fault voltage-adaptive linear active disturbance rejection control method is designed, which is mainly used to address the overcurrent problem at the moment of fault occurrence and recovery. Additionally, to address the overcurrent caused by reactive power control during the fault period, a reactive power outer-loop smooth switching method is introduced. Finally, a hardware-in-the-loop (HIL) experimental platform based on a real-time simulator and an actual PV inverter controller is built to verify the effectiveness and superiority of the proposed method in suppressing overcurrent.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Distributed Federated Reinforcement Learning Approach for Scheduling User-Side Flexibility Resources in Virtual Power Plants 虚拟电厂用户侧灵活性资源调度的分布式联邦强化学习方法

IF 3.1

IET Smart Grid Pub Date : 2026-01-28 DOI: 10.1049/stg2.70043

Heng Hu, Jian Liu, Meng Hou, Ying Liu, Yunpeng Jiang, Chuan Liu

{"title":"A Distributed Federated Reinforcement Learning Approach for Scheduling User-Side Flexibility Resources in Virtual Power Plants","authors":"Heng Hu, Jian Liu, Meng Hou, Ying Liu, Yunpeng Jiang, Chuan Liu","doi":"10.1049/stg2.70043","DOIUrl":"10.1049/stg2.70043","url":null,"abstract":"The high penetration of renewables increases the volatility of the net load, revealing flexibility shortages in distribution networks. This paper proposes a coordination framework for multiple virtual power plants (VPPs) that aggregates distributed flexibility resources (e.g., electric vehicles, battery energy storage systems and shiftable loads) to enhance the adaptability of the system. The flexibility supply–demand imbalances is first quantified by using unified margin and risk indices, then a cost-flexibility co-optimisation model is formulated to align local dispatch with system requirements. A distributed federated reinforcement learning (FRL) algorithm with doubly stochastic aggregation is developed for decentralised, privacy-preserving and communication-efficient training. Unlike centralised approaches, the proposed FRL algorithm enables distributed agents to collaboratively learn optimal scheduling strategies through local interactions and neighbour-based model updates, improving scalability, robustness and adaptability. The results of the case studies demonstrate rapid convergence, a significant improvement in peak-period flexibility insufficiency and reduced operational costs, thereby validating the effectiveness of our proposed approach in improving future grid flexibility and overall economic performance.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Climate-Driven Low-Carbon Dispatch Strategy for Photovoltaic-Storage-Charging Microgrids 气候驱动的光伏-储能-充电微电网低碳调度策略

IF 2.7

IET Smart Grid Pub Date : 2026-01-28 DOI: 10.1049/stg2.70058

Wanyue Xuan, Dejie Zhao, Rijia Ding

{"title":"Climate-Driven Low-Carbon Dispatch Strategy for Photovoltaic-Storage-Charging Microgrids","authors":"Wanyue Xuan, Dejie Zhao, Rijia Ding","doi":"10.1049/stg2.70058","DOIUrl":"https://doi.org/10.1049/stg2.70058","url":null,"abstract":"The operation of photovoltaic-storage-charging microgrids is increasingly challenged by the volatility of renewable resources and demand patterns driven by dynamic climate conditions. To address these challenges, this paper proposes a climate-driven low-carbon dispatch strategy for photovoltaic-storage-charging microgrids. First, to accurately capture system uncertainties associated with fine-scale atmospheric dynamics, a convolutional neural network–long short-term memory (CNN–LSTM) deep learning model is constructed based on a 15-min dispatch resolution. Simultaneously, a multifeature long short-term memory (LSTM) model, integrating temporal periodicity and historical dependencies, is developed to predict weather-sensitive electric vehicle charging loads. Second, to enhance system resilience against climate-induced power fluctuations, the operational constraints of the energy storage are modelled explicitly, incorporating a battery degradation cost model to quantify asset lifespan loss. Building on this, a dual-objective optimisation framework is formulated that internalises dynamic carbon trading costs into the economic dispatch. This model coordinates the power interaction among the photovoltaic system, energy storage and the main grid to maximise total operating revenue while minimising carbon footprints. Simulation results verify that the proposed strategy effectively balances economic efficiency and carbon reduction, achieving a system carbon emission reduction of 39.82%, demonstrating superior adaptability to climate-driven variations in renewable generation and load demand.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146199436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.7

IET Smart Grid Pub Date : 2026-01-21

引用次数: 0

A Frequency Response Modelling Method for the Wind Farm Considering Operational State Diversity Among Wind Turbine Generators 考虑风力发电机组运行状态多样性的风电场频率响应建模方法

IF 2.7

IET Smart Grid Pub Date : 2026-01-21 DOI: 10.1049/stg2.70052

Yuanting Hu, Pengquan Zeng, Jiapeng Cui, Pupu Chao, Junkun Hao, Zhi Song, Yonglin Jin

{"title":"A Frequency Response Modelling Method for the Wind Farm Considering Operational State Diversity Among Wind Turbine Generators","authors":"Yuanting Hu, Pengquan Zeng, Jiapeng Cui, Pupu Chao, Junkun Hao, Zhi Song, Yonglin Jin","doi":"10.1049/stg2.70052","DOIUrl":"10.1049/stg2.70052","url":null,"abstract":"The current system frequency response (SFR) model that incorporates the wind farm fails to fully account for the operational variations of wind turbine generators (WTGs) across varying wind speeds and different frequency regulation control modes, indicating potential for improvement. To address this issue, this paper first considers the virtual inertia, droop, overspeed de-loading and pitch angle de-loading control of the WTG to establish a frequency response model of the WTG. Second, based on the different operating states of WTGs, the equivalent frequency response model of the wind farm is aggregated through unit grouping, and an extended SFR model is constructed by further integrating it with the traditional SFR model. Then, a detailed simulation model of the wind farm is established on the DIgSILENT PowerFactory simulation platform to validate the proposed extended SFR model. The results show that the proposed model can accurately track the frequency response characteristics of the detailed model. Finally, using the proposed SFR model, an analysis is conducted on the impact of the wind farm's frequency regulation parameters and wind speed scenarios on system frequency stability.","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"9 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.70052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146083407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0