Energy最新文献

{"title":"Incremental learning user profile and deep reinforcement learning for managing building energy in heating water","authors":"Linfei Yin,&nbsp;Yi Xiong","doi":"10.1016/j.energy.2024.133705","DOIUrl":"10.1016/j.energy.2024.133705","url":null,"abstract":"<div><div>Deep reinforcement learning (DRL) has garnered growing attention as a data-driven control technique in the field of built environments. However, the existing DRL approaches for managing water systems cannot consider information from multiple time steps, are prone to overestimation, fall into the problem of locally optimal solutions, and fail to cope with time-varying environments, resulting in an inability to minimize energy consumption while considering water comfort and hygiene of occupants. Therefore, this study proposes an incremental learning user profile and deep reinforcement learning (ILUPDRL) method for controlling hot water systems. This study employs hot water user profiles to reflect the hot water demand (HWD) habits. The proposed ILUPDRL addresses the challenges arising from evolving HWD through incremental learning of hot water user profiles. Moreover, to enable the ILUPDRL to consider information from multiple time steps, this study proposes the recurrent proximal policy optimization (RPPO) algorithm and integrates the RPPO into the ILUPDRL. The simulation results show that the ILUPDRL achieves up to 67.53 % energy savings while considering the water comfort and water hygiene of occupants.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133705"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661539","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":"Predictive combination model for CH4 separation and CO2 sequestration with CO2 injection into coal seams: VMD-STA-BiLSTM-ELM hybrid neural network modeling","authors":"Haiteng Xue ,&nbsp;Gongda Wang ,&nbsp;Xijian Li ,&nbsp;Feng Du","doi":"10.1016/j.energy.2024.133744","DOIUrl":"10.1016/j.energy.2024.133744","url":null,"abstract":"<div><div>In the experimental process of separating coal seam gas using the CO₂ displacement method, establishing a predictive model for key variables is essential to optimize displacement parameters, increase coal seam gas recovery, and improve CO₂ sequestration efficiency. Traditional modeling methods often struggle with the complex nature of industrial data and are susceptible to overfitting due to multicollinearity caused by long-term datasets. This paper presents a hybrid predictive model based on variational mode decomposition (VMD), a spatiotemporal attention mechanism (STA), a bidirectional long short-term memory network (BiLSTM), and an extreme learning machine (ELM). During the offline phase, VMD is used to decompose raw data into intrinsic mode functions (IMFs). The hidden state from the last time step of the STA-BiLSTM is then added to the original data to enrich the features for ELM training. In the online prediction phase, the outputs from the VMD-STA-BiLSTM and VMD-STA-BiLSTM-ELM models are combined using an error reciprocal method to generate the final prediction. The proposed model is validated with experimental datasets from CO₂ displacement for coal seam CH₄ under various conditions, as well as with N₂-ECBM and CO₂-ECBM engineering datasets. The results show that the hybrid model surpasses VMD-ELM, STA-BiLSTM-ELM, BiLSTM, STA-BiLSTM, ELM, TCN, and Attention-TCN models in predictive accuracy. Even in multi-step and rolling predictions, the model exhibits minimal impact from cumulative errors, maintaining accurate forecasts with strong generalization and robustness. It effectively captures feature patterns across different datasets and accurately predicts unknown data. The model shows potential for application in diverse scenarios and complex environments, offering reliable support and decision-making for the field application of CO₂ displacement in coal seam CH₄ separation. It is an effective and promising predictive approach to enhance coal seam gas recovery and CO₂ sequestration efficiency.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133744"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661542","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":"Experimental and numerical investigations on NH3/H2 fueled combustion in the combustor with block for improved micro power generation","authors":"Peng Teng,&nbsp;Qingguo Peng,&nbsp;Long Zhang,&nbsp;Ruixue Yin,&nbsp;Xinghua Tian,&nbsp;Hao Wang,&nbsp;Zhixin Huang","doi":"10.1016/j.energy.2024.133733","DOIUrl":"10.1016/j.energy.2024.133733","url":null,"abstract":"<div><div>To advance the application of zero-carbon fuels in micro combustion, enhance energy conversion, and reduce NO_x emissions in NH₃/H₂-fueled micro power generators, a micro-combustor with an inserted block is proposed and tested under various chamber configurations and operational conditions. Experimental and