Applied Energy最新文献

{"title":"Reinforcement learning algorithms in AC, DC, and hybrid microgrids applications: A comprehensive review","authors":"M. Nasir ,&nbsp;R.C. Bansal ,&nbsp;M. Saloumi","doi":"10.1016/j.apenergy.2025.126724","DOIUrl":"10.1016/j.apenergy.2025.126724","url":null,"abstract":"<div><div>Over the past few years, the adoption of modern and intelligent energy systems, such as smart grids, microgrids, and smart buildings, has significantly increased. This surge in adoption is attributed to their advanced features, including bidirectional power flows, sophisticated metering systems, and the efficient integration of renewable energy resources. Despite the benefits, the growing adoption of these systems introduces new challenges in various aspects of power system management, particularly in operation and control. Additionally, the employment of advanced sensors and intelligent meters generates vast amounts of data, paving the way for innovative, data-driven approaches to tackle complex operational and control challenges. Among these strategies, Reinforcement Learning (RL) has emerged as a preferred technique for its applications in Energy Management System (EMS), addressing optimization challenges, controlling power flow, and beyond. This review paper provides a comprehensive analysis of RL in the context of microgrid systems. It explores RL’s fundamental principles, classifies the major algorithm types, and evaluates their applications across diverse microgrid architectures. Moreover, the paper critically examines the challenges associated with applying RL in microgrid systems and identifies promising avenues for future research, emphasizing both the limitations of current approaches and the domains that demand further investigation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126724"},"PeriodicalIF":11.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216547","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":"Hydrogen supply chains: modeling challenges and sustainability gaps","authors":"V.E.S.F. Oliveira ,&nbsp;B.B.T. do Carmo ,&nbsp;F.F. da Costa Fontes","doi":"10.1016/j.apenergy.2025.126827","DOIUrl":"10.1016/j.apenergy.2025.126827","url":null,"abstract":"<div><div>Amid global efforts to decarbonize energy systems, hydrogen has emerged as a key solution for the transition to clean energy. However, the design of hydrogen supply chains (HSCs) remains a complex challenge, particularly in integrating sustainability pillars into strategic planning. Although several studies have proposed mathematical models for HSCs, few have critically examined how these models address together environmental, economic, and social dimensions. This study fills that gap by conducting a systematic literature review focusing on optimization approaches applied to HSC design, with a special emphasis on sustainability integration. Using the PRISMA methodology, a curated selection of 42 interconnected articles was analyzed in three stages: characterization of the literature, classification of modeling approaches, and systematization of future research perspectives. As its main contributions, this review reveals that most models emphasize economic and environmental objectives, whereas social aspects and life cycle considerations remain underexplored; highlights the limited incorporation of uncertainty modeling and policy instruments in existing frameworks; identifies key methodological advances; maps emerging research trends; and offers a structured agenda for future studies, emphasizing the need for more holistic, resilient, and inclusive approaches in HSC design.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126827"},"PeriodicalIF":11.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216544","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":"Hydrolysis of Al for hydrogen production: A joint experimental and first-principles density functional theory investigation","authors":"Rasiha Nefise Mutlu ,&nbsp;Esra Eroglu ,&nbsp;Hande Ustunel ,&nbsp;Daniele Toffoli ,&nbsp;Jayaraman Kandasamy ,&nbsp;Mehmet Karaca ,&nbsp;Iskender Gokalp","doi":"10.1016/j.apenergy.2025.126814","DOIUrl":"10.1016/j.apenergy.2025.126814","url":null,"abstract":"<div><div>Efficient and environmentally friendly H₂ production is one of the most pressing challenges that face modern energy science. Hydrolysis of water over metals is used as an affordable and sustainable method for H₂ production. Due to its abundance, low cost, and low toxicity, aluminum (Al) is a promising candidate material to be used for water dissociation. In this work, we investigate using impedance measurements, XRD, SEM, and hydrogen volume measurement methods, the H₂ evolution reactions from Al wires and Al powder in a NaOH solution. The experimental results are interpreted with the help of first-principles density functional theory (DFT) calculations. Our results shed light on several important aspects of the reaction's mechanism, such as the removal of the native oxide and the evolution of the surface morphology. We computationally design a six-step reaction mechanism that describes the erosion of the surface and release of Al(OH)₄ ⁻. Our results indicate that the reaction proceeds with low activation barriers at the initial stages, but these barriers increase as more H₂O molecules adsorb and dissociate on the surface. We observe that factors controlling the rate-determining step, and the computed activation barrier, compare well with the experimentally derived values.