Pub Date : 2024-11-22DOI: 10.1016/j.enconman.2024.119301
Min-Gyu Ham, Seong-Yong Woo, Kyung-Hun Kim, Se-Hoon Oh, Seung Jin Oh, Kyaw Thu, Young-Deuk Kim
Dissipating the adsorption heat generated during air dehumidification and providing the desorption heat required for regeneration pose significant challenges in energy-intensive adsorptive air-dehumidification systems. We present an adsorptive-dehumidification system that utilizes a heat pipe–based desiccant-coated heat-exchanger (DCHE) module to overcome the limitations of conventional adsorptive-dehumidification systems. The DCHE-module fabrication involved the synthesis of a composite adsorbent using silica gel, binders (styrene-butadiene rubber and carboxymethyl cellulose), and a graphene solution, followed by an analysis of its physical properties. Although the composite adsorbent exhibited a 21 % lower water–vapor uptake than virgin silica gel, its thermal conductivity was approximately 25 times higher, indicating a notable advantage of the DCHE over a desiccant-packed heat exchanger (DPHE). The performance of the proposed adsorptive-dehumidification system was evaluated in terms of various operating parameters, including the regeneration inlet temperature and cycle time, with emphasis on the moisture removal rate (MRR) and cooling capacity (CC). Under specific conditions, the proposed adsorptive-dehumidification system achieved an MRR of 52.17 g/h and CC of 52.05 W. Sustainable dehumidification and regeneration was achieved by recovering heat from the heat pipes without requiring additional cooling and heating to dissipate the adsorption and desorption heat. Consequently, the maximum coefficient of performance of the system with a single DCHE module under the given operating conditions was approximately 2.60, which can be enhanced by a linear increase in dehumidification capacity with the multi-stage module design. These findings demonstrate a viable approach for developing low-energy, sustainable dehumidification systems that will ultimately contribute to the implementation of net-zero buildings.
{"title":"Performance and feasibility assessment of an adsorptive-dehumidification system utilizing a heat pipe-based desiccant-coated heat exchanger","authors":"Min-Gyu Ham, Seong-Yong Woo, Kyung-Hun Kim, Se-Hoon Oh, Seung Jin Oh, Kyaw Thu, Young-Deuk Kim","doi":"10.1016/j.enconman.2024.119301","DOIUrl":"https://doi.org/10.1016/j.enconman.2024.119301","url":null,"abstract":"Dissipating the adsorption heat generated during air dehumidification and providing the desorption heat required for regeneration pose significant challenges in energy-intensive adsorptive air-dehumidification systems. We present an adsorptive-dehumidification system that utilizes a heat pipe–based desiccant-coated heat-exchanger (DCHE) module to overcome the limitations of conventional adsorptive-dehumidification systems. The DCHE-module fabrication involved the synthesis of a composite adsorbent using silica gel, binders (styrene-butadiene rubber and carboxymethyl cellulose), and a graphene solution, followed by an analysis of its physical properties. Although the composite adsorbent exhibited a 21 % lower water–vapor uptake than virgin silica gel, its thermal conductivity was approximately 25 times higher, indicating a notable advantage of the DCHE over a desiccant-packed heat exchanger (DPHE). The performance of the proposed adsorptive-dehumidification system was evaluated in terms of various operating parameters, including the regeneration inlet temperature and cycle time, with emphasis on the moisture removal rate (MRR) and cooling capacity (CC). Under specific conditions, the proposed adsorptive-dehumidification system achieved an MRR of 52.17 g/h and CC of 52.05 W. Sustainable dehumidification and regeneration was achieved by recovering heat from the heat pipes without requiring additional cooling and heating to dissipate the adsorption and desorption heat. Consequently, the maximum coefficient of performance of the system with a single DCHE module under the given operating conditions was approximately 2.60, which can be enhanced by a linear increase in dehumidification capacity with the multi-stage module design. These findings demonstrate a viable approach for developing low-energy, sustainable dehumidification systems that will ultimately contribute to the implementation of net-zero buildings.","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"58 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142684265","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}
Over the past decades, the increasing energy demand has accelerated the construction of wind farms, raising higher expectations for precise load and power assessments in wind turbine performance. Traditional methods, which rely on analytical wake models and performance curves, often fail to adapt to complex inflow scenarios, leading to significant inaccuracies in predicting turbine loads and power output. This research addresses these challenges by introducing a novel two-phase framework for various phases of wind farm planning and development, using the NREL 5MW baseline wind turbine as a case study. The first part involves deriving recommended values for simplified thrust modulation factors at the preliminary design phase, enabling swift evaluation of maximum and fatigue thrust loads crucial for wind farm optimization. The second part focuses on designing and training a machine learning model at the detailed design phase. A gradient-boosting-based framework based on LightGBM provides comprehensive methods for assessing wind turbine load and power, enhancing the precision and efficiency of these assessments. The proposed model achieves significant improvements in predictive accuracy, achieving mean R-Squared of 0.995, 0.988, and 0.995 for power, peak load, and damage equivalent load evaluation, respectively. The framework streamlines the assessment process, enhancing both the accuracy and speed of power and load evaluations for wind farm design. This is expected to reduce computational costs and improve the effectiveness of downstream tasks, such as layout optimization and wake steering.
