Article
Engineering, Industrial
Xiangying Shan, Weichao Yu, Jing Gong, Weihe Huang, Kai Wen, Hao Wang, Shipeng Ren, Di Wang, Yongheng Shi, Chunyue Liu
Summary: This study proposes a methodology to evaluate the gas supply reliability of natural gas pipeline networks, considering the uncertainty of gas supply capacity. The methodology consists of four parts: gas supply capacity calculation model, gas demand prediction model, gas supply calculation model, and gas supply reliability index system. A real natural gas pipeline network in China is used to confirm the feasibility of the methodology, and the results show a significant improvement in gas supply reliability compared to methods that ignore resource uncertainty. The significance of natural gas resources in gas supply reliability is investigated through sensitivity analysis.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Thermodynamics
Jun Zhou, Yunxiang Zhao, Tiantian Fu, Xuan Zhou, Guangchuan Liang
Summary: This study focuses on optimizing the design parameters of underground natural gas storage pipeline network using a Multiple Condition Hybrid model and Hybrid Genetic Algorithm, demonstrating significant cost reductions can be achieved under boundary conditions.
Article
Engineering, Mechanical
Weichao Yu, Jing Gong, Weihe Huang, Hongfei Liu, Fuhua Dang, Jili Luo, Yuanhang Sun
Summary: The reliability assessment of natural gas pipeline networks is crucial, with divisions into mechanical reliability, hydraulic reliability, and gas supply reliability. Various methods were developed in the study to consider uncertainty and hydraulic characteristics. A case study confirmed the feasibility of the methodology, revealing the impact of market demand uncertainty on meeting gas supply tasks.
JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME
(2021)
Article
Energy & Fuels
Maksim Lysyy, Martin A. Ferno, Geir Ersland
Summary: Underground hydrogen storage in porous media is proposed as a solution to balance seasonal fluctuations in supply and demand. However, there is still insufficient understanding of how hydrogen flows in porous media, specifically regarding relative permeability hysteresis and its impact on storage performance. This study focuses on reservoir simulation and shows that neglecting relative permeability hysteresis leads to overestimation of working gas capacity and recovered hydrogen volume. The study also highlights the importance of accurate modeling of hysteresis for predicting bottom-hole pressures in underground hydrogen storage.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Industrial
Qian Chen, Lili Zuo, Changchun Wu, Yankai Cao, Yaran Bu, Feng Chen, Rehan Sadiq
Summary: An integrated methodology is proposed to assess the gas supply reliability of a gas pipeline network considering stochastic demands. The methodology includes selecting typical scenarios, assessing gas supply conditions using Latin hypercube sampling with the Cholesky decomposition method, and optimizing supply schemes using the Dijkstra algorithm. The assessment results cover probability distributions of gas shortages, identification of vulnerable units, reasons for gas supply shortages, and supply reliability for both the network and individual customers.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Thermodynamics
Sergio Cabrales, Carlos Valencia, Carlos Ramirez, Andres Ramirez, Juan Herrera, Angela Cadena
Summary: The reliability of a natural gas system is crucial for uninterrupted service. This study proposes a methodology involving stochastic cost-benefit analysis, a pipeline contingency model, and a supply contingency model to assess the impact of new infrastructure. The application of this methodology to the Colombian natural gas system shows that the expected benefit-cost ratio of a new pipeline is 2.02, with a 99.0% probability of economic benefit exceeding the cost.
Article
Engineering, Industrial
Kai Yang, Lei Hou, Jianfeng Man, Qiaoyan Yu, Yu Li, Xinru Zhang, Jiaquan Liu
Summary: This study proposes an evaluation method for gas supply reliability based on demand-side economic risk. The user's supply sequence is integrated into the cost matrix to optimize the distribution of demand flow under gas shortage. A calculation model for economic loss cost is established, and a reliability index based on economic risk is used to evaluate supply security.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Economics
David Csercsik
Summary: In this paper, a mechanism for allocation of pipeline capacities based on convex combinatorial auction is proposed and compared with the current model used in the EU through simulation.
