Global Energy Interconnection最新文献

{"title":"A review of hydrogen production and storage technologies for power system integration and applications","authors":"Ibrahim B. Mansir ,&nbsp;Paul C. Okonkwo ,&nbsp;Talal F. Qahtan","doi":"10.1016/j.gloei.2026.01.001","DOIUrl":"10.1016/j.gloei.2026.01.001","url":null,"abstract":"<div><div>The fast-changing trajectory of energy systems toward renewables requires flexible, low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems. Moreso, hydrogen is increasingly viewed as a multi-scale flexibility resource capable of supporting deep decarbonization in renewable-dominated power systems, yet existing reviews often treat production, storage, and conversion technologies in isolation. Hydrogen offers the ability to convert, store and reconvert energy on various timescales. This review critically analyses the current literature of hydrogen production and storage in relation to power systems integration, synthesizing technical, economic and operational advances. The study synthesizes recent advances in electrolysis, particularly PEM and high-temperature SOEC systems, together with emerging PEC routes, biomass-to-hydrogen processes, and long-duration storage technologies. It considers, for storage, the performance and maturity of compressed gas, liquid hydrogen, metal and complex hydrides, liquid organic hydrogen carriers, and geological formations. Integration studies show that the value of hydrogen is enhanced as the share of renewables increases, providing seasonal storage, grid balancing, and sector coupling via power-to-hydrogen-to-power configurations. Yet technical, economic and other hurdles such as conversion losses, infrastructure requirements, and safety considerations are still holding back widespread implementation. The review also underlines the value of policy frameworks, such as country-level hydrogen strategies, carbon pricing, tax incentives, and harmonized safety standards to speed up adoption and reduce barriers to costs. The review synthesizes offer planners, operators, and policymakers a clear roadmap for aligning hydrogen deployment strategies with evolving technical requirements and high-renewable power-system conditions. By summarizing what is known and discussing opportunities for the future, this review is intended to be a roadmap towards maximizing hydrogen in reaching a flexible, resilient and carbon free power system.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"9 1","pages":"Pages 83-107"},"PeriodicalIF":2.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147413965","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":"Advances in proton exchange membranes for wide-temperature-range fuel cells","authors":"Yunjie Yang ,&nbsp;Junxin Chen ,&nbsp;Sai Liu ,&nbsp;Xiang Ao ,&nbsp;Haoliang Feng ,&nbsp;Le Shi","doi":"10.1016/j.gloei.2025.12.002","DOIUrl":"10.1016/j.gloei.2025.12.002","url":null,"abstract":"<div><div>Proton exchange membranes (PEMs) play a central role in determining the efficiency, durability, and operational flexibility of PEM fuel cells (PEMFCs). However, conventional PEMs exhibit strong temperature-dependent proton-transport behavior, which limits their ability to support both rapid start-up at low temperatures and stable operation at elevated temperatures. Water-mediated PEMs show excellent conductivity under low-temperature and high-humidity conditions but suffer from dehydration and structural instability in the high-temperature regime. In contrast, water-independent PEMs, particularly phosphoric-acid-doped systems, conduct protons efficiently under anhydrous high-temperature conditions yet experience acid leaching that hampers room-temperature start-up and long-term durability. This review summarizes the fundamental proton-transport mechanisms that govern temperature-dependent performance and discusses recent advances in materials design aimed at enabling wide-temperature-range PEM operation. For water-mediated membranes, strategies such as incorporating hydrophilic fillers, constructing confined hydrophilic domains, and introducing additional proton-transfer sites have been developed to mitigate water loss and stabilize proton conduction. For water-independent membranes, approaches including strengthening polymer–acid interactions, engineering nanoscale confinement, designing multilayer architectures, and constructing multi–proton-carrier networks effectively improve acid retention and broaden operational temperature windows. Emerging fixed-carrier systems based on phosphonic-acid-grafted polymers, metal–organic frameworks, and covalent organic frameworks offer new pathways for stable anhydrous proton conduction across a wide temperature range. We conclude by outlining key challenges and future research opportunities, including reducing the dependence on volatile or leachable proton carriers, developing adaptive nanochannel architectures, improving anhydrous high-temperature conduction, and establishing scalable membrane fabrication methods. Continued innovation in these directions is expected to enable next-generation wide-temperature-range PEMs capable of flexible, high-efficiency operation from sub-zero to high-temperature conditions.