Huangming rooftop solar power generation

Is rooftop photovoltaic power generation possible in China?

The eastern region has great accumulated photovoltaic electricity potential, which is 3.21 times that of the western region. Rooftop photovoltaic system plays an important role in solar energy power generation especially in urban. In this paper, we present an assessment method for the PV power generation potential of rooftop in China.

How to assess PV power generation potential of rooftop in China?

In this paper, we present an assessment method for the PV power generation potential of rooftop in China. Using machine learning model processes the big data that consists of the gross domestic product, building footprint, road length and population, at a high geographic resolution of 10 km by 10 km.

How many solar thermal heaters does Huang Ming produce a year?

Huang Ming's Himin produces all-glass vacuum tubes, solar water heaters, PV lighting, solar-thermal high-temperature power generation, and solar architecture. As of 2011, Himin Solar produces 2 million m2 solar thermal heaters every year. In total by 2011, it has produced 10 million m2.

What is the potential of rooftop PV in Guangzhou?

A novel systematic method for assessing the potential of urban rooftop PV is proposed. Residential areas contribute 50% of the total rooftop PV potential in Guangzhou, China. The rooftop PV potential in Guangzhou reaches 44.06–72.12 billion kWh per year. Rooftop PV reduces carbon emissions in the power sector in Guangzhou by 72.12–100%.

What is a high-resolution solar photovoltaic potential map of China?

A high-resolution solar photovoltaic potential map of China utilizes the open dataset and one novel neural network model. The data are stated by provinces and cities showing the regional differences. The rooftop photovoltaic generation will be closed to half of the electricity generation of China mainland in 2020.

Does a high-resolution global assessment of rooftop solar photovoltaics potential exist?

Yet, only limited information is available on its global potential and associated costs at a high spatiotemporal resolution. Here, we present a high-resolution global assessment of rooftop solar photovoltaics potential using big data, machine learning and geospatial analysis.