Abstract
Carbon reduction goals have driven China to become the world’s largest renewable energy system (RES) that is dominated by hydropower, wind power and solar power. However, the meteorological sensitivity of wind and solar power greatly affects the reliability and generating capability of the RES, particularly in extreme weather events. Quantifying the electricity supply and flexibility of hydropower is crucial for compensating extreme wind and solar power generation. Here we investigate the influence of extreme weather combinations and future climate on the generating capability of the national RES and quantify the flexibility demand and hydropower supply in typical extreme weathers. Our analysis reveals that the annual utilization hours of the hydropower–wind–solar system are projected to decline by nearly 12% from the current stage to 2060 under conditions of extreme drought, low wind and weak solar radiation. When encountered with extremely strong solar radiation and wind, the probability of flexibility shortages in hydropower is estimated to rise to 47% by 2030 and further increase to 60% by 2060. Nearly half of the provinces will require tens of millions of kilowatts of energy storage by 2030 to supplement the flexibility supply gap of hydropower, and by 2060, both the number of provinces that require such a large-scale energy storage and the storage capacity needs might double. Our findings provide early warnings in extreme electricity supply and underscore the growing necessity for building dispatchable power plants and exploring the flexibility of existing hydropower systems.
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Data availability
ERA5 data are available at https://www.ecmwf.int/. CMIP6 data are available at https://aims2.llnl.gov/search. The operating parameters and run-off data for reservoirs and hourly load cannot be disclosed owing to our non-disclosure agreements with power grid corporations. However, they can be obtained from the corresponding author upon reasonable request. Other data used in this Article are provided in the Supplementary Information (Supplementary Tables 8–18).
Code availability
The optimal scheduling model for hydropower is solved by Lingo 18. The interprovincial power exchange model, 8,760 h production simulation and energy storage sizing optimization model are implemented via Python 3.10 and solved by Gurobi 10.0.1. The evaluation method for flexibility demand and supply is implemented via MATLAB R2018a. All the core codes are in the Supplementary Information. Other codes can be obtained from the authors upon reasonable request.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (grant nos. U23A20667, 52239001 and 52079014).
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Authors and Affiliations
Contributions
J.S., Y.W. and M.L. designed and performed the experiments. J.S. and Y.W. analysed the data and wrote the paper. C.C., J.K.K., J.W., X.G., X.L., B.Z. and L.G. reviewed and edited the paper.
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Nature Water thanks Omar J. Guerra and Amarasinghage Tharindu Perera for their contribution to the peer review of this work.
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Supplementary information
Supplementary Information
Supplementary Notes 1 and 2, Figs. 1–14 and Tables 1–18.
Supplementary Code 1
Interprovincial power exchange model.
Supplementary Code 2
8,760 h production simulation.
Supplementary Code 3
Energy storage sizing optimization model.
Source data
Source Data Fig. 1
China map; selected eight basin boundaries; provincial wind power density at 100 m and the total solar radiation.
Source Data Fig. 2
The experience frequency of inflows from 1980 to 2019 for selected eight basins; the national wind capacity factors and the number of provinces included in each level from 1980 to 2019; the national solar capacity factors and the number of provinces included in each level from 1980 to 2019.
Source Data Fig. 3
The generating capability of hydropower in 2023; the generating capabilities of wind and solar power in extremely strong and weak scenario in 2023; the generating capabilities of hybrid system under different scenarios in 2023; the generating capabilities of scenario 1 in 2023, 2030 and 2060.
Source Data Fig. 4
China map; provincial power shortage and curtailment of July in scenario 1 in 2023, 2030 and 2060 under two modes: independent operation of provincial power grids and considering the interprovincial channels.
Source Data Fig. 5
UFD and DFD under different scenarios in the current stage.
Source Data Fig. 6
The IPUPF and IPDFP under different scenarios in the current stage; the share of hydropower in total installed capacity.
Source Data Fig. 7
Power capacities of energy storage under scenario 1 in 2030 and 2060; the IPUFP and IPDFP under scenario 1 in 2030 and 2060.
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Shen, J., Wang, Y., Lin, M. et al. Quantifying the impact of extreme weather on China’s hydropower–wind–solar renewable energy system. Nat Water 3, 415–429 (2025). https://doi.org/10.1038/s44221-025-00408-9
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DOI: https://doi.org/10.1038/s44221-025-00408-9