{"title":"Towards machine learning applications for structural load and power assessment of wind turbine: An engineering perspective","authors":"Qiulei Wang, Junjie Hu, Shanghui Yang, Zhikun Dong, Xiaowei Deng, Yixiang Xu","doi":"10.1016/j.enconman.2024.119275","DOIUrl":"https://doi.org/10.1016/j.enconman.2024.119275","url":null,"abstract":"Over the past decades, the increasing energy demand has accelerated the construction of wind farms, raising higher expectations for precise load and power assessments in wind turbine performance. Traditional methods, which rely on analytical wake models and performance curves, often fail to adapt to complex inflow scenarios, leading to significant inaccuracies in predicting turbine loads and power output. This research addresses these challenges by introducing a novel two-phase framework for various phases of wind farm planning and development, using the NREL 5MW baseline wind turbine as a case study. The first part involves deriving recommended values for simplified thrust modulation factors at the preliminary design phase, enabling swift evaluation of maximum and fatigue thrust loads crucial for wind farm optimization. The second part focuses on designing and training a machine learning model at the detailed design phase. A gradient-boosting-based framework based on LightGBM provides comprehensive methods for assessing wind turbine load and power, enhancing the precision and efficiency of these assessments. The proposed model achieves significant improvements in predictive accuracy, achieving mean R-Squared of 0.995, 0.988, and 0.995 for power, peak load, and damage equivalent load evaluation, respectively. The framework streamlines the assessment process, enhancing both the accuracy and speed of power and load evaluations for wind farm design. This is expected to reduce computational costs and improve the effectiveness of downstream tasks, such as layout optimization and wake steering.","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"67 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142696818","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}
Under the transition from a traditional energy structure to renewable energy with zero carbon emissions over the whole life cycle, wind power is a typical form of renewable energy-based power generation, and the life cycle carbon emissions of wind power projects have become the focus of global attention. Because the fluctuation and randomness of wind energy directly affect the carbon emissions of wind power projects, accurately predicting wind power projects’ carbon emissions and environmental impacts during their service life is impossible. The coastal wind farm in Qinhuangdao City, China, is taken as the research case without considering the wake effect between wind turbines. A predictive composite whole-life carbon emission accounting system is constructed with the impact of wind conditions, an emission reduction indicator system is established around the entire life cycle, and the emission reduction capacity of wind power is compared with that of traditional thermal power engineering. The results show that the net carbon emission reduction of the wind power project is 7.62 E + 04 t CO2e, and net emissions are reduced by 1.35 E + 06 t CO2e compared with traditional thermal power units of the same power level. The emission reduction level reaches 71.47 %, and the return rate of emission reduction increases by 357.46 % compared with thermal power units. The return cycle of the carbon emission reduction input is 4.98 years. The research results provide an effective accounting framework for the carbon emissions and emission reduction potential of coastal wind power projects and show that the popularization and application of wind turbines can help achieve carbon peak and neutrality.
