IET Smart Grid最新文献

{"title":"A new approach to manage the connection queue","authors":"Nicolas Ostler,&nbsp;Furong Li,&nbsp;Lewis Dale","doi":"10.1049/stg2.12200","DOIUrl":"https://doi.org/10.1049/stg2.12200","url":null,"abstract":"<p>The connection queue has seen unparalleled growth over the last 24 months. With the record number of connection agreement applications representing a pivotal time for system development as we drive investment that will enable us to transition into an electrified future. The authors look to address challenges posed to the connection queue through congestion management-based techniques. Conducting a top down approach, the authors first visualise the state of the queue. Observing highest growth in pure storage based applications distributed close to traditional load centres, followed by wind projects along the East Coast and Northern Scotland. Supporting close analysis is performed on the representative B6 boundary. The authors compare methodologies, validate a process for the attribution of congestion cost and quantify the value of investment given by unit power changes. Finding that most significant value of investment in storage lies in the Southeast of England and the North of Scotland. This reflects the identified current state of constraint and most efficient current utilisation of available capacity. These approaches have been aligned with current system thinking and progress towards a new industry data sharing standard, forming strategy by which we look to transition the energy system and country into a decarbonised future.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"1064-1073"},"PeriodicalIF":2.4,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12200","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252489","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}

{"title":"Image processing-based noise-resilient insulator defect detection using YOLOv8x","authors":"Shagor Hasan,&nbsp;Md. Abdur Rahman,&nbsp;Md. Rashidul Islam,&nbsp;Animesh Sarkar Tusher","doi":"10.1049/stg2.12199","DOIUrl":"https://doi.org/10.1049/stg2.12199","url":null,"abstract":"<p>Accurate and efficient insulator defect detection is critical for power grid reliability, but it can be affected by the presence of noises in captured images and can be difficult to employ for real-time operation due to the slow processing of the detection scheme. This paper proposes a novel framework based on the YOLOv8x object detection scheme, addressing the challenge of detecting small defects in complex aerial images and providing a noise mitigation scheme. A Gaussian blur and Laplacian sharpening-based hybrid scheme is proposed to mitigate the impacts of noises in insulator images. Experimental results indicate that the proposed framework can achieve a mean average precision (mAP) of 98.4% on noise-free images, surpassing benchmark models, such as YOLOv5x and YOLOv7 by 2.1% and 3.9%, respectively. Also, while the performance of a conventional system can decrease to a mAP of 93.3% in the worst case, the implementation of the proposed mitigation scheme ensures a mAP of 96.7% for that case. With an inference speed of 56.9 ms per image, this approach offers a promising solution for real-time power line inspection, contributing to enhanced power grid maintenance and safety.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"1036-1053"},"PeriodicalIF":2.4,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248956","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}

{"title":"Intelligent islanding detection in smart microgrids using variance autocorrelation function-based modal current envelope","authors":"Shanzah Naseem,&nbsp;Sadiq Ahmad,&nbsp;Saddam Aziz,&nbsp;Muhammad Ali,&nbsp;Kazi N. Hasan,&nbsp;Ayaz Ahmad,&nbsp;Abdullah Shoukat","doi":"10.1049/stg2.12197","DOIUrl":"https://doi.org/10.1049/stg2.12197","url":null,"abstract":"<p>Islanding detection is a critical issue in grid-connected distributed microgrid systems. Distributed generation in the current power system has caused many challenges. Consequently, detecting quick and effective islanding is the most critical issue to minimise equipment failure, avoid danger, and maintain grid safety. There are various techniques for islanding identification in microgrids. Three classifications have been applied to categorise these strategies, which are: active, passive, and hybrid. This paper proposes and demonstrates an efficient and accurate approach to islanding detection based on the Variance Autocorrelation Function of a Modal Current Envelope (VAMCE) technique. Demodulation techniques including synchronous real demodulation, square law demodulation, asynchronous complex square law demodulation, and the quadrature demodulation technique are employed to detect the envelope of the 3-phase current signal. The VAMCE methodology is better suited for islanding detection because of its response to current sensitivity under islanding scenarios but not under normal conditions. Several simulations under various settings, including normal and islanded scenarios are used to analyse this method. These simulations have demonstrated different situations, such as when the system works normally and when it does not. The VAMCE along with the quadrature demodulation technique outperforms the others. The proposed solution is not only more accurate but also much faster compared to other methods. The proposed approach can identify normal and islanded situations in just 0.4 s.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"1019-1035"},"PeriodicalIF":2.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12197","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248619","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}

