Applied Energy最新文献

{"title":"Adaptive BIPV shading optimization for electricity generation and building electricity management, sDA, and DGP using multi-objective algorithms","authors":"Sepideh Miraba ,&nbsp;Ali Salehi ,&nbsp;Mohammad Rostamzadeh-Renani ,&nbsp;Reza Ehteshami ,&nbsp;Armin Shahbazi ,&nbsp;Reza Rostamzadeh-Renani ,&nbsp;Seyed Amir Hossein Hashemi Dehkordi ,&nbsp;Mohammadreza Baghoolizadeh","doi":"10.1016/j.apenergy.2025.126860","DOIUrl":"10.1016/j.apenergy.2025.126860","url":null,"abstract":"<div><h3>Background</h3><div>Adaptive Building-Integrated Photovoltaic Shading Systems (BIPVS) offer a promising solution to simultaneously address sustainable energy generation, daylight optimization, and visual comfort in office buildings. However, current studies mostly focus on static or semi-static shading solutions with limited adaptability to real-time solar conditions.</div></div><div><h3>Objective</h3><div>This study proposes a fully adaptive BIPVS shading configuration and evaluates its performance through comprehensive multi-objective optimization, targeting maximum electricity production (EP), minimum electricity consumption (EC), improved spatial daylight autonomy (sDA), and reduced daylight glare probability (DGP) in an office building located in Tehran, Iran.</div></div><div><h3>Methodology</h3><div>EnergyPlus, Radiance, and Python scripting were integrated into a novel simulation-optimization framework. Four advanced multi-objective algorithms (Multi-Objective Grey Wolf Optimizer Algorithm (MOGWO), Multi-Objective Whale Optimization Algorithm (MOWOA), Multi-Objective Ant Colony Optimization Algorithm (MOACO), Multi-Objective Moth Flame Optimization Algorithm (MOMFO)) were applied to optimize design variables, including tilt angle, azimuth angle, shading-to-window distance, window dimensions, and window-to-wall ratio. Performance was evaluated using eight criteria (Generational distance (GD), Inverted generational distance (IGD), Spacing (SP), Maximum Spread (MS), Time (T), Quality (Q), Mean ideal distance (MID), and the number of Pareto front points (NPS)), ranked by Shannon entropy, and the best solution identified by the TOPSIS method.</div></div><div><h3>Results</h3><div>The findings show that adaptive solar shading can boost net electricity generation by over 200 %, achieving up to 6661.11 kWh annually, while reducing building energy consumption by 22.29 % and improving daylight autonomy by 80 %. Additionally, glare probability was significantly reduced, enhancing occupant visual comfort. This research highlights the potential of adaptive BIPVS systems, combined with advanced optimization methods, to significantly improve building energy efficiency and indoor environmental quality, particularly in semi-arid climates.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126860"},"PeriodicalIF":11.0,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265035","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":"Current production routes and life cycle analysis of “Green Energy-Dense Fuels” from biogas: A comprehensive review","authors":"J.K. Ravindran ,&nbsp;D.P. Fagg ,&nbsp;M.C. Coelho","doi":"10.1016/j.apenergy.2025.126832","DOIUrl":"10.1016/j.apenergy.2025.126832","url":null,"abstract":"<div><div>Biogas-derived “green energy-dense” fuels such as biomethane, Fischer-Tropsch (FT) fuels, methanol and dimethyl ether (DME) are promising alternatives to fossil fuels for transport applications. This review provides a technical description of production pathways and a critical analysis of life cycle assessments (LCA) of “green energy-dense” fuels, with a focus on how methodological choices influence results.</div><div>Across the papers analyzed, biomethane outperforms natural gas in environmental impacts. Fuels such as FT-fuels, methanol and DME show mixed results and are pathway dependent. These results are highly sensitive to methodological choices such as functional units (impacts per unit fuel produced, per unit feedstock processed, or per unit transport work), allocation procedures used to distribute impacts among co-products (energy based, mass based, or cost based), and LCIA methodology used (CML, ReCiPe, Traci etc.). Even within ReCiPe, the perspective used (individualist, hierarchist, egalitarian) can significantly impact final results. It can be seen that different methodological choices can lead to up to 50% changes in final results, often leading to contradicting conclusions. System boundaries and scope definitions also contribute to incomparability of results, with many studies stating cradle-to-gate or cradle-to-grave approaches, but leaving out upstream and downstream processes.