Tele-connection of global crude oil network: Comparisons between direct trade and embodied flows

Song, Zhiguang; Qiao-ling, Zhu; Han, Mengyao

doi:10.1016/j.energy.2020.119359

Cited by 25 publications

(8 citation statements)

References 48 publications

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“…Identifying their sources is important in mitigating the impact of crude oil price shocks on the trade balance. Reference [4] presents the remote connection of global crude oil networks: a comparison of direct trade and actual flows. To illustrate the gap between crude oil trade and consumption, the internal strength of the remote connection of global crude oil is calculated, the topological differences are compared, and the energy risks between direct crude oil trade networks and specific crude oil transport networks are examined.…”

Section: Introductionmentioning

confidence: 99%

Research on Crude Oil Trade Procurement Model Based on DEA-Malmquist Algorithm

Liu

2021

Scientific Programming

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To retain valuable information to the maximum extent and enhance the ability to mine the crude oil trade purchase price demand, this paper proposes a crude oil trade purchase model based on the DEA-Malmquist algorithm. The intranet of the management and control platform shall share the same database, and the intranet shall only allow managers to access and manage the system and only allow all registered users to access and realize data exchange between the intranet and the intranet through two-dimensional code scanning; moreover, due to the resource sharing between the intranet and the intranet for crude oil trade procurement, suppliers and other registered users can immediately grasp the procurement trends of enterprises. Under the DEA-Malmquist algorithm, the uncertainty of procurement management is analyzed by fuzzy theory, and the refined procurement decision model with fuzzy parameters is established. The optimal order time and purchase quantity are determined through the symbol distance and the method of the center of gravity. Experimental results show that the method can effectively retain valuable information in the initial sequence and has better practical application value of material procurement demand intelligent mining. The proposed model obtained the highest accuracy of 98.62%.

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Section: Introductionmentioning

confidence: 99%

Research on Crude Oil Trade Procurement Model Based on DEA-Malmquist Algorithm

Liu

2021

Scientific Programming

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“…Their research is very meaningful and does a lot of favor to our study. In their research [1][2][3][4], countries are divided into two groups. One is the oil im-port-dependent country group and the other is the oil export-dependent countries.…”

Section: Related Workmentioning

confidence: 99%

Long Short-Term Memory and Graph Convolution Network for Forecasting the Crude Oil Traffic Flow

Ouyang¹,

Sun²,

Xue³

et al. 2022

IEEE Access

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Understanding maritime network structure and traffic flow changes is a challenging task that must incorporate economic, energy, geopolitics, maritime transportation, and network sciences. Crude oil is the most imported energy in the world. Investigating the crude oil maritime network status and predicting the crude oil traffic flow changes has great significance for the global trade, especially for key crude oil importing/exporting regions and countries. To address this, a system-based approach using long short-term memory and graph convolution network for the crude oil traffic flow forecasting named LGCOTFF is introduced. The LGCOTFF approach constructs a maritime transportation network firstly, and then calculates and predicts the node traffic flow based on trajectory data and crude oil berth geographical position. Firstly, we construct a maritime crude oil transportation network based on supply-demand relationship, ship trajectory and route information. Then, we design an approach to calculate how many crude oil ships finished up-load/offtake tasks in a single week for each port, and gather this data to countries and regions. Finally, we design a deep learning neural network named long short-term memory and graph convolution network (L-GCN) to extract the temporal and spatial characteristics of crude oil transportation, and predict the node traffic flow. We evaluate the proposed model on China, Russia, Middle East and America respectively and observe consistent improvement of more than 10% over state-of-the-art baselines.

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“…Existing studies have examined embodied energy as a whole or focused on fossil fuels [9,[16][17][18] .…”

Section: Introductionmentioning

confidence: 99%

“…Collectively, they have shed light on the energy footprints of different regions, countries, sectors and income groups [19][20][21][22][23] , as well as the inter-regional [9,16,24,25] and inter-sectoral transfer patterns of embodied energy [26][27][28][29] . They have also focused on energy consumption inequality and carbon leakages related to embodied fossil fuels transfer [30,31] .…”

Section: Introductionmentioning

confidence: 99%

Is embodied renewable energy transfer greening the global supply chain?

Yang,

Chen,

Poon

et al. 2023

Preprint

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Energy underpins international trade, and a greener energy mix can contribute to cleaner global supply chains (GSCs). This paper examines how energy transition has influenced GSC greening through embodied renewable energy transfer. Specifically, we analyze the contribution of countries/regions and sectors to the greening process from 2011 to 2021. We find some evidence of GSC greening over the period as the ratio of renewable energy in total transferred energy increased from 4.2% to 7.6%. Emerging economies that have advanced rapidly in energy transition are gradually overtaking developed countries in their contribution to GSC greening. Sectors with a higher electrification rate are main contributors to GSC greening led by significant inter-sectoral spillovers from the heavy industry and business services. However, transfer of embodied renewable energy by high-income developed countries is concentrated in other high-income countries raising concerns of limited access by low-income developing countries and the amelioration of global energy welfare inequality.

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Tele-connection of global crude oil network: Comparisons between direct trade and embodied flows

Cited by 25 publications

References 48 publications

Research on Crude Oil Trade Procurement Model Based on DEA-Malmquist Algorithm

Research on Crude Oil Trade Procurement Model Based on DEA-Malmquist Algorithm

Long Short-Term Memory and Graph Convolution Network for Forecasting the Crude Oil Traffic Flow

Is embodied renewable energy transfer greening the global supply chain?

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