# Spatial and Temporal Patterns of Green Energy Development in China

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Data Source and Methods

#### 2.1. Data Source

#### 2.2. Analytical Methods

#### 2.2.1. Gravity Center Model

#### 2.2.2. Solving for Gravity Center Offset Distance and Trajectory

#### 2.2.3. Trend Analysis

## 3. Results

#### 3.1. Spatial and Temporal of Non-Conventional Energy Sources

^{2}= 0.97, p < 0.01, Figure 1a). Similarly, the installed capacity of traditional energy generation grew from 3.2 TWh in 2000 to 1.7 Twh in 2021 with a significant temporal tendency of 0.71 TWh/year (R

^{2}= 0.99, p < 0.01, Figure 1a). The installed capacity of non-conventional power generation gradually grew from 0.02 TWh in 2000 to 6.8 TWh in 2021 with a significant temporal tendency of 0.28 Twh/year (R

^{2}= 0.76, p < 0.01, Figure 1a).

#### 3.2. Spatial and Temporal Variations in Energy Development

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

- Zhang, D.; Huang, G.; Xu, Y.; Gong, Q. Waste-to-Energy in China: Key Challenges and Opportunities. Energies
**2015**, 8, 14182–14196. [Google Scholar] [CrossRef] - Cohen, G.; Joutz, F.; Loungani, P. Measuring energy security: Trends in the diversification of oil and natural gas supplies. Energy Policy
**2011**, 39, 4860–4869. [Google Scholar] [CrossRef] - Caineng, Z.; Songqi, P.; Qun, Z. On the Connotation, Challenges and Significance of China’s “Energy Independence” Strategy. Pet. Explor. Dev.
**2020**, 47, 416–426. [Google Scholar] - Zhuang, L.; Xudong, Y.; Guanyi, Z.; Weigang, Z. China’s energy security situation and measures to promote coal to secure energy supply. Coal Econ. Res.
**2021**, 41, 9–13. [Google Scholar] [CrossRef] - Zhang, S.; Yang, Y.; Ding, C.; Miao, Z. The Impact of International Relations Patterns on China’s Energy Security Supply, Demand, and Sustainable Development: An Exploration of Oil Demand and Sustainability Goals. Sustainability
**2023**, 15, 12801. [Google Scholar] [CrossRef] - Wang, J.; Zhang, S.; Zhang, Q. The relationship of renewable energy consumption to financial development and economic growth in China. Renew. Energy
**2021**, 170, 897–904. [Google Scholar] [CrossRef] - Xu, L.; Wang, Q.; Li, N.; Du, X.; Wu, S.; Tian, L.; Wu, C.; Ding, Z. Spatial-temporal evolution of global energy security since 1990s. Acta Geogr. Sin.
**2017**, 72, 2166–2178. [Google Scholar] - Zhang, Y. Analysis of China’s energy efficiency and influencing factors under carbon peaking and carbon neutrality goals. J. Clean. Prod.
**2022**, 370, 133604. [Google Scholar] [CrossRef] - Zeng, M.; Wang, S.; Duan, J.; Sun, J.; Zhong, P.; Zhang, Y. Review of nuclear power development in China: Environment analysis, historical stages, development status, problems and countermeasures. Renew. Sustain. Energy Rev.
**2016**, 59, 1369–1383. [Google Scholar] [CrossRef] - Zhang, D.; Wang, J.; Lin, Y.; Si, Y.; Huang, C.; Yang, J.; Huang, B.; Li, W. Present situation and future prospect of renewable energy in China. Renew. Sustain. Energy Rev.
**2017**, 76, 865–871. [Google Scholar] [CrossRef] - Ren, G.; Wang, W.; Wu, W.; Hu, Y.; Liu, Y. Carbon Emission Prediction Model for the Underground Mining Stage of Metal Mines. Sustainability
**2023**, 15, 12738. [Google Scholar] [CrossRef] - Asif, M.; Muneer, T. Energy supply, its demand and security issues for developed and emerging economies. Renew. Sustain. Energy Rev.
