Research on Modeling Method for Long-Term Optimal Dispatching of High-Ratio New Energy Power System

With the rapid development of new energy sources and large-scale grid connection, the computational cost becomes high when dealing with long-term optimal scheduling data. In this paper, we propose a temporal cycle-based optimal scheduling modeling method, which decomposes $\mathbf{7 2 0}$ hours of data into 30 days, 24 hours a day, and a cyclic new energy unit optimal scheduling model with one hour as the scenario, which significantly reduces the computational complexity of the model. The model fully takes into account the uncertainty of wind energy and photovoltaic units in the long-term optimal scheduling process with, the objective function is to achieve the minimization of the total cost of the unit. Finally, it is analyzed by the IEEE 24-bus system, a classical power system arithmetic example, and the results show that the computational efficiency of the system is significantly improved, the rate of wind and photovoltaic abandonment is reduced, and the overall operating cost is more competitive after considering the time-cycling optimization.