Energy trade stability of China: Policy options with increasing climate risks

Guo, Kun; Luan, Liyuan; Cai, Xiaoli; Zhang, Dayong; Ji, Qiang

doi:10.1016/j.enpol.2023.113858

Cited by 3 publications

(2 citation statements)

References 64 publications

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“…Imbalances between energy production and demand have promoted inter-regional energy trade among regions. − In large countries such as China, both primary energy and secondary energy are widely traded across regions, forming a complex trade network. − Water is consumed by energy production and then transferred virtually across the energy trade network. This large-scale virtual water transfer has already raised concerns as it results in transboundary water resource displacement and impacts regional water stress .…”

Section: Introductionmentioning

confidence: 99%

Virtual Water Embodied in Interregional Energy Trade in China: A City-Level Analysis

Jin,

Feng,

Yuan

et al. 2024

Environ. Sci. Technol.

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Large volumes of water are used in energy production for both primary (e.g., fuel extraction) and secondary energy (e.g., electricity). In countries such as China, with a large internal trade in fuels and long-distance transmission grids, this can result in considerable water inequalities. Previous research focused on the water impacts of energy production at the national and provincial levels, which is too coarse to identify the spatial differences and make specific case studies. Here, we take the next step toward a spatially explicit economically integrated water-use for energy assessment by combining a bottom-up assessment approach with a city-level multiregional input−output model. Specifically, we examine the water consumption of energy production in China, distinguishing between water for primary and secondary energy at the level of coal mines, oil and gas fields, and power plants for the first time. Of the total energy-related freshwater consumption of 4.9 Gm 3 in 2017, primary energy accounted for 19% (940 Mm 3 ) and secondary energy accounted for 81% (3955 Mm 3 ). Coal was the largest water consumer for both primary and secondary energy (540 and 3880 Mm 3 , respectively), with both oil (361, and 0.5 Mm 3 , respectively) and gas (7 and 69 Mm 3 , respectively) also consuming large amounts. Intercity virtual water, that is, water embodied in energy trade across cities, reached 54% (2.6 Gm 3 ) of energy-related freshwater consumption. Across China, 32% of cities see a bilateral trade in secondary-and primary-energy-related virtual water (e.g., Daqing city exports virtual water embodied in primary fuel to other cities that is then used to produce electricity in those cities, part of which is used back in Daqing via transmission). For these 32% of cities, 73% export more virtual water than import and 27% import more virtual water than export. This study reveals significant differences in city-level virtual water patterns (e.g., scale and direction) between primary and secondary energy to provide information for cities about their virtual water inflow and outflow and the potential collaboration partners for water management.

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Section: Introductionmentioning

confidence: 99%

Virtual Water Embodied in Interregional Energy Trade in China: A City-Level Analysis

Jin,

Feng,

Yuan

et al. 2024

Environ. Sci. Technol.

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“…In recent years, the depletion of traditional energy sources such as coal, oil, and natural gas, due to over-exploitation, has led to an increasingly severe energy crisis [3]. The large-scale development and utilization of these traditional energy sources has also caused significant pollution [4]. Given the high demand for electric energy across various industries, it is crucial to develop new energy sources to ensure power stability.…”

Section: Introductionmentioning

confidence: 99%

Application of a Centroid Frequency-Based Back Propagation Neural Network Fault Location Method for a Distribution Network Considering Renewable Energy Assessment

Zhao,

Lu,

Chen

et al. 2024

Electronics

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The distribution network is a crucial component of the power system as it directly connects to users and serves the purpose of distributing power and balancing the load. With the integration of new energy sources through distributed generation (DG), the distribution network has undergone a transformation from a single power radial network into a complex multi-source network. Consequently, traditional fault location methods have proven inadequate in this new network structure. Therefore, the focus of this paper is to investigate fault location techniques specifically tailored for DG integration into distribution networks. This paper analyzes how fault conditions impact the characteristics of single-phase grounding faults and extracts spectral feature quantities to describe differences in zero-sequence currents under various fault distances. This paper also proposes a fault location method based on centroid frequency and a BPNN (back propagation neural network). The method uses centroid frequency to describe the features of zero-sequence currents; to simulate the mapping relationship between fault conditions and spectral features, BPNN is employed. The mapping relationship differs for different lines and distribution networks. When a line faults, the spectral features are calculated, along with the transition resistance and fault closing angle. The corresponding mapping relationship is then called upon to complete distance measurements. This location method can be applied to various types of distribution lines and fault conditions with high accuracy. Even with insufficient training samples, sample expansion can ensure accuracy in fault distance measurement. We built a distribution network consisting of four feeders with different types and lengths of each line on Simulink and verified the effectiveness of the proposed method by setting different fault conditions. The results suggest that the method has a clear advantage over other frequency domain-based approaches, especially for hybrid lines and feeder lines with branches in distribution networks. Additionally, the method achieves a measurement accuracy within a range of 100 m.

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Extreme weather, policy uncertainty, and risk spillovers between energy, financial, and carbon markets

Dong,

Li,

Huang

et al. 2024

Energy Economics

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Energy trade stability of China: Policy options with increasing climate risks

Cited by 3 publications

References 64 publications

Virtual Water Embodied in Interregional Energy Trade in China: A City-Level Analysis

Virtual Water Embodied in Interregional Energy Trade in China: A City-Level Analysis

Application of a Centroid Frequency-Based Back Propagation Neural Network Fault Location Method for a Distribution Network Considering Renewable Energy Assessment

Extreme weather, policy uncertainty, and risk spillovers between energy, financial, and carbon markets

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