Unconventional Resources最新文献_第10页

Biomass-based green ammonia: Pathways, technologies, and sustainability for a carbon-neutral future 基于生物质的绿色氨：碳中和未来的途径、技术和可持续性

IF 4.6

Unconventional Resources

Pub Date : 2025-10-01 Epub Date: 2025-09-05 DOI: 10.1016/j.uncres.2025.100241

Khemlata Soni , Pranay Rajendra Lanjekar , Narayan Lal Panwar

Ammonia plays a pivotal role in the global economy, serving as a hydrogen carrier, carbon-free fuel, and a key component in nitrogen fertilizers that enhance agricultural productivity. However, the conventional Haber-Bosch (H-B) process, which relies on methane (natural gas) as a source of hydrogen, contributes approximately 2 % of global CO₂ emissions, underscoring the need for sustainable alternatives. This review explores biomass as a renewable feedstock for green ammonia production, focusing on thermochemical and biochemical conversion processes through two pathways: (1) Indirect, using renewable based hydrogen from steam methane reforming of syngas, bio-oil, biogas and glycerol obtained from biomass gasification, pyrolysis, anaerobic digestion and transesterification processes, respectively, and (2) Direct, converting nitrogen-rich biomass into ammonia through catalytic or laser-driven pyrolysis, or recovering ammonia from biohydrogen or biogas effluents via stripping. While the biochemical process has higher technology readiness, thermochemical methods, especially biomass steam gasification, are more widely used due to higher green hydrogen yields. Novel integrations, such as process simulations, cascaded designs, chemical looping, and external energy sources like solar, biomass, wind, or hybrid systems, enhance ammonia production. Green ammonia reduces CO₂ emissions by approximately 65–66 % and is less costly than conventional processes, depending on system configuration and biomass feedstock. This review examines technological advancements, economic feasibility, and environmental impacts, concluding that biomass-based green ammonia is essential for sustainable energy systems. While earlier reviews have provided broad overviews of green ammonia production, they often overlook the specific potential of biomass-based routes. This review addresses that gap by systematically analyzing biomass-driven pathways, along with their technological, economic, and environmental dimensions, to underscore the distinctive contribution of biomass to sustainable ammonia production.

氨在全球经济中发挥着关键作用，作为氢载体、无碳燃料和提高农业生产力的氮肥的关键成分。然而，传统的Haber-Bosch （H-B）工艺依赖甲烷（天然气）作为氢的来源，约占全球二氧化碳排放量的2%，这凸显了对可持续替代方案的需求。本文探讨了生物质作为绿色氨生产的可再生原料，重点介绍了两种途径的热化学和生化转化过程：(1)间接，分别利用生物质气化、热解、厌氧消化和酯交换过程中获得的合成气、生物油、沼气和甘油的蒸汽甲烷重整产生的可再生氢；(2)直接，通过催化或激光驱动热解将富氮生物质转化为氨，或通过汽提法从生物氢或沼气出水中回收氨。虽然生物化学工艺具有更高的技术成熟度，但热化学方法，特别是生物质蒸汽气化，由于更高的绿色氢产量而得到更广泛的应用。新的集成，如过程模拟、级联设计、化学环和外部能源，如太阳能、生物质能、风能或混合系统，提高了氨的生产。根据系统配置和生物质原料的不同，绿色氨可以减少约65 - 66%的二氧化碳排放，并且比传统工艺成本更低。本综述考察了技术进步、经济可行性和环境影响，得出结论认为生物质基绿色氨对可持续能源系统至关重要。虽然早期的评论提供了绿色氨生产的广泛概述，但它们往往忽视了基于生物质的路线的具体潜力。本综述通过系统分析生物质驱动的途径及其技术、经济和环境维度来解决这一差距，以强调生物质对可持续氨生产的独特贡献。

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引用次数: 0

Experimental validation and enhanced thermal prediction of a shallow solar pond using artificial neural network–based model predictive control for real-time optimization under multiple heat extraction modes 基于人工神经网络的模型预测控制在多种抽热模式下的实验验证与强化太阳浅池热预测