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"9 1","pages":"Pages 29-50"},"PeriodicalIF":2.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147413158","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":"An evaluation method for the aggregate adjustable capability of photovoltaic-storage-charging stations considering local security constraints","authors":"Chao Li ,&nbsp;Jiawei He ,&nbsp;Tingzhe Pan ,&nbsp;Zijie Meng ,&nbsp;Xinlei Cai ,&nbsp;Xin Jin ,&nbsp;Zechun Hu","doi":"10.1016/j.gloei.2025.11.002","DOIUrl":"10.1016/j.gloei.2025.11.002","url":null,"abstract":"<div><div>As renewable energy penetration continues to rise, enhancing power system flexibility has become a critical requirement. Photovoltaic–storage–charging stations (PSCSs) are key components for enhancing local regulation capability and promoting renewable integration. However, evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge. This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary (PEB) model. Then, an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region (AFR) model, which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy. To solve this formulation, it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution. Finally, a multi-station adjustable capability aggregation method considering security constraints is introduced. Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries, providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"9 1","pages":"Pages 108-118"},"PeriodicalIF":2.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147413950","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":"Performance analysis of state of charge and state of health prediction using Kalman filter techniques with battery parameter variation","authors":"Ranagani Madhavi,&nbsp;Indragandhi Vairavasundaram","doi":"10.1016/j.gloei.2025.08.004","DOIUrl":"10.1016/j.gloei.2025.08.004","url":null,"abstract":"<div><div>Accurate estimation of the State of Charge (SOC), State of Health (SOH), and Terminal Resistance (TR) is crucial for the effective operation of Battery Management Systems (BMS) in lithium-ion batteries. This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter (EKF), Extended Kalman-Bucy Filter (EKBF), Unscented Kalman Filter (UKF), and Unscented Kalman-Bucy Filter (UKBF) under varying battery parameter conditions. These include temperature fluctuation, self-discharge, current direction, cell capacity, process noise, and measurement noise. Our findings reveal significant variations in the performance of SOC and SOH predictions across filters, emphasizing that UKF demonstrates superior robustness to noise, while EKF performs better under accurate system dynamics. The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters, thereby enhancing BMS reliability and extending battery lifespan.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"9 1","pages":"Pages 143-158"},"PeriodicalIF":2.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147413969","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":"Data-driven insights for optimizing EV charging infrastructure: a case study on efficiency and utilization","authors":"Kazi Zehad Mostofa ,&nbsp;Md. Fokrul Islam ,&nbsp;Mohammad Aminul Islam ,&nbsp;Mohammad Khairul Basher ,&nbsp;Tarek Abedin ,&nbsp;Boon Kar Yap ,&nbsp;Mohammad Nur-E-Alam","doi":"10.1016/j.gloei.2025.05.005","DOIUrl":"10.1016/j.gloei.2025.05.005","url":null,"abstract":"<div><div>The increasing global adoption of electric vehicles (EVs) has led to a growing demand for a cost-effective and reliable charging infrastructure. This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency, station utilization rates, no-power session occurrences, and CO₂ reduction metrics. A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization. Results indicate a strong correlation between station utilization and energy efficiency, highlighting the importance of strategic station placement. The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring. CO₂ reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals. Based on these insights, this study recommends the implementation of predictive maintenance strategies, real-time user notifications, and diversified provider networks to improve station availability and efficiency. The proposed data-driven framework offers actionable solutions for policymakers, charging network operators, and urban planners to enhance EV infrastructure reliability and sustainability.