Article
Engineering, Industrial
Lin Fan, Huai Su, Wei Wang, Enrico Zio, Li Zhang, Zhaoming Yang, Shiliang Peng, Weichao Yu, Lili Zuo, Jinjun Zhang
Summary: This study proposes a method based on Bayesian networks to optimize the reliability of gas supply in natural gas pipeline networks. The method integrates probabilistic safety analysis with preventive maintenance and converts the system maintenance problem into a Markov decision process, solved by using deep reinforcement learning. The proposed method outperforms others in identifying optimal maintenance strategies by considering the randomness of unit failures and the uncertainty in gas demand profiles.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Weichao Yu, Weihe Huang, Yunhao Wen, Yichen Li, Hongfei Liu, Kai Wen, Jing Gong, Yanan Lu
Summary: This study proposes an integrated method based on demand-side analysis to assess the supply reliability of large-scale and complex natural gas pipeline networks. By analyzing market demand and user importance, the feasibility of the method is confirmed and suggestions for improving supply reliability are provided.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Chemistry, Analytical
Mei Li, Bing Liu, Taotao Chen, Ruidong Liu, Yingzhe Guo, Keyong Hou
Summary: We introduced neon gas as a tracer gas in natural gas pipelines and used a miniature time-of-flight mass spectrometry (mini-TOFMS) for on-site detection to locate underground natural gas pipeline leaks. The mini-TOFMS employed capillary tube sampling to directly analyze leaked neon gas without sample preparation, with a single sample analysis time of only 60 s, significantly faster than the traditional off-line gas chromatography (GC) method. The mini-TOFMS showed a linear response range from 69 ppmv to 3.0 x 105 ppmv, with a limit of detection (LOD, S/N = 3) of 19.0 ppmv. The correlation between GC and mini-TOFMS for quantitative analysis of neon was as high as 0.98. The newly designed method using mini-TOFMS was successfully demonstrated in on-site locating underground natural gas pipeline leaks, particularly for pipes with differing gas pressures buried under the same road, providing more efficient and accurate results.
Article
Multidisciplinary Sciences
Huijie Zhang, Bin Zhang, Yajun Li, Lei Wang, Yutao Li, Lei Shi, Hanxun Wang
Summary: This study presents a methodology for the probabilistic analysis of water curtain performance in underground oil storage considering the spatial variability of hydraulic conductivity. The results show that the difference between the horizontal and vertical spatial correlations of the surrounding rock significantly affects the water-sealed effect. Finally, the optimal design of the water curtain system is discussed.
SCIENTIFIC REPORTS
(2022)
Article
Energy & Fuels
Guangdong Zhang, Sen Yang, Chaoping Mo, Zhiwei Zhang
Summary: This study proposes a new simulation experiment method for converting oil reservoir into gas storage, which controls fluid pressure using capacitive liquid level meter and constant speed and constant pressure pump. This method overcomes the poor repeatability of conventional methods, facilitates oil-gas-water separation and monitoring, and conforms to the mode of injection and production in different wells.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Environmental Sciences
Hugh Z. Li, Patricia M. B. Saint-Vincent, Mumbi Mundia-Howe, Natalie J. Pekney
Summary: The 2015 Aliso Canyon storage well blowout is considered the worst natural gas leak in the history of the United States, releasing approximately 1 million metric tons of methane. A total of 129 incident-related events in underground natural gas storage were compiled from various sources, with a heavy-tailed emission pattern and the top seven events contributing to 98% of the total emissions.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Energy & Fuels
Li Jiqiang, Zhao Guanqun, Qi Zhilin, Yin Bingyi, Xu Xun, Fang Feifei, Yang Shenyao, Qi Guixue
Summary: The stress sensitivity of permeability in UGS reservoirs can significantly affect gas well injectivity and productivity, especially in the first few cycles. As the cycle number increases, the stress sensitivity index of permeability changes with the net stress variations in both the increase and decrease processes.
