International Journal of Electrical Power & Energy Systems最新文献

{"title":"Wind speed forecasting approach using conformal prediction and feature importance selection","authors":"Cesar Vinicius Zuege ,&nbsp;Stefano Frizzo Stefenon ,&nbsp;Cristina Keiko Yamaguchi ,&nbsp;Viviana Cocco Mariani ,&nbsp;Gabriel Villarrubia Gonzalez ,&nbsp;Leandro dos Santos Coelho","doi":"10.1016/j.ijepes.2025.110700","DOIUrl":"10.1016/j.ijepes.2025.110700","url":null,"abstract":"<div><div>Wind energy is a rising renewable energy source that plays an important role in the transition to a more sustainable energy system. Variation in wind power generation is one of the main challenges facing this energy source. Wind forecasting approaches are essential for planning and operating wind farms, but are complex due to the dynamic nature of the wind and the influence of local factors. This paper evaluates short-term forecasting of time series with a measure of uncertainty associated with wind speeds. The proposed method considers the conformal prediction approach and, based on Shapley values, uses optimal selection of features given their importance. Furthermore, a Bayesian Optimization with Tree-structured Parzen Estimators (BO-TPE) will be used to tune the hyperparameters of the models. The results showed that using Variational Mode Decomposition (VMD) allied with Singular Spectrum Analysis (SSA) to feed into a conformal prediction model improved the performance of the model. Taking into account a Beutenberg data set, Germany, the best model was Light Gradient Boosting Machine (LGBM)-VMD-SSA without partial fit, resulting in a root mean squared error (RMSE) criterion of 0.25031, coverage measure of 94.4%, and width measure of 1.008. When considering a dataset from Limoeiro, Brazil, the best model was also LGBM-VMD-SSA without partial fit, resulting in an RMSE of 0.21597, a coverage of 90.3%, and a width of 0.678. SHapley Additive exPlanations (SHAP) bring explainability to the model results. The models proposed in this study, hypertuned by BO-TPE with interpretable results based on SHAP, can be useful in predicting wind speed and power generation.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110700"},"PeriodicalIF":5.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pilot protection based on voltage and current correlation for DC lines in mesh DC grid without boundary","authors":"Zhihui Dai,&nbsp;Xu Shi","doi":"10.1016/j.ijepes.2025.110723","DOIUrl":"10.1016/j.ijepes.2025.110723","url":null,"abstract":"<div><div>As the scale of DC grids expands, the converter will be connected with multiple outgoing lines. In this context, locating current-limiting reactors at the outlet of the converter can effectively balance the contradiction between current-limiting requirements and construction costs. However, the absence of a clear line boundary poses challenges for DC line protection. In response, a setting-less line pilot protection is proposed for the mesh DC grid without boundary. First, through the analysis of measured impedance characteristics, it is found that for internal faults, the high-frequency voltage and high-frequency current on both ends of the line are negatively correlated. Whereas for external faults, there is at least one end of the line where the high-frequency voltage and high-frequency current are positively correlated. Then, a suitable high-pass filter is designed, and the cosine similarity is utilized to evaluate whether the filtered voltage and current waveforms display a similar trend of change, further providing a comprehensive protection scheme. Finally, numerous simulation results demonstrate that the proposed method exhibits strong endurance to fault resistance and noise environment. The proposed method remains applicable even when system parameters change and does not require complex setting.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110723"},"PeriodicalIF":5.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-stage resilience enhancement method for integrated electricity-gas systems through linepack and mobile compressors","authors":"Chao Qin ,&nbsp;Yongxue Wang ,&nbsp;Shuaihu Ye","doi":"10.1016/j.ijepes.2025.110722","DOIUrl":"10.1016/j.ijepes.2025.110722","url":null,"abstract":"<div><div>Extreme weather events pose significant threats to the Integrated Electricity-Gas Systems (IEGS), often resulting in catastrophic faults of critical components and subsequent disruptions in energy supply. This paper proposes a novel two-stage resilience enhancement method that systematically coordinates the distinct operational characteristics and complementary resilience resources of Power Distribution Systems (PDS) and Natural Gas Systems (NGS). In the pre-disaster stage, comprehensive optimization of mobile compressors, linepack capacity, and PDS topology is performed to maximize the potential for system resilience recovery. In the post-disaster stage, considering the cascading fault propagation characteristics and linepack flow dynamics, the mobile compressors are dispatched to flexibly establish gas transmission links between linepack /gas wells and isolated gas network islands, thereby facilitating the recovery of the IEGS. The proposed method is reformulated into a mixed-integer second-order cone programming model using second-order cone relaxation. The progressive hedging algorithm is employed to further improve the solution efficiency. The proposed method is validated on an IEGS with a 33-bus PDS and a 20-node NGS. Results show that the proposed method provides a robust solution for improving IEGS resilience, offering significant advancements in coordinated electricity-gas system operation during extreme weather events.