**2007**, 11, 1388–1413. [Google Scholar] [CrossRef] - Zhu, S.; Song, M.; Lim, M.K.; Wang, J.; Zhao, J. The development of energy blockchain and its implications for China’s energy sector. Resour. Policy
**2020**, 66, 101595. [Google Scholar] [CrossRef] - Zhou, J.; Shao, M. Evaluation of Green Innovation Efficiency in Chinese Provincial Regions under High-Quality Development and Its Influencing Factors: An Empirical Study Based on Hybrid Data Envelopment Analysis and Multilevel Mixed-Effects Tobit Models. Sustainability
**2023**, 15, 11079. [Google Scholar] [CrossRef] - Wei, W.; Cai, W.; Guo, Y.; Bai, C.; Yang, L. Decoupling relationship between energy consumption and economic growth in China’s provinces from the perspective of resource security. Resour. Policy
**2020**, 68, 101693. [Google Scholar] [CrossRef] - Xu, Q.; Dong, Y.-X.; Yang, R.; Zhang, H.-O.; Wang, C.-J.; Du, Z.-W. Temporal and spatial differences in carbon emissions in the Pearl River Delta based on multi-resolution emission inventory modeling. J. Clean. Prod.
**2019**, 214, 615–622. [Google Scholar] [CrossRef] - Ediger, V.Ş.; Tatlıdil, H. Forecasting the primary energy demand in Turkey and analysis of cyclic patterns. Energy Convers. Manag.
**2002**, 43, 473–487. [Google Scholar] [CrossRef] - Chen, J.; Xu, C.; Li, K.; Song, M. A gravity model and exploratory spatial data analysis of prefecture-scale pollutant and CO
_{2}emissions in China. Ecol. Indic.**2018**, 90, 554–563. [Google Scholar] [CrossRef] - Lee, S.-C.; Shih, L.-H. Forecasting of electricity costs based on an enhanced gray-based learning model: A case study of renewable energy in Taiwan. Technol. Forecast. Soc. Chang.
**2011**, 78, 1242–1253. [Google Scholar] [CrossRef] - Zhang, Y.; Zhang, J.; Yang, Z.; Li, J. Analysis of the distribution and evolution of energy supply and demand centers of gravity in China. Energy Policy
**2012**, 49, 695–706. [Google Scholar] [CrossRef] - Zhang, Y.; Liu, Y.; Zhang, Y.; Liu, Y.; Zhang, G.; Chen, Y. On the spatial relationship between ecosystem services and urbanization: A case study in Wuhan, China. Sci. Total Environ.
**2018**, 637–638, 780–790. [Google Scholar] [CrossRef] [PubMed] - Zhang, H.; Hewings, G.J.D.; Zheng, X. The effects of carbon taxation in China: An analysis based on energy input-output model in hybrid units. Energy Policy
**2019**, 128, 223–234. [Google Scholar] [CrossRef] - Likas, A.; Vlassis, N.; Verbeek, J.J. The global k-means clustering algorithm. Pattern Recognit.
**2003**, 36, 451–461. [Google Scholar] [CrossRef] - Jin, S.; Nie, X.; Wang, G.; Teng, F.; Xu, T. Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method. J. Mar. Sci. Eng.
**2023**, 11, 485. [Google Scholar] [CrossRef] - Wenjun, C.; Kaiyong, S. Characteristics of the evolution of spatial pattern of coal consumption in China’s provincial areas. Geogr. Geo-Inf. Sci.
**2014**, 30, 56–60+52. [Google Scholar] - Segura, E.; Belmonte, L.M.; Morales, R.; Somolinos, J.A. A Strategic Analysis of Photovoltaic Energy Projects: The Case Study of Spain. Sustainability
**2023**, 15, 12316. [Google Scholar] [CrossRef] - Yuan, K.; Zhang, T.; Xie, X.; Du, S.; Xue, X.; Abdul-Manan, A.F.N.; Huang, Z. Exploration of low-cost green transition opportunities for China’s power system under dual carbon goals. J. Clean. Prod.
