Spatial structure analysis of energy storage industry

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Spatial structure analysis of energy storage industry

This study utilizes collaborative energy storage patent data from 2013 to 2022 to construct a technology transfer network among Chinese provinces, analyzing the current state of spatial energy storage technologies.results indicate: (1) The technology transfer network exhibits a core–periphery structure at the provincial level, with certain provinces excelling in both the diffusion and absorption of technology; (2) While the spatial distribution patterns of the two types of technology transfer institutions are similar, significant differences exist in their spatial hierarchies; (3) The two forms of energy storage technology transfer are positively spatially correlated, exhibiting core areas, collapse areas, protrusion areas, and regions with lower energy activity; (4) Six factors – economic development, innovation investment, environmental regulation, industrial clustering, energy production, and consumption – consistently influence the directionality of technology transfer.

Study on the spatial network structure of energy carbon

(3) In terms of the research methodology, a growing number of scholars are utilizing the LMDI decomposition method, the Tobit regression analysis approach, and other similar techniques, while this paper analyses in depth the spatial correlation network structure and driving factors of energy carbon emission efficiency in China''s 282 prefecture

Spatial–temporal evolution and driving force analysis of eco

Spatial autocorrelation analysis refers to the geospatial correlation of the attribute values of a study object caused by its geographical order or location. The spatial correlation of EQ can be further explored in different spatial and temporal contexts, thus giving it strong academic research value in terms of exploring its intrinsic laws.

Spatial disparity and hierarchical cluster analysis of final energy

Furthermore, geographic factors that influence energy consumption are identified by extensive studies that underline the uneven and distinctive spatial distribution [3] addition, the interplay of energy, geography, and society was emphasized as well [4].Thus, several questions become considerable for China''s energy consumption: i) What is the difference of

Spatial structure and influencing factors of China''s energy storage

Explored China''s energy storage technology transfer network from diffusion and absorption perspectives. Investigated the spatial layout and hierarchical patterns of energy

Temporal and spatial dynamics of China''s energy industry

At this stage, the main research methods in industrial agglomeration research are industry concentration (CR n index), the locational entropy index [2], the spatial Gini coefficient [3], the Herfindahl–Hirschman index [4], the Hannah–Kay index [5] and the Ellison–Glaeser index [6]. Most of these measurement methods are endogenous or serve as empirical tests of specific

Temporal and spatial dynamics of China''s energy industry

At this stage, the main research methods in industrial agglomeration research are industry concentration (CR n index), the locational entropy index [2], the spatial Gini coefficient [3], the Herfindahl–Hirschman index [4], the Hannah–Kay index [5] and the Ellison–Glaeser index [6].Most of these measurement methods are endogenous or serve as empirical tests of

Spatial structure and influencing factors of China''s energy storage

We studied the measurement and structural factors influencing China''s provincial total-factor energy efficiency (TFEE) under resource and environmental constraints, using

Review Relationship between urban spatial structure and

The content of the two kinds of urban spatial structure and the mechanism of affecting carbon emissions are quite different. Urban interaction is more of a macroscopic emergence phenomenon in the operation of urban systems. The urban physical spatial structure has a lock-in effect on carbon dioxide emissions and is more fundamental.

Spatial dimensions of sustainable energy

The turn to sustainable energy system is a major societal goal at the global level. In this paper, we argue that this radical shift in energy provision towards increased energy efficiency and the use of renewable resources can

Energy endowment, industrial structure upgrading, and CO

As a serious environmental issue, greenhouse effect is a common challenge for human society (Huo et al., 2021; Khan et al., 2020) ina is actively taking measures such as energy restructuring and industrial structure upgrading to achieve the target of reducing the carbon dioxide emissions (CO 2) per unit GDP by more than 65% compared with that in 2005

Evolutionary characteristics and structural dependence

As a globally emerging critical mineral, lithium is increasingly prominent in international trade, emphasizing the importance for energy transition and industrial structure upgrading to understand the evolution and formation of the global lithium trade networks (GLTN).

Energy

Risk analysis; LCA (Life Cycle Assessment) Spatial analysis; Evaluation of existing energy systems; Policy analysis and policy design . The energy domain. Energy research at the University of Geneva is conducted by the following

Urban spatial structure and total-factor energy efficiency in Chinese

Compared with previous studies, the marginal contribution of this paper is mainly reflected by the following: (1) Urban spatial structure and total-factor energy efficiency are brought into the same research and analysis framework with the mechanism by which urban spatial structure influences total-factor energy efficiency then analyzed.

Analysis of spatial and temporal characteristics and influence

Furthermore, it employs the Geodetector and Geographically Weighted Regression model to analyze the impact of various environmental variables (population density, general public budget expenditure, energy consumption per unit of GDP, green space per capita, industrial structure, GDP per capita) on the spatial distribution of carbon emissions.

Exploring the spatial distribution of distributed energy in China

The global energy utilization patterns are undergoing profound changes. Distributed energy is the future trend of energy transformation, and the world''s major energy consuming countries are actively developing it (Inês et al., 2020).The International Energy Agency''s research report predicts that by 2050, 45% of the world''s total energy consumption will come from

Spatial Economic Network of China''s Lithium Industry: A

attention due to its pivotal role in energy storage and clean energy applications. This study delineates the spatial economic network of China''s lithium industry by analysing

Spatial and Temporal Analysis of Sodium-Ion

As a promising alternative to the market-leading lithium-ion batteries, low-cost sodium-ion batteries (SIBs) are attractive for applications such as large-scale electrical energy storage systems. The energy density, cycling life, and rate

A high spatial resolution suitability layers to

GRIDCERF-China is the only open-source data package that provides data for the geographically and technically suitable locations for power plant site selections in China with high spatial resolution.