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110722"},"PeriodicalIF":5.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordinated frequency regulation for thermal power unit and battery energy storage using dynamic proportional control","authors":"Gangui Yan ,&nbsp;Qianli Sha ,&nbsp;Junhui Li ,&nbsp;Zheng Fang ,&nbsp;Shuaishuai Lv ,&nbsp;Shuo Zhan ,&nbsp;Lin Yue","doi":"10.1016/j.ijepes.2025.110724","DOIUrl":"10.1016/j.ijepes.2025.110724","url":null,"abstract":"<div><div>This paper addresses the issues of significant frequency regulation losses, short lifespan and poor economic performance of battery energy storage system in the combined frequency regulation process with the thermal power unit by proposing a coordinated frequency regulation control strategy for the thermal power unit and battery energy storage system using data-driven and dynamic proportional control. First, the mechanism model and operational data are combined to design a data-driven automatic generation control frequency regulation characteristic model for the thermal power unit, and a coordinated frequency regulation system model for the thermal power unit and battery energy storage system is then constructed, tailored to the automatic generation control frequency regulation environment. Considering the state of charge of battery energy storage system, the dynamic proportional control strategy for the thermal power unit and battery energy storage system is designed. The frequency regulation loss cost of the thermal power unit is quantified, and an economic model for the thermal power unit and battery energy storage system is constructed. Hippopotamus optimization algorithm is applied to optimize the relevant parameters of the dynamic proportional control strategy, resulting in a control scheme that maximizes overall benefits. Finally, the effectiveness and superiority of the proposed strategy are validated using one month of actual operational data from a 330 MW unit in a power plant.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110724"},"PeriodicalIF":5.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel FRT strategy for transformerless MMC to improve current differential protection performance under single-phase grounding faults","authors":"Yuze Li ,&nbsp;Peng Guo ,&nbsp;Qianming Xu ,&nbsp;Josep M. Guerrero","doi":"10.1016/j.ijepes.2025.110729","DOIUrl":"10.1016/j.ijepes.2025.110729","url":null,"abstract":"<div><div>AC/DC distribution networks are interconnected by converters such as modular multilevel converters (MMCs). In AC/DC distribution networks, single-phase grounding (SPG) faults can cause enormous challenges in relay protection. Additionally, traditional MMCs’ fault ride-through (FRT) strategies cause further degradation of the protection performance. Furthermore, under SPG faults, the voltages of the nonfaulted phases swell beyond the high-voltage ride-through (HVRT) capabilities of MMCs using traditional FRT strategies, which can lead to their shutdown. Therefore, this manuscript has proposed a novel FRT strategy for transformerless MMC to solve these two problems. For the first problem, this manuscript has proposed a positive-sequence (PS) and zero-sequence (ZS) current injection method aimed at improving the sensitivity of current differential protection without requiring adjustments to the relay parameters. The optimal phase angles for the injected PS and ZS currents are derived based on the proposed interconnected sequence network. In addition, since the line impedances may not be accurately measured during fault conditions, the appropriate phase angle ranges for PS and ZS current injections have been studied. For the second problem, this manuscript has proposed the self-cooperative FRT method to promote MMC’s HVRT capability. This approach enables MMCs to withstand severe and minor SPG faults. What’s more, the PS and ZS current references for the FRT strategy have been discussed. The effectiveness of the proposed FRT strategy has been validated in MATLAB/Simulink.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110729"},"PeriodicalIF":5.