{"title":"Large language models in renewable energy systems: A comprehensive review of forecasting, control, policy, and fault diagnosis","authors":"Napa Chandana , Selika Narasimha Rao , Madavena Kumaraswamy , Archana Pallakonda , Rayappa David Amar Raj","doi":"10.1016/j.nxener.2026.100586","DOIUrl":"10.1016/j.nxener.2026.100586","url":null,"abstract":"<div><div>The change toward a sustainable energy future demands intelligent solutions for planning, forecasting, and optimization in renewable energy systems. Recent advances in Artificial Intelligence (AI), particularly Large Language Models (LLMs) such as generative pretrained transformer, bidirectional encoder representations from transformers, large language model meta AI, and Falcon, provide new opportunities by enabling robust analysis of structured and unstructured data. LLMs can interpret technical documents, make heterogeneous datasets, and support applications like forecasting, fault detection, smart grid control, policy analysis, and public engagement. This paper systematically reviews the role of LLMs across renewable energy domains, classifies applications, and highlights their potential to bridge gaps in data-driven decision-making. We propose a taxonomy of LLM applications, analyze use cases, assess limitations, and outline future research trends. By integrating cutting-edge AI methods with sustainability goals, this work highlights the role of LLMs in building resilient, intelligent, and climate-conscious energy ecosystems.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100586"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147713454","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-04-07DOI: 10.1016/j.nxener.2026.100604
Sevgi Altınkök
{"title":"Experimental validation of high-performance commercial thermal interface materials in PV-TEG hybrid systems","authors":"Sevgi Altınkök","doi":"10.1016/j.nxener.2026.100604","DOIUrl":"10.1016/j.nxener.2026.100604","url":null,"abstract":"<div><div>The \"Efficiency Dilemma\" caused by high photovoltaic (PV) cell temperatures and ineffective heat transfer significantly limits the performance of photovoltaic-thermoelectric (PV-TEG) hybrid systems. A critical bottleneck in these systems is the thermal contact resistance (TCR) arising from microscopic roughness at the PV-TEG interface. Recent literature has largely focused on mitigating TCR through the laboratory synthesis of complex nanocarbon-based composites. However, these methods often present challenges regarding scalability, cost, and complexity. This study proposes a practical engineering solution by experimentally validating the efficacy of a commercially available, high-performance thermal interface material (TIM) with a thermal conductivity of 6.0 W m<sup>−1</sup>K<sup>−1</sup>, significantly exceeding typical lab-synthesized values. Experimental tests were conducted using a calibrated halogen-tungsten solar simulator to replicate the thermal characteristics of solar radiation under controlled laboratory conditions with active cooling support. The study comparatively analyzed 2 scenarios: (i) a reference \"dry contact\" setup and (ii) an improved interface using the commercial high-performance TIM. Thermal imaging analysis and electrical measurements demonstrated that the commercial TIM effectively eliminated interfacial air gaps, reducing the PV surface temperature by 10.4°C and enhancing the TEG open-circuit voltage <span><math><mrow><msub><mrow><mo>(</mo><mi>V</mi></mrow><mrow><mi>oc</mi></mrow></msub><mo>)</mo></mrow></math></span> by 75.8% compared to the dry contact scenario. These findings confirm that accessible, off-the-shelf high-performance thermal pastes offer a viable and superior alternative to complex synthesized composites for the thermal management of PV-TEG systems.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100604"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147709905","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-04-06DOI: 10.1016/j.nxener.2026.100592
Shin-ichi Inage , Akira Yanagisawa
{"title":"Green hydrogen: Reassessing priorities for sustainable deployment","authors":"Shin-ichi Inage , Akira Yanagisawa","doi":"10.1016/j.nxener.2026.100592","DOIUrl":"10.1016/j.nxener.2026.100592","url":null,"abstract":"<div><div>Green hydrogen is increasingly promoted as a key pillar in the transition toward decarbonized energy systems. However, its dual role—as both a clean fuel and an essential industrial feedstock—calls for a more differentiated analysis. This study presents a comprehensive techno-economic evaluation of using green hydrogen to fuel a 1 MW combined cycle gas turbine, comparing its performance and lifecycle costs against conventional liquefied natural gas-fired systems and battery energy storage solutions. The findings suggest that, under current technological and economic conditions, hydrogen-fueled power generation faces significant challenges in terms of efficiency and capital recovery, primarily due to low volumetric energy density and substantial conversion losses. In contrast, industrial applications such as ammonia production and low-carbon steelmaking offer contexts in which green hydrogen’s unique properties deliver irreplaceable value. These results indicate that deployment strategies for green hydrogen may benefit from prioritizing high-impact industrial sectors, while fuel-related applications should be approached selectively, with careful consideration of infrastructure demands and opportunity costs. This work aims to support more balanced and pragmatic hydrogen policies that align with both long-term climate goals and near-term economic realities.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100592"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147710011","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-01-31DOI: 10.1016/j.nxener.2026.100518