IF 4.6

Unconventional Resources

Pub Date : 2025-10-01 Epub Date: 2025-09-05 DOI: 10.1016/j.uncres.2025.100240

Abdelkrim Terfai , Younes Chiba , Mounir Zirari , Mohamed Najib Bouaziz

This study presents the experimental validation and enhanced thermal modeling of a Shallow Solar Pond (SSP) operating under three distinct heat extraction modes: direct, open cycle, and closed cycle. A custom-designed SSP, insulated and equipped with double-glazing and a PVC heat exchanger and black-painted bottom, was monitored under clear-sky conditions. 14 Artificial Neural Network (ANN) configurations were trained, with the optimal Bayesian Regularization-based model (two hidden layers, 15 neurons) achieving exceptional predictive accuracy (R² = 0.99919, RMSE = 32.7580 %, MRE = 0.62 %) for temperatures across all system components and operational modes. The ANN model effectively captured complex nonlinear dynamics, including transient heating and cooling phases. The integration of this ANN with a Model Predictive Control (MPC) framework enabled real-time optimization of the fluid flow rate in the closed-cycle mode, which was identified as the most efficient configuration. The MPC-ANN strategy reduced the outlet temperature tracking error by over 50 % (MAE = 1.42 °C vs. 2.97 °C without MPC), demonstrating superior thermal stability and adaptive control under fluctuating solar irradiance. This work confirms the closed-cycle SSP's superiority for stable energy delivery and establishes a robust ANN-MPC framework for real-time operational optimization of solar thermal systems.

本研究提出了浅层太阳池（SSP）在三种不同的热提取模式下运行的实验验证和增强的热建模：直接、开式循环和闭式循环。在晴空条件下，一个定制设计的SSP进行了监测，该SSP隔热，配有双层玻璃和PVC热交换器，底部漆成黑色。对14个人工神经网络（ANN）配置进行了训练，其中基于贝叶斯正则化的最优模型（两个隐藏层，15个神经元）对所有系统组件和运行模式的温度具有出色的预测精度（R2 = 0.99919, RMSE = 32.7580%, MRE = 0.62%）。人工神经网络模型有效地捕获了复杂的非线性动力学，包括瞬态加热和冷却阶段。将该人工神经网络与模型预测控制（MPC）框架相结合，实现了闭环模式下流体流量的实时优化，这被认为是最有效的配置。MPC- ann策略将出口温度跟踪误差降低了50%以上（MAE = 1.42°C，而没有MPC的情况下为2.97°C），显示出卓越的热稳定性和在波动太阳辐照度下的自适应控制。这项工作证实了闭循环SSP在稳定能量输送方面的优势，并为太阳能热系统的实时运行优化建立了一个强大的ANN-MPC框架。

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引用次数: 0

The impact of magmatic intrusion on the microscopic composition and pore structure of coal seams in the Kailuan coalfield 岩浆侵入对开滦煤田煤层微观组成及孔隙结构的影响

IF 4.6

Unconventional Resources

Pub Date : 2025-10-01 Epub Date: 2025-09-25 DOI: 10.1016/j.uncres.2025.100250

Minrui Cui , Qianlong Xiao , Bin Xing , Lin Bai , Yeting Wan , Xiangjun Cai , Wu Li

