Applied Energy最新文献

{"title":"Techno-economic planning of spatially-resolved battery storage systems in renewable-dominant grids under weather variability","authors":"Seyed Ehsan Ahmadi ,&nbsp;Elnaz Kabir ,&nbsp;Mohammad Fattahi ,&nbsp;Mousa Marzband ,&nbsp;Dongjun Li","doi":"10.1016/j.apenergy.2025.126706","DOIUrl":"10.1016/j.apenergy.2025.126706","url":null,"abstract":"<div><div>The ongoing energy transition is significantly increasing the share of renewable energy sources (RES) in power systems; however, their intermittency and variability pose substantial challenges, including load shedding and system congestion. This study examines the role of the battery storage system (BSS) in mitigating these challenges by balancing power supply and demand. We optimize the location, size, and type of batteries using a two-stage stochastic program, with the second stage involving hourly operational decisions over an entire year. Unlike previous research, we incorporate the comprehensive technical and economic characteristics of battery technologies. The New York State (NYS) power system, currently undergoing a significant shift towards increased RES generation, serves as our case study. Using available load and weather data from 1980 to 2019, we account for the uncertainty of both load and RES generation through a sample average approximation approach. Our findings indicate that BSS can reduce renewable curtailment by 34 % and load shedding by 21 %, contributing to a more resilient power system in achieving NYS 2030 energy targets. Furthermore, the cost of employing BSS for the reduction of load shedding and RES curtailment does not increase linearly with additional capacity, revealing a complex relationship between costs and renewable penetration. This study provides valuable insights for the strategic BSS deployment to achieve a cost-effective and reliable power system in the energy transition as well as the feasibility of the NYS 2030 energy targets.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126706"},"PeriodicalIF":11.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105403","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 socio-economic assessment of an off-grid renewable energy system for an improved electric mobility","authors":"A. Mauro ,&nbsp;R. Santagata ,&nbsp;A. Stasi ,&nbsp;L. Vanoli","doi":"10.1016/j.apenergy.2025.126743","DOIUrl":"10.1016/j.apenergy.2025.126743","url":null,"abstract":"<div><div>The electrification of the transportation sector is expected to mitigate the significant impacts coming from both energy production and road mobility. As a consequence, the energy production/distribution/consumption path is expected to be substantially affected, as well as policies and regulations. The most promising outcome of this strategy is represented by the opportunity of enhancing the use of sustainable energy sources and of substituting the diffused emissions of road traffic with more centralized, and therefore more monitored and manageable, emission points within energy production plants. In this work, a novel renewable energy system for recharging electric vehicles in an off-grid configuration is analysed. The system produces electricity from photovoltaic and syngas, the latter obtained from wood biomass. The assessment is performed by means of the LEAF integrated procedure, coupling the life cycle assessment and emergy accounting perspectives. This multi-criteria procedure is paired with the calculation of emergy conversion factors based on LCA inventories, reinforcing the bond between the two methods. This novel procedure develops and analyses different methodological and material scenarios. The case study is confirmed as a feasible strategy, compared to the common electricity production and fossil fuel road mobility, simultaneously dealing with renewable energy production, waste recovery and remote areas development, in a circular economy perspective.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126743"},"PeriodicalIF":11.