Medium and long term load forecasting considering the uncertainty of distributed installed capacity of photovoltaic generation

Nowadays, the scale of distributed photovoltaic generation integrated into the distributed network and its penetration rate are growing continuously. The increase of installed capacity of distributed PV generation, sensitive to the market and national policies, is highly uncertain. Besides, the output of PV generation is highly random and clustered. This has posed great challenges to the medium and long term load forecasting of power system. In this paper, a neural network expert system model is proposed to predict the installed capacity of distributed PV on the target year. A method is put forward to predict the effective clipping capacity of the distributed PV generation during peak hours, providing new ideas for long term load forecasting with the distributed PV power integrated into the grid.