在传统能源结构向全生命周期零碳排放的可再生能源转型的背景下，风力发电是一种典型的以可再生能源为基础的发电形式，风电项目的生命周期碳排放成为全球关注的焦点。由于风能的波动性和随机性直接影响风电项目的碳排放量，因此无法准确预测风电项目在其寿命期内的碳排放量和对环境的影响。本文以中国秦皇岛市沿海风电场为研究案例，在不考虑风机之间的尾流效应的情况下，对风电场的碳排放进行了预测。以秦皇岛市沿海风电场为研究案例，在不考虑风电机组之间的尾流效应的情况下，构建了风况影响的预测性复合全生命周期碳排放核算体系，建立了全生命周期的减排指标体系，并将风电的减排能力与传统火电工程的减排能力进行了比较。结果表明，风电项目的碳净减排量为 7.62 E+04 t CO2e，与同功率等级的传统火电机组相比，净减排量减少了 1.35 E+06 t CO2e。与火电机组相比，减排水平达到 71.47%，减排回报率提高了 357.46%。碳减排投入的回报周期为 4.98 年。研究成果为沿海风电项目的碳排放和减排潜力提供了有效的核算框架，表明风电机组的推广应用有助于实现碳峰值和碳中和。
{"title":"Life cycle carbon emission accounting of a typical coastal wind power generation project in Hebei Province, China","authors":"Wei Gao, Mengyao Han, Lijuan Chen, Chao Ai, Siyuan Liu, Shengwei Cao, Longzheng Wei","doi":"10.1016/j.enconman.2024.119243","DOIUrl":"https://doi.org/10.1016/j.enconman.2024.119243","url":null,"abstract":"Under the transition from a traditional energy structure to renewable energy with zero carbon emissions over the whole life cycle, wind power is a typical form of renewable energy-based power generation, and the life cycle carbon emissions of wind power projects have become the focus of global attention. Because the fluctuation and randomness of wind energy directly affect the carbon emissions of wind power projects, accurately predicting wind power projects’ carbon emissions and environmental impacts during their service life is impossible. The coastal wind farm in Qinhuangdao City, China, is taken as the research case without considering the wake effect between wind turbines. A predictive composite whole-life carbon emission accounting system is constructed with the impact of wind conditions, an emission reduction indicator system is established around the entire life cycle, and the emission reduction capacity of wind power is compared with that of traditional thermal power engineering. The results show that the net carbon emission reduction of the wind power project is 7.62 E + 04 t CO<ce:inf loc=\"post\">2</ce:inf>e, and net emissions are reduced by 1.35 E + 06 t CO<ce:inf loc=\"post\">2</ce:inf>e compared with traditional thermal power units of the same power level. The emission reduction level reaches 71.47 %, and the return rate of emission reduction increases by 357.46 % compared with thermal power units. The return cycle of the carbon emission reduction input is 4.98 years. The research results provide an effective accounting framework for the carbon emissions and emission reduction potential of coastal wind power projects and show that the popularization and application of wind turbines can help achieve carbon peak and neutrality.","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"6 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142696821","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}
Pub Date : 2024-11-22DOI: 10.1016/j.enconman.2024.119299
Kunpeng Yuan, Binghong Chen, Shiquan Shan, Jun Shu, Qiguo Yang
Near-field radiative heat transfer enhances the intensity of the thermal radiation significantly through evanescent waves, while the combination of selective emitters can effectively improve the output power and system efficiency of solar thermophotovoltaic systems. By calculating the polariton dispersion relation between different layers and combining the energy transmission coefficient of the emitter at different layers, the mechanism by which the emitter enhances near-field radiative heat transfer was analyzed. Concurrently, a comprehensive consideration was given to the conversion of solar radiation to thermal energy, the transformation of thermal radiation into electrical energy, and the impact of the circulating water-cooling system on performance. The analysis indicates that with concentration ratio of > 70 and operating temperatures ranging from 900 K to 1200 K, the output power of near-field solar thermophotovoltaic system can achieve a range of 8905 W/m2 to 52875 W/m2, and the system efficiency can be stably maintained above 20 %.
近场辐射传热通过蒸发波显著增强了热辐射强度，而选择性发射器的组合则能有效提高太阳能热光电系统的输出功率和系统效率。通过计算不同层间的极化子色散关系，并结合发射器在不同层的能量传输系数，分析了发射器增强近场辐射传热的机理。同时，综合考虑了太阳辐射向热能的转化、热辐射向电能的转化以及循环水冷却系统对性能的影响。分析表明，在浓度比为 70、工作温度为 900 K 至 1200 K 的条件下，近场太阳能光热发电系统的输出功率可达 8905 W/m2 至 52875 W/m2，系统效率可稳定保持在 20% 以上。
{"title":"Cylindrical near-field solar thermophotovoltaic system with multilayer absorber/emitter structures: Integrated solar radiation absorption and cooling energy consumption","authors":"Kunpeng Yuan, Binghong Chen, Shiquan Shan, Jun Shu, Qiguo Yang","doi":"10.1016/j.enconman.2024.119299","DOIUrl":"https://doi.org/10.1016/j.enconman.2024.119299","url":null,"abstract":"Near-field radiative heat transfer enhances the intensity of the thermal radiation significantly through evanescent waves, while the combination of selective emitters can effectively improve the output power and system efficiency of solar thermophotovoltaic systems. By calculating the polariton dispersion relation between different layers and combining the energy transmission coefficient of the emitter at different layers, the mechanism by which the emitter enhances near-field radiative heat transfer was analyzed. Concurrently, a comprehensive consideration was given to the conversion of solar radiation to thermal energy, the transformation of thermal radiation into electrical energy, and the impact of the circulating water-cooling system on performance. The analysis indicates that with concentration ratio of > 70 and operating temperatures ranging from 900 K to 1200 K, the output power of near-field solar thermophotovoltaic system can achieve a range of 8905 W/m<ce:sup loc=\"post\">2</ce:sup> to 52875 W/m<ce:sup loc=\"post\">2</ce:sup>, and the system efficiency can be stably maintained above 20 %.","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"58 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142684405","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}