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105405","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":"Decarbonizing power generation through Iron-based fuel cycles: A thermodynamic and thermo-economic analysis","authors":"Yanlong Lv ,&nbsp;Yuhao Wang ,&nbsp;Feng Liu ,&nbsp;Jun Sui","doi":"10.1016/j.apenergy.2025.126751","DOIUrl":"10.1016/j.apenergy.2025.126751","url":null,"abstract":"<div><div>A novel zero‑carbon power generation system for a 300 MW plant is proposed, utilizing iron as a chemical energy carrier to integrate renewable energy. In the proposed system, iron combustion drives the steam Rankine cycle for electricity generation, and the produced iron oxide is reduced by hydrogen from an alkaline electrolyzer powered by renewable energy, completing the cycle. Relative to a conventional 300 MW coal-fired plant based on 5E (Energy, exergy, environmental, economic and exergoeconomic) analysis, the proposed system demonstrates a 0.72 % improvement in energy efficiency and a 12.35 % increase in exergy efficiency. The power conversion efficiency of the proposed system is 10.64 % higher than that of the methanol-based hydrogen production system. The life cycle assessment has validated the environmental friendliness of the system during its operation process. The cost of electricity production is reduced from 94.57 $/MWh to 60.01 $/MWh, with minimal influence from iron costs due to low cycle losses. Economic analysis indicates that the photovoltaic system, alkaline electrolyzer, and steam Rankine cycle contribute to 98.31 % of total economic losses. The proposed system facilitates long-distance, efficient renewable energy utilization and zero‑carbon power generation, providing a feasible framework for energy decarbonization and cross-regional renewable energy integration.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126751"},"PeriodicalIF":11.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105400","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":"Identifying thermal effects in an innovative thermally-electrochemically co-driven electrochemically mediated CO2 capture system","authors":"Xiaomei Wu ,&nbsp;Huifeng Fan ,&nbsp;Yang Yang ,&nbsp;Yuanhao Mao ,&nbsp;Yunsong Yu ,&nbsp;Zaoxiao Zhang","doi":"10.1016/j.apenergy.2025.126742","DOIUrl":"10.1016/j.apenergy.2025.126742","url":null,"abstract":"<div><div>The integration of renewable electricity and low-grade waste heat with electrochemically mediated amine regeneration (EMAR) presents a viable pathway toward developing sustainable and economically feasible CO₂ capture technology. Clarifying the thermal effects of the thermally-electrochemically co-driven EMAR process is critical for optimizing system energy efficiency, particularly for large-scale industrial applications. This study investigates the thermal impacts on CO₂ absorption properties, electrolyte characteristics, electrochemical behavior, and regeneration efficiency of the proposed system, using a combination of thermodynamic calculations and experimental methods. Experimental data demonstrate that the absorption temperature of 40 °C is optimal for achieving superior CO₂ absorption kinetics and maximizing the absorption load. Furthermore, elevated temperatures significantly reduce electrolyte viscosity, enhancing ion diffusion and lowering overall system impedance. This facilitates improved efficiency in both oxidation and reduction reactions within the electrochemical cells, markedly enhancing overall electrochemical performance. For the desorption performance, when the temperature increased from 20 °C to 80 °C, the minimum theoretical thermodynamic energy consumption is reduced by 5.02 %. More strikingly, experimental results indicate a substantial 60.9 % reduction in practical energy consumption, dropping from 102 kJ/mol to 39.9 kJ/mol, signifying a dramatic improvement in the energy utilization efficiency of the CO₂ desorption process. Considering the typical temperature of waste heat from factories, heat exchange efficiency, and the volatility of the solution, 60 °C is the recommended desorption temperature. These findings demonstrate the feasibility of the proposed thermally-electrochemically co-driven EMAR process and provide a guidance for determining the operating temperature of CO₂ absorption and desorption processes, which may establish an environmentally sustainable and economically viable solution to support global carbon neutrality.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126742"},"PeriodicalIF":11.