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decentralized optimization for coordinated participation of local energy communities in ancillary services markets with desired energy sharing and costs","authors":"Pierluigi Siano ,&nbsp;Marialaura Di Somma ,&nbsp;Mohammad Dolatabadi","doi":"10.1016/j.ijepes.2025.110694","DOIUrl":"10.1016/j.ijepes.2025.110694","url":null,"abstract":"<div><div>Achieving the multiple benefits associated with Local Energy Communities (LECs) for both community members and grid operators requires advanced energy management through inter-community coordination, optimizing virtual energy sharing and ancillary service (AS) provision. This task is challenging because local requirements must be considered alongside global ones; individually, each LEC might be unable to guarantee sufficient power flexibility, which becomes feasible through coordinated efforts among multiple communities. This paper presents a novel inter-community coordination method, based on decentralized optimization to ensure the joint participation of multiple LECs in the AS market. The proposed coordination method considers as objective function the remuneration for AS provision combined with revenues associated with the incentives for the energy shared as established by the Italian regulation, while energy costs are considered as a constraint. In addition, the proposed method allows the LEC manager to assess the impact of peer-to-peer (P2P) energy exchanges on the coordination of LECs, the incentives for virtual energy sharing and the remuneration for AS provision. Multiple case studies are analyzed to evaluate the performance of the proposed method for two LECs, and the results demonstrate its effectiveness for inter-communities’ coordination while keeping the energy shared close to the desired value and the energy costs unchanged. P2P energy exchanges in each LEC tend to reduce energy costs and increase the self-consumption rate, while their impact on the provided flexibility depends on PV energy production. Under a coordinated management obtained with the proposed decentralized optimization, each LEC’s objective function remains within roughly 1 % of its ideal solution. In summer scenarios, joint flexibility increases each community’s economic objective from approximately €659–€745 to €2154 and €1601, respectively, highlighting that revenue from ancillary services can easily compensate for any reductions in shared-energy incentives. In winter scenarios, with lower PV energy production, flexibility revenues decrease, yet the communities remain within 1% of their optimal local targets, further demonstrating the method's effectiveness.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110694"},"PeriodicalIF":5.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the impact of load forecasting accuracy on congestion management in distribution grids","authors":"Maximilian Bernecker ,&nbsp;Marc Gebhardt ,&nbsp;Souhir Ben Amor ,&nbsp;Martin Wolter ,&nbsp;Felix Müsgens","doi":"10.1016/j.ijepes.2025.110713","DOIUrl":"10.1016/j.ijepes.2025.110713","url":null,"abstract":"<div><div>Digitalization is a global trend in energy systems and beyond. However, it is often unclear what digitalization means exactly in the context of energy systems and how the benefits of digitalization can be quantified. Providing additional information, e.g., through sensors and metering equipment, is one concrete angle where digitalization contributes. This paper provides a framework to quantify the value of such additional information in distribution grids. We analyze to what extent smart meters improve the accuracy of day-ahead load forecasts and quantify the savings in congestion management costs resulting from the improved accuracy.</div><div>To quantify the cost reduction, we conduct a case study employing a simplified IEEE test system. Historical electricity load data from over 6,000 smart meters was used to improve day-ahead load forecasts. We assessed and compared the forecasting performance to estimates based on standard load profiles with multiple load forecast simulations in the network based on uncertainty parameterizations from forecasts with and without smart meter data.</div><div>Calculating redispatch cost in the distribution grid, we find that the forecast based on smart meter data reduces key redispatch parameters such as the share of expected voltage violations, the amount of rescheduled generation by more than 90%. These improvements translate into a reduction in congestion management costs by around 97%. Furthermore, we shed light on whether the gains increase linearly with the number of smart meters and available data in the grid. When smart meter shares are increased uniformly throughout the grid, savings are concave, i.e., the first 10% of smart meters reduces congestion management costs by around 20% while the last 10% reduces these costs only marginally. Focusing smart meter installation on the most congested nodes reduces congestion management costs by around 60% with just 10% smart meter coverage, significantly outperforming a uniform rollout. However, savings in congestion management alone are not likely to recover the installation and operation costs of the installed smart meter.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110713"},"PeriodicalIF":5.