Applied Energy最新文献

{"title":"Disturbed security-constrained and time-variant optimal power flow for dynamic power system based on chaotic-genetic-centroid puffin optimization","authors":"Xiaochen Zhang ,&nbsp;Kaijie Xu ,&nbsp;Shengchen Liao ,&nbsp;Lin Qiu ,&nbsp;Chengjin Ye ,&nbsp;Youtong Fang","doi":"10.1016/j.apenergy.2025.126287","DOIUrl":"10.1016/j.apenergy.2025.126287","url":null,"abstract":"<div><div>Although the Security-Constrained Optimal Power Flow (SCOPF) model provides an effective model for simulating fault scenarios in power systems, it often overlooks bus-level fluctuations. Therefore, this paper introduces the Disturbed Security-Constrained Optimal Power Flow (D-SCOPF) to model the instability of power systems, leading to the development of a disturbed topology varying (DTV) test system. Additionally, to simulate the dynamic and time-varying properties of power systems, the fluctuations in electric vehicle load are incorporated into the system, resulting in the construction of a Time-Variant (TV) test system. These enhancements improve model realism but also significantly increase computational complexity. As a result, finding feasible solutions in such a complex model becomes a substantial challenge. Considering the high-dimensional and multi-constraint properties of the OPF problem, this paper proposes a novel Chaotic-Genetic-Centroid Puffin Optimization (CGC-PO) algorithm based on Arctic Puffin Optimization (APO). CGC-PO aims to specifically improve APO’s exploration, exploitation, and population merging processes through centroid opposition-based learning, normalized chaotic local search, and genetic hybrid incorporation. To validate the feasibility of the proposed algorithm, a series of tests were first conducted on benchmark functions, followed by quantitative, convergence, and statistical analyses. Besides, different modified test systems were constructed based on the IEEE 30-bus, IEEE 57-bus, IEEE 118-bus and Illinois 200-bus systems. Both single-objective and multi-objective optimization functions were evaluated on these test systems. By comparing the results with those obtained from several well-known optimization algorithms, including TLBO, PSO, PLO, SMA, HGS, MGO, ALA, MSO and APO, the effectiveness, superiority, and robustness of the proposed CGC-PO algorithm are demonstrated.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126287"},"PeriodicalIF":10.1,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481816","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":"Data-driven control, optimization, and decision-making in active power distribution networks","authors":"Nanpeng Yu ,&nbsp;Shaorong Zhang ,&nbsp;Jingtao Qin ,&nbsp;Patricia Hidalgo-Gonzalez ,&nbsp;Roel Dobbe ,&nbsp;Yang Liu ,&nbsp;Anamika Dubey ,&nbsp;Yubo Wang ,&nbsp;John Dirkman ,&nbsp;Haiwang Zhong ,&nbsp;Ning Lu ,&nbsp;Emily Ma ,&nbsp;Zhaohao Ding ,&nbsp;Di Cao ,&nbsp;Junbo Zhao ,&nbsp;Yuanqi Gao","doi":"10.1016/j.apenergy.2025.126253","DOIUrl":"10.1016/j.apenergy.2025.126253","url":null,"abstract":"<div><div>This paper reviews the burgeoning field of data-driven algorithms and their application in solving increasingly complex decision-making, optimization, and control problems within active distribution networks. By summarizing a wide array of use cases, including network reconfiguration and restoration, crew dispatch, Volt-Var control, dispatch of distributed energy resources, and optimal power flow, we underscore the versatility and potential of data-driven approaches to improve active distribution system operations. The categorization of these algorithms into four main groups-mathematical optimization, end-to-end learning, learning-assisted optimization, and physics-informed learning-provides a structured overview of the current state of research in this domain. Additionally, we delve into enhanced algorithmic strategies such as non-centralized methods, robust and stochastic methods, and online learning, which represent significant advancements in addressing the unique challenges of active distribution systems. The discussion extends to the critical role of datasets and test systems in fostering an open and collaborative research environment, essential for the validation and benchmarking of novel data-driven solutions. In conclusion, we outline the primary challenges that must be navigated to bridge the gap between theoretical research and practical implementation, alongside the opportunities that lie ahead. These insights aim to pave the way for the development of more resilient, efficient, and adaptive active distribution networks, leveraging the full spectrum of data-driven algorithmic innovations.