IET Energy Systems Integration最新文献

{"title":"Changes in performance and thermal stability of Ni0.8Co0.1Al0.1/graphite batteries with excessive water","authors":"Xi Liu, Jingbo Mao, Hongtao Yan, Chunjing Lin, Chuang Qi, Tao Yan, Li Lao, Yazhou Sun","doi":"10.1049/esi2.12148","DOIUrl":"https://doi.org/10.1049/esi2.12148","url":null,"abstract":"During the production process of lithium‐ion batteries, there exists a scenario of excessive water inside the battery due to poor water control in the factory environment. In addition, the battery housing may be damaged by corrosion, external vibration etc., which would cause water to enter the battery. To the best of the authors’ knowledge, there is little literature to reveal the influencing mechanism related to the above issue. The effects of excessive water on battery performance and safety were discussed. The results show that when the battery absorbs excessive water, the capacity decreases and the self‐discharging rate increases rapidly. The self‐heating temperature of the battery shows an increasing trend. The thermal runaway temperature decreases significantly with the time from self‐heating to thermal runaway dramatically shortened. The thermal stability of the battery deteriorates throughout the reaction process. This is mainly due to the mechanisms by which the water absorbed in the battery reacts with the electrolyte and the electrode material, resulting in the decrease of the electrolyte conductivity and the corrosion of the electrode material, as well as the thickening of the Solid Electrolyte Interface film and the accumulation of impurities. The findings are of positive significance in demonstrating the quantitative relationship between excessive water and the performance and safety of batteries. Also, it can add to the understanding of the complex scenarios of battery spontaneous failure, which is vital for solving battery self‐thermal runaways.","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140745503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simplified control parameter optimisation method of the hybrid modular multilevel converter in the medium‐voltage DC distribution network for improved stability under a weak AC system","authors":"Jin Xu, Qian Xiao, Hongjie Jia, Yunfei Mu, Yu Jin, Wenbiao Lu, Shiqian Ma","doi":"10.1049/esi2.12147","DOIUrl":"https://doi.org/10.1049/esi2.12147","url":null,"abstract":"To improve the stability of the hybrid modular multilevel converter (MMC), a simplified dominant mode‐based control parameter optimisation method of the hybrid MMC system is proposed. Firstly, in the medium‐voltage DC distribution network, the small‐signal model of the hybrid MMC is established. Secondly, the influence of a weak AC system on stability is analysed through eigenvalue analysis. Finally, a simplified objective function is designed for eigenvalues of the dominant mode by considering only real parts, and improved small‐signal stability can be achieved by control parameters optimisation. The proposed method optimises all control parameters at the same time, which further reduces the number of algorithm iterations. Simulation results show that by the proposed control parameter optimisation method, the hybrid MMC has better transient performance and reduced disturbance under SCR variation, indicating a significantly improved system stability, and the dynamic response time can be reduced.","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140758664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guest Editorial: Dynamic analysis, control, and situation awareness of power systems with high penetrations of power electronic converters","authors":"Jiebei Zhu,&nbsp;Huadong Sun,&nbsp;Yongning Chi,&nbsp;Xiaorong Xie,&nbsp;Jiabing Hu,&nbsp;Haoran Zhao,&nbsp;Siqi Bu,&nbsp;Yan Xu,&nbsp;Fei Teng,&nbsp;Qiteng Hong,&nbsp;Leijiao Ge","doi":"10.1049/esi2.12146","DOIUrl":"https://doi.org/10.1049/esi2.12146","url":null,"abstract":"<p>In recent decades, global power grids have evolved with a rapid and extensive development of power electronic converters (PEC), including renewable energy systems (RES), high-voltage DC (HVDC) transmission, flexible AC transmission system (FACTS), energy storages, and microgrids. <span>The distinct characteristics of power electronic devices</span> <span>traditional synchronous generators, especially their rapid control speed, wide-band performance and lack of inertia response and spinning reserve, are altering grid dynamics, and inducing new stability challenges</span>. Continuation of such trends could further exacerbate the risk to the stability of power grids because of factors such as low inertias, lack of spinning reserve to quickly nullify active power mismatch between demand and supply.