Pub Date : 2024-11-20DOI: 10.1016/j.enconman.2024.119265
Rahim Boylu, Mustafa Erguvan, Shahriar Amini
This study explores CO2 regeneration in a packed bed reactor using Zeolite 13X under microwave conditions, aiming to minimize energy consumption and maximize efficiency. Microwave irradiation as a heat source in CO2 regeneration was applied after capturing CO2 in adsorption due to the rapid heating ability of microwaves, while Zeolite 13X was selected due to its high selectivity and high CO2 capture capacity. CO2 concentrations of feeding gas were set to 5 % and 15 % throughout the adsorption process to simulate natural gas and coal fired flue gases, respectively. Several parameters such as cavity orientation of the microwave, regeneration temperature, and microwave initial power were varied to investigate optimum conditions of CO2 regeneration by evaluating energy requirement, CO2 purity and productivity, as well as temperature distribution for the regeneration process. While regeneration temperature and microwave initial power were changed from 45 °C to 80 °C and 5 W to 30 W, respectively, microwave cavity orientation was used either in E-mode or H-mode. The key findings show that around 20 % less energy was consumed when E-mode is used in the system. In addition, overall CO2 purities were found to be more than 95 % for both conditions of 5 % and 15 % CO2 concentrations. Considering temperature homogeneity of the solid sorbent in regeneration, at least 90 % homogenous temperature distribution was observed in all regeneration conditions.
本研究探讨了在微波条件下使用沸石 13X 在填料床反应器中进行二氧化碳再生的问题，旨在最大限度地降低能耗和提高效率。由于微波具有快速加热的能力，因此在吸附捕集二氧化碳后，采用微波辐照作为二氧化碳再生的热源，而沸石 13X 则因其高选择性和高二氧化碳捕集能力而被选中。在整个吸附过程中，进气中的二氧化碳浓度分别设定为 5% 和 15%，以模拟天然气和燃煤烟气。通过评估能量需求、二氧化碳纯度和生产率以及再生过程的温度分布，改变微波腔方向、再生温度和微波初始功率等参数来研究二氧化碳再生的最佳条件。再生温度和微波初始功率分别从 45 °C 变为 80 °C 和从 5 W 变为 30 W，微波腔方向则采用 E 模式或 H 模式。主要研究结果表明，在系统中使用 E 模式时，能耗降低了约 20%。此外，在二氧化碳浓度为 5% 和 15% 的两种条件下，二氧化碳的总体纯度均超过 95%。考虑到再生过程中固体吸附剂的温度均匀性，在所有再生条件下均观察到至少 90% 的均匀温度分布。
{"title":"CO2 regeneration in a packed bed reactor using zeolite 13X under microwave conditions","authors":"Rahim Boylu, Mustafa Erguvan, Shahriar Amini","doi":"10.1016/j.enconman.2024.119265","DOIUrl":"10.1016/j.enconman.2024.119265","url":null,"abstract":"<div><div>This study explores CO<sub>2</sub> regeneration in a packed bed reactor using Zeolite 13X under microwave conditions, aiming to minimize energy consumption and maximize efficiency. Microwave irradiation as a heat source in CO<sub>2</sub> regeneration was applied after capturing CO<sub>2</sub> in adsorption due to the rapid heating ability of microwaves, while Zeolite 13X was selected due to its high selectivity and high CO<sub>2</sub> capture capacity. CO<sub>2</sub> concentrations of feeding gas were set to 5 % and 15 % throughout the adsorption process to simulate natural gas and coal fired flue gases, respectively. Several parameters such as cavity orientation of the microwave, regeneration temperature, and microwave initial power were varied to investigate optimum conditions of CO<sub>2</sub> regeneration by evaluating energy requirement, CO<sub>2</sub> purity and productivity, as well as temperature distribution for the regeneration process. While regeneration temperature and microwave initial power were changed from 45 °C to 80 °C and 5 W to 30 W, respectively, microwave cavity orientation was used either in E-mode or H-mode. The key findings show that around 20 % less energy was consumed when E-mode is used in the system. In addition, overall CO<sub>2</sub> purities were found to be more than 95 % for both conditions of 5 % and 15 % CO<sub>2</sub> concentrations. Considering temperature homogeneity of the solid sorbent in regeneration, at least 90 % homogenous temperature distribution was observed in all regeneration conditions.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119265"},"PeriodicalIF":9.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705926","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}
Pub Date : 2024-11-20DOI: 10.1016/j.enconman.2024.119276
Teng Guo, Guochen Sang, Yangkai Zhang, Pengyang Cai, Xiaoling Cui, Zhixuan Wang