With the continuous growth in global coal demand, the impact of magma intrusion on coal micro-components, pore structure, and gas storage characteristics has gradually become a significant factor influencing the economic efficiency and safety of coal mining operations. This study focuses on the Qianjiaying, Lvjiatuo, Fangezhuang, and Linxi mines in the Kailuan mining area, systematically analyzing the mechanisms of magma intrusion and its potential threats to mining safety. The study reveals that the impact range of vitrinite reflectance changes is smaller than the actual thermal influence range of magma. Magma intrusion causes significant changes in coal micro-components, particularly the carbonization of vitrinite and inertinite, as well as a marked increase in natural coke. Vitrinite is notably more sensitive to thermal effects than inertinite. Additionally, magma intrusion alters the pore structure of coal seams through thermo-mechanical coupling, significantly affecting the development of mesopores and micropores. The results show that as the distance from magma increases, micropores first increase, then decrease, and later increase again, while mesopores rapidly decrease and eventually stabilize. In areas close to the magma, pore structures tend to become more uniform, while those further from the intrusion gradually return to normal. Furthermore, magma intrusion enhances the secondary hydrocarbon generation in coal seams, producing large amounts of gas. The form of magma intrusion, whether continuous or discontinuous, has different effects on gas accumulation and release: continuous magma beds facilitate gas accumulation, while discontinuous magma dikes cause gas to escape. The findings provide important theoretical insights for coal mining, utilization, and gas prevention strategies.

随着全球煤炭需求的不断增长，岩浆侵入对煤炭微组分、孔隙结构和储气特性的影响逐渐成为影响煤炭开采经济效益和安全生产的重要因素。以开滦矿区前家营、吕家沱、方家庄、临西4个矿区为研究对象，系统分析岩浆侵入机理及其对采矿安全的潜在威胁。研究表明，镜质组反射率变化的影响范围小于岩浆的实际热影响范围。岩浆侵入导致煤微组分发生显著变化，特别是镜质组和惰质组的炭化，天然焦炭明显增加。镜质组明显比惰质组对热效应更敏感。岩浆侵入通过热-力耦合改变了煤层孔隙结构，显著影响了中孔和微孔的发育。结果表明：随着离岩浆距离的增加，微孔先增加后减少，再增加，而中孔则迅速减少并趋于稳定；在靠近岩浆的区域，孔隙结构趋于均匀，而远离岩浆的区域，孔隙结构逐渐恢复正常。岩浆侵入增强了煤层二次生烃作用，产生大量瓦斯。岩浆侵入的形式，无论是连续的还是不连续的，对气体的聚集和释放有不同的影响：连续的岩浆床有利于气体的聚集，而不连续的岩浆脉则导致气体的逸出。这一发现为煤炭开采、利用和瓦斯防治策略提供了重要的理论见解。

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引用次数: 0

Boosting Thermoelectric Power Generation with Black Body Coatings and Oil Thermal Storage tank 利用黑色车身涂层和储油罐促进热电发电

IF 4.6

Unconventional Resources

Pub Date : 2025-09-02 DOI: 10.1016/j.uncres.2025.100237

Jalal Faraj , Georges El Achkar , Mohammad Hammoud , Rani Taher , Samer Ali , Maya Julian , Chafic Salame , Mahmoud Khaled

Thermoelectric generators (TEGs) are a sustainable way to transform waste heat into electricity, with applications including waste heat recovery, renewable energy, and industrial exhaust gas systems. Despite their promise, TEGs' modest power output limits their widespread implementation. This paper describes an engineering solution for improving TEG performance by using solar energy as the major heat source and including an oil tank as a thermal energy storage device. The change entails transforming the hot surface of commercial and standard TEG modules into a blackbody surface to increase heat absorption. Unlike traditional settings, this study investigates the combined impact of black-coated surfaces and an oil tank on the hot side to optimize heat input. This technique provides a cost-effective and ecologically responsible option for increasing TEG efficiency. To proceed, a regular commercial TEG module, a TEG module with black body film, and a TEG module with both black body film combined with an oil tank are studied under the same conditions. The output power density and temperature differential of each arrangement were measured and compared. Replacing the white surface on the hot side of the TEG module with a blackbody surface boosted power density by 1500 mW/m², reaching 2250 mW/m². Adding an oil tank to the black surface increased the output to 3500 mW/m². These enhancements emphasize the potential of TEGs to greatly boost power output, notably in solar-powered systems and industrial waste heat recovery applications aiming at sustainable energy production.