PETROLEUM EXPLORATION AND DEVELOPMENT
(2021)
Article
Energy & Fuels
Guiliang Li, Bingyuan Hong, Haoran Hu, Bowen Shao, Wei Jiang, Cuicui Li, Jian Guo
Summary: In this study, an early warning model for island-type petrochemical parks was constructed using the back propagation (BP) neural network and particle swarm optimization (PSO). The model was validated using a real park as a case study. The results showed that the optimized neural network was more accurate in early warning, providing an effective tool for safety management in island-type petrochemical parks.
Article
Thermodynamics
Bingyuan Hong, Xiaoping Li, Yu Li, Shilin Chen, Yao Tan, Di Fan, Shangfei Song, Baikang Zhu, Jing Gong
Summary: This paper proposes a steady-state hydraulic simulation model that takes into consideration the characteristics of pressure-exchange ejector. The model is validated by experimental and field data, providing guidance for gas field production.
Article
Thermodynamics
Bingyuan Hong, Xuemeng Cui, Bohong Wang, Di Fan, Xiaoping Li, Jing Gong
Summary: This paper proposes a comprehensive method that considers the various costs of modular equipment and the impact of utilization time on equipment value in unconventional gas field development, aiming to achieve the best economic performance. A real case study is conducted to demonstrate the practicality and advantages of the proposed model.
Article
Energy & Fuels
Kai Wen, Hailong Xu, Wei Qi, Haichuan Li, Yichen Li, Bingyuan Hong
Summary: In this paper, a heat transfer model of a natural gas pipeline based on data feature extraction and first principle models was proposed. The NARX neural network, time series decomposition, and system identification methods were used to model the changes of gas temperatures of the pipeline. The results showed that the data-driven model has advantages over the physics-based simulation models in both accuracy and efficiency.
Article
Thermodynamics
Kai Wen, Dan Qiao, Chaofei Nie, Yangfan Lu, Feng Wen, Jing Zhang, Qing Miao, Jing Gong, Cuicui Li, Bingyuan Hong
Summary: This paper proposes an optimization method for the supply and demand balance of natural gas pipeline networks by considering carbon emission targets and making peak shaving and flow rate allocation schemes. The method accurately describes the hydraulic situation under each allocation scheme and can optimize economic efficiency by 15.58%. It also reduces annual carbon emissions by 58% in large-scale pipeline networks.
Article
Thermodynamics
Kai Wen, Jianfeng Jiao, Kang Zhao, Xiong Yin, Yuan Liu, Jing Gong, Cuicui Li, Bingyuan Hong
Summary: A novel rapid operation control method for natural gas pipeline networks is proposed based on multi-user demand prediction and pipeline flow state inversion. The method analyzes the historical consumption of various users and predicts their demand in the short term using a Nonlinear autoregressive (NAR) neural network. The rapid transient inversion method is derived from the partial differential control equation to realize the inverse of the pipeline flow state, and combined with the equipment model to achieve rapid control of the pipeline networks.
Article
Thermodynamics
Bingyuan Hong, Yanbo Li, Yu Li, Jing Gong, Yafeng Yu, Andong Huang, Xiaoping Li
Summary: The aim of this study is to investigate the erosion laws of 90 degrees elbow, right-angle pipe, and blind tee based on the production parameters of a gas field. The results show that the maximum erosion rate of pipe wall increases exponentially with the fluid velocity. With the development of mining, the lower the free water content, the more serious the pipe wall erosion. Additionally, under the same working conditions, the blind tee is relatively erosion-resistant compared to the 90 degrees elbow and right-angle pipe.
CASE STUDIES IN THERMAL ENGINEERING
(2023)
Article
Energy & Fuels
Huanying Liu, Yulin Liu, Changhao Wang, Yanling Song, Wei Jiang, Cuicui Li, Shouxin Zhang, Bingyuan Hong
Summary: A novel natural gas demand combination forecasting model is constructed in this study to accurately predict the future natural gas demand. By comparing the performance of different forecasting models, the results show that the combinatorial forecasting model has the smallest error, verifying its high accuracy and good stability advantages. Finally, the study analyzes relevant data from 1999 to 2022 and predicts China's natural gas demand in the next 10 years. The results indicate that the annual growth rate of China's natural gas demand in the next 10 years will reach 13.33%, reaching 8.3 x 10(11) m(3) in 2033, highlighting the urgent need for China to rapidly develop gas supply capacity.