Clarifying the thermal mechanism of buildings provides a basis for the scientific design and optimization of envelopes. This study explored the mechanism of outdoor thermal disturbances, thermal storage materials, the building noumenon and internal heat sources (IHS) affecting indoor thermal conditions (ITC) by analytical method. The triple envelope incorporated with phase change material (EIPCM) form of “outer insulation layer + structural layer + inner PCM layer” was determined and theoretically derived a predictive model of the indoor thermal conditions (PMITC) to evaluate thermal comfort in five representative regions of northwest China. Following that analyzed the significance of the influencing factors on ITC employing linear regression. The results illustrated that ITC was mainly affected by the coupling of four aspects factors. More in detail, solar radiation entering the room exploited the most prominent effect on the increase in average indoor temperature. PCM layer only affected the temperature amplitude but not the average indoor temperature. The sensible heat storage of the structural layer had a weaker effect on ITC than the PCM layer. The lowest temperatures in Yinchuan and Xi’an were both above 16 °C, while Urumqi had a higher temperature fluctuation of 2.1 °C and an average indoor temperature of 6.32 °C lower than Xi’an. Based on the estimate of ITC and degree hours (DH), the application effects of PCM in buildings in five regions can be summarized as complete thermal comfort (Yinchuan and Xi’an), partial thermal comfort (Lanzhou and Xining) and complete thermal discomfort (Urumqi). For the different factors that affected ITC, the window-to-wall ratio (WWR) had the highest coefficient of determination exceeding 93 % and the building dimension performed the lowest around 26 %.
{"title":"Study on indoor thermal conditions of a triple envelope incorporated with PCM in the passive solar building under different climates by analytical method","authors":"Teng Guo, Guochen Sang, Yangkai Zhang, Pengyang Cai, Xiaoling Cui, Zhixuan Wang","doi":"10.1016/j.enconman.2024.119276","DOIUrl":"10.1016/j.enconman.2024.119276","url":null,"abstract":"<div><div>Clarifying the thermal mechanism of buildings provides a basis for the scientific design and optimization of envelopes. This study explored the mechanism of outdoor thermal disturbances, thermal storage materials, the building noumenon and internal heat sources (IHS) affecting indoor thermal conditions (ITC) by analytical method. The triple envelope incorporated with phase change material (EIPCM) form of “outer insulation layer + structural layer + inner PCM layer” was determined and theoretically derived a predictive model of the indoor thermal conditions (PMITC) to evaluate thermal comfort in five representative regions of northwest China. Following that analyzed the significance of the influencing factors on ITC employing linear regression. The results illustrated that ITC was mainly affected by the coupling of four aspects factors. More in detail, solar radiation entering the room exploited the most prominent effect on the increase in average indoor temperature. PCM layer only affected the temperature amplitude but not the average indoor temperature. The sensible heat storage of the structural layer had a weaker effect on ITC than the PCM layer. The lowest temperatures in Yinchuan and Xi’an were both above 16 °C, while Urumqi had a higher temperature fluctuation of 2.1 °C and an average indoor temperature of 6.32 °C lower than Xi’an. Based on the estimate of ITC and degree hours (DH), the application effects of PCM in buildings in five regions can be summarized as complete thermal comfort (Yinchuan and Xi’an), partial thermal comfort (Lanzhou and Xining) and complete thermal discomfort (Urumqi). For the different factors that affected ITC, the window-to-wall ratio (WWR) had the highest coefficient of determination exceeding 93 % and the building dimension performed the lowest around 26 %.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119276"},"PeriodicalIF":9.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705127","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}
Pub Date : 2024-11-19DOI: 10.1016/j.enconman.2024.119232
Rafael Augusto Costa Silva , Alisson Aparecido Vitoriano Julio , Osvaldo José Venturini , Juarez Corrêa Furtado Júnior , José Carlos Escobar Palacio , Arnaldo Martín Martínez Reyes
This work, conducted exergy and thermoeconomic analyses of sugarcane biorefineries for different biomass allocations and conversion technologies. Using the Kriging method to determine biomass allocation, this article evaluated the performance of a sugarcane biorefinery based on the 2nd Law of Thermodynamics. By this combination of techniques, it is possible to provide better guidance to decision-making. Therefore, through exergy analysis, it is possible to improve the allocation of biomass and energy resources to be more appropriate. Therefore, biorefineries can be more efficient and synthesize products at lower costs. Moreover, the highest exergy efficiency, 43.7 %, occurred when all sugarcane bagasse was destined for the thermochemical route, 60 % for Fischer-Tropsch synthesis, and 40 % for a BIG-GTCC. On the other hand, the lowest exergy efficiency, 39.63 %, was observed in the conventional case, indicating that prioritizing biomass conversion to any kind of fuel is more productive than allocating it to produce electricity in a Rankine Cycle, regardless of technology and biofuel. Moreover, from the exergoeconomic insight, a promising trade-off was determined: the thermochemical routes proved to be better in efficiency, both energetically and exergetically, while the biochemical routes, indicated potential profitability. Furthermore, the exergoeconomic analysis demonstrated that increasing the exploration of second-generation biomass in the biorefinery lowers the exergy costs of every product. Overall, this research highlights the potential associated with sugarcane biorefineries going into expansion and modernization since its resources can be valorized in terms of efficiency and monetary value.