热电发电机（teg）是一种将废热转化为电能的可持续方式，其应用包括废热回收、可再生能源和工业废气系统。尽管他们的承诺，适度的功率输出限制了他们的广泛应用。本文介绍了一种以太阳能为主要热源，采用油罐作为蓄热装置来提高TEG性能的工程解决方案。这种改变需要将商用和标准TEG模块的热表面转化为黑体表面，以增加吸热。与传统设置不同，本研究考察了黑色涂层表面和热侧油箱的综合影响，以优化热量输入。该技术为提高TEG效率提供了一种具有成本效益和生态责任的选择。为此，在相同的条件下，研究了普通商用TEG模块、黑体膜TEG模块和黑体膜与油箱结合的TEG模块。测量并比较了不同排列方式的输出功率密度和温度差。用黑体表面取代TEG模块热侧的白色表面，使功率密度提高了1500 mW/m2，达到2250 mW/m2。在黑色表面增加一个油箱，将输出增加到3500mw /m2。这些改进强调了teg在大大提高功率输出方面的潜力，特别是在旨在实现可持续能源生产的太阳能系统和工业废热回收应用中。

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引用次数: 0

Development of an improved numerical model for fracture propagation in hydraulic fracturing of low-permeability formations using FracproPT software 利用FracproPT软件开发了一种改进的低渗透地层水力压裂裂缝扩展数值模型

Unconventional Resources

Pub Date : 2025-07-01 Epub Date: 2025-04-19 DOI: 10.1016/j.uncres.2025.100193

Najeeb Anjum Soomro

The primary technologies employed to access unconventional resources today are horizontal drilling and single or multi-stage fracturing. Micro-seismic data frequently corroborates that hydraulic fracturing in shale reservoirs generates intricate fracture networks due to complex geology and the activation of pre-existing natural fractures, which cannot be accurately represented by traditional planar bi-wing fracture models.''

This research utilizes a dataset of reservoir characteristics, petrophysical features, and fracture treatments to develop a novel, sophisticated simulation model that demonstrates enhanced techniques for optimizing oil and gas output. The primary factors examined that significantly influence fracture behavior are flow rate, kind of proppants, and fracturing fluid.

The fracturing behavior and its controlling and optimization are the primary components utilized to augment production. The FracproPT software demonstrates the impact of proppant, flow rate, and fracturing fluid.

A comparison between a real model and a simulation model is presented, as the production of the stimulated well can be improved through the implementation of superior simulation models in future well stimulation efforts.

The ideal final fracture therapy is defined by maximal fracture length, width, and height.''

The research shows laboratory data for multiple fracturing fluids exhibiting varying surface activities, which were pumped into the assembly chamber. Recent fracture therapies have effectively employed a slick water formulation including water and dry polymer, with or without the inclusion of surfactant (Tri-ethanol Amine - TEA). This study evaluates commonly used surfactants and a microemulsion technology.

Simulation results indicate that the ideal fracture shape and conductivity, constrained by pumping limitations, are achieved at an injection rate of 100 bpm, a gel loading of 50 ppg, and a proppant size of 20/40 mesh sand. This paper enhances comprehension of fracture behavior in reservoirs and acts as a reference for optimizing hydraulic fracturing techniques.

目前用于开采非常规资源的主要技术是水平钻井和单段或多级压裂。微地震数据经常证实，页岩储层水力压裂由于复杂的地质条件和已存在天然裂缝的激活而产生复杂的裂缝网络，这是传统的平面双翼裂缝模型无法准确表示的。“这项研究利用储层特征、岩石物理特征和裂缝处理数据集，开发了一种新颖、复杂的模拟模型，展示了优化油气产量的增强技术。影响裂缝行为的主要因素是流量、支撑剂种类和压裂液。压裂行为及其控制和优化是增产的主要手段。FracproPT软件显示了支撑剂、流量和压裂液的影响。通过对真实模型和模拟模型的比较，可以在未来的增产工作中通过实施更好的模拟模型来提高增产井的产量。理想的最终骨折治疗是由最大骨折长度、宽度和高度来定义的。“研究表明，多种压裂液的实验室数据显示，这些压裂液被泵入装配室后，表现出不同的表面活性。最近的压裂治疗有效地使用了滑溜水配方，包括水和干聚合物，有或没有表面活性剂（三乙醇胺- TEA）。本研究评价了常用的表面活性剂和微乳液技术。模拟结果表明，在受泵送限制的情况下，当注入速度为100 bpm、凝胶加载量为50 ppg、支撑剂尺寸为20/40目砂时，可以获得理想的裂缝形状和导流能力。提高了对储层裂缝动态的认识，为优化水力压裂技术提供了参考。

