IET Energy Systems Integration最新文献

{"title":"Revisiting the role of thermal energy storage in low-temperature electrified district heating systems","authors":"Hai Lu,&nbsp;Hao Zhang,&nbsp;Shuai Lu","doi":"10.1049/esi2.12174","DOIUrl":"https://doi.org/10.1049/esi2.12174","url":null,"abstract":"<p>Decarbonising the energy supply system is crucial to mitigate climate challenges. An emerging type of the multi-energy system, that is, the low-temperature electrified district heating system is gaining increasing popularity as a potential solution for future low-carbon heat supply. This paper investigated its operational optimisation with thermal energy storage (TES) installed at building sides. The optimisation model was to obtain the minimum operation costs of all heat pumps in this system. The TES was meant to achieve energy arbitrage through load shift, but it was observed from the optimised results that the TES did not play an active role in the optimisation. Five possible causes were identified and further investigated to reveal their impacts on the optimisation process. Results showed that the thermal capacitance, thermal resistance, and indoor temperature range of the building were major influencing factors, while the electricity price tariff and heat loss parameters of TES were minor ones. The results indicate that there is no need to equip the TES for operational optimisation purposes when the building thermal capacitance is larger than a threshold value, the thermal resistance is smaller than a threshold value, or the indoor temperature range is broader than a threshold value. These threshold values are case-specific and can be determined with the simulation model and method developed in this paper.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"845-861"},"PeriodicalIF":1.6,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253349","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":"Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics","authors":"Zeming Chen,&nbsp;Zhigang Li,&nbsp;Huajian Li,&nbsp;Jiahui Zhang,&nbsp;Yixuan Li,&nbsp;Jiehui Zheng","doi":"10.1049/esi2.12176","DOIUrl":"https://doi.org/10.1049/esi2.12176","url":null,"abstract":"<p>State estimation plays an important role in the monitoring and control of integrated electric–gas systems (IEGSs), but it faces limitations due to insufficient measurement configurations and low data redundancy in these systems; additional measurement configurations are needed to increase the overall system observability. Owing to the lack of suitable observability analysis methods, optimal measurement configurations for IEGSs remain underexplored. This paper presents an IEGS observability analysis method that incorporates gas flow dynamics via the Lie derivative. This method incorporates the complex topological structure of the gas network and the dynamic process of gas flow into the IEGS observability analysis. Furthermore, the measurement configuration problem for IEGSs considering gas flow dynamics is formulated as a rank-constrained optimization problem. To handle the rank constraints effectively, an iterative cutting method is developed with convergence guarantees. Finally, the efficacy and practicality of the proposed methods are validated through case studies of varying scales. The proposed optimal measurement configuration model reduces measurement configuration costs while maintaining system observability.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"891-902"},"PeriodicalIF":1.6,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12176","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253064","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":"Studies on effective solar photovoltaic integration in distribution network with a blend of Monte Carlo simulation and artificial hummingbird algorithm","authors":"Ibrahim Cagri Barutcu,&nbsp;Gulshan Sharma,&nbsp;Emre Çelik,&nbsp;Pitshou N. Bokoro","doi":"10.1049/esi2.12175","DOIUrl":"https://doi.org/10.1049/esi2.12175","url":null,"abstract":"<p>In this paper, the two level stochastic optimisation approach has been suggested. In the lower level, the probability distribution functions (pdfs) for bus voltages and branch currents have been determined using the Monte Carlo simulation (MCS) to be employed in chance-constrained probabilistic optimisation by taking into account solar radiation and power consumption uncertainties in the distribution networks (DNs). In the upper level, artificial hummingbird algorithm (AHA) handles the expected power loss minimisation subjected to chance constraints, which are related to bus voltages and branch currents, by optimising photovoltaic (PV) system capacities. This research examines the effect of uncertainties in PV system performing under diverse solar radiation and varying PV