{"title":"Exergoeconomic insights into sugarcane biomass conversion: Integrating thermochemical and biochemical technologies for enhanced efficiency and profitability","authors":"Rafael Augusto Costa Silva , Alisson Aparecido Vitoriano Julio , Osvaldo José Venturini , Juarez Corrêa Furtado Júnior , José Carlos Escobar Palacio , Arnaldo Martín Martínez Reyes","doi":"10.1016/j.enconman.2024.119232","DOIUrl":"10.1016/j.enconman.2024.119232","url":null,"abstract":"<div><div>This work, conducted exergy and thermoeconomic analyses of sugarcane biorefineries for different biomass allocations and conversion technologies. Using the Kriging method to determine biomass allocation, this article evaluated the performance of a sugarcane biorefinery based on the 2nd Law of Thermodynamics. By this combination of techniques, it is possible to provide better guidance to decision-making. Therefore, through exergy analysis, it is possible to improve the allocation of biomass and energy resources to be more appropriate. Therefore, biorefineries can be more efficient and synthesize products at lower costs. Moreover, the highest exergy efficiency, 43.7 %, occurred when all sugarcane bagasse was destined for the thermochemical route, 60 % for Fischer-Tropsch synthesis, and 40 % for a BIG-GTCC. On the other hand, the lowest exergy efficiency, 39.63 %, was observed in the conventional case, indicating that prioritizing biomass conversion to any kind of fuel is more productive than allocating it to produce electricity in a Rankine Cycle, regardless of technology and biofuel. Moreover, from the exergoeconomic insight, a promising trade-off was determined: the thermochemical routes proved to be better in efficiency, both energetically and exergetically, while the biochemical routes, indicated potential profitability. Furthermore, the exergoeconomic analysis demonstrated that increasing the exploration of second-generation biomass in the biorefinery lowers the exergy costs of every product. Overall, this research highlights the potential associated with sugarcane biorefineries going into expansion and modernization since its resources can be valorized in terms of efficiency and monetary value.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119232"},"PeriodicalIF":9.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705129","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}
Pub Date : 2024-11-19DOI: 10.1016/j.enconman.2024.119279
Hanmo Wang, Han Xu
Solar-driven polygeneration systems have the potential to significantly reduce global carbon emissions. However, the inherent variability of solar energy and the volatility of building energy demands result in extreme complexity in supply–demand matching of energy. Reversible solid oxide cells (rSOCs), which can store electricity as fuels in solid oxide electrolysis cell (SOEC) mode and generate electricity and heat using the stored fuels in solid oxide fuel cell (SOFC) mode, are well-suited to address this challenge. Previous relevant studies considering matching of energy supply and demand are relatively limited and are not able to achieve complete electricity self-sufficiency on solar energy. This study developed a completely electricity self-sufficient solar-driven rSOC-based polygeneration system composed of an rSOC, photovoltaic (PV) device, parabolic trough collector (PTC), and other balance of plants for residential buildings, without additional electricity supply and storage equipments. The system operation strategy based on hourly supply–demand matching of electricity was proposed: PV-SOEC-PTC mode for polygeneration of electricity, hydrogen, and heat in case of sufficient solar energy, and PV-SOFC or SOFC mode for cogeneration of electricity and heat in case of insufficient or no solar energy. Crucially, this study devised a method to optimize the sizing of the key energy-supplying components (PV device, rSOC, and PTC). The optimized system demonstrated an annual polygeneration efficiency of 68.61 % at a total cost rate of 0.7782 USD/h, which represents a 2.57 % increase and a 46.1 % decrease in comparison to a system in which the PV capacity was maximized to meet the peak demand. The hourly efficiencies of hydrogen production and power generation of rSOC, and polygeneration of the system were in the ranges of 89.00 %–99.70 %, 50.15 %–73.46 %, and 34.68 %–88.64 %, respectively. Furthermore, the total hydrogen surplus of 454 kg during spring, summer, and autumn was sufficient to offset the hydrogen deficit of 235 kg in winter, ensuring year-round self-sufficiency of electricity.