</div><div>Another key limitation is the emphasis on greenhouse gas emissions, with less focus given to other impact categories such as acidification, eutrophication, resource use, and land use. Emerging technologies such as electrochemical syngas production, waste heat utilization and tail gas reforming and recirculation are underexplored in LCAs. The use of multi-criteria decision analysis (MCDA) along with LCAs will give a broader perspective of these fuels beyond just environmental impacts.</div><div>This review demonstrates that methodological choices in LCA can have a significant impact on the sustainability of “green energy-dense” fuels. There is a requirement to harmonize LCA frameworks and standards as well as a need for more detailed and transparent reporting along with the integration of other tools like MCDA to provide clear results to enable sustainable energy transition.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126832"},"PeriodicalIF":11.0,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265033","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":"Benchmarking thermal energy storage cost for industrial process heat","authors":"Hope M. Wikoff,&nbsp;David Garfield,&nbsp;Shannon Hwang,&nbsp;Macarena Mendez Ribo,&nbsp;Mark Ruth,&nbsp;Samantha B. Reese","doi":"10.1016/j.apenergy.2025.126873","DOIUrl":"10.1016/j.apenergy.2025.126873","url":null,"abstract":"<div><div>Process heat accounts for roughly half of industrial energy demand, and currently 95 % of process heat is derived from the combustion of natural gas, oil, and coal. Electrification of industrial heating could be an alternative, potentially expanding locations suitable for manufacturing; however, industrial facility owners may desire energy storage to stabilize energy costs. In this work, the economic benefits of pairing thermal storage with electrified process heat to reduce the average price paid for energy are analyzed. Cost savings focus on energy arbitrage, or leveraging flexible energy pricing schemes, alone. The cost of natural gas combustion across decades (2019–2060) is compared to the costs of electricity and thermal energy storage in four United States Independent System Operator (ISO) regions. Systems installed today may not yield positive net present value (NPV) compared to the use of natural gas. However, using estimated electricity prices, systems installed in 2030 using arbitrage alone could be profitable when compared to natural gas in some regions of the U.S. Furthermore, if capital expenditures could be reduced by 50 % for sensible thermal storage systems by 2030, profitable systems are found across all regions. This implies that electrification of industrial process heat, when paired with inexpensive thermal energy storage systems, could be less expensive than brownfield natural gas systems, using arbitrage as the only source of revenue and without a dependency on any future policy drivers such as pricing externalities that could further incentivize the electrification of industrial process heat.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126873"},"PeriodicalIF":11.0,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264921","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":"Uncertainty-aware deep learning with physics-informed bayesian sampling for lithium-ion battery prognostics","authors":"Isaiah Oyewole,&nbsp;Wael Hassanieh,&nbsp;Meriam Chelbi,&nbsp;Abdallah Chehade","doi":"10.1016/j.apenergy.2025.126880","DOIUrl":"10.1016/j.apenergy.2025.126880","url":null,"abstract":"<div><div>Accurate state-of-health (SOH) estimation and remaining useful life (RUL) prediction are critical for the reliability, longevity, and safety of lithium-ion battery systems. While data-driven methods have advanced battery prognostics, most struggle with dynamic operating conditions, heterogeneous degradation patterns, and limited ability to provide reliable uncertainty quantification (UQ). To address these challenges, we propose DG-PNUTS, an uncertainty-aware deep learning framework that integrates dual gated recurrent unit (GRU) networks with a physics-informed Bayesian No-U-Turn Sampler (NUTS). NUTS is an adaptive Markov Chain Monte Carlo (MCMC) algorithm that enables principled posterior inference and UQ. The framework employs a divide-and-conquer strategy by training multiple GRUs on subgroups of aged battery data, effectively capturing heterogeneity. For in-service batteries with limited historical data, Bayesian multi-source domain adaptation transfers knowledge from pre-trained models, with the physics-informed NUTS enhancing inference and reliability. A standalone GRU is further utilized for RUL prediction based on the estimated SOH and extracted health indicators. The proposed method was validated on multiple publicly available accelerated aging datasets, demonstrating superior accuracy, robustness across varying operating conditions and chemistries, and reliable UQ compared to benchmark methods. These results highlight the effectiveness of combining deep learning with physics-informed Bayesian MCMC sampling for uncertainty-aware battery prognostics.