Potential Driving Factors on Surface Solar Radiation Trends over China in Recent Years

Wang, Qiuyan; Zhang, Hua; Wild, Martin

doi:10.5194/egusphere-egu21-5264

Cited by 3 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Second is calculating capital flow using the theory of national economic accounting. Wang and Fan (2004), and Hu and Wu (2012) deduced the scale of capital flow by measuring the reverse scale of regional goods flow. Third is calculating the total capital flow from different channels respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Regional capital flow and capital allocation efficiency of high‐tech enterprises in China

Geng

2023

J Corp Accounting Finance

View full text Add to dashboard Cite

From the perspective of capital flow, the study analyses the preference and spatial difference of capital flow of high‐tech enterprises, and uses the Super‐SBM‐DEA model to analyze the capital allocation efficiency. On this basis, the influence of capital flow of financial institutions, capital market, government, and foreign capital flow on capital allocation efficiency is further analyzed. We found the influence of different channels of capital flow on the capital allocation efficiency is heterogeneous. Finally, suggestions are made to optimize capital flow and improve the capital allocation efficiency of high‐tech enterprises in different regions.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Regional capital flow and capital allocation efficiency of high‐tech enterprises in China

Geng

2023

J Corp Accounting Finance

View full text Add to dashboard Cite

show abstract

An Assessment of the Influences of Clouds on the Solar Photovoltaic Potential over China

Jiang¹,

Yi²

2023

Remote Sensing

View full text Add to dashboard Cite

Clouds are important modulators of the solar radiation reaching the earth’s surface. However, the impacts of cloud properties other than cloud cover are seldom mentioned. By combining the satellite-retrieved cloud properties, the latest radiative transfer model, and an advanced PVLIB-python software for solar photovoltaic (PV) estimation, the impacts of different types of clouds on the maximum available solar PV potential (measured with the plane-of-array-irradiance, POAI) are quantified. The impacts of ice and liquid water clouds are found to be the highest on Tibetan Plateau over western China in spring, and central and southern China in winter, respectively. The reduction of POAI by liquid water clouds is almost twice of that by ice clouds except for spring. It is found that the POAI can be reduced by 27–34% by all clouds (ice + liquid water clouds) in different seasons. The sensitivities of the solar PV potential to the changes in cloud properties including the cloud fraction, cloud top pressure, cloud effective radius, and cloud water path are also analyzed. Three kinds of settings of PV panel tilting, namely fixed tilt, one-axis tracking, and two-axis tracking, are considered. It is found that the cloud properties are essential to estimate the solar PV potentials, especially for the cloud fraction. The attenuation of solar radiation by clouds are growingly larger as the solar plane tilting settings get more complicated. The outlook of solar PV potential is quite variable as the changes in cloud properties are highly uncertain in the future climate scenarios.

show abstract

Development of a Machine Learning Forecast Model for Global Horizontal Irradiation Adapted to Tibet Based on Visible All-Sky Imaging

Chen

Nima

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

The Qinghai-Tibet Plateau is rich in renewable solar energy resources. Under the background of China’s “dual-carbon” strategy, it is of great significance to develop a global horizontal irradiation (GHI) prediction model suitable for Tibet. In the radiation balance budget process of the Earth-atmosphere system, clouds, aerosols, air molecules, water vapor, ozone, CO2 and other components have a direct influence on the solar radiation flux received at the surface. For the descending solar shortwave radiation flux in Tibet, the attenuation effect of clouds is the key variable of the first order. Previous studies have shown that using Artificial intelligence (AI) models to build GHI prediction models is an advanced and effective research method. However, regional localization optimization of model parameters is required according to radiation characteristics in different regions. This study established a set of AI prediction models suitable for Tibet based on ground-based solar shortwave radiation flux observation and cloud cover observation data of whole sky imaging in the Yangbajing area, with the key parameters sensitively tested and optimized. The results show that using the cloud cover as a model input variable can significantly improve the prediction accuracy, and the RMSE of the prediction accuracy is reduced by more than 20% when the forecast horizon is 1 h compared with a model without the cloud cover input. This conclusion is applicable to a scenario with a forecast horizon of less than 4 h. In addition, when the forecast horizon is 1 h, the RMSE of the random forest and long short-term memory models with a 10-min step decreases by 46.1% and 55.8%, respectively, compared with a 1-h step. These conclusions provide a reference for studying GHI prediction models based on ground-based cloud images and machine learning.

show abstract

Potential Driving Factors on Surface Solar Radiation Trends over China in Recent Years

Cited by 3 publications

References 27 publications

Regional capital flow and capital allocation efficiency of high‐tech enterprises in China

Regional capital flow and capital allocation efficiency of high‐tech enterprises in China

An Assessment of the Influences of Clouds on the Solar Photovoltaic Potential over China

Development of a Machine Learning Forecast Model for Global Horizontal Irradiation Adapted to Tibet Based on Visible All-Sky Imaging

Contact Info

Product

Resources

About