{"title":"Design and optimization of solar-driven reversible solid oxide cell-based polygeneration system for residential buildings","authors":"Hanmo Wang, Han Xu","doi":"10.1016/j.enconman.2024.119279","DOIUrl":"10.1016/j.enconman.2024.119279","url":null,"abstract":"<div><div>Solar-driven polygeneration systems have the potential to significantly reduce global carbon emissions. However, the inherent variability of solar energy and the volatility of building energy demands result in extreme complexity in supply–demand matching of energy. Reversible solid oxide cells (rSOCs), which can store electricity as fuels in solid oxide electrolysis cell (SOEC) mode and generate electricity and heat using the stored fuels in solid oxide fuel cell (SOFC) mode, are well-suited to address this challenge. Previous relevant studies considering matching of energy supply and demand are relatively limited and are not able to achieve complete electricity self-sufficiency on solar energy. This study developed a completely electricity self-sufficient solar-driven rSOC-based polygeneration system composed of an rSOC, photovoltaic (PV) device, parabolic trough collector (PTC), and other balance of plants for residential buildings, without additional electricity supply and storage equipments. The system operation strategy based on hourly supply–demand matching of electricity was proposed: PV-SOEC-PTC mode for polygeneration of electricity, hydrogen, and heat in case of sufficient solar energy, and PV-SOFC or SOFC mode for cogeneration of electricity and heat in case of insufficient or no solar energy. Crucially, this study devised a method to optimize the sizing of the key energy-supplying components (PV device, rSOC, and PTC). The optimized system demonstrated an annual polygeneration efficiency of 68.61 % at a total cost rate of 0.7782 USD/h, which represents a 2.57 % increase and a 46.1 % decrease in comparison to a system in which the PV capacity was maximized to meet the peak demand. The hourly efficiencies of hydrogen production and power generation of rSOC, and polygeneration of the system were in the ranges of 89.00 %–99.70 %, 50.15 %–73.46 %, and 34.68 %–88.64 %, respectively. Furthermore, the total hydrogen surplus of 454 kg during spring, summer, and autumn was sufficient to offset the hydrogen deficit of 235 kg in winter, ensuring year-round self-sufficiency of electricity.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119279"},"PeriodicalIF":9.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705128","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}
Pub Date : 2024-11-18DOI: 10.1016/j.enconman.2024.119155
Chaonan Tian , Tong Niu , Tao Li
Accurate wind power forecasting is crucial for enhancing the stability and security of power grid operations and scheduling. However, previous studies have primarily focused on data preprocessing or model optimization, often neglecting the challenge of efficiently forecasting wind power for newly built wind farms with limited historical data. To address this issue, we developed a novel wind power forecasting system consisting of six modules that leverage a transformer network and a parameter-sharing transfer learning strategy, with a strong emphasis on model interpretability. In this forecasting system, the feature selection module and attention mechanism work together to identify key features from the input set and assign importance weights to each selected feature rather than treating all features equally. To validate the effectiveness of our proposed forecasting system, we conducted three simulation experiments using ten multivariate datasets from two wind farms in China. The results were compared against six benchmarks and various feature selection methods. Our findings demonstrate that the proposed wind power forecasting system outperforms all benchmarks. On average, across the three experiments, it achieved considerable performance improvements of 46.29% in mean absolute error and 31.02% in root mean square error compared to the worst-performing multi-layer perceptron. Additionally, the implementation of the transfer learning strategy markedly enhanced the forecasting system’s accuracy, leading to average reductions of 13.84% in mean absolute error and 7.77% in root mean square error.