{"title":"Using assurance frameworks to manage the risks and uncertainties of an energy sector digital spine","authors":"Henry James Thraves,&nbsp;Anna Theoharis,&nbsp;Wai Yan Sonia Pang,&nbsp;Graham Faiz,&nbsp;Matthew Celnik","doi":"10.1049/stg2.12195","DOIUrl":"https://doi.org/10.1049/stg2.12195","url":null,"abstract":"<p>The energy transition requires a profound transformation of the entire energy system. The adoption of diverse, distributed renewable energy sources into the energy mix requires many assets, actions, stakeholders, and decisions to communicate with each other. The digital spine can serve as the energy system's connective tissue, enabling secure data sharing and enhancing visibility across all energy stakeholders. This will promote collaboration, innovation, and informed decision-making within the UK's energy sector. However, significant risks accompany this shift, including data quality and security, organisational readiness, and the complexity and scalability of the digital infrastructure. This report will discuss these risks and suggest mitigation measures to promote trust in the digital spine. Only by achieving stakeholder buy-in through trust of the digital spine will this digital technology achieve widespread acceptance. Digital assurance helps to generate an ecosystem of trust built on transparent arguments about consequences and uncertainty for digital technologies, such as the digital spine. DNV believes that their suite of recommend practises can help to mitigate risks relating to the digital spine. The report concludes by outlining the next steps towards realising a digital spine, emphasising the role of independent assurance frameworks in achieving this goal.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"1054-1063"},"PeriodicalIF":2.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12195","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248620","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}

{"title":"Open data for modelling the impacts of electric vehicles on UK distribution networks: Opportunities for a digital spine","authors":"Isaac Flower,&nbsp;Furong Li,&nbsp;Julian Padget","doi":"10.1049/stg2.12193","DOIUrl":"https://doi.org/10.1049/stg2.12193","url":null,"abstract":"<p>This paper provides a detailed overview of the current snapshot of available open data for modelling the impacts of electric vehicles (EVs) on the UK distribution network, highlighting opportunities for a digital spine. We are the first to review open data available for UK distribution networks, focusing on spatial data. We also explore data for census small geographies, vehicle ownership, EV charger locations and data on their usage. Several issues are identified, including inconsistencies in dataset availability, file naming conventions, feature definitions and geographic discrepancies. We specifically analyse EV charger connection data for secondary distribution substations from two UK Distribution Network Operators (DNOs). The validity of the data is assessed by comparing it to known public charger locations from OpenChargeMap. While one DNO provides data coverage for &gt;95% of its substations, it is valid for only 24.1% of substations with at least one public charger. Conversely, the other DNO provides data coverage for 1% of its substations due to privacy-related obfuscation, with data valid for 98.3% of substations with at least one public charger. Addressing these challenges through standardised data-sharing practices and implementing a digital spine could enhance the accuracy and reliability of EV-grid integration models. These improvements are essential for facilitating the seamless integration of EVs into the grid and supporting the transition to a sustainable energy system.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"983-999"},"PeriodicalIF":2.4,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12193","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253576","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}