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 997-1009"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792272","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":"Renewable energy finance, policy, and building energy technologies: trends, case studies, and innovations in North America","authors":"Christian K. Ezealigo ,&nbsp;Precious O. Ezealigo","doi":"10.1016/j.gloei.2025.07.003","DOIUrl":"10.1016/j.gloei.2025.07.003","url":null,"abstract":"<div><div>This paper analyzes North American shifts in renewable energy finance and building energy technologies from 2022 to 2025. Fueled by net-zero targets and policy incentives, clean energy investment now surpasses fossil fuel spending. We examine key financial tools—green bonds, corporate power purchase agreements (PPAs), public–private partnerships, and tax credits—and parallel advances in smart meters, grid-interactive efficient buildings, battery storage, heat pumps, and net-zero construction. Through case studies of municipal retrofit financing, integrated smart homes, and net-zero campuses, we illustrate emerging finance–technology–policy ecosystems poised to accelerate the energy transition and bolster climate resilience.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 969-981"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792273","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":"Optimization of microgrid scheduling based on multi-strategy improved MOPSO algorithm","authors":"Yang Xue ,&nbsp;Shiwei Liang ,&nbsp;Fengwei Qian ,&nbsp;Jinyi Tang","doi":"10.1016/j.gloei.2025.11.001","DOIUrl":"10.1016/j.gloei.2025.11.001","url":null,"abstract":"<div><div>A multi-strategy Improved Multi-Objective Particle Swarm Algorithm (IMOPSO) method for microgrid operation optimization is proposed for the coordinated optimization problem of microgrid economy and environmental protection. A grid-connected microgrid model containing photovoltaic cells, wind power, micro gas turbine, diesel generator, and storage battery is constructed with the aim of optimizing the multi-objective grid-connected microgrid economic optimization problem with minimum power generation cost and environmental management cost. Based on the optimization of the standard multi-objective particle swarm optimization algorithm, four strategies are introduced to improve the algorithm, namely, Logistic chaotic mapping, adaptive inertia weight adjustment, adaptive meshing using congestion distance mechanism, and fuzzy comprehensive evaluation. The proposed IMOPSO is applied to the microgrid optimization problem and the performance is compared with other unimproved multi-objective gray wolf algorithm (MOGWO), multi-objective ant colony algorithm (MOACO), and MOPSO algorithms, and the total cost of the proposed method is reduced by 3.15%, 8.34%, and 10.27%, respectively. The simulation results show that IMOPSO can more effectively reduce the cost and optimize power distribution, and verify the effectiveness of the proposed method.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 959-968"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792232","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":"Long term wind energy forecasting using machine learning techniques","authors":"Marcos V.M. Siqueira ,&nbsp;Vitor H. Ferreira ,&nbsp;Angelo C. Colombini","doi":"10.1016/j.gloei.2025.05.013","DOIUrl":"10.1016/j.gloei.2025.05.013","url":null,"abstract":"<div><div>Ensuring the reliability of wind energy as a dependable source requires overcoming challenges posed by the inherent volatility and stochastic nature of wind patterns. Long-term forecasting provides strategic advantages in managing energy generation projects, enabling the development of effective portfolio management strategies. The primary objective of this study was the development of forecasting methods to support strategic decision-making within the scope of wind energy operations, specifically targeting the Pindaí Wind Complex and its commercial dispatch. The study integrated Big Data analytics, data engineering, and computational techniques through the application of machine learning algorithms: including eXtreme Gradient Boosting, Multilayer Perceptron, Support Vector Regression, Ridge Regression, and Random Forests, aiming to generate forward-looking projections of the complex’s energy production for the year 2023. To this end, five supervised machine learning techniques were modeled and implemented. These techniques were grounded in their respective mathematical and structural formulations, and the empirical foundation for modeling was provided by historical power generation data from the Pindaí Wind Complex, combined with high-resolution realized and forecasted meteorological data retrieved via the Open-Meteo API. The models are trained using historical monthly generation data from the Pindaí Wind Complex, which has an installed capacity of 79.9 MW and is located in the northeastern region of Brazil, along with meteorological data from reanalysis models, such as air temperature, relative humidity, precipitation, surface pressure, wind speed at 10 m, wind speed at 100 m, and wind gusts. These methodologies are applied to forecast monthly wind generation for the year 2023, and the outputs are systematically compared using evaluation metrics to determine the most suitable modeling approach. The results highlight the superiority of the Multilayer Perceptron, Support Vector Regression, and eXtreme Gradient Boosting models, which achieved Kling-Gupta Efficiency (KGE) of 0.89, 0.89, and 0.90, mean absolute scaled error (MASE) of 0.29, 0.31, and 0.18, root mean square errors (RMSE) of 0.56, 0.59, and 0.35, and mean absolute errors (MAE) of 0.48, 0.52, and 0.29, respectively.