{"title":"Developing an interpretable wind power forecasting system using a transformer network and transfer learning","authors":"Chaonan Tian , Tong Niu , Tao Li","doi":"10.1016/j.enconman.2024.119155","DOIUrl":"10.1016/j.enconman.2024.119155","url":null,"abstract":"<div><div>Accurate wind power forecasting is crucial for enhancing the stability and security of power grid operations and scheduling. However, previous studies have primarily focused on data preprocessing or model optimization, often neglecting the challenge of efficiently forecasting wind power for newly built wind farms with limited historical data. To address this issue, we developed a novel wind power forecasting system consisting of six modules that leverage a transformer network and a parameter-sharing transfer learning strategy, with a strong emphasis on model interpretability. In this forecasting system, the feature selection module and attention mechanism work together to identify key features from the input set and assign importance weights to each selected feature rather than treating all features equally. To validate the effectiveness of our proposed forecasting system, we conducted three simulation experiments using ten multivariate datasets from two wind farms in China. The results were compared against six benchmarks and various feature selection methods. Our findings demonstrate that the proposed wind power forecasting system outperforms all benchmarks. On average, across the three experiments, it achieved considerable performance improvements of 46.29% in mean absolute error and 31.02% in root mean square error compared to the worst-performing multi-layer perceptron. Additionally, the implementation of the transfer learning strategy markedly enhanced the forecasting system’s accuracy, leading to average reductions of 13.84% in mean absolute error and 7.77% in root mean square error.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119155"},"PeriodicalIF":9.9,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705130","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}
Pub Date : 2024-11-18DOI: 10.1016/j.enconman.2024.119274
Xiaotong Yan , Fei Zhang , Kan Kan , Yuan Zheng , Zhe Xu , Huixiang Chen , Maxime Binama
Pumped storage power plants are widely known for their ability to flexibly transition from pump to turbine operating mode and vice versa, in line with the power system requirements. Therefore, it is of great importance to accurately predict the hydraulic instability during such a transient process to enhance operational stability and the associated safety. In addition, an appropriate understanding of the effect of key control parameters is essential to optimize control strategies. In line with this, based on numerical simulation method, this study seeks to investigate the fast pump-to-turbine transition process. To achieve this, three different control schemes with different guide vane pre-opening angles were studied from three perspectives; namely, external parameter changes, pressure fluctuation characteristics, and the evolution mechanism of flow patterns. The research results indicate that during the transition, pre-opening the guide vanes can significantly accelerate changes in rotational speed and flow rate, thereby facilitating a faster transition. Different control schemes exhibit similar evolutionary trends in external parameters, pressure fluctuations, and flow patterns, but they differ in timing and amplitude. Increasing the pre-opening angle from 38.5% to 53.8% of the no-load position can effectively reduce the transition duration by 11.1% and decrease the peak-to-peak pressure fluctuations in the vaneless region by 2.2%. Although the maximum positive axial force increases by 16.0%, the increase remains insignificant in magnitude. Notably, the results suggest a decreasing trend in the effectiveness of further increasing the pre-opening angle in minimizing the transition duration. Simultaneously, the positive axial force and pressure fluctuation intensity show an accelerating growth. Therefore, increases in the pre-opening angle should be moderate. Therefore, increases in the pre-opening angle should be moderate. This study provides theoretical guidance for accelerating the fast pump-to-turbine transition process and optimizing control strategies.
{"title":"Hydraulic instability of pump-turbine during fast pump-to-turbine transition under different control schemes: Changing guide vane pre-opening angles","authors":"Xiaotong Yan , Fei Zhang , Kan Kan , Yuan Zheng , Zhe Xu , Huixiang Chen , Maxime Binama","doi":"10.1016/j.enconman.2024.119274","DOIUrl":"10.1016/j.enconman.2024.119274","url":null,"abstract":"<div><div>Pumped storage power plants are widely known for their ability to flexibly transition from pump to turbine operating mode and vice versa, in line with the power system requirements. Therefore, it is of great importance to accurately predict the hydraulic instability during such a transient process to enhance operational stability and the associated safety. In addition, an appropriate understanding of the effect of key control parameters is essential to optimize control strategies. In line with this, based on numerical simulation method, this study seeks to investigate the fast pump-to-turbine transition process. To achieve this, three different control schemes with different guide vane pre-opening angles were studied from three perspectives; namely, external parameter changes, pressure fluctuation characteristics, and the evolution mechanism of flow patterns. The research results indicate that during the transition, pre-opening the guide vanes can significantly accelerate changes in rotational speed and flow rate, thereby facilitating a faster transition. Different control schemes exhibit similar evolutionary trends in external parameters, pressure fluctuations, and flow patterns, but they differ in timing and amplitude. Increasing the pre-opening angle from 38.5% to 53.8% of the no-load position can effectively reduce the transition duration by 11.1% and decrease the peak-to-peak pressure fluctuations in the vaneless region by 2.2%. Although the maximum positive axial force increases by 16.0%, the increase remains insignificant in magnitude. Notably, the results suggest a decreasing trend in the effectiveness of further increasing the pre-opening angle in minimizing the transition duration. Simultaneously, the positive axial force and pressure fluctuation intensity show an accelerating growth. Therefore, increases in the pre-opening angle should be moderate. Therefore, increases in the pre-opening angle should be moderate. This study provides theoretical guidance for accelerating the fast pump-to-turbine transition process and optimizing control strategies.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119274"},"PeriodicalIF":9.9,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705925","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}
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