{"title":"Modelling and management of flexible residential building components using system based heuristic approaches","authors":"Srinivas Yelisetti,&nbsp;Vikash Kumar Saini,&nbsp;Rajesh Kumar,&nbsp;Ehsan Heydarian-Forushani,&nbsp;Ameena S. Al Sumaiti","doi":"10.1049/stg2.12194","DOIUrl":"https://doi.org/10.1049/stg2.12194","url":null,"abstract":"<p>The building energy management system (BEMS) components, that is, the heating, ventilation, and air conditioning (HVAC) systems, refrigerators, and lighting significantly impact energy consumption. This paper presents the modelling, including HVAC and refrigerator with interior heat and external illuminus of lighting for residential buildings. The energy consumption of these components has been examined using eight meta-heuristic algorithms with weather conditions of five cities in India. The statistical and box-plot analysis results recommended the original artificial ecosystem algorithm compared to others for energy management. The results of the proposed smart residential building have been compared with the published model results of a residential building with and without BEMS and an economic analysis has also been carried out. The simulation results show that the maximum load has been shifted to off-peak durations. The energy savings in the proposed BEMS compared to existing BEMS and without BEMS are 34% and 57%, respectively.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"967-982"},"PeriodicalIF":2.4,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253135","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}

{"title":"An efficient hybrid algorithm based on particle swarm optimisation and teaching-learning-based optimisation for parameter estimation of photovoltaic models","authors":"Dianlang Wang,&nbsp;Zhongrui Qiu,&nbsp;Qi Yin,&nbsp;Haifeng Wang,&nbsp;Jing Chen,&nbsp;Chengbi Zeng","doi":"10.1049/stg2.12198","DOIUrl":"https://doi.org/10.1049/stg2.12198","url":null,"abstract":"<p>In recent years, many meta-heuristic algorithms have been investigated to estimate the parameters of photovoltaic (PV) models. However, the accuracy of the estimated parameters still needs to be concerned, especially for some complex PV models with many unknown parameters. In order to estimate the unknown parameters of the PV models more precisely and reliably, an efficient hybrid algorithm based on particle swarm optimisation and teaching-learning-based optimisation (PSOTLBO) is proposed in this paper. In PSOTLBO, inspired by the learner phase of teaching-learning-based optimisation (TLBO), an improved learner phase is designed and introduced into the basic PSO to enhance the global search ability and the ability to get rid of local optimum. The improved learner phase divides the population into four groups according to three values, which are the average fitness values of the overall population, the population in the first half of the fitness ranking and the population in the second half of the fitness ranking. Typically, each group has its particular movement pattern concentrating on exploration or exploitation respectively to improve the search efficiency of the algorithm. Furthermore, to deal with individuals beyond the boundary, a new designed probabilistic rebound strategy is introduced, which increases the diversity of population and avoids population aggregation at the search boundary. Then, the proposed PSOTLBO is applied to estimate the parameters of the single diode model, double diode model and PV module model. The comparative results between PSOTLBO and other 14 advanced algorithms show that the average root mean square error values of different PV models obtained by PSOTLBO are 9.86021878E−04, 9.82630511E−04, 2.42507487E−03, 1.72981371E−03, and 1.66006031E−02, respectively, which indicate that PSOTLBO can provide more accurate and stable parameter estimation results than other compared algorithms. Furthermore, the convergence experimental results demonstrate that PSOTLBO has outstanding performance in convergence speed and stability.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"1000-1018"},"PeriodicalIF":2.4,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253134","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}