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引用次数: 0

Heat production of sedimentary rocks in Chengdao-Kendong area, Bohai Bay basin 渤海湾盆地埕岛—垦东地区沉积岩产热作用

Unconventional Resources

Pub Date : 2025-07-01 Epub Date: 2025-06-26 DOI: 10.1016/j.uncres.2025.100207

Xiaolin Liu , Anyu Jing , Yuanjin Sun , Chao Sun , Ruibo Jiang , Xing Mu , Xiaoxue Jiang , Fang Xie , Yaodong Xu , Chuanqing Zhu

Sedimentary heat flow, as part of terrestrial heat flow, plays a key role in hydrocarbon generation by affecting the temperature of source rocks, thus influencing the thermal evolution and maturity of organic matter. The radioactive heat production rate of rocks is essential for studying sedimentary heat flow. Based on empirical formulas proposed by previous researchers that relate natural gamma log to heat production rates, this study calculated 26,707 rock heat production rate data points from 60 wells in the Chengdao-Kendong area. Results show that the average heat production rate of the sedimentary layers is 1.06 ± 0.34 μW/m³,and the different lithologies are as follows: mudstone 1.28 μW/m³, sandstone 1.05 μW/m³, conglomerate 1.01 μW/m³, glutenite 0.93 μW/m³, limestone 0.44 μW/m³, dolomite 0.45 μW/m³.The radioactive heat production ranges from 3.0 to 6.8 mW/m². In the Changdi and Gudong areas, sedimentary layers contribute 6.3–10 % of the terrestrial heat flow, while the Kendong area's contribution is around 4.3 %. Moreover, the distribution of terrestrial heat flow is closely related to variations in basement depth, mainly influenced by mantle heat flow in the Chengdao-Kendong area.

沉积热流作为陆相热流的一部分，通过影响烃源岩的温度，从而影响有机质的热演化和成熟度，在生烃过程中起着关键作用。岩石的放射性产热率是研究沉积热流的必要条件。根据前人提出的自然伽马测井与产热率关联的经验公式，计算了埕岛—垦东地区60口井的26707个岩石产热率数据点。结果表明：沉积层平均产热速率为1.06±0.34 μW/m3，不同岩性分别为泥岩1.28 μW/m3、砂岩1.05 μW/m3、砾岩1.01 μW/m3、砂砾岩0.93 μW/m3、灰岩0.44 μW/m3、白云岩0.45 μW/m3。放射性产热范围为3.0 ~ 6.8 mW/m2。在昌地和鼓洞地区，沉积层对大地热流的贡献率为6.3 ~ 10%，而在肯东地区，沉积层对大地热流的贡献率约为4.3%。此外，大地热流分布与基底深度变化密切相关，主要受埕岛—肯东地区地幔热流的影响。

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引用次数: 0

Multi-objective optimization model and algorithm implementation of the distributed power generation system for renewable energy in China and Russia 中俄可再生能源分布式发电系统多目标优化模型及算法实现

