Applied Energy最新文献

{"title":"Transformer-enhanced multi-agent reinforcement learning for dynamic electric logistics Fleet routing under time-varying traffic","authors":"Wei Liu ,&nbsp;Youqi Wang ,&nbsp;Bingbing Li ,&nbsp;Yixun Wen ,&nbsp;Hao Zhang ,&nbsp;Weichao Zhuang ,&nbsp;Guodong Yin ,&nbsp;Boli Chen","doi":"10.1016/j.apenergy.2026.127612","DOIUrl":"10.1016/j.apenergy.2026.127612","url":null,"abstract":"<div><div>This paper proposes a Transformer-Enhanced Multi-Agent Reinforcement Learning (TE-MARL) framework for electric logistics fleet routing under time-varying traffic and coupled power-grid loads, with the goal of minimizing overall operating cost. First, we develop a linear congestion model with a 30-min smooth transition to approximate the continuous dynamics of traffic flows. In parallel, we establish an energy consumption–charging coupling model that captures the effects of congestion, speed, specific energy consumption, and peak–valley grid-load fluctuations on charging efficiency. Next, we design a three-module Transformer-based policy network that incorporates traffic-aware attention to strengthen the representation of congestion features. The framework employs centralized training with decentralized execution (CTDE) and Proximal Policy Optimization (PPO) to enhance generalization and stability in highly dynamic environments. Beyond conventional objectives such as minimizing travel time and energy consumption, we introduce a Traffic Adaptability Cost metric to quantify the robustness of routing solutions to traffic fluctuations. Extensive experiments under high station density and multi-vehicle coordination compare TE-MARL with state-of-the-art learning-based and heuristic baselines. The results indicate that, on a representative C100-S20-V8 instance, TE-MARL reduces total travel time and total energy consumption by 20.4% and 17.6% relative to a MARL baseline, and by 14.9% and 10.9% relative to a hybrid Q-DH method, while achieving 100% feasibility and higher traffic adaptability. These gains substantially mitigate the risks of peak-hour time-window violations and excessive energy use.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127612"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical insights into the interplay between mass transport and parasitic hydrogen evolution in vanadium redox flow batteries","authors":"Haoyao Rao ,&nbsp;Fan Yang ,&nbsp;Lyuming Pan ,&nbsp;Meisheng Han ,&nbsp;Jing Sun ,&nbsp;Jiayou Ren ,&nbsp;Honghao Qi ,&nbsp;Xiaoqian Xu ,&nbsp;Yubai Li ,&nbsp;Puiki Leung ,&nbsp;Qinping Jian ,&nbsp;Lei Wei ,&nbsp;Tianshou Zhao","doi":"10.1016/j.apenergy.2026.127565","DOIUrl":"10.1016/j.apenergy.2026.127565","url":null,"abstract":"<div><div>Efforts to increase power density, primarily motivated by the need to reduce capital cost, have become a central focus in research on redox flow batteries (RFBs). However, the increase in power density intensifies the parasitic hydrogen evolution reaction (HER) at the negative electrode, posing a significant operational challenge for RFBs. Conventional engineering countermeasures frequently involve lowering the charging cut-off voltage to mitigate HER. However, this approach reduces electrolyte utilization, ultimately leading to increased electrolyte costs. To enable more rigorous control strategies and elucidate the mechanistic basis of hydrogen evolution, a three-dimensional model incorporating HER phenomena in vanadium RFBs is developed in this work. The numerical simulation and accompanying experiments indicate that HER displays pronounced spatial heterogeneity across the porous electrode, producing hotspots for gas formation and accumulation, where active-species concentrations are low and under-rib convection is weak. Enhancing mass transport and improving the uniformity of active-species distribution are shown to substantially mitigate HER. We find that increasing the electrolyte flow rate from 1 to 11 mL min⁻¹ cm⁻² reduced the hydrogen gas fraction within the electrode from ∼1.2% to ∼0.4% while raising state of charge (SOC) from 0.8 to 0.9, a strategy that suggests simultaneous improvement of SOC and suppression of the HER side reaction is achievable, but this method incurs higher pumping losses. Moreover, HER is sensitive to other operating conditions (e.g., current density and cut-off voltage), which similarly imply trade-offs between instantaneous power density, electrolyte utilization, and parasitic losses. Collectively, the model and supporting experiments provide mechanistic insight into HER behavior during RFB operation, offering guidance to mitigate these trade-offs and minimize parasitic reactions, thereby enhancing overall system efficiency and durability.