penetration level scenarios on expected power losses with stochastic DN limits. The stochastic optimisation approach has been compared with the deterministic method for observing the efficiency with optimal power usage. This research improves the knowledge base for optimal PV installation in DN by combining AHA with MCS and emphasising chance-constrained methods. To indicate the efficacy of proposed strategy, the optimisation outcomes are tested utilising MCS under various uncertainty circumstances and DN parameters are assessed in terms of probabilities of exceeding limitations. The results are compared with the application of firefly algorithm (FA) using stochastic assessment and simulations. The simulation results show that the AHA technique outperforms the FA method in terms of effectively minimising power losses with less simulation time.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"862-890"},"PeriodicalIF":1.6,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248747","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":"Robust network topology for unbalanced active distribution networks with uncertain injections","authors":"Sanat Kumar Paul,&nbsp;Abheejeet Mohapatra,&nbsp;Dulal Chandra Das","doi":"10.1049/esi2.12172","DOIUrl":"https://doi.org/10.1049/esi2.12172","url":null,"abstract":"<p>This research paper introduces a comprehensive formulation for robust dynamic network reconfiguration (NR) of unbalanced active electric distribution networks (DNs). Network reconfiguration is a potent strategy to minimise active power loss in DN as it involves altering network topology through sectionalising (normally closed) and tie-line switches (normally open). However, NR is usually a mixed integer NP-hard non-linear optimisation problem due to the discrete nature of the switches. Hence, including variable injection uncertainties (from generation or load) for an unbalanced active DN with all its attributes further poses a significant challenge in solving NR. The proposed formulation addresses these challenges in a robust optimisation (RO) framework to get a robust topology and power and voltage set points for dispatchable Distributed Generators (DGs). Also, Chance-Constrained robust formulations are proposed to regulate the conservatism of RO. Numerical analyses demonstrate the impact of conservative robust NR on DG set points compared to the non-robust NR method. Tests on a modified unbalanced IEEE 34-bus system and comparison with previous formulations verify the efficacy of the proposed approach, showcasing its effectiveness.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"828-844"},"PeriodicalIF":1.6,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253463","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":"Feature selection and data-driven model for predicting the remaining useful life of lithium-ion batteries","authors":"Yuhao Zhang,&nbsp;Yunfei Han,&nbsp;Tao Cai,&nbsp;Jia Xie,&nbsp;Shijie Cheng","doi":"10.1049/esi2.12171","DOIUrl":"https://doi.org/10.1049/esi2.12171","url":null,"abstract":"<p>To ensure long and reliable operation of lithium-ion battery storage workstations, accurate, fast, and stable lifetime prediction is crucial. However, due to the complex and interrelated ageing mechanisms of Li-ion batteries, using physical model-based methods for accurate description is challenging. Therefore, building data-driven models based on direct measurement data (voltage, current, capacity, etc.) during battery operation may be a more effective approach. This paper employs a time series analysis of discharge capacity/voltage curves to perform feature predication. The goal is to predict the state of health using a short-term model and the remaining useful life of batteries using a long-term iterative model. The validity of this method is verified using the open-source MIT battery dataset. Comparisons with models reported in the literature demonstrate that this method is generalisable and ensures accuracy across a wider range of predictions.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"776-788"},"PeriodicalIF":1.6,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253149","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":"A Bi-level stacked LSTM-DNN-based decoder network for AGC dispatch under regulation market framework in presence of VPP and EV aggregators","authors":"Kingshuk Roy,&nbsp;Sanjoy Debbarma,&nbsp;Siddhartha Deb Roy,&nbsp;Liza Debbarma","doi":"10.1049/esi2.12169","DOIUrl":"https://doi.org/10.1049/esi2.12169","url":null,"abstract":"<p>The consideration of mileage settlement in the frequency regulation market has encouraged fast-acting units, such as converter-interfaced generators (CIG) and electric vehicle stations, to actively participate in load-generation balancing through automatic