numerical tests are conducted in micro-combustors with varied block settings, burner dimensions, NH₃ blended ratios (<em>m</em>_N), and fuel flow rates (<em>V</em>_f). The results indicate that <em>m</em>_N significantly impacts the generation and consumption of H, O, and OH radicals, as well as NO, affecting flame regime and heat transfer. Specifically, adding 5∼15 % NH₃ improves the operating performance of the burner, with the highest mean temperature achieved in combustor #24C3-0.4 at <em>m</em>_N = 15 %. Block insertion alters flame characteristics and enhances gas-wall heat transfer, and the combustor with thinner blocks at higher <em>m</em>_N and thicker blocks at lower <em>m</em>_N contributes to better thermal performance. Furthermore, combustors with thinner blocks exhibit lower NO emissions. The working performance of the micro-thermophotovoltaic system can be enhanced by selecting the appropriate burner length with block thickness <em>W</em> = 0.4 mm and position <em>L</em>_b = 7 mm based on <em>V</em>_f. The maximum electrical power of 3.7 W is achieved with a burner length of 28 mm for the system using InGaAsSb cells at <em>V</em>_f = 1200 mL/min.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133733"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661484","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":"Process simulation, thermodynamic and system optimization for the low-carbon alcohols production via gasification of second-generation biomass","authors":"Wenyu Mo ,&nbsp;Beichen Yu ,&nbsp;Long Jiang ,&nbsp;Kai Xu ,&nbsp;Jun Xu ,&nbsp;Yi Wang ,&nbsp;Sheng Su ,&nbsp;Song Hu ,&nbsp;Jun Xiang","doi":"10.1016/j.energy.2024.133770","DOIUrl":"10.1016/j.energy.2024.133770","url":null,"abstract":"<div><div>Biomass-to-liquid fuels technology offers a promising method for high-value biomass conversion, addressing environmental toxicity and fossil fuel non-renewability. However, challenges such as low system efficiency and identifying efficiency losses persist. In this study, a comprehensive process model of a low-carbon alcohols production system via biomass gasification was developed, based on the first demonstration project in China. The innovation of this study lies in its detailed experimental validation, as the model simulation was performed using laboratory data and verified with pilot-scale platform data ensuring high accuracy. Additionally, the study conducted a thorough sensitivity analysis of system parameters, energy, and exergy assessments to find the proper operating conditions, including equivalent ratio, biomass type, and reactor temperature and pressure. The simulation results demonstrated an energy efficiency of 34.67 % and an exergy efficiency of 31.24 %. Through operating parameters and heat recovery measures, these efficiencies increased by 11.66 % and 8 %, respectively. This research not only obtains improved operating parameters for the pilot-scale platform but also provides actionable insights for enhancing the yields of target products and upgrading low-grade energy utilization. These findings offer valuable guidance for the commercialization of bio-syngas alcohols production systems, highlighting significant advancements in efficiency and system performance.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133770"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661537","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":"Self-superheated combined flash binary geothermal cycle using transcritical-CO2 power cycle with LNG heat sink as the secondary cycle","authors":"Subha Mondal ,&nbsp;Sudipta De","doi":"10.1016/j.energy.2024.133742","DOIUrl":"10.1016/j.energy.2024.133742","url":null,"abstract":"<div><div>Combined flash binary geothermal cycle (CFBGC) is an efficient geothermal energy conversion technology. Natural gas (NG) is a preferred fuel in the current energy scenario. LNG gasification is a needed step for delivering NG among the end users. In the present study, a self-superheated single-flash geothermal steam cycle, a transcritical CO₂ power cycle and an LNG gasification unit are integrated into a CFBGC. This study shows that the LNG gasification rate and power output can be increased simultaneously by increasing the steam turbine inlet pressure. At a higher steam turbine inlet pressure, desirable steam quality (i.e., 0.9) at the steam turbine exit is maintained by implementing self superheating of the steam. It is observed that 15 °C DSH of steam enables the CFBGC to operate at a steam turbine inlet pressure that substantially enhances the output power without a noticeable increase in levelized electricity cost (LEC). The CFBGC operating at this condition yields 9.97 % higher power output compared to that of the CFBGC operating at steam turbine inlet pressure requiring no DSH of steam. As a geothermal-based power plant emits very low CO₂, the proposed energy system may emerge as a future sustainable energy option.