Research on optimal scheduling of water and light complementation based on multi-objective genetic algorithm

With the continuous growth of global economy and population, the demand for energy in human society is increasing rapidly. Traditionally used fossil fuels are often limited and non-renewable, causing great damage to the environment while emitting large amounts of greenhouse gases into the atmosphere, leading to global warming. Water-light complementary power generation is an important form of power generation to promote photovoltaic grid connection and build a new power system. However, the photoelectric output has significant intermittency, fluctuation and randomness, and direct connection to the grid will cause great pressure on the peak regulation and stable operation of the power grid. The hydropower unit has the advantages of quick start and stop, flexible operation, large amplitude of output change, rapid response to load change, and plays an important role in the peak regulation and frequency regulation of the power grid. In this paper, the optimal scheduling model of water-light complementation is established, and the typical output characteristics of photovoltaic power stations are analyzed. Taking the maximum peak load balancing capacity and the minimum deviation between the output and load demand of the complementary system during the scheduling period as the objective function, genetic algorithm is adopted to solve the problem. Finally, it is concluded that water-light complementation can significantly improve the peak load balancing capacity of the system.