EMPIRICAL ANALYSIS OF NATURAL AND SOCIAL FACTORS AFFECTING NEWLY INSTALLED CAPACITY OF RURAL ROOFTOP DISTRIBUTED PHOTOVOLTAIC SYSTEM AT COUNTY LEVEL IN JIANGSU PROVINCE

Zhu Tao; Chang Xiangyang; Zhu Fanglin; Deng Aidong; Zhu Lin

doi:10.19912/j.0254-0096.tynxb.2022-1158

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (5) : 217-225. DOI: 10.19912/j.0254-0096.tynxb.2022-1158

EMPIRICAL ANALYSIS OF NATURAL AND SOCIAL FACTORS AFFECTING NEWLY INSTALLED CAPACITY OF RURAL ROOFTOP DISTRIBUTED PHOTOVOLTAIC SYSTEM AT COUNTY LEVEL IN JIANGSU PROVINCE

Zhu Tao¹, Chang Xiangyang¹, Zhu Fanglin², Deng Aidong³, Zhu Lin⁴

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Abstract

Rural rooftop distributed photovoltaic system is developing rapidly. However, there is no systematic analysis on the influencing factors and degree of its development. Aiming to solve this problem, this research establishes empirical models on panel data of 64 county-level regions for 39 months, and then evaluates on the whole level of Jiangsu province and regional comparison of southern, middle and northern part of Jiangsu. The results show that there is little correlation between newly installed capacity of rural rooftop distributed PV and natural endowments such as solar energy resources. The development is spontaneous and disorderly, lacking guidance and policy planning. Newly installed capacity is closely related to social factors such as residents’income. Residents who install rural rooftop distributed PV are mainly low-income groups. The coverage rate of rural rooftop distributed PV need to be increased. The residents’ awareness of participation in clean energy usage and green and low-carbon concept is not deep enough. The government should enhance the publicity of rural rooftop distributed PV。

Key words

solar energy / rural areas / influence factor analysis / distributed / rooftop PV / county level

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Zhu Tao, Chang Xiangyang, Zhu Fanglin, Deng Aidong, Zhu Lin. EMPIRICAL ANALYSIS OF NATURAL AND SOCIAL FACTORS AFFECTING NEWLY INSTALLED CAPACITY OF RURAL ROOFTOP DISTRIBUTED PHOTOVOLTAIC SYSTEM AT COUNTY LEVEL IN JIANGSU PROVINCE[J]. Acta Energiae Solaris Sinica. 2023, 44(5): 217-225 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1158

References

[1] 张彩庆, 龚运. 农村最优能源消费结构及测算方法研究:以京津冀地区为例[J]. 江苏农业科学, 2018, 46(16): 359-362.
ZHANG C Q, GONG Y.Study on optimal energy consumption structure and calculation method in rural area-Taking Beijing-Tianjin: Hebei region as an example[J]. Jiangsu agricultural sciences, 2018, 46(16): 359-362.
[2] 李琼慧, 叶小宁, 胡静, 等. 分布式能源规模化发展前景及关键问题[J]. 分布式能源, 2020, 5(2): 1-7.
LI Q H, YE X N, HU J, et al.Outlook and critical issues of large-scale development on distributed energy resource[J]. Distributed energy, 2020, 5(2): 1-7.
[3] 杜松怀, 孙若男, 杨曼, 等. 光伏扶贫农村综合能源站设计与优化配置方法[J]. 农业机械学报, 2021, 52(增刊1): 367-376.
DU S H, SUN R N, YANG M,et al.Optimal allocation method of rural integrated energy station under background of photovoltaic poverty alleviation[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(S1): 367-376.
[4] 雷小苗, 何继江, 杨守斌, 等. 能源转型视域下“零碳乡村”的可行性和环保性: 以陕西关中C县F村为例[J]. 北京理工大学学报(社会科学版), 2020, 22(5): 32-41.
LEI X M, HE J J, YANG S B, et al.Feasibility and environmental protection of “zero carbon rural” from the perspective of energy transition: take F Village in Middle area of shaanxi province as an example[J]. Journal of Beijing Institute of Technology(social sciences edition), 2020, 22(5): 32-41.
[5] 王晓珍, 郑颖, 蒋子浩, 等. 补贴政策对家用光伏购买意愿的影响: 基于心理距离和风险偏好的实证分析[J]. 软科学, 2019, 33(4): 130-135.
WANG X Z, ZHENG Y, JIANG Z H, et al.Impact of subsidy policy on home photovoltaic purchase intention: based on psychological distance and risk preference[J]. Soft science, 2019, 33(4): 130-135.
[6] 仇焕广, 严健标, 江颖, 等. 中国农村可再生能源消费现状及影响因素分析[J]. 北京理工大学学报(社会科学版), 2015, 17(3): 10-15.
QIU H G, YAN J B, JIANG Y, et al.Renewable energy consumption in rural China:current situation and major driven factors[J]. Journal of Beijing Institute of Technology(social sciences edition), 2015, 17(3): 10-15.
[7] 贾亚雷, 石建国, 庞永超, 等. 基于省级截面数据的分布式光伏发电补贴政策实证分析[J]. 可再生能源, 2016, 34(10): 1435-1440.
JIA Y L, SHI J G, PANG Y C, et al.An Empirical analysis of subsidy policy on distributed photovoltaic power generation based en provincial cross-sectional data[J]. Renewable energy resources, 2016, 34(10): 1435-1440.
[8] 闫彤. 基于面板数据的新能源政策效果评价研究[D]. 北京: 华北电力大学, 2020.
YAN T.Research on effectiveness assessment of new energy policy based on panel data[D]. Beijing: North China Electric Power University, 2020.
[9] 董长贵, 周润民, 李佳颖. 补贴政策对中国光伏装机市场的影响: 基于面板数据回归的实证分析[J]. 资源科学, 2021, 43(6): 1065-1076.
DONG C G, ZHOU R M, LI J Y.The effect of feed-in tariff on China’s photovoltaic capacity development: an empirical analysis based on panel data regression[J]. Resources science, 2021, 43(6): 1065-1076.
[10] 任惠, 孙辰军, 陈静, 等. 分布式光伏配网补贴方法的长期效果分析[J]. 太阳能学报, 2019, 40(7): 1881-1889.
REN H, SUN C J, CHEN J, et al.Long-term effect analysis of distribution subsidy on development of DGPV[J]. Acta energiae solaris sinica, 2019, 40(7): 1881-1889.
[11] 黄珺仪. 补贴政策对风电产业发展影响的实证分析[J]. 生态经济, 2018, 34(5): 115-120.
HUANG J Y.An empirical analysis of the impact of subsidy policy on wind power industry[J]. Ecological economy, 2018, 34(5): 115-120.
[12] 沈根祥. 计量经济学[M]. 上海: 上海财经大学出版社, 2013: 51.
SHEN G X.Introductory Econometrics[M]. Shanghai: Shanghai University of Finance and Economics Press, 2013: 51.