</p><p>Therefore, scientific investigations on novel dynamic modelling and stability analysis methods, data-driven monitoring and situation awareness on grid inertia-power-frequency evolution, grid dynamic frequency forecast methodologies in consideration of novel PEC control schemes, and advanced PEC grid integration control schemes to minimise frequency management risks become increasingly crucial for the secured operations of power systems with high PEC penetrations. In this Special Issue, namely ‘Dynamic Analysis, Control, and Situation Awareness of Power Systems with High Penetrations of Power Electronic Converters’, we have presented eight original papers of sufficient quality and innovation. The 10 eventually accepted papers can be clustered into three two categories, namely novel control design, stability and fault analysis.</p><p>Zhu et al. present a supercapacitor-based coordinated synthetic inertia (SCSI) scheme for a voltage source converter-based HVDC (VSC-HVDC) integrated offshore wind farm (OWF). The proposed SCSI allows the OWF to provide a designated inertial response to an onshore grid. The results show that the proposed SCSI scheme can provide required inertial support from WTG-installed supercapacitors to the onshore grid through the VSC-HVDC link, significantly improving the onshore frequency stability (https://doi.org/10.1049/esi2.12137).</p><p>Ghamari et al. design a Lyapunov-based adaptive backstepping control approach for a power Buck converter, as an advanced version of the Backstepping method utilising Lyapunov stability function to reach a higher stability and a better disturbance rejection behaviour in the practical applications. In addition, to compensate for disturbances with wider ranges such as supply voltage variation, parametric variation and noise, this paper applies a metaheuristic algorithm in the control scheme called grey wolf optimisation algorithm of a nature-inspired algorithm with faster decision-making dynamics along with more accuracy over different optimisation algorithms (https://doi.org/10.1049/esi2.12098).</p><p>Arunagiri et al. present a new technique based on active damped dual loop <i>αβ</i>-frame curr","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140331161","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":"Joint contribution of RTEM and AGC system for frequency stabilisation in renewable energy integrated power system","authors":"Liza Debbarma, S. Debbarma, K. Roy, S. Roy, P. Singh","doi":"10.1049/esi2.12145","DOIUrl":"https://doi.org/10.1049/esi2.12145","url":null,"abstract":"Increasing penetration of variable renewable generations will diminish system inertia thereby degrading the conventional frequency regulation capability. As a result, maintaining frequency stability will be more and more challenging with traditional approaches. Even though renewable sources integration would jeopardise the grid stability, it also presents several opportunities as well. For example, converter‐interfaced generators can bid in real‐time electricity markets (RTEM) and provide short‐time dispatch to minimise load‐generation mismatch. In this paper, an integrated approach that accommodates discrete automatic generation control (AGC) system with a regulation mileage framework and RTEM model to balance generation and consumption is proposed. The RTEM model is assumed to have a five‐minute dispatch trading interval which is to some extent comparable to the discrete AGC system. Furthermore, a fractional order PID (FOPID) controller is equipped in the AGC system whose parameters are tuned using a novel metaheuristic‐based optimisation called Lichtenberg Algorithm (LA). The proposed framework is tested in a three‐area system under several operating conditions to reveal the improvement in the dynamic performance of the system. The objective function is also incorporated with mileage payment that allows a fair compensation rule for all the units.","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140216088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigation of limitation imposed on hosting capacity in low voltage networks by their distribution transformer loading and degradation considerations","authors":"Agaba Ame‐Oko, Olga Lavrova","doi":"10.1049/esi2.12143","DOIUrl":"https://doi.org/10.1049/esi2.12143","url":null,"abstract":"A distribution transformer's thermal operating conditions can impose a limitation on the Hosting Capacity (HC) of an electrical distribution feeder for PV interconnections in the feeder's low‐voltage network. This is undesirable as it curtails PV interconnection of both residential and commercial customers in the secondary networks at a time when there are record numbers of interconnection requests by utilities' customers. The authors analyse the limitations on HC due to transformer loading and degradation considerations. Then, the paper proposes a battery energy storage system (BESS) dispatch strategy that will mitigate the limitation on distribution feeder HC by distribution transformers. Three scenarios of HC were simulated for a test network—HC evaluation without restrictions by the distribution transformer (scenario 1), HC evaluation with restrictions by the distribution transformer (scenario 2), and HC evaluation without restriction by the distribution transformer, and