Statistical machine learning techniques of weather simulation for the fishery-solar hybrid systems

The economically developed and densely population-rich southeastern part of China has always been a load center for electricity. However, due to the high population density, land resources in southeastern China are tight, making it impossible to build large-scale contiguous ground-mounted photovoltaics (PV) plants as in western China (Fu, 2022a). Therefore, distributed PV has become the preferred choice in southeastern China. Combining the characteristics of coastal and wetlands of rivers and lakes, a new concept of the fishery-solar hybrid system is proposed, which is a new model of distributed PV combined with the fishery, that is, the photovoltaic panel array is set up above the water surface of the fish pond, and the water below the photovoltaic panels can be used for fish and shrimp farming, and the photovoltaic array can also provide good shading for fish farming (Fu, 2022b). Through the clean, efficient, low-carbon innovation model, we can improve the added value of land, and also achieve complementary development between multiple industries. The project is doubly beneficial to achieve the carbon peaking and carbon neutrality goal and economic development.