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126253"},"PeriodicalIF":10.1,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470239","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":"Renewable hydrogen and ammonia production: Location-specific considerations and competitive market dynamics in Europe","authors":"Ioannis Kountouris,&nbsp;Mariano Forcellati,&nbsp;Isidoros Pantelidis,&nbsp;Dogan Keles","doi":"10.1016/j.apenergy.2025.126168","DOIUrl":"10.1016/j.apenergy.2025.126168","url":null,"abstract":"<div><div>The transition to clean energy in Europe is closely tied to the viability of renewable and low-carbon hydrogen and ammonia production. However, many hydrogen projects remain in the conceptual and feasibility stages, with only a few advancing to the final investment decision, often constrained by the need to ensure profitability. This study presents a new modeling framework complemented by the European Union’s policy and regulatory environment, assessing the cost-effectiveness of hydrogen and ammonia production. Our analysis reveals that incorporating technical constraints such as minimum part-load leads to a 4 % variation in the estimated levelized cost of ammonia. Through a comparative evaluation of European port locations investing in onsite assets, we identify weather uncertainty and renewable energy potential as the most critical factors influencing cost-effectiveness, followed by local financing terms. Business models that capitalize on advantageous power purchase agreements, frequent access to low-cost electricity through grid sourcing, low grid emissions, and favorable network tariff structures can significantly enhance their competitive edge. Our findings underscore the importance of policies that leverage locational advantages, suggesting that Europe’s clean energy transition can be accelerated by tailored support strategies that exploit regional strengths. This research contributes to ongoing discussions on renewable fuel production, hydrogen modeling, and the intersection of policy and regulation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126168"},"PeriodicalIF":10.1,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481812","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":"Performance assessment and fast diagnosis of a μ-CHP solid oxide fuel cell system","authors":"Hangyu Yu ,&nbsp;Florian Bernard Berset ,&nbsp;Pyry Mäkinen ,&nbsp;Cédric Frantz ,&nbsp;Philippe Aubin ,&nbsp;Arne Sommerfeld ,&nbsp;Gregor Holstermann ,&nbsp;Tafarel de Avila Ferreira ,&nbsp;Hamza Moussaoui ,&nbsp;Guillaume Jeanmonod ,&nbsp;Ligang Wang ,&nbsp;Matthias Boltze ,&nbsp;Grégory François ,&nbsp;Jan Van herle","doi":"10.1016/j.apenergy.2025.126321","DOIUrl":"10.1016/j.apenergy.2025.126321","url":null,"abstract":"<div><div>Online performance characterization and faulty condition diagnosis of micro-combined-heat-and-power (<span><math><mi>μ</mi></math></span>-CHP) solid oxide fuel cell (SOFC) system is crucial for ensuring safe in-house operation and lifespan prolongation. However, fast accurate detection of faulty conditions and performance characterization of compact SOFC system remains a problem. This study applied multiple diagnostic methods to characterize a <span><math><mi>μ</mi></math></span>-CHP SOFC system, including chronopotentiometry, electrochemical impedance spectroscopy (EIS), total harmonic distortion (THD) tool. Performance characterization and condition diagnosis were performed under different power demands, fuel starvation, high-carbon fuel feed and long-term operation. EIS results under normal conditions and fuel starvation showed that the bottom 27-cell half stack, located away from the fuel inlet, received less fuel compared to the top 30-cell half stack. Dispersion analysis indicated the safe fuel utilization for the system should be maintained below 81 % to avoid fuel starvation. THD measurements revealed that fuel starvation could be effectively detected by sinusoidal excitation with frequencies between 0.01 and 0.1 Hz, where a high THD index was observed. The carbon deposition behavior was examined by adjusting the carbon to oxygen ratio (COR) at the catalytic partial oxidation reactor inlet. With COR up to 1, no significant carbon deposition was detected according to the EIS measurements, system voltage and temperature monitoring. During long-term operation under normal conditions, no substantial degradation was detected, demonstrating stable and reliable power and heat generation. The novelty of this work included (1) the identification of operational variability between two half stacks, (2) the rapid detection of fuel starvation conditions using THD analysis, (3) performance assessment under high carbon fuel feed, and (4) long-term degradation characterization.