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127565"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordination of community energy storage system and prosumers for FCAS via battery modular management and capacity rental","authors":"Mingyang Sun ,&nbsp;Cuo Zhang ,&nbsp;Jing Qiu ,&nbsp;Gang Lei ,&nbsp;Xin Lu ,&nbsp;Jianguo Zhu","doi":"10.1016/j.apenergy.2026.127553","DOIUrl":"10.1016/j.apenergy.2026.127553","url":null,"abstract":"<div><div>Due to their superior rapid response capabilities, community energy storage systems (CESS) can readily secure bids for frequency control ancillary services (FCAS). However, insufficient attention has been paid to the constrained integration of CESS and prosumers for FCAS, particularly to ensure the safe operation of CESS. This paper proposes a coordination framework based on a battery modular energy management model for CESS and prosumers within a community. The battery module's lifespan is considered and extended by regulating the depth-of-discharge range for each CESS module. Leveraging the CESS capacity rental can ensure uninterrupted FCAS performance, even in the presence of severe CESS module degradation and substantial frequency deviations. The coordination framework can foster additional arbitrage opportunities for prosumers. The effectiveness of the proposed coordination framework for CESS and prosumers, as well as the capacity rental model, is validated through simulations on a modified IEEE 39-bus system in various CESS states. A rolling quota allocation algorithm is proposed to dynamically adjust the participation quotas of residential and industrial prosumers based on their activity levels, thereby establishing a differentiated allocation mechanism that effectively addresses the limitations of traditional static schemes in adapting to changes in prosumer behavior. The simulation results show that the proposed method can effectively mitigate CESS degradation and enhance profitability for proactive prosumers and CESS.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127553"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aboveground seasonal energy storage: comparative analysis of hydrogen and its derivatives","authors":"F.B. Bozzolo Lueckel ,&nbsp;M.Á. Lynch ,&nbsp;R.F.D Monaghan","doi":"10.1016/j.apenergy.2026.127545","DOIUrl":"10.1016/j.apenergy.2026.127545","url":null,"abstract":"<div><div>Seasonal energy storage is key to the future of fully decarbonised energy systems. Geological features capable of storing hydrogen at low costs are not universally available, and solutions to store renewable energy above ground will be required. In this study, an isolated energy hub investment optimisation model is developed with a constant demand centre of 100 MW, and different aboveground seasonal energy storage solutions are evaluated with different minimum load operation levels. In addition, the effects of different temporal optimisation resolutions and optimisation windows are evaluated. The results show that the current utility-scale lithium-ion battery system performs poorly in techno-economic terms at the seasonal storage level. Similarly, compressed hydrogen tanks are among the least competitive options. In contrast, ammonia and methanol are the most cost-effective solutions for new development sites reaching break-even electricity selling prices of 116€/MWh. However, for power generation sites with existing infrastructure like gas turbines, storage and pipelines, Fischer-Tropsch fuels become the most competitive option. Process capacity flexibility is also studied, and it is shown that it significantly decreases the costs. For these evaluated processes to reach commerciality, developing flexible production processes is crucial and should be prioritised. Finally, it is shown that seasonal storage investment is lower when lower temporal optimisation resolutions are used and increased when longer optimisation windows are considered.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127545"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MP-Grid: Detecting power grid outages with topological machine learning","authors":"Md Joshem Uddin ,&nbsp;Damilola R. Olojede ,&nbsp;Roshni Anna Jacob ,&nbsp;Baris Coskunuzer ,&nbsp;Jie Zhang","doi":"10.1016/j.apenergy.2026.127501","DOIUrl":"10.1016/j.apenergy.2026.127501","url":null,"abstract":"<div><div>A resilient power network is the cornerstone of a secure and economically stable society. With the frequency of power network outages rising due to extreme weather events and cyber-physical attacks, it has become imperative to detect these occurrences in the power grid promptly. To address this, we propose a novel approach for outage detection and resilience improvement of power distribution networks, leveraging the latest tools of topological data analysis which is an emerging direction in graph representation learning. Specifically, we introduce multiparameter persistent homology to smart grids, which enables capturing the finer topological patterns within the network through the utilization of multiple user-defined functions (such as bus voltage and branch currents). By using bus voltages and branch flows as filtration functions, the multiparameter persistent homology summaries capture how outages fragment the grid into disconnected regions, linking topological signatures directly to physical state changes. Our model demonstrates superior performance when compared to existing methods, with an average improvement of 2.66%, 3.73%, and 6.34% over ten other baseline models for the IEEE 37-bus, IEEE 123-bus, and 342-node LVN networks, respectively. The efficacy of our proposed topological machine learning model is also validated across large-sized realistic networks such as the IEEE 8500 bus and NREL’s synthetic San Francisco Bay Area networks. The computational efficiency and scalability exhibited by the proposed model underscore its practical utility and effectiveness in real-time detection capability.