Research on China’s rural household energy consumption – Household investigation of typical counties in 8 economic zones

Xiao-hua, Wang; Li, Kunquan; Li, Hua; Dan, Bai; Liu, Jingru

doi:10.1016/j.rser.2016.10.004

Cited by 77 publications

(6 citation statements)

References 15 publications

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“…There is an extensive literature examining household energy consumption in China, with certain studies focusing only on rural or urban areas [23]- [25], while others consider the overall [26]- [28]. At present, there are fewer quantitative studies of fixed-point surveys at the farm household level, and mostly for Beijing, Tianjin, Hebei, Northeast, Southeast and other regions of the actual household research data analysis of rural household living energy consumption structure [29]- [31]. The existing surveys, studies and statistics on energy types and their utilization methods only carry out statistics and analysis on energy types, total utilization and industry distribution from a macro perspective.…”

Section: Literature Reviewmentioning

confidence: 99%

Calculation of the Proportion of Population Using Clean Cooking Fuel and Technology Based on Earth Big Data: A Case Study in the South of the Yangtze River in China

Pan,

Yuan,

Guo

et al. 2023

IEEE Access

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Cooking is a very decentralized and private way of energy consumption in human activities. The existing investigation and statistical analysis can't effectively calculate the proportion of population relying on clean cooking fuel and utilization technology in the region. Therefore, based on the big data of the earth, this paper adopts the combination of spatial analysis and statistical analysis to determine the survey sample area, and according to the economic conditions, topographic characteristics, national policies for new energy construction and living habits of the provinces and cities under investigation, the questionnaire survey is conducted for the research area to calculate the proportion of the regional population relying on clean cooking fuels and utilization technologies. Taking the south of the Yangtze River in China as an example, the paper effectively calculates that 88.25% of the population depends on clean cooking fuel and technology in this region, of which 89.81% are in urban areas and 79.87% are in rural areas. Analysis of the survey data shows that the proportion of the population using clean cooking fuels and technologies is related to factors such as economic development, income and resource endowment. There is a large urban-rural gap in terms of energy consumption tendency and structure in the south of the Yangtze River in China and cooking energy consumption in rural households also varies from region to region. The technical ideas and conclusions of the paper have high reference application value, which can help promote the upgrading of clean energy utilization and provide data basis for relevant decision and policy making. INDEX TERMS Clean cooking fuel and utilization technology, population ratio, earth big data

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Section: Literature Reviewmentioning

confidence: 99%

Calculation of the Proportion of Population Using Clean Cooking Fuel and Technology Based on Earth Big Data: A Case Study in the South of the Yangtze River in China

Pan,

Yuan,

Guo

et al. 2023

IEEE Access

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“…In recent years, under the dual pressure of increasing energy consumption and the "Carbon Peak, Carbon Neutral" strategic goal, the relationship between energy supply and demand is increasingly tense, and the change of energy utilization mode is imminent [1] [2]. How to improve the efficiency of energy use, reduce the cost of energy use, reduce environmental pollution and achieve sustainable development of energy is gradually becoming a common concern [3]. The county energy internet (CEI) integrates multiple energy resources to improve energy efficiency and energy supply reliability, which is a crucial and practical way to advance the energy transition.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Collaborative Planning of County Energy Internet

Wang

Chen

Yin

et al. 2023

J. Phys.: Conf. Ser.

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Building a County Energy Internet (CEI) is crucial for achieving green and low-carbon transition and sustainable development of county energy systems. This paper proposes a bi-level collaborative planning method for CEI to configure devices’ capacities in multiple regional CEIs (RCEIs) and plan the interconnected networks simultaneously. Firstly, the models of multi-energy devices and networks are constructed. Then, an optimal partitioning method based on a clustering algorithm is proposed to divide the CEI into multiple RCEIs by considering the load distribution pattern and complementary characteristics. On top of that, a bi-level planning model for CEI is established, wherein the lower-level problem aims at configuring the capacities of devices in RCEIs through mixed-integer linear programming (MILP), while the upper-level problem is the determination of the interconnected multi-energy network topologies by searching the minimum spanning tree. This two-level planning problem is resolved iteratively, in which the network topologies of CEI and energy imbalance in each RCEI are shared information. Case studies on the modified CEI validate the effectiveness and practicality of the proposed method.

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“…China is a largely agricultural country-nearly half of the population lives in rural areas. In the vast rural areas, farmers still use fuelwood, straw, and coal, and other solid fuels as their main cooking energy sources [14][15][16]. In rural China, 307 million people still rely on biomass to cook, and about 33 percent still have no access to CCE [2,17,18].…”

Section: Introductionmentioning

confidence: 99%

Labor Off-Farm Employment and Farmers’ Cooking Clean Energy Use: Evidence from Rural China

et al. 2022

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(Motivation) With the transfer of labor force and the continuous improvement of household income, the household energy consumption structure is also changing. (Gaps) However, few studies have explored the correlations between labor off-farm employment (LOE) and farmers’ cooking clean energy (CCE) consumption. (Methodologies) Using survey data of 8198 farmers in 27 provinces from China’s labor dynamic survey in 2016, the IV-Probit model was used to analyze the impact of LOE on CCE use, and the mediation effect model was used to examine the specific mechanism of action between them. (Results) The results found that: (1) LOE accounted for about 39%, and farmers’ utilization rate of CCE accounted for 40%. (2) LOE has significantly promoted the use of CCE by farmers, and this action mechanism is mainly realized through three paths, that is, per capita annual cash income, social relationship network, and family population structure. (3) The heterogeneity analysis results showed that the head of the household having a university education or above, the family being located in rural areas and mountainous areas, and LOE will have a greater positive impact on the farmers’ CCE use. (Policy) From the micro perspective of LOE, this study can deepen our understanding of LOE and CCE use decisions, and then provide a reference for the rational allocation of labor resources and farmers’ CCE-related policy formulation.

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Research on China’s rural household energy consumption – Household investigation of typical counties in 8 economic zones

Cited by 77 publications

References 15 publications

Calculation of the Proportion of Population Using Clean Cooking Fuel and Technology Based on Earth Big Data: A Case Study in the South of the Yangtze River in China

Calculation of the Proportion of Population Using Clean Cooking Fuel and Technology Based on Earth Big Data: A Case Study in the South of the Yangtze River in China

Hierarchical Collaborative Planning of County Energy Internet

Labor Off-Farm Employment and Farmers’ Cooking Clean Energy Use: Evidence from Rural China

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