A high-resolution prediction dataset for solar energy across China (2015-2060)

TL;DR

This paper presents a high-resolution, long-term solar radiation prediction dataset for China from 2015 to 2060, supporting renewable energy planning and climate strategies.

Contribution

It develops a detailed hourly solar radiation dataset across China using advanced modeling and bias correction, filling a gap in long-term solar energy data.

Findings

WRF-Chem model accurately reproduces solar radiation patterns.

PV power potential is projected to roughly double by 2060.

Interannual GHI variability is mainly influenced by TCC, with limited AOD impact.

Abstract

A high spatiotemporal resolution and accurate middle-to-long-term prediction data is essential to support China's dual-carbon targets under global warming scenarios. In this study, we simulated hourly solar radiation at a 10 km* 10 km resolution in January, April, July, and October at five-year intervals from 2015 to 2060 across China using the WRF-Chem model driven by bias-corrected CMIP datasets and future emission inventories. We further calculated the monthly photovoltaic power potentials based on an improved assessment model. Results indicate that the WRF-Chem model can reproduce the spatiotemporal evolution of solar radiation with small simulation errors. GHI in 2030 and 2060 over China are characterized by a pronounced west-to-east gradient. The interannual fluctuations of GHI from 2015 to 2060 over China's major PV power generation bases are small, and the interannual variability of GHI is mainly dominated by TCC and the influence of AOD is limited. National averaged PV power generation in China shows a significant growth trend and increases from 68.7 TWh in 2015 to 129.7 TWh in 2060, which is approximately twice the 2015 value. The dataset will provide an important scientific basis for renewable energy planning and grid security under China's dual-carbon strategy.