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133742"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661535","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":"Frequency security constraint in unit commitment with detailed frequency response behavior of wind turbines","authors":"Jianshu Yu,&nbsp;Pei Yong,&nbsp;Juan Yu,&nbsp;Zhifang Yang","doi":"10.1016/j.energy.2024.133735","DOIUrl":"10.1016/j.energy.2024.133735","url":null,"abstract":"<div><div>With the high penetration of wind turbines, the necessity of incorporating frequency security considerations into power system scheduling rises. Existing methods achieve the explicit modeling of frequency security constraints by simplifying the frequency response behavior of wind turbines. However, simplifications might lead to inaccuracy. To address this issue, this paper models the frequency response from wind turbines in detail and proposes a novel framework to construct the frequency security constraint for unit commitment (UC). First, the frequency security constraint is positioned at the segment that is effective for the dispatch decision instead of the whole boundary, which is unnecessary and complicated. Then, an analytical linear surrogate expression of the frequency security boundary is constructed through a data-driven approach. To ensure the accuracy of the surrogate constraint, a neighborhood sampling strategy is proposed to collect balanced samples. Furthermore, to reduce the linearization error of the surrogate constraints, supplementary constraints are added to restrict the width of the surrogate constraint. Finally, to address the modeling errors that may deviate from the frequency security requirements, a correction strategy is proposed. Case studies validate the proposed method and verify that it exceeds existing methods in the modeling accuracy of the power system frequency security.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133735"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661428","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":"Thermal-hydraulic characteristics of an earth air heat exchanger: An experimental analysis","authors":"Emad M.S. El-Said","doi":"10.1016/j.energy.2024.133766","DOIUrl":"10.1016/j.energy.2024.133766","url":null,"abstract":"<div><div>The pipe layout design has a great effect on the thermal-hydraulic characteristics of earth air heat exchanger (EAHE) systems. So, in the current study proposed four new buried pipe design configurations; low to high to low, high to low to high, spiral, and circular, in addition to the straight or uniform for comparison. These five configurations are tested and analyzed experimentally depending on the thermo-hydraulic performance for summer cooling requirements with variation of Re in the range of 18041–40843. The results show that changing the uniform design of the EAHE with fixed pipe length enhances both the heat transfer process and pressure loss values. At the same operating conditions, the circular design has the best performance compared to the other ones. For all pipe shapes, the cooling effect increases with the increase of air <em>Re</em>. The thermal-hydraulic performance of the circular design pipe is higher than that of the other pipe designs. The highest coefficient of performance (COP) average values that can be obtained at Re = 18041 is 3.05 for circular shape and enhances by 48.08 % compared to uniform shape. The effectiveness of EAHE with circular shape is improved by about 3.52 % compared to uniform shape at Re = 18041. Spiral design is optimum design based on the <em>Nu</em> value which reaches about 48 with enhancement 12.56 % and 0.34 % compared to uniform and circular shapes respectively, at Re = 40843. The hydrothermal performance factor is highest in the case of circular shape with value about 21.9 at Re = 21257. By increasing <em>Re</em>, the drawbacks of the increasing in the total entropy generation are reflected negatively on the exergy efficiency. The specific cost of the circular shape at Re = 40843 is the optimum value by about 0.7 $/W. Spiral and circular shapes have a decrease of CO₂ emissions less than uniform shape by percentage varied from 2.93 % to 13.84 % for decrease in the Re from 21257 to 40843. It is concluded that using EAHE with four new shapes is highly efficient in increasing cooling capacity and energy consumption in buildings.