International Journal of Electrical Power & Energy Systems最新文献

{"title":"Optimal control strategy on hybrid energy storage systems to improve system inertia for a bipolar DC microgrid","authors":"Yuechao Ma ,&nbsp;Guangchen Liu ,&nbsp;Hongbin Hu ,&nbsp;Jun Tao ,&nbsp;Yu Xu","doi":"10.1016/j.ijepes.2025.110628","DOIUrl":"10.1016/j.ijepes.2025.110628","url":null,"abstract":"<div><div>For an islanded bipolar DC microgrid with positive and negative hybrid energy storage systems (HESSs), researchers need to take into account a special problem related to improving the system inertia by the HESSs. To solve this issue, an optimization control strategy for multiple HESSs is proposed. The strategy includes a battery and a supercapacitor (SC) for each HESS, with inertia improvement for the SCs. Specifically, to effectively improve the system inertia, a dynamic power distribution strategy is proposed for solving the unreasonable power distribution problem on positive and negative SCs caused by the asymmetric load power on the positive and negative systems. Subsequently, to improve the system inertia at the right time, 2 operating-state discriminators, one working as an output discriminator and the other as a recovery discriminator, are introduced for each SC. These discriminators are employed for avoiding the influence of SCs on the state-of-charge balancing on the positive and negative batteries and to control the output and recovery actions of the SCs. Based on the 2 operating-state discriminators, 2 virtual DC generators (VDCGs) are introduced into the output paths of the SCs for improving the positive and negative system inertia when the output signals of the operating-state discriminators are activated. Furthermore, to improve the entire system inertia in a bipolar DC microgrid and solve the paradox between the inertia improvement and the lag in the dynamic response speed, a particle swarm algorithm is adopted to joint optimize the parameters of the 2 VDCGs. Finally, to make the SCs output power and improve system inertia repeatedly, 2 time-varying virtual inductors are introduced into the recovery paths of the SCs for accelerating the recovery speed of terminal voltages for SCs when the recovery signals of the operating-state discriminators are activated. The simulation results in different working conditions reveal that the proposed control strategy helps in obtaining reasonable output powers of the positive and negative HESSs, improving the system inertia, ensuring the reliable operation of the SCs, and achieving the optimal operation of the system. Therefore, the accuracy and effectiveness of the proposed control strategy were verified.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110628"},"PeriodicalIF":5.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online Neural Dynamics Forecasting for power system security","authors":"Mert Karacelebi,&nbsp;Jochen L. Cremer","doi":"10.1016/j.ijepes.2025.110566","DOIUrl":"10.1016/j.ijepes.2025.110566","url":null,"abstract":"<div><div>The increase in variable renewable energy sources has brought about significant changes in power system dynamics, mainly due to the widespread adoption of power electronics and nonlinear controllers. The resulting complex system dynamics and the unpredictable nature of disturbances pose substantial challenges for real-time dynamic security assessment (DSA). Machine learning (ML) methods offer advantages in terms of computational speed compared to numerical methods and simulators. Offline-trained ML models, however, are limited by their training domain; e.g., they cannot easily consider various grid topologies and data changes. Neural Ordinary Differential Equations (NODEs) leverage the integration of neural networks and ODE solvers to enable continuous-time dynamic trajectory predictions from time series data, resolving the limitation on topological and data changes. This paper introduces the Online Neural Dynamics Forecaster (ONDF) workflow, designed to monitor and assess system security in real-time using multiple NODEs trained solely with local post-fault measurements. Through several case studies, we compare the regression and DSA classification capabilities of ONDF with various ML models. Our findings demonstrate that ONDF provides a novel and scalable approach for system operators to make informed decisions and apply corrective control actions based on predicted dynamics.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110566"},"PeriodicalIF":5.