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126880"},"PeriodicalIF":11.0,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264920","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":"Deep reinforcement learning for HVAC control with nonlinear parametric thermal network modeling for passive building envelopes","authors":"Yu Lu ,&nbsp;Wenqi Wang ,&nbsp;Chuyao Wang ,&nbsp;Ze Li ,&nbsp;Yiying Zhou ,&nbsp;Xu Chen ,&nbsp;Tsz Chung Ho ,&nbsp;Chi Yan Tso","doi":"10.1016/j.apenergy.2025.126863","DOIUrl":"10.1016/j.apenergy.2025.126863","url":null,"abstract":"<div><div>The incorporation of passive cooling envelopes into buildings can effectively reduce energy consumption. However, due to their limited cooling capacity, HVAC systems are still required to maintain indoor thermal comfort. In buildings using passive radiative cooling roofs and thermochromic windows as passive cooling envelopes, inappropriate HVAC control strategies are more likely to occur due to the changeable optical and thermal properties. Such improper HVAC control results in significant waste during system operation, which remains an unsolved problem. Therefore, optimizing HVAC operation in passively cooled buildings is essential not only for ensuring thermal comfort but also for further reducing energy consumption. Achieving both objectives depends on effectively capturing the building's thermal behavior and efficient control methods. To incorporate the thermal behavior of passive cooling envelopes into the HVAC control system, this study first develops a resistance-capacitance thermal network based on a modified matrix to predict the thermal behavior of passively cooled buildings. Then, a model-based policy optimization deep reinforcement learning (DRL) control method is proposed to enhance HVAC system performance in such buildings. The results show that the modified matrix significantly improves the prediction accuracy of the thermal behavior of passively cooled buildings compared to current global identification methods, which increases coefficient of determination from 0.90, 0.73, 0.88 to 0.94, 0.92, 0.95 for radiative cooling roofs, thermochromic windows, and a combination of both envelopes, respectively. Moreover, the proposed DRL control method can reduce building energy consumption by 17.7 % for radiative cooling roofs, 10.6 % for thermochromic windows, and 21.1 % when both strategies are applied simultaneously, compared to the baseline control method. This study provides valuable insights into optimization of HVAC system operations in buildings equipped with passive cooling envelopes.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126863"},"PeriodicalIF":11.0,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265070","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":"Subjective-objective median-based importance technique (SOMIT) to aid multi-criteria renewable energy evaluation","authors":"Ding Ding ,&nbsp;Yang Li ,&nbsp;Poh Ling Neo ,&nbsp;Zhiyuan Wang ,&nbsp;Chongwu Xia","doi":"10.1016/j.apenergy.2025.126872","DOIUrl":"10.1016/j.apenergy.2025.126872","url":null,"abstract":"<div><div>Accelerating the renewable energy transition requires informed decision-making that accounts for the diverse financial, technical, environmental, and social trade-offs across different renewable energy technologies. A critical step in this multi-criteria decision-making (MCDM) process is the determination of appropriate criteria weights. However, deriving these weights often solely involves either subjective assessment from decision-makers or objective weighting methods, each of which has limitations in terms of cognitive burden, potential bias, and insufficient contextual relevance. This study proposes the subjective-objective median-based importance technique (SOMIT), a novel hybrid approach for determining criteria weights in MCDM. By tailoring SOMIT to renewable energy evaluation, the method directly supports applied energy system planning, policy analysis, and technology prioritization under carbon neutrality goals. The practical utility of SOMIT is demonstrated through two MCDM case studies on renewable energy decision-making in India and Saudi Arabia. Using the derived weights from SOMIT, the technique for order preference by similarity to ideal solution (TOPSIS) method ranks the renewable energy alternatives, with solar power achieving the highest performance scores in both cases (e.g., 0.5725 in the India case). The main contributions of this work are five-fold: 