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105401","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":"Interactive multiscale modeling to bridge atomic properties and electrochemical performance in Li-CO2 battery design","authors":"Mohammed Lemaalem ,&nbsp;Selva Chandrasekaran Selvaraj ,&nbsp;Ilias Papailias ,&nbsp;Naveen K. Dandu ,&nbsp;Arash Namaeighasemi ,&nbsp;Larry A. Curtiss ,&nbsp;Amin Salehi-Khojin ,&nbsp;Anh T. Ngo","doi":"10.1016/j.apenergy.2025.126693","DOIUrl":"10.1016/j.apenergy.2025.126693","url":null,"abstract":"<div><div>Li-CO₂ batteries are promising energy storage systems due to their high theoretical energy density and CO₂ fixation capability, relying on reversible Li₂CO₃/C formation during discharge/charge cycles. We present a multiscale modeling framework integrating Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties. The considered Li-CO₂ battery consists of a lithium metal anode, an ionic liquid electrolyte, and a carbon cloth cathode with Sb_0.67Bi_1.33Te₃ catalyst. DFT and AIMD determined the electrical conductivities of Sb_0.67Bi_1.33Te₃ and Li₂CO₃ using the Kubo–Greenwood formalism and studied the CO₂ reduction mechanism on the cathode catalyst. MD simulations calculated the CO₂ diffusion coefficient, Li<span><math><msup><mspace></mspace><mo>+</mo></msup></math></span> transference number, ionic conductivity, and Li<span><math><msup><mspace></mspace><mo>+</mo></msup></math></span> solvation structure. The FEA model, parameterized with atomistic simulation data, reproduced the available experimental voltage–capacity profile at 1 mA/cm² and revealed spatio-temporal variations in Li₂CO₃/C deposition, porosity, and CO₂ concentration dependence on discharge rates in the cathode. Accordingly, Li₂CO₃ can form large and thin film deposits, leading to dispersed and local porosity changes at 0.1 mA/cm² and 1 mA/cm², respectively. The capacity decreases exponentially from 81,570 mAh/g at 0.1 mA/cm² to 6200 mAh/g at 1 mA/cm², due to pore clogging from excessive discharge product deposition that limits CO₂ transport to the cathode interior. Therefore, the performance of Li-CO₂ batteries can be improved by enhancing CO₂ transport, regulating Li₂CO₃ deposition, and optimizing cathode architecture.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126693"},"PeriodicalIF":11.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105404","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 cross-chain electricity transaction scheme for multi-microgrid with user privacy protection and regulation","authors":"Shaomin Zhang ,&nbsp;Jiatao Li ,&nbsp;Baoyi Wang","doi":"10.1016/j.apenergy.2025.126741","DOIUrl":"10.1016/j.apenergy.2025.126741","url":null,"abstract":"<div><div>Multi-microgrid smart electricity market can facilitate energy complementarity between microgrids and improve the utilization rate of renewable energy. However, in the transaction payment between multiple blockchain-based microgrids, transaction data and transaction assets on different blockchains are not only difficult to interoperate, but also attackers can obtain private information such as the account addresses and transaction amount of electricity prosumers from the blockchain ledger. This allows attackers to infer the true identities of users, undermining the security and fairness of electricity transaction. To address these issues, a cross-chain electricity transaction scheme for multi-microgrid with user privacy protection and regulation is proposed. Firstly, Pedersen commitment is used to encrypt the transaction amount, and Signature of Knowledge is used to encrypt the electricity transaction payment message while hiding the true identities of the users, achieving anonymous payment. Secondly, the stealth address generation algorithm in the blockchain is improved, achieving unlinkability between users' real address and payment address, preventing inference attacks and enhancing address generation efficiency. Finally, relay chain technology is used to ensure the security of cross-chain electricity transaction payment between different microgrids. Theoretical analysis proves the scheme's unforgeability, anonymity, and traceability. Performance evaluation indicates that the scheme has low computational costs.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126741"},"PeriodicalIF":11.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105402","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 comprehensive review of lithium-ion battery modelling research and prospects: in-depth analysis of current research and future directions","authors":"Bowen Zheng ,&nbsp;Zhichao Deng ,&nbsp;Zhenhao Luo ,&nbsp;Shuoyuan Mao ,&nbsp;Minggao Ouyang ,&nbsp;Xuebing Han ,&nbsp;Hewu Wang ,&nbsp;Yalun Li ,&nbsp;Yukun Sun ,&nbsp;Depeng Wang ,&nbsp;Yuebo Yuan ,&nbsp;Liangxi He ,&nbsp;Zhi Yang ,&nbsp;Yanlin Zhu","doi":"10.1016/j.apenergy.2025.126688","DOIUrl":"10.1016/j.apenergy.2025.126688","url":null,"abstract":"<div><div>With the rapid development of global energy transition and low-carbon technologies, lithium-ion battery, as the core energy storage unit, is highly dependent on accurate battery modelling for its performance enhancement and safety management. Battery