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic model of electric vehicles’ flexibility in residential areas","authors":"Emir Nukic ,&nbsp;Victor Levi ,&nbsp;Nikola Vojnovic ,&nbsp;Dragan Cetenovic","doi":"10.1016/j.ijepes.2025.110725","DOIUrl":"10.1016/j.ijepes.2025.110725","url":null,"abstract":"<div><div>This paper presents a probabilistic model for the flexibility assessment of electric vehicles in residential areas. The flexibility is modelled and evaluated in terms of the aggregate charging demand which can be rescheduled to prevent exceeding network capacity. Developed model and corresponding calculations are based on the algebra of random variables. Main factors which affect the flexibility of electric vehicles are identified and modelled first. Modelled quantities and their mutual links are then incorporated into the probabilistic model. Cumulative distribution of charging duration, discrete probability of charging on particular day and discrete probabilities of possible start charging time are presented in the paper as the probabilistic model outputs. Finally, limits of available flexible capacity [kW] are calculated and presented as the main flexibility indicator for specified test cases. Presented results illustrate a potential for rescheduling charging sessions in different cases/scenarios. Developed model is expected to be of particular interest for distribution network planning during the 2020s and early 2030s.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110725"},"PeriodicalIF":5.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk and resilience based residential electric vehicle integration framework for restoration of modern power distribution networks","authors":"Abdullah Ali M. Alghamdi ,&nbsp;Dilan Jayaweera","doi":"10.1016/j.ijepes.2025.110690","DOIUrl":"10.1016/j.ijepes.2025.110690","url":null,"abstract":"<div><div>The restoration of power distribution networks following extreme events is a critical challenge, particularly when traditional utility-owned mobile power sources (MPSs) are limited in number, capacity, and deployment flexibility. Residential electric vehicles (EVs) present a scalable and decentralized alternative due to their widespread availability and bidirectional charging capabilities. However, the large-scale integration of non-predetermined residential EVs into power restoration remains under-explored. This paper proposes the Individually-Owned EV Integration Innovative Framework (IIIF) to optimize residential EV participation in grid restoration. The IIIF introduces a novel EV user behaviour model, suggesting a 24% likely improvement in participation prediction accuracy used in the restoration process and leading to more effective EV mobilization. Additionally, a dynamic clustering framework is integrated to enhance EV allocation to public EV charging points (EVCPs), increasing EVCP utilization and optimizing EV distribution to reduce congestion and waiting times. The IIIF also incorporates an advanced EV dispatch model, which optimizes routing decisions to minimize power consumption and enhance discharging efficiency, leading to improved power delivery compared to conventional strategies. To ensure resilience, the IIIF integrates a risk assessment and backup strategy, activating MPSs when EVs alone are insufficient to meet restoration demand. Performance evaluation on the IEEE 123-bus system demonstrates that the IIIF reduces power restoration time by 27% and decreases total operational costs by 19% compared to conventional EV-based and MPS-only restoration approaches. These findings establish the IIIF as a benchmark framework for resilient, cost-effective, and large-scale EV integration in power distribution network restoration.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110690"},"PeriodicalIF":5.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks","authors":"Bingbing Yu ,&nbsp;Yonggang Wang ,&nbsp;Jun Wang ,&nbsp;Yuanchu Ma ,&nbsp;Wenpeng Li ,&nbsp;Weigang Zheng","doi":"10.1016/j.ijepes.2025.110703","DOIUrl":"10.1016/j.ijepes.2025.110703","url":null,"abstract":"<div><div>With the burgeoning development of the wind power industry, the significance of wind power forecasting in enhancing electricity generation efficiency, minimizing energy waste, and improving electrical grid management is increasingly highlighted. To enhance the stability and accuracy of wind power forecasting, a hybrid model integrating Kepler optimization algorithm (KOA), variational mode decomposition (VMD), and stochastic configuration network (SCN) is proposed. Firstly, the series of wind power data is decomposed using the VMD method optimized by the KOA, aiming to smooth the wind power series while preserving its inherent characteristics. Subsequently, permutation entropy (PE) is employed to order and reconstruct the decomposed wind power subsequences, with the selection of input features by the maximal information coefficient (MIC) and autocorrelation function (ACF). Following this, KOA is utilized to optimize the parameters of the SCN model, further enhancing the predictive performance of the SCN. Finally, a multi-seasonal and multi-scenario wind power forecasting analysis is conducted by using an actual data set from an offshore wind farm in China. Compared with the basic VMD model, the data decomposition efficiency of the optimized VMD model has been improved by 28.86%. Meanwhile, the prediction average error of the proposed model has decreased by 0.1385 compared with the basic prediction<!--> <!-->model. The results demonstrate that the proposed hybrid model exhibits superior stability and accuracy in short-term wind power prediction.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"168 ","pages":"Article 110703"},"PeriodicalIF":5.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}