Unconventional Resources

Pub Date : 2025-07-01 Epub Date: 2025-05-22 DOI: 10.1016/j.uncres.2025.100201

Yingkai Ma

This study focuses on solving multi-objective optimization problems in distributed power generation systems (DPGS) for renewable energy in China and Russia, including low economic efficiency, poor environmental benefits, and insufficient system reliability. It proposes a hybrid optimization model that integrates deep learning with an improved particle swarm optimization algorithm, namely Adaptive Linear Decreasing Inertia Weight Particle Swarm Optimization with Mutation Strategy (ALD-MPSO). By introducing a Dense Bidirectional Long Short-Term Memory with Attention Mechanism (DBI-LSTM-AM) model, which combines a Bidirectional Long Short-Term Memory (Bi-LSTM) network, Dense layers, and an Attention Mechanism (AM), the model performs time-series forecasting of energy demand. Coupled with the ALD-MPSO algorithm, the model simultaneously optimizes economic efficiency, environmental benefits, and system reliability. The study designs a renewable energy prediction and optimization model for DPGS, based on the fusion of the DBI-LSTM-AM and ALD-MPSO algorithms (DBI-LSTM-2AM-PSO). Finally, the model's performance is evaluated. Experimental results show that the proposed model achieves superior prediction accuracy (95.53 %), with an F1 score of 91.41 %, and a mean squared error (MSE) of 0.049, outperforming the benchmark algorithms. Additionally, the fitness value in MOO is reduced to 0.47, with a training time of only 25.7 s and low computational resource consumption (Center Processing Unit usage at 10.55 %). This study provides effective technical support for the intelligent management of DPGS in the renewable energy sectors of China and Russia.

本研究主要解决中俄两国可再生能源分布式发电系统（DPGS）中存在的经济效率低、环境效益差、系统可靠性不足等多目标优化问题。提出了一种将深度学习与改进的粒子群优化算法相结合的混合优化模型，即基于突变策略的自适应线性减少惯性权粒子群优化（ALD-MPSO）。该模型将双向长短期记忆（Bi-LSTM）网络、密集层和注意机制（AM）相结合，引入高密度双向长短期记忆与注意机制（DBI-LSTM-AM）模型，对能源需求进行时间序列预测。该模型结合ALD-MPSO算法，同时实现了经济效益、环境效益和系统可靠性的优化。本研究基于DBI-LSTM-AM和ALD-MPSO算法（DBI-LSTM-2AM-PSO）的融合，设计了DPGS可再生能源预测与优化模型。最后，对模型的性能进行了评价。实验结果表明，该模型具有较高的预测精度（95.53%），F1分数为91.41%，均方误差（MSE）为0.049，优于基准算法。此外，MOO中的适应度值降低到0.47，训练时间仅为25.7 s，计算资源消耗低（Center Processing Unit使用率为10.55%）。本研究为中俄两国可再生能源领域DPGS的智能化管理提供了有效的技术支撑。

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引用次数: 0

Geochemical characterization and evaluation of shale oil bearing characteristics of Permian Pingdiquan Formation in eastern Junggar Basin 准噶尔盆地东部二叠系平底泉组页岩含油特征地球化学表征及评价

Unconventional Resources

Pub Date : 2025-07-01 Epub Date: 2025-06-03 DOI: 10.1016/j.uncres.2025.100205

Yuchen Liu , Weibiao Zhang , Xin Yang , Huixi Lin

Of the Permian Pingdiquan Formation in eastern Junggar Basin, western China, the continental shale oil is the principal prospective unconventional resources target. Our research described the analysis on core samples from the Permian Pingdiquan Formation in eastern Junggar Basin. Geochemical technologies, like contents of total organic carbon (TOC), Rock-Eval pyrolysis, and clay mineral identification through X-ray diffraction (XRD), were analyzed on the specimens. Shale oil bearing characteristics were deeply dissected through two-dimensional nuclear magnetic resonance (2D NMR) and the quantitative grain fluorescence on extract (QGF-E) technology. The results indicated that the source rocks of the Pingdiquan Formation in Qitaizhuang area possessed an elevated abundance of organic matters meeting the criteria of high-quality source rocks. However, the Mulei sag and Shiqiantan sag developed medium-poor source rock segments, which mainly due to the high paleo-productivity of source rocks in Qitaizhuang area. The combination of high-frequency QGF and 2D NMR can analyze the content of shale oil in shale reservoirs. The oil saturation in Qitaizhuang area was higher than Mulei sag and Shiqiantan sag. MAX-EX/MAX-EM and R1 indicated that the oil density and viscosity in Qitaizhuang area was higher than other areas. This further proved that the oil in Qitaizhuang area was from near source, while the oil in Shiqiantan and Mulei sag was from fruther source. The oil content of shale reservoir in eastern Junggar Basin was controlled by the overall organic carbon content and its pore throat construction. Our research lays a foundation for shale oil exploitation exploration in the Permian Pingdiquan Formation of eastern Junggar Basin.

