Applied Energy最新文献

{"title":"Impact of electricity price input methods on economic optimisation models: A case study of district heating thermal energy storage in Finland","authors":"Ilia Skorniakov ,&nbsp;Behnam Talebjedi ,&nbsp;Timo Laukkanen ,&nbsp;Sanna Syri","doi":"10.1016/j.apenergy.2026.127554","DOIUrl":"10.1016/j.apenergy.2026.127554","url":null,"abstract":"<div><div>Various methods are used to incorporate electricity price data into optimisation models for techno-economic assessments of energy systems. While many studies rely on time-series electricity prices, they often optimise the system over an entire year to reduce computational complexity — an assumption that may not reflect practical decision-making conditions. This study evaluates the validity of that assumption by comparing three modelling approaches: the <em>Basic</em> model, which uses a full-year electricity price dataset; the <em>Dynamic</em> model, which operates with a 36-hour rolling window of known prices; and the <em>Adaptive</em> model, which augments the rolling window with a 12-hour AI-based forecast. The case study examines a hot water tank integrated into a Finnish district heating system, tested across storage capacities from 100 to 20,000 m³ and multiple heat demand scenarios.</div><div>Results indicate that compared to the Basic model, the Dynamic and Adaptive models estimate lower annual profits. At optimal storage sizes, profit deviations remain below 4% for the Adaptive model and under 7% for the Dynamic model. However, for large storage volumes and low demand, deviations increase to 40% and 70%, respectively. The gap between the Adaptive and Dynamic models also grows with storage size, reaching up to 17%. Rolling-window models require significantly more computation time - approximately 14 and 25 times longer than the Basic model.</div><div>These findings emphasise the importance of choosing a modelling approach aligned with study goals. Simplified models suit early-stage assessments, whereas for more serious evaluations, the implementation of rolling-window approaches is advised, given the volatility of current electricity markets.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127554"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385977","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":"Scaling up floating offshore wind farm installation: From conventional to modular strategies","authors":"Manu Centeno-Telleria ,&nbsp;Raúl Guanche ,&nbsp;Markel Penalba","doi":"10.1016/j.apenergy.2026.127560","DOIUrl":"10.1016/j.apenergy.2026.127560","url":null,"abstract":"<div><div>With only small-scale floating offshore wind (FOW) farms installed to date, and commercial-scale projects anticipated in the coming years, reconsidering conventional installation strategies is essential to understand the challenges associated with scaling up. To this end, this paper introduces a novel discrete-event simulation model, <em>instaSIM®</em>, which is validated against data corresponding to the Hywind Scotland farm, demonstrating discrepancies of less than five days between simulated and observed durations. Once validated, different scenarios for scaling up FOW installation are evaluated. Results indicate that farms comprising more than 10–15 turbines cannot be installed within a single year using the conventional installation strategy, with installation costs increasing significantly due to metocean-related delays. To address these limitations, three modular installation strategies are proposed and evaluated for a 40-turbine and 600-MW FOW farm: parallel, consecutive and hybrid. Compared to the conventional baseline of 1200 days and 225 M€, all three strategies reduce total installation costs by 54%. However, the total duration varies across strategies: the parallel approach requires 137 days (88% reduction), while the hybrid strategy requires 500 days (58% lower) and the consecutive configuration extends to 1232 days. In addition to cost savings, the modular strategies enable an earlier power generation and faster CAPEX recovery. By the time the conventional strategy completes installation and starts producing energy, the consecutive, hybrid and parallel approaches would have already produced 3.8 TWh, 6.4 TWh and 7.7 TWh of electricity, respectively, corresponding to revenues of 840 M€, 1370 M€ and 1650 M€, and CAPEX recoveries of 29%, 48% and 57%.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127560"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386306","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":"Online identification of characteristic change points in capacity degradation trajectories of lithium-ion batteries","authors":"Ding Zhao ,&nbsp;Mingbiao Chen ,&nbsp;Wenye Lin ,&nbsp;Qingyao Qiao ,&nbsp;Bingsen Wang ,&nbsp;Jiahuan Lu ,&nbsp;Georgios Kokogiannakis ,&nbsp;Zhenjun Ma ,&nbsp;Wenji Song ,&nbsp;Ziping Feng","doi":"10.1016/j.apenergy.2026.127581","DOIUrl":"10.1016/j.apenergy.2026.127581","url":null,"abstract":"<div><div>To elucidate the evolutionary characteristics of the current available capacity of lithium-ion batteries, this study proposes an online identification framework of characteristic change points (CCPs) for capacity degradation curves. Firstly, health indicators are extracted from a short period of data before the end of constant current charging. The interaction of three data-driven algorithms and multiple feature intervals in terms of capacity estimation accuracy is systematically