Energy Conversion and Management-X最新文献

{"title":"Carbon-based electrocatalysts for hydrogen evolution reaction","authors":"Khalid Ahmed ,&nbsp;Summaiya Hameed ,&nbsp;Kumar Patchigolla ,&nbsp;Nashwan Dawood ,&nbsp;Zafar Khan Ghouri","doi":"10.1016/j.ecmx.2025.100892","DOIUrl":"10.1016/j.ecmx.2025.100892","url":null,"abstract":"<div><div>In the pursuit of clean and sustainable hydrogen energy production, water splitting has emerged as a promising method. However, the cost and scarcity of Pt-group metals as effective electrocatalysts hydrogen evolution reaction (HER) poses challenges for widespread application. Transition metal compounds have shown potential as alternatives, the search for highly active HER catalysts from abundant and cost-effective materials persists. Carbon-based compounds offer an appealing solution, leveraging their unique hybridization properties for tailored manipulation of structures and morphologies. By enhancing the electrocatalytic activity of carbon-based catalysts through the incorporation of transition metal nanoparticles and nonmetal doping into the carbon skeleton, new active sites for HER can be generated. This review aims to explore the activity, durability, and efficiency of various electrocatalysts for water splitting, with a particular emphasis on non-noble-metal-based and metal-free electrocatalysts. By highlighting the recent progress in carbonaceous materials for hydrogen evolution reaction in both acidic and alkaline media, the review seeks to provide insights into new strategies and opportunities for enhancing electrocatalytic performance and stability. Ultimately, the goal is to empower ongoing research efforts, stimulate innovation, and overcome existing limitations for hydrogen energy production.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100892"},"PeriodicalIF":7.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind farm analysis using SailoR diagram-based diagnostics to quantify yaw misalignment correction","authors":"Alain Ulazia ,&nbsp;Gabriel Ibarra-Berastegi ,&nbsp;Jon Sáenz ,&nbsp;Sheila Carreno-Madinabetia ,&nbsp;Unai Elosegui","doi":"10.1016/j.ecmx.2025.100890","DOIUrl":"10.1016/j.ecmx.2025.100890","url":null,"abstract":"<div><div>This study introduces a novel application of indices derived from the SailoR diagram for detecting and correcting yaw misalignment in wind turbines, which involves an original visualization of principal component analysis. The angular disparity between principal components, visualized as ellipses on the SailoR diagram, serves as a metric for comparing deviations between anemometers within a designated group (External Deviation index) and between the turbine’s anemometer and its yaw angle system (Internal Deviation index). A normalized criterion, incorporating anomalies in power production (Power Bias index), yaw angle, and absolute angle deviation, is established to compare the error of each turbine relative to its respective group. By integrating these indices with the general deviation of each turbine, the analysis effectively discriminates between external and internal error sources and quantifies the magnitude of each deviation. A case study involving a real wind farm with three distinct turbine groups demonstrates the efficacy of this integrated methodology as a valuable tool for initial diagnosis, enabling the identification, discrimination (internal/external), and quantification of yaw misalignment.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100890"},"PeriodicalIF":7.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of vortex water turbine design for sustainable energy generation (principles, optimization, and validation)","authors":"Zamzami ,&nbsp;Akhyar Akhyar ,&nbsp;Sarwo Edhy Sofyan ,&nbsp;Suriadi ,&nbsp;Khairil","doi":"10.1016/j.ecmx.2025.100895","DOIUrl":"10.1016/j.ecmx.2025.100895","url":null,"abstract":"<div><div>This paper provides a thorough analysis of water vortex turbines, emphasizing their role in enhancing sustainable energy generation in situations of limited water flow. The research examines fundamental design elements such as the impact of water flow rate and basin size on turbine effectiveness. Additionally, it explores key factors in turbine blade design, such as shape, quantity, material composition, and the effects of turbine placement within the vortex on operational efficiency. The significance of optimization techniques in enhancing water vortex turbine technology is examined, with a specific focus on numerical optimization and computational fluid dynamics (CFD). These methodologies play a crucial role in enhancing turbine design to attain maximum performance outcomes. The analysis of design factors such as blade shape, blade angle, and flow configuration is essential in evaluating their influence on energy generation and effectiveness. The significance of experimental validation through prototype testing and performance analysis is also highlighted in this article. Prototype testing offers empirical data on shaft power, torque, and efficiency, while performance analysis involves comparing these findings with theoretical predictions to confirm the design’s effectiveness. The article explores advancements in intelligent water vortex turbine design, incorporating cutting-edge manufacturing methods like Computer-Aided Design (CAD) modeling, simulation, and 3D printing. This technology enables accurate design and production of intricate shapes, enhances turbine efficiency, and ensures efficient water sealing. In summary, this assessment underscores the significant promise of water vortex turbines in generating sustainable energy, particularly in regions with limited water flow. The incorporation of optimization methods and advanced manufacturing processes allows for the creation of highly effective and dependable water vortex turbines, establishing them as a feasible option in the realm of renewable energy. Suggestions for future research include enhancing turbine design and confirming its performance in practical settings.