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal protection coordination for directional overcurrent relays in radial distribution networks with inverter-based distributed energy resources","authors":"Jie Li ,&nbsp;Jingtong Feng ,&nbsp;Min Huang ,&nbsp;Shenquan Liu ,&nbsp;Gang Wang","doi":"10.1016/j.ijepes.2025.110622","DOIUrl":"10.1016/j.ijepes.2025.110622","url":null,"abstract":"<div><div>The optimal setting of directional overcurrent relays ensures the reliable protection and fast fault clearance of radial distribution networks. However, the increasing proliferation of inverter-based distributed energy resources can result in protection coordination failure or high operating times of directional overcurrent relays in radial distribution networks. This paper investigates the adverse impacts of grid-connected inverter-based distributed energy resources that adopt the active/reactive power control strategy on the protection speed, sensitivity and selectivity of directional overcurrent relays in radial distribution networks. A multi-objective optimal protection coordination model is formulated, which incorporates the protection performance of directional overcurrent relays, operation conditions and economics that result from the inverter-based distributed energy resources and power grids. The Pareto-front of the proposed optimal protection coordination problem is obtained by the improved multi-objective particle swarm optimization, where a time–space section evaluation utilizes the K-means clustering method to improve the computational efficiency. Furthermore, an analytic hierarchy process and criteria importance through intercrieria correlation weights-based technique for order preference by similarity to ideal solution algorithm is proposed to determine the optimal directional overcurrent relay settings. The developed coordinated framework is applied to a radial distribution network with inverter-based distributed energy resources in MATLAB and PSCAD/EMTDC simulation. The comparative analysis is provided and the effectiveness of the proposed scheme is validated through extensive case studies.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110622"},"PeriodicalIF":5.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extreme outage prediction in power systems using a new deep generative Informer model","authors":"Razieh Rastgoo ,&nbsp;Nima Amjady ,&nbsp;Syed Islam ,&nbsp;Innocent Kamwa ,&nbsp;S.M. Muyeen","doi":"10.1016/j.ijepes.2025.110627","DOIUrl":"10.1016/j.ijepes.2025.110627","url":null,"abstract":"<div><div>Extreme weather events have made growing concerns over electric power grid infrastructure as well as the residents living in disaster areas. Moreover, the potential damages due to the extreme events can make serious challenges for supply reliability and security, leading to widespread power outages in power systems. This paper proposes a deep learning-based framework for power data rebalancing and outage prediction in power systems to cope with the extreme events. To this end, we propose an Adaptive Wasserstein Conditional Generative Adversarial Network for data generation. Also, we propose a new Wasserstein Bidirectional Generative Adversarial Network with the Informer model, embedded in both the Generator and Discriminator Networks, plus an Encoder Network for the outage prediction in power systems. Two-step classification approach has been used in the proposed outage prediction model: classifying the power grid components into impacted and non-impacted categories and classifying the impacted category into in-service and out-of-service categories. In addition, a new classification-specific loss function is proposed for the minimax objective function of the Vanilla Generative Adversarial Network to improve the prediction performance in the latent space. Evaluation results of the proposed model and 15 comparative models in three groups using six evaluation metrics on a real-world test case demonstrate the superiority of the proposed model compared to all comparative models. These results confirm that the proposed outage prediction model can be effectively employed for accurately predicting extreme outages in power systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110627"},"PeriodicalIF":5.0,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of inertia demand in power systems considering wind power virtual inertia","authors":"Hongchun SHU,&nbsp;Haifei DONG,&nbsp;Jing CHEN,&nbsp;Guangxue WANG,&nbsp;Xi WANG,&nbsp;Botao SHI","doi":"10.1016/j.ijepes.2025.110597","DOIUrl":"10.1016/j.ijepes.2025.110597","url":null,"abstract":"<div><div>The high proportion of renewable energy integrated into the grid through numerous power electronic devices has reduced the overall system inertia level and operational stability and caused poor disturbance resistance. Considering the frequency stability of power systems, this study proposes an inertia demand assessment method for renewable energy power systems. The proposed method evaluates the inertia requirements of a power system at a certain level of renewable energy penetration to ensure that the system’s operational frequency stays with the safety boundaries after a system disturbance instead of increasing the inertia level to 100% synchronous machines. This can meet the inertia requirements of a power system while ensuring frequency safety, thus reducing the system’s inertia reserves. In addition, the inertia demand assessment considers the virtual inertia of renewable energy. The proposed method is verified using an IEEE 39 bus time-domain simulation model constructed in the RTLAB simulation environment. The inertia requirements are estimated under different wind power penetration levels of 20%, 40%, and 60%. The proposed method is also compared with the traditional method that uses only the <em>f</em>_min constraint to demonstrate the effectiveness and accuracy of the proposed method in estimating inertia requirements of wind-integrated power systems with virtual inertia. The proposed method is further validated using actual grid data from Yunnan under two operational scenarios corresponding to the wet and dry seasons. The results show that by using both the <em>RoCoF</em>_max and <em>f</em>_min constraints, the proposed method can achieve a more accurate assessment of the inertia level in large-scale wind-integrated power systems with virtual inertia compared to the methods that use only one constraint.