investigated. Then, the parameter combinations for the improved cumulative sum (CUSUM) algorithm are selected and validated through single-factor analysis, orthogonal experimental design, and main effect analysis. Specifically, the improved CUSUM algorithm exhibits an average error of only 16.42 cycles and an average latency of merely 4.20 cycles. Finally, the proposed improved CUSUM algorithm is applied to identify the CCPs in the battery capacity degradation curves of different morphological types. The validation performance of the proposed algorithm demonstrates its capability of identifying both routine degradation patterns and anomalous transitions. The identified CCPs can serve as evaluation indicators for multiple application scenarios, such as battery design, usage strategy optimization, and second-life utilization.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127581"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386224","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":"Model framework and performance analysis of photovoltaic-driven multistage membrane distillation systems for efficient water-power co-supply","authors":"Yahui Du ,&nbsp;Jiyuan Wu ,&nbsp;Zhihua Zhou ,&nbsp;Yuechao Chao ,&nbsp;Xueqing Yang ,&nbsp;Junwei Liu ,&nbsp;Cheng Wang ,&nbsp;Weidong Chen ,&nbsp;Chua Kian Jon Ernest ,&nbsp;Jinyue Yan","doi":"10.1016/j.apenergy.2026.127506","DOIUrl":"10.1016/j.apenergy.2026.127506","url":null,"abstract":"<div><div>Water and electricity are fundamental resources for human survival and societal development. This work designs a photovoltaic and membrane distillation (PV-MD) system for the distributed co-production of power and freshwater by harvesting both solar radiation and PV waste heat. An integrated heat-mass-power transfer model is developed and experimentally validated, allowing for accurate performance prediction under various structural and environmental conditions. Parametric analysis identifies membrane thickness and PV efficiency as critical design factors, while solar irradiation and humidity are the dominat external influences. Energy flux analysis underscores the trade-off between freshwater production and power generation under varying operation conditions. Furthermore, the hybrid cooling configuration demonstrates superior performance over conventional heat sinks, enhancing freshwater yield by 24.64% and PV power output by 4.28%. For opyimally designed systems, climate-specific modeling across diverse representative climates demonstrates strong adaptability, achieving freshwater production gains of 0.54%–19.71% and PV power increase of 0.10%–1.06% compared to heat sinks. This study provides valuable insights into the power-water synergy within PV-MD systems and offers the targeted guidance for system-level design and performance optimization across diverse climates.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127506"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385941","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 systematic synthesis of sky image enhancement techniques for ground-based solar irradiance forecasting","authors":"Mateusz Piechocki,&nbsp;Marek Kraft","doi":"10.1016/j.apenergy.2026.127533","DOIUrl":"10.1016/j.apenergy.2026.127533","url":null,"abstract":"<div><div>The development of the renewable energy sector, especially solar energy, is essential to mitigate the rapidly progressing climate change. However, the inherent uncertainty related to the stability of solar energy production capabilities prevents large-scale integration of solar-based sources into power grids. Therefore, this work addresses this practical challenge by presenting a systematic, large-scale synthesis and validation of a comprehensive neural network-based image enhancement pipeline for ground-based solar forecasting. This consolidated pipeline includes a Sun mask, optical flow, a cloud channel, and a novel irradiance value channel for early-stage spatio-temporal fusion. As a second key methodological novelty, we introduce the mean adaptive BerHu penalty as a loss function, which is shown to be uniquely suited for robustly handling the high dynamic range of solar irradiance values. The proposed comprehensive pipeline, when evaluated on a spatio-temporal model, outperforms existing methods from the literature. This strong performance is not architecture-specific, as demonstrated by our cross-architecture study, in which the pipeline’s portability achieves an average forecast skill of 19.35% among evaluated models for the 15-minute forecasting horizon. This is due to physically referenced, representation-level enhancements that act as an architecture-agnostic driver of forecasting skill going beyond incremental, model-specific tuning. Its practical applicability is further confirmed by its effectiveness across multiple intra-hour time horizons, with significant skill improvements for both ultra-short 5-minute (16.22%) and longer 30-minute (22.52%) periods. Finally, its practical deployability was confirmed through extensive validation on resource-constrained edge devices. The source code used in this study is publicly available to promote research reproducibility.