Article
Thermodynamics
Jihong Ye, Wei Jiang, Xinxiang Yang, Bingyuan Hong
Summary: With the expansion of the petrochemical industry, safety production accidents have had a serious impact on people's lives and property. This paper proposes an emergency response framework for configuring and managing emergency supplies, using a multi-objective optimization method. The framework considers the pre-disaster and post-disaster stages and provides solutions for material configuration and delivery optimization. The study demonstrates the validity and practicality of the framework using a petrochemical enterprise in Zhoushan, Zhejiang as an example. It shows that the framework can reduce the safety and environmental impact of accidents and improve commodity scheduling efficiency.
Article
Energy & Fuels
Fangwei Lou, Benji Wang, Rui Sima, Zuan Chen, Wei He, Baikang Zhu, Bingyuan Hong
Summary: This paper studies a new non-local means algorithm optimized through the Black Widow Optimization Algorithm to improve the accuracy of pipeline temperature monitoring using the Brillouin Optical Time Domain Analysis system. The field test demonstrates that the new algorithm excels in preserving detailed information within the Brillouin Gain Spectrum and achieves a higher signal-to-noise ratio compared to other non-local means algorithms. The improved method has a better denoising effect and broad application prospects in pipeline safety.
Article
Thermodynamics
Bingyuan Hong, Dan Qiao, Yichen Li, Xiaoqing Sun, Baolong Yang, L. Li, Jing Gong, Kai Wen
Summary: This paper proposes a supply-demand balance method for natural gas pipeline network, and determines the transportation scheme through flow rate allocation. The thermal process is coupled with hydraulic calculation to improve accuracy. The results show the feasibility of transportation decision-making and the accuracy of the proposed model. After optimization, carbon emissions decrease by about 37.81%. The study also analyzes the impact of hydraulic calculation on carbon emissions calculation and highlights the necessity of coupled thermal characteristics in transportation scheme.
Article
Thermodynamics
Xiaoping Li, Qi Yang, Xugang Xie, Sihang Chen, Chen Pan, Zhouying He, Jing Gong, Bingyuan Hong
Summary: A whole process commissioning simulation model is proposed to solve the gas resistance and overpressure in continuously undulating pipelines. The model can calculate the location and volume of gas accumulation and monitor the pressure drop in real time. It has high accuracy, good applicability, and feasibility.
Article
Green & Sustainable Science & Technology
Bingyuan Hong, Bowen Shao, Mengxi Zhou, Jiren Qian, Jian Guo, Cuicui Li, Yupeng Xu, Baikang Zhu
Summary: This paper presents a framework for evaluating the disaster-bearing capacity of natural gas pipeline third-party damage based on probabilistic neural networks. With the utilization of cluster analysis, it was determined that Gaussian mixed model clustering method ultimately identified a total of 5 different levels of disaster-bearing capacity. The proposed evaluation method can provide scientific basis for the prevention and control of third-party damage in oil and gas pipelines and pipeline planning.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Thermodynamics
Xiao Cen, Zengliang Chen, Haifeng Chen, Chen Ding, Bo Ding, Fei Li, Fangwei Lou, Zhenyu Zhu, Hongyu Zhang, Bingyuan Hong
Summary: This paper proposes a prediction method based on the user profiling method to accurately predict user repurchase behavior. The results show that the prediction models have high accuracy, making them valuable for integrated energy supply stations and the energy transition.
Article
Energy & Fuels
Bingyuan Hong, Yanbo Li, Xiaoping Li, Gen Li, Andong Huang, Shuaipeng Ji, Weidong Li, Jing Gong, Jian Guo
Summary: The erosion characteristics of 304 stainless steel and L245 carbon steel in gas-solid two-phase flow were investigated. The research found that the most severe erosion occurs at an angle of approximately 30 degrees for both types of steel. The 304 stainless steel and L245 carbon steel were found to be cut at low angles and impacted at high angles to form erosion pits. The erosion rate is not sensitive to short erosion time and a modified erosion model was proposed to accurately predict the erosion under various industrial conditions.
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