准噶尔盆地东部二叠系平底泉组陆相页岩油是主要的非常规资源远景区。本文对准噶尔盆地东部二叠系平底泉组岩心样品进行了分析。对样品进行了总有机碳（TOC）含量测定、岩石热解测定、x射线衍射（XRD）黏土矿物鉴定等地球化学技术分析。采用二维核磁共振（2D NMR）和定量颗粒荧光（QGF-E）技术对页岩含油特征进行了深入剖析。结果表明，七台庄地区平底泉组烃源岩有机质丰度较高，符合优质烃源岩标准。而木雷凹陷和石前滩凹陷发育中-差烃源岩段，这主要是由于七台庄地区烃源岩古生产力较高所致。高频QGF与二维核磁共振相结合可以分析页岩储层中页岩油的含量。七台庄地区含油饱和度高于木雷凹陷和石前滩凹陷。MAX-EX/MAX-EM和R1表明七台庄地区的原油密度和粘度高于其他地区。这进一步证明了七台庄地区的原油为近源原油，而石前滩和木雷凹陷的原油为远源原油。准噶尔盆地东部页岩储层含油量受整体有机碳含量及其孔喉构造控制。本研究为准噶尔盆地东部二叠系平底泉组页岩油开发勘探奠定了基础。

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引用次数: 0

A comprehensive review of smart energy management systems for photovoltaic power generation utilizing the internet of things 基于物联网的光伏发电智能能源管理系统综述

Unconventional Resources

Pub Date : 2025-07-01 Epub Date: 2025-04-25 DOI: 10.1016/j.uncres.2025.100197

Challa Krishna Rao , Sarat Kumar Sahoo , Franco Fernando Yanine

Renewable energy represents the most reliable and widely recognized solution for meeting the escalating global energy demands. The optimization of solar energy generation necessitates a strong focus on predictive maintenance and advanced deployment methodologies. To enhance solar power utilization, Internet of Things enabled solar monitoring systems have been proposed for real-time data acquisition and analytics, facilitating performance forecasting and ensuring consistent power output. A critical challenge in demand-side energy management lies in optimizing the integration of renewable resources while maintaining cost efficiency and minimizing energy losses. Therefore, strategic planning for the integration of renewable energy sources is imperative. Intelligent energy management systems play a pivotal role in optimizing energy distribution, particularly in scenarios with high grid dependency. Cloud computing infrastructures address the complexities and scalability challenges posed by expanding smart grids, enabling real-time data processing and adaptive energy control mechanisms. This study explores the practical implementation of energy management system in industrial settings and research domains, both of which serve as key stakeholders in advancing smart energy solutions. A comprehensive review of internet of things applications in photovoltaic power generation highlights key research objectives and technological developments in the field. The evolving landscape of internet of things driven innovations presents numerous research opportunities, including the formulation of performance evaluation metrics and the development of novel optimization techniques. Additionally, the growing emphasis on energy management within intelligent architectural frameworks underscores the necessity for deeper investigations into adaptive control strategies and system interoperability. This ongoing research is essential for driving advancements in internet of things enabled energy solutions and enhancing the efficiency of smart grid ecosystems.