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127533"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385961","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":"“The influence of electrification scenarios in road transport on the climate targets”","authors":"Philipp Anstett,&nbsp;Michael Schulthoff,&nbsp;Martin Kaltschmitt","doi":"10.1016/j.apenergy.2026.127435","DOIUrl":"10.1016/j.apenergy.2026.127435","url":null,"abstract":"<div><div>The transport sector accounts for about 22% of Germany's greenhouse gas (GHG) emissions and is amongst the most difficult parts of the energy system to decarbonize. The most commonly discussed options for the transport sector are the electrification of drivetrains and the use of renewable fuels. Especially in road transport, the future development depends on millions of individual purchase decisions, which introduces significant uncertainty regarding the speed and extent of electrification. Against this background, this study generates possible ramp-up curves for battery electric vehicles (BEV) using well-established diffusion models, historical vehicle stock data, data for BEV in Germany and literature expectations for future development trends concerning the electrification in road transport. These ramp-up curves are integrated into the vehicle stock in order to investigate the impact of different ramp-ups of BEV on the legal framework and GHG emission reduction obligations in the transport sector. The results show that the energy demand (and its composition) of the sector is strongly influenced by the degree of electrification in road transport. However, even with high shares of BEV in the vehicle stock, a significant use of renewable fuels will be necessary to meet the regulatory framework conditions under the Renewable Energy Directive (RED), the German GHG quota and the German Climate Change Act (KSG) in order to realize both blending quotas and absolute GHG emission reductions according to the German sector targets for transport.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127435"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386030","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":"Unlocking the potential of densely-packed bifacial curved photovoltaics: Holistic Modeling approach for optimizing energy yield and economic viability","authors":"Junmeng Zhang ,&nbsp;Chenyuan He ,&nbsp;Bin Fang ,&nbsp;Canglong Hu ,&nbsp;Ning Ding ,&nbsp;Zhengrong Shi ,&nbsp;Jingyong Cai","doi":"10.1016/j.apenergy.2026.127541","DOIUrl":"10.1016/j.apenergy.2026.127541","url":null,"abstract":"<div><div>Bifacial curved photovoltaic (bcPV) technology presents promising pathway for enhancing energy generation in space-constrained applications. However, the complex interplay between module curvature, bifacial gains, and array-level shading effects creates significant challenges for performance optimization and economic viability assessment. This study addresses this gap by developing dynamic optoelectronic model for bcPV systems, integrating micro-surface discretization with view factor analysis to resolve irradiance on both surfaces. The model incorporates detailed self-shading and inter-module shading for arrays, coupled with an equivalent electrical circuit. Key findings show that for single bcPV module, increasing the central angle to 110° enhances bifacial power gain to 27.71% but results in 1.77% net energy loss compared to flat bifacial module due to noon-time performance reduction. In array configurations under fixed land-area constraint, increasing curvature allows for higher installation density, boosting the total annual energy yield by up to 40.12% for 172° central angle compared to flat array. However, this gain is offset by higher capital costs and increased power loss ratios, resulting in levelized cost of electricity (LCOE) increase of up to 6.73%. The study reveals critical trade-off between energy density and economic efficiency, providing quantitative framework to guide the optimal design of bcPV systems for specific applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127541"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386031","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":"Decision-oriented assessment of redox flow batteries for grid-scale energy storage: Scalability, system complexity, and intelligent operation","authors":"Behnam Seyyedi ,&nbsp;Esmaeil Habibi","doi":"10.1016/j.apenergy.2026.127548","DOIUrl":"10.1016/j.apenergy.2026.127548","url":null,"abstract":"<div><div>Redox flow batteries (RFBs) are widely regarded as promising candidates for grid-scale, long-duration energy storage due to their intrinsic safety, decoupled scaling of power and energy, and long cycle life. However, despite decades of intensive research and significant advances in electrolyte chemistry, electrode design, and system modeling, commercial deployment remains limited and concentrated in a small number of mature chemistries, indicating that performance-oriented optimization alone is insufficient to ensure deployability. In this review, we introduce a decision-oriented assessment framework-Scalability-Complexity-Intelligence (SCI) - to systematically evaluate RFB technologies based on their readiness for long-term operation, tolerance to system-level complexity, and the conditional value of intelligent control. Electrolyte chemistries, electrode and membrane components, modeling strategies, and hybrid system architectures are examined through a unified lens that emphasizes durability, manufacturability, operational predictability, and levelized cost of storage. The analysis demonstrates that many proposed RFB concepts achieve promising laboratory metrics at the expense of escalating system complexity, undermining