with the implementation of the proposed BESS mitigation strategy (scenario 3). Simulation results show that transformer lifetime is depleted to about 6% of expected lifetime for unrestricted HC in scenario 1. Curtailing the HC by 32% in scenario 2 improves the lifetime to 149% of expected lifetime. Implementing the proposed BESS in scenario 3 improves the transformer lifetime to 127% and increases the HC by 62% above the curtailed value in scenario 2, and by 10% above the original HC in scenario 1. The BESS strategy implementation produced cost savings of 49% and 27% of the transformer cost in scenarios 2 and 3, respectively, due to deferred transformer replacement. Conversely, there is a 1600% replacement cost incurred in scenario 1, which underscores the need for a mitigation strategy. The proposed BESS strategy does not only improve the HC of a distribution feeder but also increases a distribution transformer's lifetime leading to replacement cost savings.","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140233588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved topology identification for distribution network with relatively balanced power supplies","authors":"Wenpeng Luan,&nbsp;Da Xu,&nbsp;Bo Liu,&nbsp;Wenqian Jiang,&nbsp;Li Feng,&nbsp;Wenbin Liu","doi":"10.1049/esi2.12142","DOIUrl":"10.1049/esi2.12142","url":null,"abstract":"<p>Having correct distribution network topology information is essential for system state estimation, line loss analysis, electricity theft detection and fault location. At present, with continuous deployment of smart sensors, a large amount of monitoring data is collected, which enables refined management for distribution network. A data-driven low voltage (LV) distribution network topology identification method is proposed, which realises transformer-customer pairing and customer phase identification for distribution network with relatively balanced power supplies. Firstly, an integrated similarity coefficient of voltage curve is proposed, which can reflect the neighbourhood relationship within stations while increase the distinction between stations; the K-Nearest Neighbour (KNN) algorithm is used to propagate the service transformer labels to complete transformer-customer association. Then, the influence of power fluctuation on voltage curve is analysed and a dynamic sliding window model is adopted to search for voltage segments with significantly difference among three phase feeders to formulate a voltage time series to identify customer phase. Finally, the results are corrected and verified based on the principle of network power balance. The proposed algorithm is tested in two different real substations in China and Europe and shows high accuracy and robustness especially in distribution network with relatively balanced power supplies.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12142","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140237557","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":"Wind energy system fault classification and detection using deep convolutional neural network and particle swarm optimization‐extreme gradient boosting","authors":"Chun‐Yao Lee, Edu Daryl C. Maceren","doi":"10.1049/esi2.12144","DOIUrl":"https://doi.org/10.1049/esi2.12144","url":null,"abstract":"Wind energy is crucial in the global shift towards a sustainable energy system. Thus, this research innovatively addresses the challenges in wind energy system fault classification and detection, emphasising the integration of robust machine learning methodologies. Our study focuses on enhancing fault management through supervisory control and data acquisition (SCADA) systems, addressing imbalanced data representation issues and error vulnerabilities. A key innovation lies in applying particle swarm optimisation‐tuned extreme gradient boosting (XGBoost) on imbalanced SCADA datasets, combining resampled SCADA data with deep learning features produced by deep convolutional neural networks. The novel use of PSO‐XGBoost showcases effectiveness in optimising parameters and ensuring model robustness. Furthermore, our research contributes to supervised and unsupervised anomaly detection models using Seasonal‐Trend decomposition using locally estimated scatterplot smoothing and PSO‐XGBoost, presenting substantial advancements in fault classification and prediction metrics. Overall, the study offers a unique, integrated framework for fault management, demonstrating improved reliability in predictive maintenance architectures. Lastly, it highlights the transformative potential of advanced machine learning in enhancing sustainability within efficient and clean energy production.","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140250745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interval analysis of the small-signal stability of grid-connected voltage-source converter system considering multiparameter uncertainty","authors":"Fuxin Ouyang,&nbsp;Zhenguo Shao,&nbsp;Changxu Jiang,&nbsp;Yan Zhang,&nbsp;Feixiong