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126321"},"PeriodicalIF":10.1,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470233","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":"Potential solution to wheat straw-to-methanol for marine fuel under carbon emission restrictions: A comparative energy, exergy, economic, and environmental analysis","authors":"Danfeng Wang ,&nbsp;Yuxin Wen ,&nbsp;Jie Zhang ,&nbsp;Qianqian Chen ,&nbsp;Yu Gu ,&nbsp;Xinqing Chen ,&nbsp;Zhiyong Tang","doi":"10.1016/j.apenergy.2025.126338","DOIUrl":"10.1016/j.apenergy.2025.126338","url":null,"abstract":"<div><div>Green methanol has emerged as a sustainable alternative marine fuel, yet its industrialization requires a systematic evaluation of technical routes under carbon emission restrictions. This study conducted process modeling and comparative analysis of three wheat straw-to-methanol routes: Route 1 (partial grid electricity), Route 2 (self-generated electricity), and Route 3 (integrated hydrogen production). Route 1, using grid electricity, resulted in a carbon emission of 40.78 g CO₂eq/MJ methanol. Route 2, utilizing self-generated electricity, achieved 22.70 g CO₂eq/MJ methanol, matching Route 1 when renewable electricity was used. Route 3 achieved the highest methanol yield and energy efficiency, with minimal exergy loss in syngas conditioning, but exhibited the poorest economic performance. Route 3's carbon emissions were highly sensitive to the renewable electricity structure. Overall, Route 1 using grid electricity was unsuitable. Route 2, with its competitive carbon emissions and economic performance, was ideal for early industrialization, especially in regions with limited renewable energy resources. Route 3 was best suited for areas with abundant straw and strong renewable energy resources, suggesting a phased implementation of Routes 1 and 3 using renewable electricity. This study provided potential solutions for the industrialization of biomass-to-methanol under carbon emission restrictions, offering data support and valuable insights for researchers, investors, and industry stakeholders.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126338"},"PeriodicalIF":10.1,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364989","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":"Capacity credit evaluation of generalized energy storage considering strategic capacity withholding and decision-dependent uncertainty","authors":"Ning Qi ,&nbsp;Pierre Pinson ,&nbsp;Mads R. Almassalkhi ,&nbsp;Yingrui Zhuang ,&nbsp;Yifan Su ,&nbsp;Feng Liu","doi":"10.1016/j.apenergy.2025.126310","DOIUrl":"10.1016/j.apenergy.2025.126310","url":null,"abstract":"<div><div>This paper proposes a novel capacity credit evaluation framework to accurately quantify the contribution of generalized energy storage (GES) to resource adequacy, considering both strategic capacity withholding and decision-dependent uncertainty (DDU). To this end, we establish a market-oriented risk-averse coordinated dispatch method to capture the cross-market reliable operation of GES. The proposed method is sequentially implemented along with the Monte Carlo simulation process, coordinating the pre-dispatched price arbitrage and capacity withholding in the energy market with adequacy-oriented re-dispatch during capacity market calls. In addition to decision-independent uncertainties in operational states and baseline behavior, we explicitly address the inherent DDU of GES (i.e., the uncertainty of available discharge capacity affected by the incentives and accumulated discomfort) during the re-dispatch stage using the proposed data-driven distributionally robust chance-constrained approach. Furthermore, a capacity credit metric called equivalent storage capacity substitution is introduced to quantify the equivalent deterministic storage capacity of uncertain GES. Simulations on the modified IEEE RTS-79 benchmark system with 20 years real-world data from Elia demonstrate that the proposed method yields accurate capacity credit and improved economic performance. We show that the capacity credit of GES increases with more strategic capacity withholding but decreases with more DDU levels. Key factors, such as capacity withholding and DDU structure impacting GES’s capacity credit are analyzed with insights into capacity market decision-making.