Semantic Scholar Open Access 2020 357 sitasi

Rapid cost decrease of renewables and storage accelerates the decarbonization of China’s power system

Gang He Jiang Lin F. Sifuentes Xu Liu N. Abhyankar +1 lainnya

Abstrak

The costs for solar photovoltaics, wind, and battery storage have dropped markedly since 2010, however, many recent studies and reports around the world have not adequately captured such dramatic decrease. Those costs are projected to decline further in the near future, bringing new prospects for the widespread penetration of renewables and extensive power-sector decarbonization that previous policy discussions did not fully consider. Here we show if cost trends for renewables continue, 62% of China’s electricity could come from non-fossil sources by 2030 at a cost that is 11% lower than achieved through a business-as-usual approach. Further, China’s power sector could cut half of its 2015 carbon emissions at a cost about 6% lower compared to business-as-usual conditions. The decrease in costs of renewable energy and storage has not been well accounted for in energy modelling, which however will have a large effect on energy system investment and policies. Here the authors incorporated recent decrease in costs of renewable energy and storages to refine the pathways to decarbonize China’s power system by 2030 and show that if such cost trends for renewables continue, more than 60% of China’s electricity could come from non-fossil sources by 2030 at a cost that is about 10% lower than achieved through a business-as-usual approach.

Penulis (6)

G

Gang He

J

Jiang Lin

F

F. Sifuentes

X

Xu Liu

N

N. Abhyankar

A

Amol A. Phadke

Format Sitasi

He, G., Lin, J., Sifuentes, F., Liu, X., Abhyankar, N., Phadke, A.A. (2020). Rapid cost decrease of renewables and storage accelerates the decarbonization of China’s power system. https://doi.org/10.1038/s41467-020-16184-x

Akses Cepat

Lihat di Sumber doi.org/10.1038/s41467-020-16184-x
Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
Total Sitasi
357×
Sumber Database
Semantic Scholar
DOI
10.1038/s41467-020-16184-x
Akses
Open Access ✓