**2023**, 414, 137590. [Google Scholar] [CrossRef] - Jia, X.; Zhang, Y.; Tan, R.R.; Li, Z.; Wang, S.; Wang, F.; Fang, K. Multi-objective energy planning for China’s dual carbon goals. Sustain. Prod. Consum.
**2022**, 34, 552–564. [Google Scholar] [CrossRef] - Huang, R.; Zhang, S.; Wang, P. Key areas and pathways for carbon emissions reduction in Beijing for the “Dual Carbon” targets. Energy Policy
**2022**, 164, 112873. [Google Scholar] [CrossRef] - Hao, J.; Gao, F.; Fang, X.; Nong, X.; Zhang, Y.; Hong, F. Multi-factor decomposition and multi-scenario prediction decoupling analysis of China’s carbon emission under dual carbon goal. Sci. Total Environ.
**2022**, 841, 156788. [Google Scholar] [CrossRef] - National Bureau of Statistics of China. China Statistical Yearbook; China Statistics Press: Beijing, China, 2022. [Google Scholar]
- National Bureau of Statistics of China. China Electricity Statistical Yearbook; China Statistics Press: Beijing, China, 2021. [Google Scholar]
- Wang, Y.; Wang, R.; Tanaka, K.; Ciais, P.; Penuelas, J.; Balkanski, Y.; Sardans, J.; Hauglustaine, D.; Liu, W.; Xing, X.; et al. Accelerating the energy transition towards photovoltaic and wind in China. Nature
**2023**, 619, 761–767. [Google Scholar] [CrossRef] [PubMed] - Anderson, J.E. The Gravity Model. Annu. Rev. Econ.
**2011**, 3, 133–160. [Google Scholar] [CrossRef] - Dong, Z.; Ullah, S. Towards a Green Economy in China? Examining the Impact of the Internet of Things and Environmental Regulation on Green Growth. Sustainability
**2023**, 15, 12528. [Google Scholar] [CrossRef] - Zhu, R.; Xue, H. Wind energy zoning in China. J. Sol. Energy
**1983**, 123–132. Available online: https://xueshu.baidu.com/usercenter/paper/show?paperid=72e31d77f0bbd4c1893e343ed8e45f8e&site=xueshu_se (accessed on 30 August 2023). - Herbert, G.J.; Iniyan, S.; Sreevalsan, E.; Rajapandian, S. A review of wind energy technologies. Renew. Sustain. Energy Rev.
**2007**, 11, 1117–1145. [Google Scholar] [CrossRef] - The European Wind Energy Association. The Economics of Wind Energy; EWEA: Brussels, Belgium, 2009. [Google Scholar]
- Chen, X.; Liu, Y.; Wang, Q.; Lv, J.; Wen, J.; Chen, X.; Kang, C.; Cheng, S.; McElroy, M.B. Pathway toward carbon-neutral electrical systems in China by mid-century with negative CO
_{2}abatement costs informed by high-resolution modeling. Joule**2021**, 5, 2715–2741. [Google Scholar] [CrossRef] - Zhang, S.; He, Y. Analysis on the development and policy of solar PV power in China. Renew. Sustain. Energy Rev.
**2013**, 21, 393–401. [Google Scholar] [CrossRef] - Pillai, S.a.; Green, M. Plasmonics for photovoltaic applications. Sol. Energy Mater. Sol. Cells
**2010**, 94, 1481–1486. [Google Scholar] [CrossRef] - Zhao, X.; Zeng, Y.; Zhao, D. Distributed solar photovoltaics in China: Policies and economic performance. Energy
**2015**, 88, 572–583. [Google Scholar] [CrossRef] - Huang, P.; Negro, S.O.; Hekkert, M.P.; Bi, K. How China became a leader in solar PV: An innovation system analysis. Renew. Sustain. Energy Rev.
**2016**, 64, 777–789. [Google Scholar] [CrossRef] - Huang, L.; Zhou, Y.; Han, Y.; Hammitt, J.K.; Bi, J.; Liu, Y. Effect of the Fukushima nuclear accident on the risk perception of residents near a nuclear power plant in China. Proc. Natl. Acad. Sci. USA
**2013**, 110, 19742–19747. [Google Scholar] [CrossRef] [PubMed] - Wang, Q.; Li, R.; He, G. Research status of nuclear power: A review. Renew. Sustain. Energy Rev.
**2018**, 90, 90–96. [Google Scholar] [CrossRef]