scalability and long-term reliability, whereas technologies characterized by intrinsic chemical stability, transparent degradation behavior, and simplified system architectures exhibit stronger alignment with deployment realities. Advanced modeling, digital twins, and AI-assisted control are shown to deliver meaningful benefits primarily in chemically stable and operationally predictable systems, where intelligence enhances reliability rather than compensating for fundamental material or architectural limitations. By explicitly distinguishing deployable solutions from conditionally viable pathways and systemically constrained concepts, this review provides actionable guidance for researchers, system designers, and energy stakeholders seeking to translate redox flow battery innovation into reliable grid-scale energy storage infrastructure.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127548"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386147","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 scenario-responsive siting framework of CO₂ capture and electrochemical conversion systems using integrated spatial and multi-criteria decision analysis","authors":"Weishan Bai ,&nbsp;Ahmed Badreldin ,&nbsp;Yuning Ye ,&nbsp;Xinyu Li ,&nbsp;M.G. Toufik Ahmed ,&nbsp;Carter Racine ,&nbsp;M.M. Faruque Hasan ,&nbsp;Wenyu Zhang ,&nbsp;Ying Li ,&nbsp;Xinyue Ye","doi":"10.1016/j.apenergy.2026.127583","DOIUrl":"10.1016/j.apenergy.2026.127583","url":null,"abstract":"<div><div>The growing interest in electrochemical CO₂ reduction to value-added hydrocarbons and oxygenates reflects the urgent need for sustainable carbon utilization pathways. While a range of products has been demonstrated, only a few have matured electrocatalysts with systematically optimized electrochemical performance metrics. These metrics critically affect overall production costs. Therefore, the need for a flexible siting framework that actively identifies optimal CO₂ electrolyzer locations based on plant specific sizing and production requirements is warranted for the advancement of this technology. We present a scenario-responsive decision-making framework for CO₂ electrolyzer siting, integrating Geographic Information Systems (GIS), the Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Analytic Network Process (ANP). Three spatial siting factors were defined in this study as key factors influencing site suitability, including land cost, transportation accessibility, and CO₂ source accessibility. The framework model's interdependencies among siting factors and computes land suitability using both general and scenario-adjusted weightings reflecting product type and plant capacity. Suitability of siting was evaluated for 15 deployment scenarios combining three capacities (1 MW, 20 MW, 100 MW) and five products (CO, HCOOH, C₂H₄, CH₃OH, C₂H₅OH) in two industrial clusters in Texas Houston and San Antonio. Results reveal regional differences: Houston's suitability patterns were highly sensitive to scenario weightings, while San Antonio exhibited more stable patterns. The model identified a small set of high-performing parcels, including one optimal site per region across most scenarios. These findings underscore the importance of city-specific siting, as regional variations limit the reliability of generalized assumptions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127583"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386227","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":"Coordinated robust planning of multi-energy microgrids with P2P trading: A variational inequality based distributed approach","authors":"Zheng Xu ,&nbsp;Zhi Wu ,&nbsp;Yue Chen ,&nbsp;Haifeng Qiu ,&nbsp;Linwei Sang ,&nbsp;Pengxiang Liu ,&nbsp;Hengqing Ye","doi":"10.1016/j.apenergy.2026.127538","DOIUrl":"10.1016/j.apenergy.2026.127538","url":null,"abstract":"<div><div>The coordinated planning of multi-energy microgrids (MEMGs) plays a pivotal role in improving energy efficiency within peer-to-peer (P2P) energy markets. However, source-demand uncertainty introduces energy fluctuations that jeopardize system stability, and the multi-agent coupling structure of planning models often depends on convexity assumptions to enable tractable distributed solutions. To tackle these challenges, this paper develops a coordinated planning framework for multiple MEMGs that integrates P2P energy sharing with stochastic source-load modeling. The multi-agent cost minimization problem is formulated under mixed-integer programming (MIP) settings. Then, a monotone variational inequality (MVI)-driven equilibrium model is constructed to capture interactions among MEMGs, and an alternative optimization procedure (AOP) is incorporated to address the non-convexity arising from integer variables. Subsequently, a distributed adaptive prediction–correction algorithm with theoretical convergence guarantees is developed to solve the multi-block MVI formulation with minimal information exchanged. Additionally, the generalized Nash bargaining solution is employed to ensure incentive compatibility and fair profit distributions among MEMG investors. Numerical experiments demonstrate the effectiveness and advantages of the proposed framework in enhancing efficiency, safeguarding privacy, and fostering cooperation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127538"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385937","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}