Vitória N. Silva Oliveira, Rafaelle Gomes Santiago, Moises Bastos-Neto, Célio L. Cavalcante Jr., F. Murilo T. Luna
{"title":"Power-to-methanol process assessment using enhanced kinetic models","authors":"Vitória N. Silva Oliveira, Rafaelle Gomes Santiago, Moises Bastos-Neto, Célio L. Cavalcante Jr., F. Murilo T. Luna","doi":"10.1016/j.nxener.2026.100518","DOIUrl":"10.1016/j.nxener.2026.100518","url":null,"abstract":"<div><div>In the energy transition scenario, Power-to-X processes play a crucial role by converting surplus electricity from renewable sources into fuels, chemicals, and other energy carriers. These technologies not only help to balance the supply and demand of energy but also promote decarbonization. In this study, the conversion of carbon dioxide and hydrogen into methanol (Power-to-Methanol) as a strategic solution to store and transport hydrogen was evaluated by modeling and simulation. The investigation addressed the rate laws governing the reactions in the hydrogenation of pollutant gases into methanol. Refitted and original Bussche-Froment (BF) and Graaf kinetic models were used to understand and identify the key factors in process efficiency for improving competitiveness compared to conventional processes. The sensitivity analysis revealed some similarities in both models; however, discrepancies in conversion predictions reached up to 49%, particularly at intermediate residence times, low temperatures, and high pressures. Selecting an appropriate residence time (below 0.1 h) proved critical to reducing divergences between models, providing actionable insight for reliable process design and optimization. These discrepancies between the models contribute to a broad theoretical optimal operating window for the process. Considering both models, the methanol production and CO<sub>2</sub> conversions were higher in temperatures between 200 and 250 °C. In this optimal temperature range, increasing the pressure contributed to higher methanol production. Increasing H<sub>2</sub>/CO<sub>2</sub> ratio favored CO<sub>2</sub> conversion, achieving an average for both models of 44% with a ratio of 8:1. However, a ratio of 3:1 for the Graaf model and 2:1 for the BF model resulted in maximum methanol production. Finally, increasing the CO concentration raised the obtained methanol concentration but resulted in lower carbon dioxide conversion.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100518"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079381","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-01-14DOI: 10.1016/j.nxener.2025.100509
Nadjia Khatir , Safia Nait-Bahloul
{"title":"Evidential multi-model CNN integration for visual fault detection in solar panels","authors":"Nadjia Khatir , Safia Nait-Bahloul","doi":"10.1016/j.nxener.2025.100509","DOIUrl":"10.1016/j.nxener.2025.100509","url":null,"abstract":"<div><div>This study proposes an evidential fusion framework for classifying visual defects in solar panels using convolutional neural networks (CNNs) and Dempster-Shafer theory (DST). Three pretrained CNN models: ResNet50, MobileNetV2, and EfficientNetB0 are fine-tuned to detect multiple defect types, and their outputs are fused at the logit level using DST. Unlike conventional ensemble strategies such as majority voting, the proposed method explicitly accounts for uncertainty and conflict among predictions by assigning belief masses to sets of hypotheses. Experimental evaluations conducted on a multiclass solar panel dataset demonstrate that DST fusion consistently outperforms individual models and majority voting across all macro-averaged metrics, particularly in underrepresented or visually ambiguous classes such as <em>Physical-Damage</em> and <em>Dusty</em>. These findings underscore the potential of uncertainty-sensitive model fusion to enhance the robustness and interpretability of automated photovoltaic inspection systems.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100509"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981498","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-04-08DOI: 10.1016/j.nxener.2026.100610
Valerie Ziemsky , Simon Pichlmaier , Markus Gyetko
