Energy最新文献

{"title":"Numerical investigation of T2∗-based and T2-based petrophysical parameters frequency-dependent in shale oil","authors":"Jilong Liu,&nbsp;Ranhong Xie,&nbsp;Jiangfeng Guo","doi":"10.1016/j.energy.2024.133788","DOIUrl":"10.1016/j.energy.2024.133788","url":null,"abstract":"<div><div>In this paper, the <em>T</em>₂∗-based relaxation theory and numerical simulation method in shale oil were established for the first time, which have been verified through free induction decay (FID) pulse sequence experiments. For the first time, the digital core technology was combined with organic carbon and Rock-Eval analysis, X-ray diffraction quantitative analysis experiments to construct representative digital shale cores. The effects of magnetic field frequency (<em>f</em>), mineral contents and types, as well as the magnetic susceptibilities difference (MSD) on <em>T</em>₂∗ responses were simulated based on the random walk method. For the first time, the frequency conversion cross-plots for <em>T</em>₂∗-based and <em>T</em>₂-based petrophysical parameters were proposed. The results show these effects on NMR-based petrophysical parameters are non-negligible. When <em>T</em>_d = 1 μs, <em>T</em>_E = 0.08 ms, <em>f</em> is 200 MHz, pyrite content is 5.43 %, and MSD is 9 × 10⁻⁵SI, the porosity, <span><math><mrow><msubsup><mi>T</mi><mrow><mn>2</mn><mtext>LM</mtext></mrow><mo>∗</mo></msubsup></mrow></math></span>, and organic matter content of <em>T</em>₂∗ distribution is 1.32 %, 0.013 ms, and 9.019 %, which are 1.33 times, 0.006 times, and 1.37 times those of <em>T</em>₂ distribution. This work contributes to frequency conversion of petrophysical parameters between in the laboratory NMR instrument and NMR logging.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133788"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661420","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":"Improvement of biogas productivity from distillery wastewater by partial potassium reduction pretreatment using two-step microfiltration and nanofiltration","authors":"Kessara Seneesrisakul ,&nbsp;Kittitut Kunta ,&nbsp;Krittiya Pornmai ,&nbsp;Masahiko Abe ,&nbsp;Prapan Ariyamethee ,&nbsp;Tanakorn Boonayamanop ,&nbsp;Sumaeth Chavadej","doi":"10.1016/j.energy.2024.133779","DOIUrl":"10.1016/j.energy.2024.133779","url":null,"abstract":"<div><div>The main purpose of the current study was to employ filtration pretreatment to lower the K concentration in distillery wastewater (DW) from a very high level (8800 mg/L) close to severe inhibition (&gt;12000 mg/L) to 4350 mg/L, which was in the moderate toxic range (2500–4500 mg/L) for methanogens. The filtration pretreatment system consisted of the two steps of microfiltration (MF) to remove large solid particles and nanofiltration (NF) to reduce K concentration in the retained DW. Both steps of MF and NF were operated in batch mode with continuous recirculation. The permeate of the MF step was fed to the NF unit in conjunction with different dilution ratios (dilution water volume-to-feed volume) to lower the K content in the retentate. The higher the cumulative dilution ratio, the lower the K concentration in the retentate of the NF step. However, it has to be traded off against the increasing total volume of permeate with the higher cumulative dilution ratio. Thus, at the optimum cumulative dilution ratio of 0.5:1, the DW from filtration pretreatment with a high COD value of 111500 mg/L and a low K content of 4350 mg/L was found to have significantly higher methanogenic productivities in terms of average production rate and yields of both biogas and methane with a higher optimum COD loading rate, as compared to those of the untreated DW. Moreover, the use of the two-step filtration in this investigation could significantly lower the dilution ratio as compared to the sole dilution method (0.5:1 against 2:1).</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133779"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661431","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":"Heuristics for multi-objective operation of EV charging stations based on Chicken Swarm Optimization","authors":"Sulabh Sachan","doi":"10.1016/j.energy.2024.133749","DOIUrl":"10.1016/j.energy.2024.133749","url":null,"abstract":"<div><div>The emissions of greenhouse gasses and high vehicle operating cost are the widespread issues, majorly derived by the large number of conventional fossil-fuel based vehicles. This had led many automobile manufacturers to move towards electric vehicles (EVs). However, EVs significantly impact the power grid because of the energy needed to re-energize their batteries. This study introduces an effective multi-objective function that utilizes Chicken Swarm Optimization (CSO) to perform the optimal operation for the Charging Stations (CSs) within the distribution network. The aim here is to reduce the power losses, the average voltage deviation index (AVDI), voltage stability index (VSI), and the impact of harmonic distortion. The simulations are conducted on 69-bus radial distribution network.