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100895"},"PeriodicalIF":7.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sorghum straw pellets: A dispatchable energy source for renewable energy transition","authors":"Bruno Rafael de Almeida Moreira,&nbsp;Damian Hine,&nbsp;Ian D. Godwin,&nbsp;Sudhir Yadav","doi":"10.1016/j.ecmx.2025.100893","DOIUrl":"10.1016/j.ecmx.2025.100893","url":null,"abstract":"<div><div>The global transition to renewable energy is challenged by factors like intermittent solar and wind power, particularly in countries like Australia, where diverse landscapes and unique weather conditions add complexity. Biomass-to-solid fuels offer a reliable, dispatchable energy solution. This review synthesises the literature on sorghum biomass pelleting and evaluates its bioenergy potential, integrating data from the Sorghum Harvest Report and the Australian Biomass for Bioenergy Assessment. The pelleting process significantly enhances the energy density of sorghum straw from 3.7 GJ/m3 to 10.2 GJ/m3. If all available sorghum straw were converted into pellets, it could generate approximately 165.8 PJ/yr of bioenergy, representing 15.4% of Australia’s agricultural bioenergy potential (1077.5 PJ/yr). Sorghum-based pellets could contribute 43.5% to Australia’s bioelectricity potential (380.9 PJ/yr), surpassing other bioenergy sources, including cane bagasse (26.3%) and wood (23.4%). The use of sorghum straw pellets for bioenergy production has the potential to enable Australia to produce clean, reliable, and affordable energy, while providing new income opportunities for sorghum growers and contributing to rural economic development. This review also addresses sustainability concerns, such as the “fuel-food-feed” dilemma, proposing strategies for strategic resource allocation, the protection of marine ecosystems from agricultural runoff, and the repurposing of abandoned mining sites. By elucidating the availability and quality of sorghum straw, this study mitigates uncertainties that hinder the development of scalable biomass-to-pellet conversion technologies. The findings contribute to the broader discourse on achieving a sustainable, net-zero energy transition in Australia, with potential global implications for the development of decentralised, dispatchable renewable energy solutions.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100893"},"PeriodicalIF":7.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aerodynamic optimization of small diffuser Augmented Wind Turbines: A differential evolution approach","authors":"Turan Dias Oliveira,&nbsp;Luzia Aparecida Tofaneli,&nbsp;Alex Álisson Bandeira Santos","doi":"10.1016/j.ecmx.2025.100891","DOIUrl":"10.1016/j.ecmx.2025.100891","url":null,"abstract":"<div><div>In order to contain the increase in the concentration of CO2 in the atmosphere and its harmful consequences, studies point to the need to increase the participation of non-fossil energy in the world energy matrix. Among the possible alternatives, wind energy has proven to be economically viable and has its growth established in a global scenario. Although a large part of wind generation occurs due to large turbines, small wind turbines meet the demands of distributed and isolated generation. The efficiency of wind turbines, however, is theoretically limited and one possible way to improve the use of wind energy is the use of Diffuser Augmented Wind Turbines (DAWTs). This work aims to study the impact of wind characteristics on the optimal aerodynamic design of a DAWT blade considering non-uniform flow generated using the diffuser. A new expression for the correction of thrust coefficients for high values of axial induction factor is proposed, so that it is suitable for the evaluation of turbines with and without diffusers. Differential Evolution (DE) is used for the evolution of an initial random population of wind turbine rotors to an optimum final population, maximizing energy conversion. The aptitude of each individual to be evolved is evaluated through Blade Element Momentum (BEM) method, using the proposed correction equation. The optimized variables modify the rotor rotation, chord and twist distributions along the turbine radius and pitch angle. The proposed BEM approach, when compared to experimental results for turbines with and without diffusers, showed an average discrepancy of 4.45% for turbines without diffusers and 0.28% for turbines with diffusers, better agreement than other approaches found in the literature. Through the DE optimization it was noted that most of the parameters studied were highly dependent on the wind regime. The use of diffusers in turbines optimized for operation without diffusers allowed for an energy production improvement of up to 28.4% and proved to be dependent on the geometry of the diffuser and the wind regime. A specific optimization process for diffuser operation can lead to energy production improvement up to 32.6% and may affect the benefit of installing the device by up to 22.7%.