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110597"},"PeriodicalIF":5.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deadbeat-based control for MMC-HVDC power systems","authors":"Milovan Majstorović ,&nbsp;Vaibhav Nougain ,&nbsp;Leposava Ristić ,&nbsp;Aleksandra Lekić","doi":"10.1016/j.ijepes.2025.110583","DOIUrl":"10.1016/j.ijepes.2025.110583","url":null,"abstract":"<div><div>With the domination of modular multilevel converters (MMCs) interfaced power grids, especially for transmission of the wind generated energy, the control of such power electronic interfaced grids is of an utmost important for the proper operation and grid stability. This control is very complex due to multivariable intercoupling and plausible nonlinearity. To enhance the grid stability and reduce the total harmonic distortion (THD) of the converter, the paper proposes development of an optimal voltage level-model predictive control (OVL-MPC) for a fast dynamic response, integrated with classical proportional–integral (PI) outer-loop control for robust steady-state performance. This control eliminates the problems of poor steady-state performance of MPC while achieving faster transient response in comparison to the classical proportional integral (PI) dual-loop control. The work proposes OVL-MPC for lower computational burden in comparison to switching state-based MPC, for the inner loop replacing the classical PI inner loop. With the inherent advantages of lower computational burden and superior transient performance, AC current deadbeat controller is used for the modulation in OVL-MPC. To improve the robustness of the control method, the Moore–Penrose pseudo-inversion is applied to address control parameter mismatches, while the Smith predictor compensates for time delays. The designed control algorithm is tested with two real-time simulation platforms, i.e., OPAL-RT and RTDS for thorough power system validation.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110583"},"PeriodicalIF":5.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristic analysis and assessment of disharmony oscillation in multi-VSCU system","authors":"Qiyi Yu,&nbsp;Yi Tang","doi":"10.1016/j.ijepes.2025.110607","DOIUrl":"10.1016/j.ijepes.2025.110607","url":null,"abstract":"<div><div>Previous studies have shown that disharmony among two or three voltage-source-controlled units (VSCUs) may occur on alternating current (AC) transmission lines under steady-state or quasi-static operating condition. As the number of VSCUs increases in a local AC power grid, the probability of multi-VSCU disharmony occurrence increases which may lead to more complex oscillation. For disharmony in multi-VSCU system, this paper analyzes the disharmony oscillation (DHO) characteristics on power grid side and evaluates the degree of disharmony. First, this paper classifies the frequency disharmony problem and elaborates on the equivalent model of the local AC power grid with multiple disharmonized VSCUs. Second, load and line flow oscillation characteristics under disharmony operating condition are discussed. The index for evaluating the degree of disharmony is defined. Finally, case studies based on different load levels and topologies show the abnormal characteristics of power flow and variation law between the degree of disharmony and power flow. The relevant results can provide a reference for monitoring disharmony and verifying DHO suppression methods.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110607"},"PeriodicalIF":5.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HVDC converter simulation model with turn-off characteristics of series thyristors","authors":"Yupeng He,&nbsp;Yechun Xin,&nbsp;Guoqing Li,&nbsp;Tuo Wang,&nbsp;Shouqi Jiang,&nbsp;Weiru Wang,&nbsp;Yanxu Wang","doi":"10.1016/j.ijepes.2025.110620","DOIUrl":"10.1016/j.ijepes.2025.110620","url":null,"abstract":"<div><div>The converter models in common electromagnetic transient simulation software cannot reflect the dynamic turn-off process and the dispersity of series thyristors, which leads to inaccurate judgment and simulation of the commutation failure (CF). To characterize the turn-off process of the thyristor precisely from the micro-physical mechanism, the dynamic dissipation characteristics of charge carriers during the turn-off process are analyzed. The current zero-crossing rate, forward current, and junction temperature are extracted as the key influence factors of