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 1030-1046"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792230","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":"Enhancing grid stability and V2G integration by optimizing three-phase bidirectional EV chargers using ANFIS and FPGA-based control systems","authors":"Nagarajan Munusamy,&nbsp;Indragandhi Vairavasundaram","doi":"10.1016/j.gloei.2025.06.002","DOIUrl":"10.1016/j.gloei.2025.06.002","url":null,"abstract":"<div><div>State this study looks at how well a three-phase bidirectional converter works for Vehicle-to-Grid (V2G) services by using both Adaptive Neuro-Fuzzy Inference System (ANFIS) and Proportional-Integral (PI) controllers. When compared with ANFIS controllers, traditional controllers such as PI and PID show challenges. They may not sufficiently react to changing conditions or non-linearity’s and use fixed gain values requiring hand tuning. By means of learning, ANFIS controllers can thus dynamically change their parameters, so providing enhanced accuracy and flexibility in real-time control. The main objectives are to control the DC link voltage, lower total harmonic distortion (THD), and lower the errors. The Synchronous Reference Frame (SRF) transformation changes three-phase AC into a two-axis (d-q) system, making it easier to control active and reactive power separately. We developed a thorough Simulink model in MATLAB 2023a to model the bidirectional off-board fast charger at a power level of 60 kW. After validation, a 5-kW hardware prototype was built in the lab. The main platform is an AC-DC converter, followed by a DC-DC converter. A programmable DC power supply, Chroma 62050H-600S, connected to the DC-DC converter, mimics the dynamic characteristics of a battery. The control algorithm, deployed on a Spartan-6 LX9 FPGA, manages both voltage and current, maintaining a stable DC link voltage of 800 V. The results obtained indicate that the ANFIS controller outperforms a conventional PI controller when handling dynamic load variations.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 1047-1061"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792275","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":"Dynamic characteristics of sub-cycle incipient faults in medium-voltage cable joints","authors":"Zhipeng Yu ,&nbsp;Yongpeng Xu ,&nbsp;Guoliang Qi ,&nbsp;Wenwei Tan ,&nbsp;Weiliang Guan ,&nbsp;Xiuchen Jiang","doi":"10.1016/j.gloei.2025.05.009","DOIUrl":"10.1016/j.gloei.2025.05.009","url":null,"abstract":"<div><div>Permanent faults in medium-voltage cable joints significantly impact the reliability of distribution networks. Radial breakdowns caused by water ingress often lead to several self-extinguishing arc discharges—referred to as incipient faults—before developing into permanent faults. Effective monitoring of incipient faults can help reduce outage costs associated with permanent faults. However, the specific fault scenarios of incipient faults remain insufficiently understood. To address this gap, this study designed a simulation experiment replicating incipient fault conditions in medium-voltage cable joints under humid environments, based on actual operating scenarios. The experiment compared the insulation strength required to trigger incipient faults and examined both non-electrical fault characteristics, such as insulation damage and arc flame intensity, and electrical characteristics, such as fault current and impedance. Experimental observations show that, in cable joints, gaps without accumulated water retain sufficient insulation strength to prevent breakdown. However, the infiltration of accumulated water shortens the effective insulation path, thereby lowering the breakdown threshold. The peak current of an incipient fault can range from hundreds to thousands of amperes, with a duration of approximately 1/8 to 1/4 of a power–frequency cycle. During incipient faults, arc burning on the pore wall leaves conductive traces, which progressively reduce the insulation strength of the surrounding environment. As these traces accumulate over multiple events, the likelihood of breakdown increases, ultimately resulting in a permanent fault. Permanent faults are characterized by intense, sustained arc discharges that persist over a macroscopic time scale and exhibit flat-shoulder waveforms within individual cycles, with discharge intensity increasing progressively over time.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 6","pages":"Pages 1062-1072"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792229","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}