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133749"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An IGDT-WDRCC based optimal bidding strategy of VPP aggregators in new energy market considering multiple uncertainties","authors":"Jun-Hyeok Kim,&nbsp;Jin Sol Hwang,&nbsp;Yun-Su Kim","doi":"10.1016/j.energy.2024.133712","DOIUrl":"10.1016/j.energy.2024.133712","url":null,"abstract":"<div><div>This study addresses the volatility and uncertainty challenges in managing renewable energy within electricity markets, particularly focusing on the role of Virtual Power Plant (VPP) aggregators. Recognizing the risks these uncertainties pose to the revenue and stability of power systems, the paper presents a novel information gap decision theory (IGDT)-Wasserstein metric based distributionally robust chance constraint (WDRCC) approach to devise an optimal bidding strategy for VPP operators. It involves a data-driven distributionally robust optimization framework, leveraging the worst-case scenario from the distributed resource uncertainties, guided by an ambiguity set rooted in the Wasserstein metric. Furthermore, the distributionally robust chance constraint modeling is introduced ensuring that uncertainty constraints of distributed resources meet a predefined risk level. Although this method shows promising out-of-sample performance, it relies on forecasted energy prices, a notable limitation given the price volatility and information inadequacy in the newly-opened market. To address this, the risk-averse bidding strategy, grounded in IGDT, is proposed simulataneously to safeguard the operator’s expected returns against price uncertainties, implementing an advanced piecewise linear approximation technique, ”nf4l,” for linearizing the bi-linear term from IGDT. The effectiveness of this approach is empirically validated through a comprehensive case study and sensitivity analysis.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133712"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661555","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":"Green hydrogen, power, and heat generation by polymer electrolyte membrane electrolyzer and fuel cell powered by a hydrokinetic turbine in low-velocity water canals, a 4E assessment","authors":"Omid Rasooli,&nbsp;Masood Ebrahimi","doi":"10.1016/j.energy.2024.133781","DOIUrl":"10.1016/j.energy.2024.133781","url":null,"abstract":"<div><div>Thousands of kilometers of man-made low-velocity water transfer canals around the world can be used as a source of renewable energy for electricity and green hydrogen production. These canals have not been well investigated as an energy source, according to the literature. In the present paper, three technologies of Hydrokinetic Turbine (HKT), Polymer Electrolyte Membrane Fuel Cell, and Electrolyzer (PEM-FC/EL) are utilized to produce electricity, green hydrogen, and heat using these canals. Thermodynamic, economic, and environmental models of the cycle are presented, coded in the Engineering Equation Solver software, and finally validated with published research and manufacturers’ data. Two scenarios were examined, first HKT, PEMEL, and PEMFC were used for electricity generation (power-to-hydrogen-to-power, P2X2P) and second only HKT and PEMEL were used for green hydrogen production (power-to-hydrogen, P2X). While both scenarios are economical, the P2X scenario has a smaller payback period (less than 2 years) and a higher net present value. Practical correlations are derived to determine the rate of hydrogen production, power generation, and emission reduction as a function of water velocity. The round-trip energy and exergy efficiency of the system is 46.17 % and 20.78 % and it reduces carbon dioxide by 0.874 tons/year when water velocity is 1.5 m/s.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133781"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661436","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 novel hybrid low-temperature thermal catalysis and radiative sky cooling system for day and night air purification and cooling","authors":"Feiyang Xu ,&nbsp;Lei Che ,&nbsp;Guoyu Zhang ,&nbsp;Xuhui Cao ,&nbsp;Niansi Li ,&nbsp;Ge Song ,&nbsp;Kai Zhang ,&nbsp;Jie Ji ,&nbsp;Bendong Yu","doi":"10.1016/j.energy.2024.133795","DOIUrl":"10.1016/j.energy.2024.133795","url":null,"abstract":"<div><div>Thermal catalytic oxidation is an air purification technology that can efficiently and stably degrade volatile organic compounds. However, using thermal catalysis to purify indoor air in the summer can cause problems of indoor overheating. Radiative sky cooling is a passive cooling method that dissipates heat through reflection and radiation, which can provide sub-ambient cooling during day and night. In this study, a novel hybrid low-temperature thermal catalysis and radiative sky cooling system for day and night air purification and cooling was proposed, which combined thermal catalysis with radiative sky cooling, and used low-temperature driven thermal catalysts to solve the problem of indoor overheating in summer. A numerical model of the hybrid system was established to simulate the formaldehyde degradation and cooling performance of the system under different operating conditions. The results show that under summer conditions with an average daily temperature of 35 °C and humidity levels between 70 % and 80 %, the system produced a total of 665.29 m³/m² of clean air after running for an entire day. The average single-pass conversion rate of formaldehyde was 0.46, and the maximum temperature difference between indoor and outdoor air was 5 °C. This provides guidance for the integration of the hybrid system with buildings.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133795"},"PeriodicalIF":9.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661554","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":"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}