turn-off characteristics. Then, based on the analysis of the difference in the dynamic dissipation characteristics of charge carriers, a novel nonlinear segmentation mathematical model describing the turn-off process of thyristor is proposed. Considering the dispersity of the reverse recovery charge between series thyristors, a converter model with turn-off characteristics of series thyristors is proposed. The experiment results from the thyristor test platform and the LCC experiment platform verify the accuracy of the proposed thyristor and converter models separately. The simulation errors of peak turn-off current, reverse recovery charge, and turn-off time are less than 5%. Under the single-phase and three-phase short-circuit ground faults, the proposed converter model can judge the CF and simulate the characteristics of the CF more accurately.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110620"},"PeriodicalIF":5.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Congestion management in distribution grids using local flexibility markets: Investigating influential factors","authors":"Mehdi Attar ,&nbsp;Sami Repo ,&nbsp;Ville Heikkilä ,&nbsp;Olli Suominen","doi":"10.1016/j.ijepes.2025.110601","DOIUrl":"10.1016/j.ijepes.2025.110601","url":null,"abstract":"<div><div>The article presents findings on congestion management (CM) in distribution grids using the local flexibility market (LFM). It employs a co-simulation platform to decompose system complexity into manageable components, enabling realistic and comprehensive modeling. Through simulation, the study examines the effectiveness of flexibility in CM and the data exchange dynamics between the distribution system operator (DSO), LFM, and flexibility service provider (FSP) using a case study based on real data from a 359-bus distribution grid in Finland. Regarding flexibility effectiveness, the case study reveals that a larger BA in LFM can intensify voltage congestion, despite enhancing market liquidity. This underscores the trade-off between congestion mitigation and market liquidity, which must be carefully considered when determining BA size in LFM. The study also explores the rebound phenomenon and its negative impact on the grid, highlighting two key influencing factors: the charging/discharging inefficiency of battery storage and the grid’s operational state during rebound events. On data exchange, the article outlines key considerations for communication between the DSO, LFM, and FSP. These include message content, methods for calculating key parameters (such as BA, using sensitivity analysis), and the sequence of message exchanges between stakeholders.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110601"},"PeriodicalIF":5.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remaining useful life prediction of Lithium-ion batteries based on data preprocessing and CNN-LSSVR algorithm","authors":"Ti Dong ,&nbsp;Yiming Sun ,&nbsp;Jia Liu ,&nbsp;Qiang Gao ,&nbsp;Chunrong Zhao ,&nbsp;Wenjiong Cao","doi":"10.1016/j.ijepes.2025.110619","DOIUrl":"10.1016/j.ijepes.2025.110619","url":null,"abstract":"<div><div>Lithium-ion batteries are now widely available in power and energy systems. Targeting the thorny issues of limited battery historical cycle data and the impact of uncertainty in the data collection process in practical applications, this study proposes a Remaining useful life (RUL) prediction method for lithium-ion batteries based on the data preprocessing and the joint convolutional neural network (CNN)-least squares support vector regression (LSSVR) algorithm. Based on the performance degradation characteristics of the battery, the method proposes new RUL assessment indexes and corresponding health factors. The innovative Multi-Resolution Singular Value Decomposition (MRSVD) method is implemented to reduce the interference caused by noise and error. Eventually, the CNN-LSSVR algorithm and mutant particle swarm optimisation algorithm are utilised to solve the mapping regression and hyper-parameter optimisation problems, respectively, to achieve a complete prediction of RUL. In this work, the feasibility of the method is verified using publicly available datasets and compared with other common noise reduction and prediction algorithms after noise reduction and prediction experiments. The results show that the available capacity and internal resistance of the battery as health factors can effectively achieve degradation performance prediction. Compared with other traditional algorithms, the proposed RUL prediction method can reduce the mean absolute error and root mean square error by at least 37% and 61%, respectively, and has better stability. The RUL prediction method provided pave the new way for accurate prediction of battery data with limited number of samples and high noise characteristics. The fast and accurate battery RUL prediction method proposed in this work is highly beneficial for enhancing the stable and economic operation of power and energy systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110619"},"PeriodicalIF":5.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}