modelling has gone through a development process from mechanism-driven to data-driven, and from single-scale to multi-scale fusion, forming three main technology systems: Firstly, the equivalent circuit model (ECM), based on the Thevenin framework, uses RC networks to fit battery external characteristics. With hysteresis module embedding and genetic algorithm optimization, it enables millisecond-level responses in BMS real-time control, showing engineering application advantages. However, its modelling logic is limited to port characteristics, lacking deep physical mechanism explanation. Secondly, the physical field model, based on porous electrode theory and partial differential equations, accurately describes lithium-ion transport and electrochemical kinetics, supporting new battery material research and development. Yet, its high computational complexity hinders fast calculation despite mechanistic precision. Lastly, data-driven models leverage data-driven approaches for strong generalization in nonlinear tasks like SOC/RUL prediction. Hybrid architectures improve cross-scenario accuracy via multimodal fusion but suffer from weak interpretability and poor small-sample adaptability. This paper systematically compares the modelling principles, computational costs, prediction accuracies, and typical applications of these three types of models, and analyses the engineering adaptation advantages of the equivalent circuit model, the mechanistic depth of the physical field model, and the data-driven potential of the black box model. Meanwhile, this paper also points out the common challenges faced by traditional models in terms of novel battery system adaptability, multi-field coupling modelling complexity, and deployment of edge computing devices. The research outlook will focus on multi-scale hybrid modelling and data-driven fusion, combined with current large model applications, to provide theoretical support and technical paths for battery R&amp;D, system design and full life cycle management.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126688"},"PeriodicalIF":11.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060244","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":"Hierarchical distributed optimization based bidding algorithm for electric water heater flexibility aggregators in nordic energy activation markets","authors":"Surya Venkatesh Pandiyan,&nbsp;Jayaprakash Rajasekharan,&nbsp;Sebastien Gros","doi":"10.1016/j.apenergy.2025.126662","DOIUrl":"10.1016/j.apenergy.2025.126662","url":null,"abstract":"<div><div>Coordinated flexibility from electric water heaters (EWHs) holds significant potential to provide frequency regulation services through reserve markets, particularly manual frequency restoration reserve (mFRR) in near real-time Energy Activation Markets (EAM). To fully exploit this potential, EWH aggregators require bidding algorithms that are not only high-performing but also scalable and computationally efficient. This work introduces a model predictive control (MPC)-based optimization model and proposes a novel Hierarchical Distributed Optimization (HDO) algorithm specifically designed to meet these demands. The proposed HDO algorithm adopts a two-level hierarchical structure: the upper-level focuses on binary bidding decisions (i.e., to bid or not), while the lower-level manages control decisions for individual EWHs. An iterative coordination approach is developed in which both levels are solved sequentially and iteratively until convergence is reached. A problem-specific heuristic is developed for the upper-level, integrating local search techniques with shadow price (dual variable) information to enhance tractability and improve computational efficiency. At the lower-level, Lagrangian dual decomposition is employed to decompose the centralized problem into smaller, independent sub-problems, each corresponding to an individual EWH, which can be solved in parallel during dual ascent, thereby significantly improving scalability. To further accelerate convergence during dual ascent, a Newton-based dual update strategy is incorporated, improving performance over standard gradient-based methods. Performance evaluation under deterministic setting for providing up-regulation service, using real-world market price data and synthetic hot water demand profiles, demonstrates that the proposed method achieves significant computational gains and scalability while delivering solutions with optimality levels comparable to a centralized commercial solver.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126662"},"PeriodicalIF":11.