1) the proposed SOMIT reduces the number of required subjective comparisons from the conventional quadratic order to a linear order; 2) SOMIT is more robust to outliers in the alternatives-criteria matrix (ACM); 3) SOMIT balances subjective expert knowledge with objective data-driven insights, thereby mitigating bias; 4) SOMIT is inherently modular, allowing both its individual parts and the complete approach to be seamlessly coupled with a wide range of MCDM methods commonly applied in energy systems and policy analysis; 5) a dedicated Python library, pysomit, is developed for SOMIT, providing an accessible and efficient tool to implement SOMIT in practical renewable energy evaluation and decision-support applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126872"},"PeriodicalIF":11.0,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264919","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 microgrids to facilitate the clean energy transition in remote, northern communities","authors":"Ian Maynard ,&nbsp;David MacKay ,&nbsp;Kristen R. Schell ,&nbsp;Ryan Kilpatrick ,&nbsp;Ahmed Abdulla","doi":"10.1016/j.apenergy.2025.126758","DOIUrl":"10.1016/j.apenergy.2025.126758","url":null,"abstract":"<div><div>Most remote and northern communities rely on diesel for their electrical and thermal energy needs. Communities and governments are working toward diesel exit strategies, but the role of hydrogen technologies has not been explored. These could serve both electrical and thermal demand, reduce emissions, and enhance energy security and community ownership. Here, we determine the installed capacities, costs, hydrogen storage needs, and water resource requirements of hydrogen microgrids across a large, diverse sample of communities. We also compare the cost of hydrogen microgrids to that of diesel microgrids. Our results optimize resource deployment, demonstrate how sub-components must operate to serve both demand types, and yield insights on storage and resource needs. We find that hydrogen microgrids are cheaper, in levelized cost terms, than diesel systems in 28 of 37 communities investigated; if wind power capital costs escalate to CAD 20,000/kW, as recently seen in one project, only 3 of the 37 communities net hydrogen microgrids that are cheaper than diesel variants. Hydrogen storage plays a large role in maintaining reliability and reducing cost—both it and water needs are modest. The former can be met with current technologies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126758"},"PeriodicalIF":11.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262638","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":"Environmental and economic assessment of large-scale hydrogen supply chains across Europe: LOHC vs other hydrogen technologies","authors":"I. Rey,&nbsp;V.L. Barrio,&nbsp;I. Agirre","doi":"10.1016/j.apenergy.2025.126862","DOIUrl":"10.1016/j.apenergy.2025.126862","url":null,"abstract":"<div><div>The transition to decarbonized energy systems positions hydrogen as a critical vector for achieving climate neutrality, yet its large-scale transportation and storage remain key challenges. This study presents a comprehensive life cycle assessment (LCA) and economic analysis of large-scale H₂ supply chains, evaluating the liquid organic hydrogen carrier (LOHC) system based on benzyltoluene/perhydro-benzyltoluene (H0-BT/H12-BT) against conventional technologies: compressed gaseous hydrogen (CGH₂), liquid hydrogen (LH₂) and liquid ammonia (LNH₃). The analysis includes multiple H₂ transportation scenarios across Europe, considering the steps: conditioning, sea transportation, post-processing and land distribution by truck or pipeline. Environmentally, LOHC currently faces higher environmental impacts than CGH₂, driven by energy-intensive dehydrogenation process. Truck-based distribution further amplifies impacts, particularly over long distances, while pipeline-based distribution significantly reduces the environmental burdens where infrastructure exists. Sensitivity analysis reveals that using H₂ for dehydrogenation heat lowers process-level impacts but increases overall supply chain impacts, questioning its net environmental benefit. Economically, LOHC remains competitive despite high dehydrogenation costs, benefiting from low sea transportation expenses, compatibility with existing fossil fuel infrastructure and potential for future CAPEX and OPEX improvements. While CGH₂ outperforms LH₂ and LNH₃, avoiding energy-intensive liquefaction and cracking, its storage requirements add considerable costs. For land distribution, LOHC trucks are optimal at lower capacities, whereas repurposed natural gas pipelines favour CGH₂ at higher scale, reducing costs by up to 84 %. Despite current trade-offs, the scalability, flexibility and synergies with existing infrastructure position LOHC as a promising solution for long-distance H₂ transport, contingent on technological maturation to mitigate dehydrogenation impacts.