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126814"},"PeriodicalIF":11.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216522","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":"Dust aerosol effects on decentralized solar: A cause of systematic undersizing of solar panels in West Africa","authors":"Stewart A. Isaacs ,&nbsp;Olga Kalashnikova ,&nbsp;Michael J. Garay ,&nbsp;Aaron van Donkelaar ,&nbsp;Melanie Hammer ,&nbsp;Danielle R. Wood ,&nbsp;Wesley L. Harris","doi":"10.1016/j.apenergy.2025.126756","DOIUrl":"10.1016/j.apenergy.2025.126756","url":null,"abstract":"<div><div>Decentralized solar is an emerging strategy for advancing modern energy access among rural populations globally. However, both natural and anthropogenic aerosols can significantly worsen solar panel performance. Although the effect of aerosols is typically assessed using satellite or reanalysis data during system sizing, these datasets often underestimate extreme aerosol conditions in West Africa.</div><div>This study evaluates the impact of aerosols on photovoltaic (PV) output by developing irradiance and generation models that accept as input three reanalysis and satellite-derived datasets with varying spatial and temporal resolution. The accuracy of each dataset is evaluated through comparisons to ground-based AERONET measurements. We find none of the aerosol datasets capture the highest aerosol loadings well, underestimating the 99th percentile aerosol optical depth (AOD) values between 18–49 %, which can lead to undersizing PV systems by up to 11 % for high-reliability designs.</div><div>To capture total regional dust impacts, we combine dust aerosol with dust soiling loss modeling. Modeled irradiance shows that daily energy losses during the annual Harmattan dry season can reach 50 %, and seasonal energy losses caused by dust can be between 19–40 %. In locations within the Sahel, soiling dominates dust-associated losses (62–66 % of total losses), while for coastal locations near the Gulf of Guinea, dust aerosols drive losses (56 %).</div><div>These findings highlight the need for location-specific mitigation strategies to effectively address PV dust losses. The modeling framework developed in this study can be used to improve the siting, sizing and maintenance strategies for PV systems in dry regions worldwide.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126756"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145154390","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":"End-effect mitigation in renewable energy systems with energy storage using value function approximation of terminal energy level","authors":"Dongho Han,&nbsp;Seongmin Heo","doi":"10.1016/j.apenergy.2025.126785","DOIUrl":"10.1016/j.apenergy.2025.126785","url":null,"abstract":"<div><div>The growing integration of renewable energy sources into power systems introduces operational challenges due to their inherent uncertainty and intermittency. In particular, the end-effect remains a critical barrier to realistic long-term scheduling, where energy storage system (ESS) tends to be completely discharged near the end of the planning horizon. To address this, we propose a novel terminal energy valuation method for ESSs within a two-stage stochastic programming (2SSP) framework, integrating reinforcement learning (RL) with value function approximation. By formulating system operations as a Markov decision process, our method iteratively updates the value of the terminal energy level in ESS using the value iteration algorithm. We first employ a linear value function approximator and then enhance performance using a neural network-based approximator. Comparative experiments demonstrate that our RL-based 2SSP significantly improves long-term profits, effectively mitigates the end-effect, and outperforms existing approaches such as fixed terminal constraints, rolling horizon frameworks, and static terminal energy valuations.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126785"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216528","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":"Phase change materials for flexible refrigerated warehouses: a multi-level review of material properties, system integration, and control strategies","authors":"Zhuoqun Xing ,&nbsp;Yiqun Pan ,&nbsp;Rongxin Yin ,&nbsp;Xiaolei Yuan ,&nbsp;Yumin Liang ,&nbsp;Xiaoyu Jia ,&nbsp;Zhizhong Huang","doi":"10.1016/j.apenergy.2025.126735","DOIUrl":"10.1016/j.apenergy.2025.126735","url":null,"abstract":"<div><div>With the rapid expansion of refrigerated warehouses (RWs) to meet growing demands for food safety and cold chain logistics, the resulting substantial energy consumption and operation costs have become critical challenges for development. However, current knowledge on the integration of PCMs into RW systems lacks a comprehensive review, leading to gaps in understanding their thermophysical suitability, specific integration configurations, and control coordination mechanisms. This