Chinese power structure in 2050 considering energy storage

China is rapidly advancing the development of its energy storage industry. In 2020, Instead, they are often based on annual and spatial scales and are primarily used to assess the effects of This study mainly focuses on the role of energy storage and demand response on Chinese future power structure, and in the sensitivity analysis

Study on the spatial network structure of energy carbon

The primary method for studying spatial concentration and gradual change entails utilizing geographic research methodologies, including spatial autocorrelation analysis [39], standard deviation ellipse analysis [40], and cold and hot spot analysis [41], to comprehensively examine the temporal and spatial distributions of carbon emissions in

Spatial structure and influencing factors of China''s energy storage

Empirical evidence from China based on a spatial Durbin model. The patent transfer provides an important indication of technology flows and knowledge diffusion across space. Drawing on

Spatial structure and influencing factors of China''s energy storage

DOI: 10.1016/j.est.2024.114791 Corpus ID: 274737723; Spatial structure and influencing factors of China''s energy storage technology transfer network @article{Lei2025SpatialSA, title={Spatial structure and influencing factors of China''s energy storage technology transfer network}, author={Yunyun Lei and Lirong Ji and Wenting Wang}, journal={Journal of Energy Storage},

Industrial innovation characteristics and spatial

Smart grid industrial agglomeration is conducive to forming an industrial group based on power transmission and transformation technology and equipment, supported by information and intelligent power equipment, covering all links of power generation, transmission, power transformation, distribution, electricity consumption and dispatching, and

Performance characteristics, spatial connection and industry

Based on the research, it recommends that balance energy storage industry spatial layout, improve battery operation sub-industry which has overall low efficiency, improving

How does industrial transformative process shape the spatial

To address this gap, we use partial redundancy analysis (PRDA) to quantify the relative impact of key industrial employment sectors. The results indicate that the transformation of industrial structure has a significant influence on the spatial dynamics and morphologies of urban built-up areas.

Research on the spatiotemporal evolution characteristics and

China is currently facing enormous pressure to reduce emissions, and in order to realize synergistic emission reduction between regions, the spatial connection effect of carbon emissions must be considered comprehensively. Based on the data of 260 cities from 2001 to 2021, the social network analysis (SNA) method is utilized to explore the evolution

Spatial correlation network structure of energy-environment

Thus, this study delves into the spatial correlation network structure of energy-environment efficiency in the Yangtze River Delta urban agglomeration and its driving factors

Energy storage in China: Development progress and

Energy, exergy and economic analysis of a novel multi-generation liquefied air energy storage system coupled with coal-fired power unit based on ejector and absorption refrigeration Spatial structure and influencing factors of China''s energy storage technology transfer network energy storage technology is the key to effectively

Spatial optimization of land use and carbon storage

In the socioeconomic system, LULC changes support human social activities and industrial processes, which in turn affect energy inputs and produce large amounts of carbon emissions. This process influences the CS balance in the ecosystem and significantly impacts the terrestrial carbon cycle (Ma et al., 2017; Higgins et al., 2023). Therefore

Industrial innovation characteristics and spatial differentiation of

With the transformation of electrification, the traditional power grid is increasingly unable to meet the growing needs of people [1], [2], [3], [4].At present, there is an urgent need for an intelligent system that can integrate energy resource development and transmission technology, existing power generation, transmission, distribution and sales functions of

Characterizing the spatial correlation network structure and

In summary, the analysis of various indicators of the overall network shows that with the high-quality development of China''s economic level, the continuous improvement of the energy market, and the industrial agglomeration of industrial production, there is a spatial connection and spillover path in TCEE of China''s inter-provincial

Spatial Analysis of Tertiary Industry Evolution Based on

The service and knowledge economy has emerged as the primary drivers of national economic growth, with the tertiary industry leading the way. To promote growth in the central plain region and achieve structural convergence of industries for sustainable, rapid, and healthy economic development, conducting a spatial structural analysis of the evolution of the

Characteristics of spatial association and driving factors of power

Employing methodologies such as the gravity model and Moran''s I analysis, it explores the spatial structural characteristics and correlation patterns of the power battery

4 FAQs about [Spatial structure analysis of energy storage industry]

What is the spatial relationship between energy consumption and economic activity?

The spatial association of industry 10, finance 11 and consumption 12 has broken the geographical proximity limit and formed a spatial correlation network. As a product of economic activity, the spatial effects of energy consumption also transcend geographical proximity and gradually assume the characteristics of a spatial network 13.

Are energy consumption structure differences related to environmental regulation differences?

The correlation coefficient between energy consumption structure differences and environmental regulation differences is positive, indicating that the difference in energy consumption structure and environmental regulation between cities is conducive to the formation of a spatial correlation network of energy-environment efficiency.

Why is in situ TEM analysis important?

Meanwhile, ultra-fast acquisition time ensures temporal resolution to monitor the dynamic reaction processes; thus, in situ TEM analysis is expected to empower researchers to elucidate complex and heterogeneous electrochemical reactions with more than one type of charge storage mechanisms.

What is ex situ analysis?

Ex situ analysis can be preliminary steps, but only the equilibrium state is probed. Therefore, to gain sufficient understanding of aforementioned dynamic changes, it is essential to apply higher-level in situ or real-time (operando) characterizations.

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