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100891"},"PeriodicalIF":7.1,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143104312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-economic analysis of a novel clc reactor-based system for energy storage and back-up power in a cruise ship","authors":"Lucas F. Calvo ,&nbsp;María Elena Diego ,&nbsp;Marco Astolfi","doi":"10.1016/j.ecmx.2025.100885","DOIUrl":"10.1016/j.ecmx.2025.100885","url":null,"abstract":"<div><div>This study investigates the performance of a novel carbon-free CLC fixed-bed reactor system proposed as a sustainable alternative to store and supply the energy demand of a 7-day Mediterranean cruise ship travelling between Spain and Italy. During navigation, propulsive and hotelling energy demand of the <em>MSC Magnifica</em> vessel is supplied by the slow diffusion-controlled oxidation of a batch of reduced fine iron-based solids, which allows to heat up a flow of pressurized air that is used to generate electricity in a downstream gas turbine and high-grade heat.<!--> <!-->This arrangement imposes very long oxidation times for the reacting solids, thus moderating bed temperatures and avoiding hot spots. An oxygen diffusion-based reactor model is employed to design and model the performance of the multi-reactor system employed, which consists of 22 high energy density reactors of 15 m length and 2.1 m² cross section with a maximum power output of 20 MW_th each. The reactors are integrated in a recuperative gas power cycle that allows fulfilling navigation energy requirements for the 7-day trip with cycle efficiencies up to 45.8 %. During in-port periods, particles are reduced using electrolytic H₂, whereas hoteling energy needs are provided by H₂-fired auxiliary boilers and the gas turbine system powered by a H₂-fired external combustor. An economic analysis shows that the proposed carbon-free system can be competitive against conventional heavy fuel oil combustion options in several scenarios with H₂ cost of 1.5–2.5 €/kg, carbon tax between 90 and 205 €/ton CO₂ and moderate capacity factors (&gt;40 trips per year). Higher H₂ costs and/or lower carbon tax values can be also accommodated with a moderate increase in the passenger ticket below 13 %.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100885"},"PeriodicalIF":7.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing photovoltaic parameters with Monte Carlo and parallel resistance adjustment","authors":"Fatima Wardi ,&nbsp;Mohamed Louzazni ,&nbsp;Mohamed Hanine ,&nbsp;Elhadi Baghaz ,&nbsp;Sanjeevikumar Padmanaban","doi":"10.1016/j.ecmx.2024.100833","DOIUrl":"10.1016/j.ecmx.2024.100833","url":null,"abstract":"<div><div>Photovoltaic power has emerged as an important component global energy revolution, providing a renewable and sustainable alternative for electricity generation. This paper describes how to use Monte Carlo optimisation (MCO) to estimate and extract the intrinsic electrical parameters of single, double, and triple diode designs, as well as make parallel resistance modifications. The above method was used to solve challenges related to nonlinear and complex solar cell equation. The function’s objective is to minimize the discrepancy between the experimental and calculated current values. Three different technologies are implemented to retrieve the fundamental parameters: RTC France solar cell, the Photowatt-PWP201 PV module, and the Schutten Solar STM6-40/36 monocrystalline solar module. In addition, the restricted objective function is computed using the experimental current–voltage curve. The extracted parameters using MCO are compared to contemporary research publications on metaheuristic optimization algorithms, iterative approaches, and analytical methods. In the end, to evaluate the algorithm’s effectiveness, statistical measurements such as Individual Absolute Error (IAE), Relative Error (RE), Mean Absolute Error (MAE), SD, TS, NFM, ACF, and RMSE are calculated to ensure the correctness of the generated parameters. The comparative study shows that the results generated by the MCO approach exhibit lower errors compared to other algorithms where RMSE reaches 0.0058.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"25 ","pages":"Article 100833"},"PeriodicalIF":7.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-layer Modeling of Bifacial Photovoltaic Panels: Evaluating the Accuracy of One-, Three-, and Five-layer Models","authors":"Mohammad Hassan Shahverdian ,&nbsp;Hoseyn Sayyaadi ,&nbsp;Ali Sohani","doi":"10.1016/j.ecmx.2025.100879","DOIUrl":"10.1016/j.ecmx.2025.100879","url":null,"abstract":"<div><div>Bifacial solar panels (BSP) absorb sunlight from both sides. BSP has gained significant popularity by increasing energy efficiency and reducing the need for more space. To predict the performance of BSP, it is necessary to perform three analyzes, optical, thermal, and electrical simultaneously, because the power generated is influenced by the surface temperature and vice versa. For the thermal modeling of the BSP, the solar panel can be examined in different layers. In this study, thermal modeling is conducted in the one, three-, and five-layer models, and these models are compared with each other from the point of view of produced power and panel temperature to determine the accuracy of each approach. A BSP is considered in the climatic conditions of Tehran, Iran. Finally, the result was obtained that in the annual analysis, the amount of energy produced by the five, three, and one-layer models is 1242.2, 1244.0, and 1246.6 kWh, respectively. The variation between the five-layer and one-layer model is 0.36 %, between the three-layer and one-layer is 0.21 %, and between the five-layer and three-layer is 0.15 %. As a result, considering the model with more layers, does not necessarily increase the accuracy of the analysis, significantly.