review, consequently, presents a timely and structured multi-level analysis of recent progress in the application of phase change materials (PCMs) to achieve flexible RWs, incorporating the aspects of material properties, system integration, and control strategies. The cutting-edge contributions of this review lie in its holistic perspective, which bridges: (1) the material science view of PCM thermophysical properties and heat transfer enhancement; (2) the thermal engineering perspective of multi-zone load characteristics and refrigeration system advancements in RWs; and (3) the systems control perspective of PCM integration and intelligent control. Persistent challenges such as PCM-refrigeration compatibility, long-term reliability, and demand response implementation highlight the need for future research to advance intelligent, resilient, and grid-interactive refrigerated warehouses, thereby establishing a robust foundation for the sustainable transformation of the cold chain sector.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126735"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145154538","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 analysis on the voltage-mediated flexibility control of a low-voltage DC building energy system","authors":"Zihao Ni ,&nbsp;Wei Tan ,&nbsp;Yi Jiang ,&nbsp;Yi Zhang","doi":"10.1016/j.apenergy.2025.126813","DOIUrl":"10.1016/j.apenergy.2025.126813","url":null,"abstract":"<div><div>The use of direct current (DC) bus voltage as a unified control signal for flexibility control has raised significant attention in low-voltage DC building energy systems, with advantages in coordinating diverse flexible resources for demand response. However, while DC bus signaling simplifies system-wide control, existing research lacks clear transient stability boundaries and dynamic interaction models under high flexible load penetration, leading to risks of voltage instability during load or source fluctuations. To bridge this gap, a simulation model of a flexible low-voltage DC (FLVDC) system is developed in MATLAB/Simulink refined to the device level, where the 750 V high-level bus voltage serves as the sole control signal to regulate device operations. The analysis framework tests stability boundaries and transient responses, including overshoot, and settling time of bus voltage and grid power dynamics under source and load steps. Validation through two real-world scenarios demonstrates that the FLVDC system achieves flexible demand response by adjusting device power consumption based on voltage-mediated control. Key findings show that the small-scale scenario features a broader stable voltage range but inferior transient performance compared to the large-scale one with more sources and loads. Droop control is shown to reduce overshoot and settling time, while rigid control provides a fixed reference value without fluctuation with grid power. Under voltage-mediated control, the FLVDC system can provide 309 W/V grid flexibility in small-scale scenario from 550 V to 1020 V and 2309 W/V in large-scale scenario from 650 V to 825 V. The simulation model can provide building operators with a feasible tool to verify system design and optimize control strategies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126813"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145154541","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":"Review on marine plastic pyrolysis oil: Turning pollution into a maritime fuel","authors":"Sina Keyhani,&nbsp;Matteo Prussi,&nbsp;David Chiaramonti","doi":"10.1016/j.apenergy.2025.126759","DOIUrl":"10.1016/j.apenergy.2025.126759","url":null,"abstract":"<div><div>Marine litter, predominantly plastic waste, represents both an escalating environmental crisis and a potential resource for sustainable fuel production. This review offers the first comprehensive assessment of using marine litter as a feedstock for pyrolysis to generate alternative fuels for the maritime sector. Among various litter types, beach and floating plastics are identified as the most suitable for pyrolysis, given their accessibility and high plastic content, while seafloor litter presents additional collection and pretreatment challenges. Literature indicates that pyrolysis can yield 45 %–60 % oil from plastic-rich waste, requiring minimal upgrading to meet marine fuel standards. The resulting marine plastic-derived pyrolysis oil demonstrates high compatibility with existing maritime infrastructure, allowing for seamless blending with conventional fuels. However, limitations such as restricted production capacity and the fossil origin of plastic suggest that marine plastic-derived pyrolysis oil should be considered a transitional solution. This work uniquely proposes the integration of pyrolysis units within port reception facilities as a strategic and efficient approach to manage marine litter and produce low-carbon maritime fuels. Despite technical and logistical challenges, marine litter pyrolysis shows promising potential as a complementary pathway for both ocean cleanup and low-carbon fuel transition in the maritime sector.