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127501"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated spatiotemporal techno-economic assessment of offshore renewable energy complementarity: A case study in China's maritime zones","authors":"Wenjie Du ,&nbsp;Guotian Cai ,&nbsp;Jixiang Zhang ,&nbsp;Yaodong Li ,&nbsp;Zhou Zhou ,&nbsp;Xiaoyu Chen ,&nbsp;Shuai Nie","doi":"10.1016/j.apenergy.2026.127513","DOIUrl":"10.1016/j.apenergy.2026.127513","url":null,"abstract":"<div><div>Offshore wind/solar/wave complementarity can unlock large scale renewable potential, yet spatial potential, temporal stability and techno-economic performance are rarely evaluated together. This paper develops a grid-level spatiotemporal techno-economic framework combining spatial suitability screening, hourly simulations, multi-indicator stability optimization and lifecycle cost evaluation. Under future floating deployment, wind-wave and wind-solar hybrids use about 69% and 31% of wind-suitable waters but deliver 98% and 73% of wind-only electricity, respectively, markedly increasing generation per unit area. Stability-optimized wind-solar reduces offshore wind variability(<em>CV</em>/<em>FR</em>) and intermittency(<em>ZS</em>), whereas wind-wave delivers even stronger <em>FR</em> and <em>ZS</em> reductions but slightly increases <em>CV</em>, with smaller generation losses (12% versus 35% for wind-solar). Techno-economic results show that wind-solar hybrids achieve the lowest LCOE, falling to 43 €/MWh (aggressive case) by 2050, while wind-wave remains about two to three times higher. Relative to wind plus storage reference, wind-solar complementarity reduces lifecycle cost by around 83% across suitable maritime zones, whereas cost reductions for wind-wave occur mainly in southern offshore regions, indicating that temporal complementarity can economically substitute most of the storage required for output smoothing. Technology progress reduces LCOE by only 0.7% for wind-solar but by 40% for wind-wave, lowering the aggressive wind-wave median to about 56 €/MWh and allowing wind-wave to outperform wind-solar in parts of sea. Overall, a cost-effective nearshore belt is dominated by wind-solar hybrids, while wind-wave becomes increasingly attractive in deeper southern offshore waters as technology advances. These findings support wind-based complementary development pathways, clarify spatiotemporal trade-offs and monsoon-driven complementarity mechanisms in China's offshore regions, and offer insights that are relevant to region-specific coastal energy transition strategies, with a framework transferable to other marine regions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127513"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large language model-enhanced home energy management with dynamic user preference elicitation and hierarchical data-sharing","authors":"Xunning Zhang ,&nbsp;Yuheng Cheng ,&nbsp;Xuanang Gui ,&nbsp;Huan Zhao ,&nbsp;Junhua Zhao ,&nbsp;Jinyue Yan","doi":"10.1016/j.apenergy.2026.127540","DOIUrl":"10.1016/j.apenergy.2026.127540","url":null,"abstract":"<div><div>The residential sector has received great attention worldwide due to its significant contribution to energy consumption and carbon emissions. Although Deep Reinforcement Learning (DRL) based Home Energy Management (HEM) has provided promising solutions for user comfort satisfaction and energy savings, existing approaches still face three challenges: (1) accurately perceiving dynamic user preferences, (2) efficient learning with limited data samples, and (3) protecting user privacy during data sharing. To address these issues, a Large Language Model (LLM)-enhanced HEM with dynamic user preference elicitation and hierarchical data-sharing is proposed, introducing three key innovations. First, the Knowledge-Guided Chain-of-Thought method is proposed to perceive dynamic user preferences from unconstrained natural language interactions, by leveraging users’ historical knowledge as explicit guidance. Second, the LLM-generated reference actions based on shared knowledge and preference descriptions are proposed to accelerate the learning process under conditions of cold-start situations. Third, a hierarchical data-sharing mechanism integrated with LLM-based knowledge extraction is introduced to enable effective knowledge inference from natural language while preserving user privacy. Simulation results in the household scenario with dynamic user preferences demonstrate that the proposed framework achieves significant improvements in both user preference elicitation and learning efficiency, ultimately leading to a 28.8% reduction in cost and a 9.3% improvement in comfort compared to fixed preference DRL methods.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127540"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multistage coordinated planning approach for RES-rich microgrids incorporating flexible power balancing unit, V2G scheduling, and hydrogen storage systems","authors":"Hossam H.H. Mousa ,&nbsp;Matti Lehtonen ,&nbsp;Karar Mahmoud","doi":"10.1016/j.apenergy.2026.127500","DOIUrl":"10.1016/j.apenergy.2026.127500","url":null,"abstract":"<div><div>The growing integration of renewable energy sources (RESs) introduces substantial operational challenges, particularly voltage and current unbalance in unbalanced microgrids. This highlights the need for effective compensation strategies, plug-in electric vehicles (PEVs) with vehicle-to-grid (V2G) services, and robust demand response (RDR) programs to mitigate unbalance and boost the hosting capacity (HC) of RES-rich microgrids incorporating hydrogen storage systems (HSSs). Accordingly, this study proposes an innovative compensation strategy employing a flexible power balancing unit (Flex-PBU) that is equipped for independently injecting/absorbing active and reactive power per phase. Smart inverters integrated with RESs provide