generation control (AGC). Conventional frequency regulation faces challenges in coping with the growing variability of CIGs and also lacks effective incentives for rapid-responding units. In this context, a bi-level AGC dispatch approach based on a stacked long short-term memory (LSTM)-deep neural network (DNN)-based decoder framework is proposed for a power system comprising diverse CIGs forming a virtual power plant and electric vehicle aggregators. The proposed decoder network is comprised of stacked LSTM and DNN, wherein the cascaded LSTM layers are introduced to accurately capture temporal information from time series input. The inclusion of a dropout mechanism further enhances the model’s generalisability in unforeseen environments. The proposed dispatch framework uses mileage-based compensation criteria to optimally allocate instructions among various participating units with differing regulation characteristics. The performance of the proposed method is analysed by considering packet loss, delay, unexpected generation failure, and denial of service attacks. The evaluation of the proposed approach reveals its superior performance compared to proportionality, particle swarm optimisation, decision tree, and DNN methods.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"799-815"},"PeriodicalIF":1.6,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143251941","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":"Structural characterisation for the synthesis of large-scale combined electric–gas networks","authors":"Adam B. Birchfield,&nbsp;Yousef Abu-Khalifa","doi":"10.1049/esi2.12170","DOIUrl":"https://doi.org/10.1049/esi2.12170","url":null,"abstract":"<p>In this paper, the authors present a methodology for building realistic synthetic test cases to model combined electric and natural gas infrastructure networks. Because these networks are synthetic, that is, fictitious, they are able to be freely shared; hence, they serve to support research and development in the area of coupled-infrastructure analysis with large-scale realistic test cases that do not contain non-public information. We anchor our process for building these synthetic networks in a structural characterisation of actual electric and natural gas networks. Supply and demand nodes are geographically placed, based on a combination of publicly available information from several sources and a clustering-based method to match the right fraction of each node type, taking into account the intersection points between the electric and gas grids. Then the networks are connected with pipelines and transmission lines using a systematic graph construction method, validated against network properties including degree distribution, clustering, graph diameter, and degree of planarity, along with operational validation to ensure the simulated solution is realistic. The methodology is demonstrated by creating and validating a test case with 6717 electric buses and 2451 gas nodes.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"816-827"},"PeriodicalIF":1.6,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253721","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":"Resilience enhancement strategies for power distribution network based on hydrogen storage and hydrogen vehicle","authors":"Pingping Xie,&nbsp;Ruoxuan Zhao,&nbsp;Yue Chen,&nbsp;Yinguo Yang,&nbsp;Qiming Yang,&nbsp;Yingming Lin,&nbsp;Gengfeng Li","doi":"10.1049/esi2.12168","DOIUrl":"https://doi.org/10.1049/esi2.12168","url":null,"abstract":"<p>In light of the increasing hydrogen permeability in distribution networks as a means to cope with extreme events and improve network resilience, this paper introduces a novel strategy for enhancing power distribution network resilience. It outlines a comprehensive approach that focuses on dispatching hydrogen storage (HS) and hydrogen vehicle (HV) within hydrogen penetrated distribution systems (HPDS), segmenting the strategy into pre-disaster and post-disaster stages. Firstly, in the pre-disaster stage, models for HS and HVs are established to gather operational data and facilitate rapid post-disaster response, alongside a coupled electric grid and road network model for optimising HV routing and dispatch. Subsequently, the post-disaster stage focuses on a scheduling model that aims to minimise load power losses and economic costs, balancing immediate power support with cost-effectiveness through detailed analysis of HS and HV dispatch strategies. Finally, this paper demonstrates the effectiveness of this strategy via a case study, highlighting significant improvements in network resilience and recovery and underscoring the potential of hydrogen technologies in enhancing infrastructure resilience.