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126759"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145154391","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":"DFDR-NLNet: A dual-frequency differentiated representation non-local network for photovoltaic panel segmentation","authors":"Yitong Fu ,&nbsp;Haiyan Li ,&nbsp;Pengfei Yu ,&nbsp;Yaqun Huang ,&nbsp;Wen Zeng","doi":"10.1016/j.apenergy.2025.126761","DOIUrl":"10.1016/j.apenergy.2025.126761","url":null,"abstract":"<div><div>Photovoltaic (PV) technology plays a crucial role in expanding renewable energy globally, yet achieving precise PV panel segmentation to optimize resource allocation and guide installation policy remains a challenge across urban, rural, and industrial environments. To address data diversity limitations, we propose a data augmentation method using a denoising diffusion probabilistic model (DDPM) to generate joint data distributions, enhancing model robustness. Building on this, we introduce a dual-frequency differentiated representation non-local network (DFDR-NLNet) for realistic PV panel segmentation. To enhance the efficiency of global contextual feature extraction in the Transformer branch, we propose a low-frequency representation Transformer that strengthens large-scale semantic modeling through frequency decomposition and preserves crucial positional cues using original phase information. Additionally, a cross-scale alignment module (CSAM) is proposed to facilitate semantic alignment and collaborative learning across different feature levels. To enhance the contribution of edge information in the segmentation process, we design an edge feature awareness module (EFAM) that focuses on high-frequency information. Finally, the correspondence between edge features and decoder representations is modeled to facilitate segmentation in ambiguous regions, via a multi-directional cross attention (MDCA). DFDR-NLNET achieves mIoUs of 83.39 %, 66.14 %, and 91.48 % on PVP-Dataset, BDAPPV, and PV01, outperforming other methods in PV panel localization and edge refinement. Furthermore, the method is used to evaluate the power generation capacity of the Kael Solar Power Plant in Senegal, where the array area is calculated to be 0.25 km², the system size is 38.13 MW, and the annual output power is 63.71 GWh.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126761"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145154536","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":"Advancing microgrid cyber resilience: Fundamentals, trends and case study on data-driven practices","authors":"Subrata K. Sarker ,&nbsp;Hamidreza Shafei ,&nbsp;Li Li ,&nbsp;Ricardo P. Aguilera ,&nbsp;M.J. Hossain ,&nbsp;S.M. Muyeen","doi":"10.1016/j.apenergy.2025.126753","DOIUrl":"10.1016/j.apenergy.2025.126753","url":null,"abstract":"<div><div>Microgrids (MGs) serve as the core components of the upcoming sustainable power systems, and ensuring their security against cyber threats presents a critical research challenge due to the widespread use of advanced energy technologies. This paper explores various strategies for maintaining the cyber-resilient operation of MGs, focusing on technical, economic, and regulatory frameworks, in addition to their operational essentials for seamless functionality. In this paper, cyber-resilient operation refers to the system’s ability to withstand, respond to, and recover from cyber incidents, thereby ensuring the continuous and reliable operation of the MG. An outline of the various security challenges linked to different cyber-attacks and MG frameworks, highlighting the importance of developing effective and adaptable solutions, is also studied in this paper. While model-based approaches offer precise detection accuracy under steady-state conditions, they often struggle in real-time dynamic scenarios due to their complexity and dependence on accurate system modeling. Conversely, data-driven approaches offer enhanced flexibility and adaptability, enabling swift responses to emerging cyber threats. This makes them a compelling alternative to dynamic model-based methods for ensuring cyber-secure operations of MGs. This study focuses on data-driven techniques, acknowledging the comparative strengths and limitations of both paradigms. This paper also outlines crucial steps for crafting scalable and efficient data-driven cyber solutions, highlighting their key characteristics that enhance MG security. It provides a thorough overview of recent data-driven cyber solutions for MGs, offering careful analysis to evaluate the effectiveness of these methods in enhancing security while identifying operational and implementation challenges. A case study on a two-area isolated microgrid is presented, where a data-driven framework optimized by Bayesian learning approximation is examined. This case study demonstrates the capability of the studied data-driven framework in enhancing the resilience of IMGs against cyber threats. Ultimately, the paper concludes with recommendations for the field of data-driven cyber solutions and MGs, aiming to foster further advancements in sustainable and reliable cybersecurity measures for MG frameworks.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126753"},"PeriodicalIF":11.0,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145154394","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}