localized voltage regulation. Moreover, a smart PEV scheduling model featuring V2G services at parking lots is developed, considering energy cost, battery degradation, and an incentive mechanism. This model dynamically aligns charging/discharging activities with forecasted RES availability, demand, battery health, and electricity prices. In addition, an RDR program is proposed to optimally adjust load profiles in response to renewable generation forecasts and price signals by integrating two new adaptive indicators into a unified control framework. To coordinate these technologies, a two-stage planning approach is adopted: in the first stage, the operation of Flex-PBUs, PEVs, and the RDR program is optimized; in the second stage, a multi-objective planning optimization determines the optimal allocation of RESs and seasonal HSSs to minimize voltage and current unbalance, alleviate line congestion, and maximize HC. Simulation results confirm the superiority of the proposed approach, maintaining power quality within standards while achieving a 190% improvement in RES penetration and an 5% reduction in line congestion.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127500"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146154247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and tackling unit commitment constraint screening under uncertainty","authors":"Xuan He ,&nbsp;Honglin Wen ,&nbsp;Yufan Zhang ,&nbsp;Yize Chen ,&nbsp;Danny H.K. Tsang","doi":"10.1016/j.apenergy.2026.127582","DOIUrl":"10.1016/j.apenergy.2026.127582","url":null,"abstract":"<div><div>Day-ahead unit commitment (UC) is a fundamental task for power system operators, where generator statuses and power dispatch are determined based on the forecasted nodal net demands. The errors inherent in renewables and load forecasting require uncertainty-aware UC solution procedures, which are nontrivial and time-consuming to solve. In this work, we design a novel screening approach under the forecasting uncertainty to achieve both computation efficiency and solution reliability requirements. Our approach accommodates such uncertainties in both chance-constrained (CC) and robust forms (RO), and can greatly reduce the UC instance size by screening out non-binding constraints. To further improve the screening efficiency, we build upon multi-parametric programming (MPP) theory to convert the underlying screening optimization problem into a piecewise affine function. A multi-area screening approach is further developed to handle the computational intractability issues for large-scale problems. We verify the proposed method’s performance on various UC setups and uncertainty situations. Experimental results show that our robust screening procedure can guarantee better feasibility, while the CC screening can produce more efficient reduced models. On average, the screening time for a single line flow constraint can be accelerated by 71.2X to 131.3X using our proposed method.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127582"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sector coupling reimagined: Synthesizing fragmented perspectives into a unified framework","authors":"Nishant Tyagi ,&nbsp;Alexander Roth ,&nbsp;Anibal Sanjab ,&nbsp;Erik Delarue","doi":"10.1016/j.apenergy.2026.127550","DOIUrl":"10.1016/j.apenergy.2026.127550","url":null,"abstract":"<div><div>Sector coupling (SC), the integration of energy vectors and end-use sectors, is increasingly central to the net-zero transition but remains conceptually fragmented. This fragmentation causes modeling inconsistencies, hinders cross-study comparison, and undermines energy policy coordination. We address this gap through a structured mapping of existing definitions, categorizing them along three dimensions, namely, structural, functional, and electricity-centric, and analyzing their limitations. Drawing on these insights, we propose a coherent definition that captures SC in its full diversity and complexity: SC is the establishment of physical or non-physical interconnections, in any direction, among energy-carrying vectors, among energy-consuming end-use sectors, between vectors and sectors, and within the layers that link them (energy processing, transfer, markets, and policy). This framing clarifies what constitutes a “sector”, distinguishes “sector coupling” from related concepts such as “flexibility”, and encompasses the entire spectrum of interlinkages in a sector-coupled energy system. Building on this definition, we organize the SC interlinkages into six categories based on their driving mechanisms: vector coupling, end-use sector coupling, vector-shift coupling, network coupling, market coupling, and policy coupling. Together, our definition and classification provide a shared conceptual foundation for the SC field. The framework’s modular architecture enables extension to new end-use sectors, non-energy material flows, and material-energy circularity pathways. It can enable modelers to avoid unintentional mismatches in model scopes, standardize SC implementation in models, and trace cascading, system-wide interactions. It can also support policymakers in designing structured scenarios, identifying which SC pathway works best in specific settings, and coordinating cross-sector cross-vector policies. By synthesizing fragmented concepts into a coherent and comprehensive whole, this work advances the theory of the SC domain.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127550"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}