**Figure 1.**This figure shows the linear regression trend (

**a**) and annual trend (

**b**) of regional inter-annual installed capacity for the period 2020–2021. The dots represent the annual series of the index under consideration, and the line represents the linear trend. The light shading represents 99% confidence intervals (

**a**). The orange bar indicates the total installed generating capacity during the period of 2000–2021, while the green and violet bars indicate the installed conventional and non-conventional energy source generation capacity during the same period, respectively (

**b**). (Source: based on (CHINA ELECTRIC POWER YEARBOOK)).

**Figure 2.**Spatial distribution of wind power production per region in China, 2011–2020. (Source: based on (CHINA STATISTICAL YEARBOOK)).

**Figure 3.**Spatial distribution of PV power production per region in China, 2011–2020. (Source: based on (CHINA STATISTICAL YEARBOOK)).

**Figure 4.**The location of the stars on the map represents the location of the nuclear power plant. Blue stars are nuclear power plants under expansion, yellow stars are nuclear power plants under construction, and orange stars are nuclear power plants already in commercial operation (

**a**). Heat map of nuclear power generation capacity by province, 2010–2020 (

**b**). Histogram of the number of nuclear power plants (

**c**). (Source: based on (CHINA STATISTICAL YEARBOOK)).

**Figure 5.**2010–2020 energy gravity center of migration trajectory in China from 2010 to 2020. The black triangle is the gravity center of electricity consumption, the red triangle is the gravity center of primary energy production, and the blue triangle is the gravity center of non-conventional energy production. (Source: based on (CHINA STATISTICAL YEARBOOK) and (CHINA ELECTRIC POWER YEARBOOK)).

**Figure 6.**Distance of migration of each energy center of gravity between 2010 and 2020. (Source: based on (CHINA STATISTICAL YEARBOOK) and (CHINA ELECTRIC POWER YEARBOOK)).

**Figure 7.**2010–2020 Non-Conventional Energy Sources: Gravity Center of Migration Trajectory in China. Red dots show the gravity center of nuclear power production, blue dots show the gravity center of wind power production, and yellow dots show the gravity center of PV production. (Source: based on (CHINA STATISTICAL YEARBOOK)).

**Figure 8.**Migration trajectory of GDP in China, 2010–2020. The triangle in (

**a**) represents the gravity center of GDP. Energy Consumption per Unit of GDP and Electricity Consumption per Unit of GDP in China, 2014–2019. (

**b**) shows the red circle representing the rate of increase, the green circle representing the rate of decrease, and the size of the circle representing the scale of the rate of change. (The data used in this figure are based on the CHINA STATISTICAL YEARBOOK and the Communiqué on indicators such as the rate of reduction in energy consumption of 10,000 CNY of gross regional product.).

**Figure 9.**Linear regression trends were analyzed for regional annual energy production or consumption indices for each energy source for the period 2010–2020. Additionally, spatial patterns of annual trends were examined. The magnitude of the rate of change was represented by shades of red, while blue represented a negative rate of change. Grey lines indicated statistical significance at the 99% confidence level. (Source: based on (CHINA STATISTICAL YEARBOOK) and (CHINA ELECTRIC POWER YEARBOOK)).

Data Type | Time Scale (Yearly) | Data Source |
---|---|---|

Primary energy production | 2010–2019 | CHINA ELECTRIC POWER YEARBOOK |

wind power, PV, nuclear energy production | 2010–2020 | CHINA STATISTICAL YEARBOOK |

National electricity consumption | 2010–2020 | CHINA ELECTRIC POWER YEARBOOK |

Installed generating capacity | 2000–2021 | CHINA ELECTRIC POWER YEARBOOK |

GDP | 2010–2020 | CHINA STATISTICAL YEARBOOK |

Electricity consumption per unit of GDP/10,000 CNY | 2014–2019 | Communiqué on indicators such as the rate of reduction in energy consumption of 10,000 CNY of gross regional product |

Energy consumption per unit of GDP/10,000 CNY | 2014–2019 | Communiqué on indicators such as the rate of reduction in energy consumption of 10,000 CNY of gross regional product |

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Yang, Y.; Wang, Z.; Zhang, Y.; Jiang, J.; He, J.
Spatial and Temporal Patterns of Green Energy Development in China. *Sustainability* **2023**, *15*, 15827.
https://doi.org/10.3390/su152215827

**AMA Style**

Yang Y, Wang Z, Zhang Y, Jiang J, He J.
Spatial and Temporal Patterns of Green Energy Development in China. *Sustainability*. 2023; 15(22):15827.
https://doi.org/10.3390/su152215827

**Chicago/Turabian Style**

Yang, Ye, Zegen Wang, Ying Zhang, Jiulin Jiang, and Jiwu He.
2023. "Spatial and Temporal Patterns of Green Energy Development in China" *Sustainability* 15, no. 22: 15827.
https://doi.org/10.3390/su152215827