{"title":"Bridging the financial gap: Analysis of parity prices and policy instruments for green hydrogen applications in hard-to-abate sectors in Germany","authors":"Valerie Ziemsky , Simon Pichlmaier , Markus Gyetko","doi":"10.1016/j.nxener.2026.100610","DOIUrl":"10.1016/j.nxener.2026.100610","url":null,"abstract":"<div><div>Green hydrogen technologies are crucial for decarbonizing hard-to-abate sectors in Germany. This paper applies a cost-based analytical framework to quantify financial gaps between projected green hydrogen supply costs and sector-specific parity prices through 2050 in 6 key applications (chemical industry, primary steel, reconversion, heavy-duty transport, shipping, aviation) and assesses the implications for policy support instruments. Key findings include: (1) Power purchase agreement (PPA) based green hydrogen costs depend on renewable energy market trends, grid fee exemptions, and free emission allowance allocations for electrolyzers; (2) Only the heavy-duty transportation and shipping sectors achieve cost parity with PPA-based hydrogen by 2050; (3) The chemical industry and aviation sector are highly sensitive to green hydrogen costs and regulatory changes, resulting in conditional technology shifts depending on hydrogen sourcing; (4) Closing the remaining financial gaps will require supply-side subsidies, as CO<sub>2</sub> price increases alone are insufficient. Policymakers should implement sector-specific support mechanisms for green hydrogen technologies, considering the varying effectiveness of CO<sub>2</sub> pricing and the different cost structures across technologies.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100610"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147709906","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-01-29DOI: 10.1016/j.nxener.2026.100517
Umang Bedi
{"title":"Recent advances in fuel cell design and modeling: A comprehensive review","authors":"Umang Bedi","doi":"10.1016/j.nxener.2026.100517","DOIUrl":"10.1016/j.nxener.2026.100517","url":null,"abstract":"<div><div>Fuel cells are gaining popularity as sustainable alternatives to traditional energy sources due to their low environmental impact and high efficiency. Among these, direct alcohol fuel cells, proton exchange membrane fuel cells, and solid oxide fuel cells are highly promising. Fuel cells convert fuels, such as alcohols and hydrogen, into electricity with considerably higher efficiency than combustion engines, producing only water as the primary by-product. This clean energy pathway supports the United Nations Sustainable Development Goal (SDG) 7 (Affordable and Clean Energy) and advances SDG 13 (Climate Action) by reducing greenhouse gas emissions and dependency on fossil fuels. However, significant challenges remain before widespread implementation of fuel cells, including financial feasibility, long-term reliability, and scalability. Therefore, this review aims to address the existing gap in understanding how recent modeling and design advancements can overcome these limitations across different types of fuel cells. This review provides a comprehensive and current synthesis of recent fuel cell modeling and design, uniquely integrating bibliometric trends, experimental advances, and computational methods across all major types of fuel cells. Emphasis is placed on numerical optimization strategies, advancements in multi-physics simulations, sustainable material innovations, and emerging approaches such as artificial intelligence-assisted modeling and integrated multi-scale frameworks. The review offers a cross-disciplinary roadmap to improve the performance, durability, and commercial viability of next-generation fuel cell technologies.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100517"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079396","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":"Standalone DC microgrids: Planning, operation and uncertainty management","authors":"Hasith Jayasinghe , Kosala Gunawardane , Md. Alamgir Hossain , Ramon Zamora","doi":"10.1016/j.nxener.2026.100511","DOIUrl":"10.1016/j.nxener.2026.100511","url":null,"abstract":"<div><div>Standalone power systems in remote areas have traditionally relied on continuously operating fossil fuel generators, leading to high operational costs, reduced efficiency, and substantial carbon emissions. Standalone direct current (DC) microgrids have emerged as a promising alternative due to their lower conversion losses, improved integration of renewable energy sources (RES), and enhanced compatibility with modern DC-native loads and storage technologies. Despite these advantages, the planning, operation, and uncertainty management of standalone DC microgrids remain technically challenging. Intermittent RES generation, stochastic load behaviour, lack of mature standards, and complex control requirements introduce significant design and operational challenges. While numerous studies have proposed methods to address issues in sizing, optimisation, control, energy management, and uncertainty management, a comprehensive and structured review that connects these aspects across the full lifecycle of DC microgrid development is still lacking. This article addresses this gap by providing a systematic review of the state-of-the-art in planning methodologies, operational strategies, and uncertainty management techniques for standalone DC microgrids. The review synthesises theoretical frameworks and practical implementations, critically evaluates existing approaches by identifying their strengths and limitations, and highlights the interdependencies among planning, real-time operation, and uncertainty mitigation. Finally, the article outlines key research challenges and future opportunities to support the reliable, cost-effective, and sustainable deployment of standalone DC microgrids. The novelty of this study lies in its integrated perspective spanning planning, operational control, and uncertainty management, offering valuable guidance for researchers, system designers, and practitioners.