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126310"},"PeriodicalIF":10.1,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470403","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":"Acceptable cost-driven multivariate load forecasting for integrated coal mine energy systems","authors":"Xiaoxuan Xing ,&nbsp;Dunwei Gong ,&nbsp;Yan Wang ,&nbsp;Xiaoyan Sun ,&nbsp;Yong Zhang","doi":"10.1016/j.apenergy.2025.126341","DOIUrl":"10.1016/j.apenergy.2025.126341","url":null,"abstract":"<div><div>Forecasting errors are inevitable in integrated energy systems with multivariate loads. To minimize costs, specialized forecasting models are essential. In this study, we propose a method for acceptable cost-driven multivariate load forecasting for the integrated coal mine energy system. By analyzing the relationship between dispatch costs and forecasting errors, the forecasting accuracy requirements for different types of loads are determined, based on which appropriate models for forecasting loads are selected. Firstly, the impact degrees of forecasting errors on dispatch costs for different kinds of loads are determined. Following that, the forecasting accuracy requirements for different types of loads within the acceptable costs are calculated by solving an optimization problem. Finally, the models for forecasting different types of loads are selected based on the forecasting accuracy requirements and the Bayesian information criterion. The proposed method is applied to an integrated coal mine energy system, and the experimental results show that the proposed method is capable of forecasting multivariate loads of the system within acceptable cost ranges.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126341"},"PeriodicalIF":10.1,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364988","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 hybrid correction framework using disentangled seasonal-trend representations and MoE for NWP solar irradiance forecast","authors":"Weijing Dou ,&nbsp;Kai Wang ,&nbsp;Shuo Shan ,&nbsp;Kanjian Zhang ,&nbsp;Haikun Wei ,&nbsp;Victor Sreeram","doi":"10.1016/j.apenergy.2025.126295","DOIUrl":"10.1016/j.apenergy.2025.126295","url":null,"abstract":"<div><div>Day-ahead solar irradiance forecast holds important value for optimizing energy utilization within the power system and ensuring stable grid scheduling. The forecast outputs of numerical weather prediction (NWP) are widely acknowledged as one of the indispensable data sources for day-ahead solar irradiance forecast tasks. In previous studies, post-processing methods have generally been employed as correction models to enhance the accuracy of NWP solar irradiance forecasts. However, irradiance sequences contain complex mixed patterns and exhibit various seasonal periodic differences. Based on the analysis of NWP global horizontal irradiance (GHI) error characteristics in this study, errors in NWP GHI forecasts also show obvious seasonal variations. Given these issues, it is challenging for a single correction model to achieve good correction performance and strong seasonal robustness. Therefore, this paper proposes a hybrid model comprising representation learning module, feature sparse activation module, and encoder-decoder-based correction module to address the aforementioned problems. A contrastive-learning-based representation learning module named CoST is introduced to learn disentangled seasonal features and trend features of irradiance sequences. A learnable mixture-of-experts (MoE) layer is adopted to sparsely activate the seasonal-trend features that contribute more to improving correction accuracy. The encoder-decoder-based correction module takes the sparsely activated seasonal-trend features as inputs, achieving the final corrected NWP GHI forecasts. The correction performance of the proposed method was validated on both publicly available datasets and actual field dataset. The results for various datasets show that our proposed CoST-MoELSTM model achieves the highest improvement for NWP forecasts, with increases of 29.82 %, 36.54 %, and 26.58 %. Additionally, we conducted a detailed analysis of the correction performance of CoST-MoELSTM across different seasons, indicating its superior seasonal robustness.