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"25 ","pages":"Article 100879"},"PeriodicalIF":7.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ANN-driven prediction of optimal machine learning models for engine performance in a dual-fuel mode powered by biogas and fish oil biodiesel","authors":"Naveen Kumar Pallicheruvu,&nbsp;Sakthivel Gnanasekaran","doi":"10.1016/j.ecmx.2024.100827","DOIUrl":"10.1016/j.ecmx.2024.100827","url":null,"abstract":"<div><div>Global climate change is increasingly driven by carbon dioxide emissions from fossil fuels, intensifying the greenhouse effect and global warming. Biodiesel, particularly fish oil biodiesel, provides a sustainable alternative that reduces greenhouse gas (GHG) emissions. In this study, the engine was tested with various blends of fish oil biodiesel and conventional diesel, using volume ratios from 20 % to 40 % in 5 % increments. Subsequently, it was operated in dual-fuel mode with two mixtures: (a) Pure Methane (CH₄) and (b) Methane (CH₄) + Carbon dioxide (CO₂). These were injected through the intake manifold at flow rates of 4, 8, and 12 LPM, alongside fresh air and the biodiesel blends. Performance analysis included emissions and combustion characteristics. These comprised nitrogen oxides (NOx), smoke, hydrocarbons (HC), carbon dioxide (CO₂), carbon monoxide (CO), brake thermal efficiency (BTE), peak pressure (PP), maximum pressure rise rate (MPRR), and vibrational characteristics under varying biogas flow rates and engine loads. Engine performance was monitored using vibrational data analysed by machine learning (ML) models based on Bayes net and random forest algorithms. B25 blend combined with M7.2C4.8 (i.e., methane 7.2 LPM and CO₂ 4.8 LPM) stands out as the top performer, achieving the highest classification accuracy at 97 %. The combustion and emission parameters for the optimal blend were predicted using a feedforward backpropagation artificial neural network (ANN) employed a 3–12-8 neuron architecture. Additionally, vibrational characteristics were analysed with another ANN configured as 2–4-4–5. The results showed that these ANN models effectively predicted engine parameters under different load conditions and achieved average R-values of 0.97 and 0.98, respectively. The B25 blend significantly reduced emissions and enhanced combustion efficiency. This highlights its potential in mitigating GHG emissions and promoting sustainable alternative fuels.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"25 ","pages":"Article 100827"},"PeriodicalIF":7.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"K-means and agglomerative clustering for source-load mapping in distributed district heating planning","authors":"Amir Shahcheraghian ,&nbsp;Adrian Ilinca ,&nbsp;Nelson Sommerfeldt","doi":"10.1016/j.ecmx.2024.100860","DOIUrl":"10.1016/j.ecmx.2024.100860","url":null,"abstract":"<div><div>This study introduces a high-resolution, data-driven approach for optimizing district heating networks using source-load mapping, focusing on Stockholm as a case study. The methodology integrates detailed building energy performance data (2014–2022) with geographic data from the Swedish Survey Agency, employing advanced clustering techniques such as K-means Clustering, Agglomerative Clustering, DBSCAN, Spectral Clustering, and Gaussian Mixture Model (GMM) Clustering to identify optimal locations for distributed heat sources, including data centers, supermarkets, and water bodies. Quantitative results show that these environmentally friendly sources could supply 54 % of Stockholm’s total annual heat demand of 7.7 TWh/year, equating to 4.2 TWh from residual heat sources. Data centers contribute 0.48 TWh, water bodies provide 3.4 TWh, and supermarkets contribute 0.3 TWh annually. Economic analysis further reveals that 98 % of residual heat sources are economically viable, with marginal costs of heat (MCOH) for data centers, supermarkets, and water bodies estimated at 12.7 EUR/MWh, 16.0 EUR/MWh, and 20.0 EUR/MWh, respectively—well below the Open District Heating (ODH) market price of 22.0 EUR/MWh. The policy implications of these findings are profound. Policymakers can leverage this methodology to identify economically viable heat sources, enabling the creation of regulations that incentivize the integration of distributed heat sources into existing district heating networks. This can lead to reduced energy costs, enhanced sustainability, and more resilient energy systems. Practically, urban planners and energy utilities can use clustering insights to optimize the placement of new infrastructure, such as data centers, ensuring they are strategically located in high-demand zones. Furthermore, the study’s methodology can be replicated in other urban contexts, offering cities worldwide a scalable tool for improving the efficiency and sustainability of their heating networks. These findings support the transition to low-carbon energy solutions and provide actionable recommendations for the long-term development of urban energy systems.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"25 ","pages":"Article 100860"},"PeriodicalIF":7.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143182285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}