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100511"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039417","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":"Decarbonization of iron and steel industries: A review of computational advancements to enhance furnace energy efficiency in the BF-BOF route","authors":"Pratibha Biswal , Jetnis Avdijaj , Alessandro Parente , Axel Coussement","doi":"10.1016/j.nxener.2026.100578","DOIUrl":"10.1016/j.nxener.2026.100578","url":null,"abstract":"<div><div>The iron and steel industry remains heavily reliant on fossil fuels for high-temperature operations and chemical reduction processes. Especially in the blast furnace-basic oxygen furnace (BF-BOF) route, which accounts for almost 70% of steel production, decarbonization remains an urgent challenge. This review comprehensively explores decarbonization strategies, focused on computational modeling approaches within three major furnaces in BF-BOF steelmaking: blast furnace (BF), basic oxygen furnace (BOF), and reheating furnace (RF). BF is a major emission-heavy unit where hydrogen injection can cut BF emissions by up to 55%, while biomass injection can achieve up to 40% reductions under optimized conditions. In BOF operations, multiphase jet-bath interactions dominate the decarburization and refining processes. RFs represent a significant energy sink due to intense thermal loads. Regenerative RF systems can deliver up to 20% fuel savings, while fuel-oxygen enrichment can reduce energy use by up to 26%. Across all furnace systems, decarbonization efforts have been increasingly relying on computational modeling for process optimization. Challenges remain in scaling high-fidelity models and integrating them with plant-level data. Future research should focus on advanced multiphysics modeling that can play a crucial role in this decarbonization effort through material flow optimization and heat and mass transfer enhancement. Further priorities include process integration for carbon capture and storage systems and digital twin development for real-time optimization of material and energy flows.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100578"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612444","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}
Next EnergyPub Date : 2026-04-01Epub Date: 2026-01-13DOI: 10.1016/j.nxener.2025.100505
Tekalign Aregu Tikish , Yared Worku , Nithyadharseni Palaniyandy , Eno E. Ebenso
{"title":"Recent advances in bimetallic-cobalt oxides and their composites as a potential candidate for supercapacitor electrode material","authors":"Tekalign Aregu Tikish , Yared Worku , Nithyadharseni Palaniyandy , Eno E. Ebenso","doi":"10.1016/j.nxener.2025.100505","DOIUrl":"10.1016/j.nxener.2025.100505","url":null,"abstract":"<div><div>The growing demand for green energy has made energy storage crucial in energy generation systems. Supercapacitors (SCs) are gaining popularity in energy storage due to their high-power density and long cycle life. Bimetallic cobalt oxides (MCo<sub>2</sub>O<sub>4</sub>) are promising electrode materials due to their enhanced electrochemical performance and synergistic effects. This review provides a unique and exclusive focus on the recent 5-year progress (2020–2025) in MCo<sub>2</sub>O<sub>4</sub> materials for SC applications. It provides a detailed analysis of various synthesis processes, the relationship between crystal structure (particularly the stable spinel structure) and electrochemical activity, the inherent battery-like charge storage mechanism of cobalt oxides, and a comparative performance evaluation. It also analyzes the electrolyte in Bimetallic Metal Oxides and their composites. The review highlights the strategic inclusion of a secondary metal (M = Ni, Cu, Fe, Mn, Zn) into cobalt oxide, which enhances key metrics, including specific capacitance, rate capability, and cyclic stability. Furthermore, this review demonstrated the strategies for improving overall SC performance through composite formation with conductive additives (carbon materials, metal oxides, conducting polymers, and MOFs). Lastly, the review concludes by summarizing the advanced and outlining crucial future research pathways to guide the development of superior bimetallic cobalt oxide-based SCs.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"11 ","pages":"Article 100505"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145950282","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}