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133766"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661532","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":"Dynamic thermal simulation of a tree-shaped district heating network based on discrete event simulation","authors":"Zichan Xie ,&nbsp;Haichao Wang ,&nbsp;Pengmin Hua ,&nbsp;Maximilian Björkstam ,&nbsp;Risto Lahdelma","doi":"10.1016/j.energy.2024.133775","DOIUrl":"10.1016/j.energy.2024.133775","url":null,"abstract":"<div><div>The computational complexity involved in modelling district heating (DH) networks impedes the integration of network operations into comprehensive DH system studies. We developed a flexible, accurate, and fast dynamic thermal simulation model utilising discrete event simulation (DES). This model is versatile, suitable for any tree-shaped DH network with a central heating plant and can estimate node temperatures and calculate pipe heat losses. The speed of the model is improved via using variable time steps and by incorporating two advanced techniques: lazy evaluation and a customised priority queue. To further improve the computational speed, we developed a technique to eliminate redundant sampling points. This model was tested and demonstrated excellent consistency with actual measurements. Remarkably, reducing sampling points can speed up the simulation by a factor of three without compromising the temperature accuracy. A 72-day simulation of a network with 102 pipes was completed within 0.219 s. Our findings highlight the significant potential of the DES model for large-scale dynamic network simulations and offer a promising solution for DH network simulations and system optimisation.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133775"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A geographic multi-scale machine learning framework for predicting solar irradiation on tilted surfaces","authors":"Sameer Al-Dahidi ,&nbsp;Bilal Rinchi ,&nbsp;Raghad Dababseh ,&nbsp;Osama Ayadi ,&nbsp;Mohammad Alrbai","doi":"10.1016/j.energy.2024.133767","DOIUrl":"10.1016/j.energy.2024.133767","url":null,"abstract":"<div><div>This study addresses the challenge of improving Global Tilted Irradiation (GTI) predictions, with Jordan serving as the case study. The novelty of the work lies in developing machine learning models that predict GTI at national, regional (3 regions), and city-specific (12 cities) levels, a previously unexplored approach in the literature. The research examines the comparative efficiency of using a single model for an entire country versus tailored models for individual regions and cities, shedding light on the trade-offs in model evaluation. Various regression models, including Neural Networks (NNs), Linear Regression (LR), Regression Trees (RTs), Ensemble of Regression Trees (ERTs), Support Vector Machine (SVM), and Kernel Approximation, were evaluated using performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R²). NNs consistently performed best, achieving the lowest RMSE (1.5787 kWh/m²) and highest R² (99.8600 %) at the regional level. Sensitivity analysis further explored the impact of different time resolutions, revealing that monthly data outperformed daily data in terms of accuracy and computational efficiency. Ultimately, we conclude that region-specific models and monthly data resolution are optimal for practical GTI prediction.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133767"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic methodology for selecting optimal technology for waste heat utilization in food processing industry","authors":"Mladen Josijevic,&nbsp;Vladimir Vukasinovic,&nbsp;Dusan Gordic,&nbsp;Vanja Sustersic,&nbsp;Dubravka Zivkovic,&nbsp;Jelena Nikolic","doi":"10.1016/j.energy.2024.133751","DOIUrl":"10.1016/j.energy.2024.133751","url":null,"abstract":"<div><div>Utilizing waste heat that is rejected from thermal processes can greatly enhance the industry's energy balance. Identifying potential waste heat sources in the food and beverage processing industry and making estimations for their possible utilization can be an extremely challenging undertaking. To determine waste heat potentials in the food processing industry and to select an optimal technology for its utilization a novel systematic methodology based on the comprehensive energy audit and mathematical optimization has been developed. The developed mixed integer nonlinear programming model incorporates all novel and the most commonly employed technologies to utilize waste heat.</div><div>The developed systematic methodology is tested on a case study, of a milk and dairy production facility. Obtained results have shown that up to 53 % of the available waste heat can be used in the scenario of limited investment costs. Otherwise, in the scenario when investment costs are not set as a limitation, 75 % of waste heat can be used, according to plant demands. Harmonising production processes is necessary to use all the waste heat. The developed systematic methodology can be applied to any food processing industry and other facilities producing waste heat because it presents a universal approach.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133751"},"PeriodicalIF":9.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661608","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}