Multi-energy complementary power generation (MEPG) technology is one of the effective utilization means of renewable energy generation. In this paper, a MEPG system is proposed, which includes a photovoltaic (PV) subsystem and ISCC (solar integrated combined cycle) subsystem. To optimize the capacity of the PV subsystem, the dynamic simulation of the MEPG system is carried out under the condition of operating for 2 hours continuously. By stabilizing the output power of the MEPG system at the target value during the operation, the relatively suitable capacity of the PV subsystem is obtained. The results show that for the MEPG system, the PV subsystem should be less than the capacity of the solar field in the ISCC subsystem.

The output power of photovoltaic (PV) power plant is influenced by the fluctuation of meteorological conditions, which, coupled with the intermittent nature of the power output, has raised concerns about the stability of power grid. According to the variations in meteorological conditions, PV power prediction technology can predict the PV output power in advance to decrease the influence of PV power generation on the stable operation of the power grid. In this paper, the PV power prediction model is built on Matlab simulation software with a BP neural network algorithm. After that, the power prediction calculation of a PV power station is carried out under the operation conditions of sunny and cloudy days. The results show that, in the periods of prediction, the power curve of the predicted value is close to the power curve of the real value, which demonstrates the great accuracy of the BP prediction model established in this paper.