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126295"},"PeriodicalIF":10.1,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365074","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":"Aggregator-driven optimisation of electric vehicle charging stations in Shenzhen: Synergising smart charging, renewable energy integration and energy storage","authors":"Wentao Xin ,&nbsp;Zhenwei Lu ,&nbsp;Zhe Yu ,&nbsp;Zhaoxuan He ,&nbsp;Hongjiang Pu,&nbsp;Bin Ye","doi":"10.1016/j.apenergy.2025.126345","DOIUrl":"10.1016/j.apenergy.2025.126345","url":null,"abstract":"<div><div>The widespread adoption of electric vehicles (EVs) presents substantial challenges such as increased peak loads, accelerated power infrastructure degradation and reduced economic efficiency. To address these issues, this study proposes an integrated multi-technology charging station model alongside an innovative analytical framework for assessing the comprehensive benefits of charging aggregators. The framework integrated a randomised load forecasting model with a smart charging strategy and was validated using real-world data obtained from 1682 charging stations, comprising 24,798 individual charging piles, in Shenzhen, China. Implementing the proposed charging station model, combined with Shenzhen's time-of-use tariff structure and an &gt;80 % renewable energy penetration rate, reduced levelised cost of energy, carbon emissions and peak load by 0.38 Yuan per kWh. Furthermore, renewable energy contributes to a 44.01 % reduction in carbon emissions in the smart charging system, outperforming the 41.24 % reduction observed in the on-demand charging system. Additionally, smart charging and on-demand charging methods reduce peak loads by 30.03 % and 15.40 %, respectively. It is found that combining energy storage with smart charging effectively mitigates their negative effects on emissions and costs. Energy storage increased annual carbon emissions (from 1.402 Mt. to 1.688 Mt) in an on-demand charging scenario, whereas it decreased them in a smart charging scenario. Although the current uneven distribution and low utilisation rate of EV charging resources in Shenzhen have resulted in financial losses for charging aggregators, the anticipated rapid growth in charging demand and improved utilisation rates are expected to substantially enhance profitability. Overall, this study provides a theoretical foundation for the sustainable development of charging infrastructure, thereby enhancing grid stability and renewable energy integration.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126345"},"PeriodicalIF":10.1,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364665","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":"Forecasting and surrogate models-based MINLP for long-term integrated design and planning of power-to-methanol","authors":"Dat-Nguyen Vo,&nbsp;Xuewen Zhang,&nbsp;Xunyuan Yin","doi":"10.1016/j.apenergy.2025.126336","DOIUrl":"10.1016/j.apenergy.2025.126336","url":null,"abstract":"<div><div>The power-to-methanol (PtMe) process faces critical challenges, including the absence of efficient forecasting models, the lack of viable frameworks for integrated design and planning (IDP) optimization, and insufficient long-term evaluations of economic and operational flexibility. To address these research gaps, this study proposes a novel approach that integrates forecasting and surrogate models with mixed-integer nonlinear programming (MINLP) to optimize the long-term IDP of the PtMe process, with the aim of reducing production costs and enhancing operational flexibility. First, we develop two forecasting models to predict renewable energy availability over the next four years and two surrogate models to accurately represent the methanol production section. These models are then integrated with models of other sections to formulate four system models for the PtMe process. The system models are integrated with a superstructure design and MINLP to formulate four optimization problems, aiming to minimize methanol production costs. The optimization results indicate that incorporating the transformer and polynomial models with MINLP is the most effective approach, with the lithium-ion battery (LiB)-Grid-PtMe configuration emerging as the optimal design. Using the transformer model reduces the required LiB storage capacity and methanol production cost by 5.7 % and 41.01 %, respectively, while selecting an efficient design and integrating the grid reduces methanol production costs by up to 68.2 %. The findings are applicable to the long-term IDP of the PtMe process. Additionally, the proposed forecasting models and solution approach can be extended to the IDP of other power-to-liquid processes.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126336"},"PeriodicalIF":10.1,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364995","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}