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126862"},"PeriodicalIF":11.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262637","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":"Building geometry-aware lifecycle optimization of hybrid renewable energy systems with solid gravity storage","authors":"Muhammed A. Hassan ,&nbsp;Mohamad T. Araji","doi":"10.1016/j.apenergy.2025.126879","DOIUrl":"10.1016/j.apenergy.2025.126879","url":null,"abstract":"<div><div>Urban buildings face challenges in integrating intermittent-supply renewable electricity sources while conforming to space and economic constraints. Solid gravity energy storage (GS) has not yet been explored in building applications despite its mechanical simplicity and long lifespan. The current literature lacks studies that link GS' optimal capacity to building geometry and energy intensity. This study introduces a novel hybrid energy system for buildings that combines façade-mounted PV panels, small rooftop wind turbines, Li-Ion batteries, and a rope-hoist-based GS. A multi-objective optimization framework is developed to minimize both the levelized cost of electricity (LCOE) and grid dependency (GD), considering realistic dispatch logic and annual operation. The system is optimized for 625 parametric building designs covering different energy use intensities (EUI) and geometric configurations, defined by façade area-to-volume, length-to-width, and height-to-footprint ratios. Tradeoff solutions achieved LCOE values between 0.051 and 0.111 USD/kWh, and GD between 0.195 and 0.888. GS was found to be the most impactful component on system autonomy, with the ratio between its capacity and the building's average daily demand ranging from 0.0 to 1.0 and strongly correlating with GD. Most optimal designs used PV extensively, wind turbines moderately, and batteries minimally. Payback periods ranged from 9 to 17 years, and carbon intensity values remained mostly below the Canadian average. Overall, the study highlights the synergy between the building design and the extent to which GS, as well as solar and wind systems, should be sized, hence offering a practical direction for low-carbon and resilient buildings.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"402 ","pages":"Article 126879"},"PeriodicalIF":11.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247957","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":"A frequency-secured load pickup strategy for black-start restoration in IBR-rich distribution systems under dynamic microgrid formation","authors":"Yanting Huang ,&nbsp;Shunbo Lei ,&nbsp;Jiahao Liu ,&nbsp;Cheng Wang ,&nbsp;Tao Jiang ,&nbsp;Akang Wang","doi":"10.1016/j.apenergy.2025.126752","DOIUrl":"10.1016/j.apenergy.2025.126752","url":null,"abstract":"<div><div>In recent years, renewable energy sources have been integrated into power grids at scale through grid-tie inverters. While these inverter-based resources (IBRs) reduce system inertia and pose challenges to frequency security, they also present opportunities for frequency support through effective control mechanisms. Traditional black-start restoration strategies relying on synchronous generators are no longer suitable for IBR-rich distribution systems. To address this challenge, this paper proposes a novel frequency-secured load pickup strategy that leverages dynamic microgrid (MG) formation to aggregate frequency support from IBRs. Grid-forming inverter-based resources provide parallel black-start services, forming boundary-dynamic MGs that progressively expand by restoring loads and connecting lines. To ensure frequency security during MG formation, key frequency indicators—including the rate of change of frequency, frequency nadir, and steady-state frequency—are employed to assess whether IBRs can manage power imbalances resulting from load pickup and renewable energy uncertainties. The flexibility of dynamic MGs facilitates operations such as merging, splitting, and reconfiguring, enabling IBRs to support neighboring MGs and maintain overall frequency stability. This problem is reformulated as a mixed-integer quadratically constrained quadratic program and solved using partial-relaxed rolling horizon optimization to reduce computational complexity. The effectiveness of the proposed strategy is validated on the IEEE-33 and IEEE-123 node test feeders.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126752"},"PeriodicalIF":11.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262575","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}