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"789-798"},"PeriodicalIF":1.6,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252707","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":"Lithium inventory estimation of battery using incremental capacity analysis, support vector machine, particle swarm optimisation","authors":"Xingbo Zhang,&nbsp;Kui Chen,&nbsp;Zhou Long,&nbsp;Yang Luo,&nbsp;Yang Li,&nbsp;Jiamin Zhu,&nbsp;Kai Liu,&nbsp;Guoqiang Gao,&nbsp;Guangning Wu","doi":"10.1049/esi2.12163","DOIUrl":"https://doi.org/10.1049/esi2.12163","url":null,"abstract":"<p>In order to guarantee the durability and security of electric vehicles (EV), the ageing estimation of lithium-ion batteries (LIBs) is of great practical significance. Lithium inventory is an important indicator for assessing the LIB ageing process. Incremental capacity (IC), particle swarm optimisation (PSO) and support vector machine (SVM) are proposed to estimate the LIBs lithium inventory. Firstly, the IC curve that reflect the electrochemical reaction is analysed, and the middle peak of IC curve that characterises the material phase transition point is selected to represent the LIB lithium inventory. IC curve is smoothed by the Savitzky–Golay method to eliminate noise. Three features of the charging voltage curve are selected as the LIB health feature, and the correlation between three features and the lithium inventory is analysed by using the grey relation analysis method. Then, the mapping relationship between the lithium inventory and three health features is established based on SVM. PSO is used to optimise SVM kernel and penalty parameters to improve the precision of LIBs lithium inventory estimation. Finally, the proposed method is verified by three ageing experiments of LIBs. The results show that the proposed method can precisely estimate the lithium inventory of different LIBs.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 S1","pages":"765-775"},"PeriodicalIF":1.6,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12163","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252457","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":"Impact analysis on distribution network due to coordinated electric ferry charging","authors":"Rajib Baran Roy,&nbsp;Sanath Alahakoon,&nbsp;Piet Janse Van Rensburg,&nbsp;Shantha Jayasinghe Arachchillage","doi":"10.1049/esi2.12165","DOIUrl":"https://doi.org/10.1049/esi2.12165","url":null,"abstract":"<p>The maritime industry is a significant emitter of greenhouse gases in marine ecosystems, prompting a global shift towards renewable-powered electric vessels, where energy storage is pivotal. The authors examine the potential ramifications of coordinating the charging of Electric Ferries (EFs) on local distribution networks, with Gladstone Marina in Queensland, Australia, serving as a case study. Employing OpenDSS software for power flow analysis, the authors utilise actual load data and simulate a network with four Battery Energy Storage Systems (BESSs) representing proposed charging stations. The authors discuss the impact on bus voltage, load current, and power flow by integrating a storage controller to optimise BESS charging and discharging dynamics. The Dynamic Link Library (DLL) of MATLAB Simulink-based BESS's dynamic model is linked with OpenDSS environment to replicate the actual electric ferry storage. Additionally, a user-written DLL in Python regulates BESS charging and discharging by the storage controller according to load demand and BESS State of Charge for ensuring efficient operation within the network. The power flow results without inclusion of BESSs to the network, referred to as the base case, are used for relative comparison with the results in the coordinated mode. The power flow analysis suggests that bus voltages rise by approximately 1%–1.5%, while load current consumption decreases by around 2%–2.5% compared to the base case with variable load. Selected lines and transformers maintain consistent power flows. Notably, a reduction in total power consumption and losses is observed, particularly under an 80% load demand increase. These findings indicate that the coordinated mode with a storage controller effectively manages BESS charging and discharging according to demand. Moreover, the storage controller ensures system parameters remain within permissible limits. The support of real and reactive power by BESSs during peak hours validates their role as peak shavers for the test network, suggesting that EFs can operate in either Grid to Ferry mode during charging and Ferry to Grid mode during discharging.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 4","pages":"638-663"},"PeriodicalIF":1.6,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12165","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143253570","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}