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An innovative coordinated control strategy for frequency regulation in power systems with high renewable penetration","authors":"Tengxi Zhang ,&nbsp;Ruifeng Shi ,&nbsp;Limin Jia ,&nbsp;Kwang Y. Lee","doi":"10.1016/j.apenergy.2025.126700","DOIUrl":"10.1016/j.apenergy.2025.126700","url":null,"abstract":"<div><div>As the share of solar and wind energy in power systems increases, the decline of traditional frequency regulation resources results in frequency instability in low-inertia systems. Traditional approaches relying on synchronous generators (SGs) face challenges in providing adequate frequency response, necessitating advanced control technologies for asynchronous units to stabilize frequency. This paper aims to improve system frequency dynamics and proposes an enhanced Dynamic Scheduling Control Strategy (DSCS) integrated with a Deep Reinforcement Learning (DRL) framework to optimize the coordination of frequency responses between SGs and power electronics-interfaced asynchronous resources in hybrid power systems (HyPS). Firstly, a scalable system frequency model of the HyPS with high renewable energy source (RES) penetration is developed, accounting for the frequency support provided by RESs under varying operational conditions. Secondly, the DRL framework is integrated and leverages the frequency dynamics analysis of the Generic System Frequency Response (G-SFR) model to establish the reward mechanism. Lastly, a 36-bus system is employed to evaluate frequency dynamics under various disturbances and renewable penetrations, showing that while the fundamental DSCS scheme maintains the frequency nadir above 49.5 Hz, the proposed method achieves a 3.73 % reduction in RMS frequency deviation through adaptive optimization in simulated daily operation. The proposed method significantly enhances frequency stability in low-inertia systems with high renewable penetration without modifying the reserve capacities of the controlled units, and its further potential is discussed in scenarios involving additional reserve allocation by renewable units.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126700"},"PeriodicalIF":11.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060241","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":"Multi-distribution fusion based Bayesian deep neural network for short-term probabilistic electricity price forecasting","authors":"Zhen Shao ,&nbsp;Guowei Zhu ,&nbsp;Yating Han ,&nbsp;Jianrui Zha ,&nbsp;Changhui Yang ,&nbsp;Fangyi Li","doi":"10.1016/j.apenergy.2025.126712","DOIUrl":"10.1016/j.apenergy.2025.126712","url":null,"abstract":"<div><div>Probabilistic electricity price forecasting (EPF) is paramount for stakeholder scheduling and trading in deregulated energy markets. However, during the process of establishing a probability prediction model, the consequential aleatoric and epistemic uncertainties are indistinguishable. This indistinguishability undermines the credibility and interpretability of forecasts, especially in complex and volatile electricity markets. This article proposes a hybrid approach under a Bayesian probability framework for performing reliable and accurate probabilistic forecasting. Specifically, it applies Bayesian deep learning model to convey the latent probability distribution of electricity prices, which represents the desirable epistemic uncertainty and inevitable aleatoric uncertainty. The embedded architecture employs a multi-head attention mechanism (MHAM) to allocate previous hidden states of long short-term memory (LSTM) cells, detecting both the local and global price patterns simultaneously. Considering the forecasting bias arising from aleatoric uncertainty in the process of establishing Bayesian networks, a new Wasserstein distance-based multi-distribution fusion mechanism driven by evidence theory is proposed and employed to identify and mitigate the aleatoric uncertainty of credible probabilistic EPF problems. The effectiveness of the proposed approach is evaluated on two real-world electricity price datasets and compared with fifteen state-of-the-art models. The proposed approach achieves CRPS scores of 6.50 and 10.21 on the respective datasets, outperforming other benchmark models and demonstrating superior predictive accuracy and robustness across diverse market conditions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126712"},"PeriodicalIF":11.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060239","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}