Chen","doi":"10.1049/esi2.12141","DOIUrl":"https://doi.org/10.1049/esi2.12141","url":null,"abstract":"<p>Grid-connected voltage source converters (VSCs) have been broadly applied in modern power system. However, instability issues may be triggered by the integration of grid-connected VSCs, jeopardising the operation of the power grid. Conventional stability analysis methods can be utilised to derive system stability margins under nominal conditions. Whereas grid-connected VSCs inevitably operate under multiparameter uncertainty, which may result in overly optimistic or even incorrect estimations of stability margins, thereby posing potential risks to system operation. To address this issue, an interval small-signal stability analysis approach is proposed to investigate the system stability under multiparameter uncertainty. First, the interval state-space model of the grid-connected VSC system is constructed based on interval symbolic linearisation. Furthermore, the interval eigenvalue decomposition is introduced to calculate the interval eigenvalue distribution of the interval state-space model. Eventually, the upper bounds of the real part of the dominant interval eigenvalues are utilised for deriving interval stable parameter regions. Results of Monte Carlo analysis and time-domain simulations of the grid-connected VSC system are utilised to verify the effectiveness of the proposed interval stability analysis method.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12141","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424867","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":"Recovery strategy of distribution network based on dynamic island rescue under extreme weather","authors":"Xinrui Liu, Qingkun Meng, Rui Wang, Chaoyu Dong, Qiuye Sun","doi":"10.1049/esi2.12140","DOIUrl":"https://doi.org/10.1049/esi2.12140","url":null,"abstract":"The frequent occurrence of various extreme weather has a great influence on the normal and stable operation of the distribution network. In order to minimise the large‐scale power loss of the distribution network caused by extreme weather, considering that most of the practical disasters are concurrent with various weather types, and each disaster is independent of each other. A unified failure rate calculation model is proposed, which includes line break, short circuit, tower fall, insulator flashover etc., to realise disaster scenario prediction. Secondly, a resilience evaluation index of island rescue based on mobile energy storage system (IR‐MESS) is proposed. Thirdly, considering the flexibility of MESS, the pre‐disaster scheduling of MESS is carried out according to the predicted disaster scenario. After the disaster occurs, a spatio‐temporal optimisation scheduling model based on the rescue state and charge state of MESS is proposed, and a dynamic IR‐MESS is formed to provide power supply for important loads in out‐of‐load areas of the distribution network. Finally, taking the actual ice disaster in northeast China as an example, the results show that the rescue strategy based on IR‐MESS proposed in this paper can effectively elevate the resilience of the distribution network.","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140081912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive survey of low-carbon planning and operation of electricity, hydrogen fuel, and transportation networks","authors":"Yeao Zhou,&nbsp;Sheng Chen,&nbsp;Jiayu Chen","doi":"10.1049/esi2.12139","DOIUrl":"10.1049/esi2.12139","url":null,"abstract":"<p>The trend of global energy systems towards carbon neutrality has led to an escalating interdependency between electricity, hydrogen fuel, and transportation networks. However, the means of surmounting the many challenges confronting the optimal coupling and coordination of electric power, hydrogen fuel, and transportation systems are not sufficiently understood to guide modern infrastructure planning operations. The present work addresses this issue by surveying the extant literature, relevant government policies, and future development trends to evaluate the present state of technology available for coordinating these systems and then determine the most pressing issues that remain to be addressed to facilitate future trends. On the one hand, the users of transportation networks represent flexible consumers of electric power and hydrogen fuel for those connected via devices such as electric vehicles and hydrogen fuel cell vehicles through charging stations and hydrogen refuelling stations. On the other hand, power grids can mitigate the negative effect of random charging behaviours on grid security through time-of-use electricity pricing, while excess renewable energy outputs can be applied to generate hydrogen fuel. The findings of this overview offer support for infrastructure planning and operations. Finally, the most urgent issues requiring further research are summarised.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140428193","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}