可再生能源代表了满足不断增长的全球能源需求的最可靠和广泛认可的解决方案。太阳能发电的优化需要高度关注预测性维护和先进的部署方法。为了提高太阳能的利用率，已经提出了物联网太阳能监测系统，用于实时数据采集和分析，促进性能预测并确保一致的功率输出。需求侧能源管理的一个关键挑战在于优化可再生资源的整合，同时保持成本效率和最大限度地减少能源损失。因此，对可再生能源的整合进行战略规划势在必行。智能能源管理系统在优化能源分配方面发挥着关键作用，特别是在高度依赖电网的情况下。云计算基础设施解决了智能电网扩展带来的复杂性和可扩展性挑战，实现了实时数据处理和自适应能源控制机制。本研究探讨了能源管理系统在工业环境和研究领域的实际实施，这两者都是推进智能能源解决方案的关键利益相关者。全面回顾了物联网在光伏发电中的应用，重点介绍了该领域的主要研究目标和技术发展。物联网驱动的创新不断发展，提供了许多研究机会，包括制定绩效评估指标和开发新的优化技术。此外，对智能架构框架内能源管理的日益重视强调了深入研究自适应控制策略和系统互操作性的必要性。这项正在进行的研究对于推动物联网能源解决方案的发展和提高智能电网生态系统的效率至关重要。

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引用次数: 0

A comprehensive review on role of information technology in city gas distribution industry 信息技术在城市燃气配送行业中的作用综述

Unconventional Resources

Pub Date : 2025-07-01 Epub Date: 2025-06-09 DOI: 10.1016/j.uncres.2025.100202

Kriti Yadav , Anirbid Sircar , Namrata Bist

India is quickly transitioning towards a gas-based society by expanding the proportion of natural gas in the nation's energy blend from 6 % to 15 % by 2030. India is investing around INR 1.2 trillion in the natural gas distribution of the city gas sector. The most recent developments in distribution include intelligent (acoustic and mechanical) methods for identification of leaks in pipelines, robotic examination, automated testing with ultrasound, thermal mass circulation detectors, geographical information systems, and intelligent carriers and cascade units. The role of the Internet of Things comes into the picture to bind all these digitalisation techniques into a smart technique. This infrastructure eliminates the need for human involvement by integrating different tools and technologies. It allows for the development of smarter cities across the world. This work reveals the possible uses of several internet techniques in the city gas distribution industry. The study introduces readers to the smart technologies used for Smart Gas Distribution, such as Geographical Information Systems, Supervisory Control and Data Acquisition Systems, Applications and Products in Data Processing, etc. The work also highlights the key challenges in the adaptation of these technologies in the gas distribution sector. The paper offers a thorough overview of the topic and motivates academicians and investors to employ a variety of internet solutions. The application of big data, artificial intelligence, and machine learning can contribute to several levels of city gas distribution. The potential risk factors and upkeep expenses might be eliminated with the presence of this intelligent network, with the help of artificial intelligence and machine learning. The distinctiveness that this study presents its ability to bring light on many technologies used in places such as North America, China, South Korea, and Europe, such as DecisionSpace365 and Birdz, and Silent Soft SA's for the gas industry.

印度正在迅速向以天然气为基础的社会转型，到2030年，天然气在该国能源结构中的比例将从6%提高到15%。印度正在投资约1.2万亿卢比用于城市天然气部门的天然气分销。配送领域的最新发展包括用于识别管道泄漏的智能（声学和机械）方法、机器人检查、超声波自动测试、热质量循环探测器、地理信息系统以及智能载体和级联单元。物联网的作用是将所有这些数字化技术结合成一种智能技术。这种基础设施通过集成不同的工具和技术消除了人工参与的需要。它使世界各地的智慧城市得以发展。这项工作揭示了几种互联网技术在城市燃气配送行业的可能用途。该研究向读者介绍了智能配气所使用的智能技术，如地理信息系统、监控和数据采集系统、数据处理中的应用和产品等。这项工作还强调了这些技术在天然气分配领域的关键挑战。该论文对该主题进行了全面概述，并激励学者和投资者采用各种互联网解决方案。大数据、人工智能和机器学习的应用可以为城市燃气分配的几个层次做出贡献。在人工智能和机器学习的帮助下，这种智能网络的存在可能会消除潜在的风险因素和维护费用。这项研究的独特之处是，它能够为北美、中国、韩国和欧洲等地使用的许多技术带来启示，例如DecisionSpace365和Birdz，以及天然气行业的Silent Soft SA。

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引用次数: 0