{"title":"Review of the opportunities and challenges to accelerate mass-scale application of smart grids with large-language models","authors":"Heng Shi,&nbsp;Lurui Fang,&nbsp;Xiaoyang Chen,&nbsp;Chenghong Gu,&nbsp;Kang Ma,&nbsp;Xinsong Zhang,&nbsp;Zhong Zhang,&nbsp;Juping Gu,&nbsp;Eng Gee Lim","doi":"10.1049/stg2.12191","DOIUrl":"https://doi.org/10.1049/stg2.12191","url":null,"abstract":"<p>Smart grids represent a paradigm shift in the electricity industry, moving from traditional one-way systems to more dynamic, interconnected networks. These grids are characterised by their intelligent automation, robust structure, and enhanced interaction with customers, backed by comprehensive monitoring and data analytics. The key of this transformation is the integration of data-driven methods into smart grids. Compared to previous big data solutions, large language models (LLMs), with their advanced generalisation abilities and multi-modal competencies, are crucial in effectively managing and integrating diverse data sources. They address challenges such as data inconsistency, inadequate quality, and heterogeneity, thereby enhancing the operational efficiency and reliability of smart grids. Furthermore, at the system level, LLMs improve human–system interactions, making smart grids more user-friendly and intuitive. Last but not the least, the structure of LLMs performs inherent advantages in bolstering system security and privacy, alongside in resolving issues related to system compatibility and integration. The paper reviews the data-empowered smart grids and for the first time finds and proposes opportunities and future directions for adopting LLMs to accelerate the mass-scale application of Smart Grids.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"737-759"},"PeriodicalIF":2.4,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12191","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248707","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}

{"title":"Sustainable hybrid renewable energy management system for a community in island: A model approach utilising Hybrid Optimization of Multiple Energy Resources optimization and priority setting-based Supervisory Control and Data Acquisition operation","authors":"Iftekhar Ahmed,&nbsp;Md. Abdur Razzak,&nbsp;Feroz Ahmed","doi":"10.1049/stg2.12192","DOIUrl":"https://doi.org/10.1049/stg2.12192","url":null,"abstract":"<p>This paper explores sustainable energy management strategies for a remote community on the Island of Bhashanchar in the Bay of Bengal, designated by the Government of Bangladesh to host Rohingya refugee camps. The island lacks utility-scale power infrastructure, relying primarily on rooftop solar systems. Addressing the challenge of efficient energy utilization, the study analyses the Bhashanchar Community System's energy dynamics, load demand, and renewable energy integration feasibility. The primary objective is to design an optimised hybrid microgrid system to balance energy supply and demand, reducing blackout risks. A Supervisory Control and Data Acquisition based load management system is introduced for real-time energy distribution, enhancing reliability. The proposed off-grid hybrid microgrid system includes solar PV, wind, diesel, biomass, wind turbine, tidal turbine, and battery storage. It incorporates priority setting mechanisms to categorise energy sources by reliability, availability, and environmental impact, ensuring consistent, reliable, and sustainable energy supply. The study demonstrates that the proposed system can achieve significant energy savings, around 23%, compared to traditional models, showcasing the effectiveness of the hybrid microgrid approach in powering remote communities with limited conventional energy access.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"940-966"},"PeriodicalIF":2.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12192","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253857","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}

{"title":"Fault location method for new distribution networks based on waveform matching of time–frequency travelling waves","authors":"Zhongqiang Zhou,&nbsp;Yuan Wen,&nbsp;Moujun Deng,&nbsp;Jianwei Ma,&nbsp;Jupeng Zeng,&nbsp;Xiaolong She","doi":"10.1049/stg2.12190","DOIUrl":"https://doi.org/10.1049/stg2.12190","url":null,"abstract":"<p>Some existing fault location methods for distribution networks rely too much on the local wave head information of the time or frequency domain signals, making it difficult to adapt to the increasingly complex structure and operating conditions of the distribution network after the new energy access. For improvement, the travelling wave (TW) time and frequency ranges that can effectively avoid waveform distortion caused by new energy access are analysed. The one-to-one matching relationship between the TW waveforms in these ranges and the fault positions is revealed. A fault TW time–frequency matrix with specific time and frequency windows is constructed, and a new distribution network fault location method is proposed based on the matching technique of waveform features, which realises the accurate fault location by exploring the proportionality between the cumulative trend of the matrix energy amplitude deviation and the fault point position. Simulation test results show that the proposed method is not affected by the complex structure of distribution networks such as new energy access and overhead-cable line mixing on fault location and flexibly transforms the fault location problem into a time–frequency TW waveform matching problem, which improves the accuracy and robustness of the fault location for new distribution networks to a degree.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 6","pages":"929-939"},"PeriodicalIF":2.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12190","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248081","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}