Optimal Scheduling Study of Hydro–Solar Complementary System Based on Improved Beluga Whale Algorithm

The optimization scheduling model of the hydro–solar complementary system has the characteristics of high dimension, nonlinearity, strong constraints, etc., and it is difficult to solve. In view of this problem, this paper proposes an Improved Beluga Whale Optimization to solve the model. The local development strategy of the IBWO is replaced by the spiral movement of the whale algorithm to enhance the local development ability of the algorithm. In addition, an elimination mechanism is added after the whale fall stage of the original algorithm to increase the population diversity and improve the ability of the algorithm to jump out of the local optimum. This paper compares the solution effect of the IBWO algorithm with several well-known algorithms on 24 classic test functions and 29 CEC2017 test functions; the superior performance of the IBWO algorithm is verified. With the maximum power generation as the goal, the power generation scheduling model of the Beipan River hydro–solar complementary system is constructed and solved by the BWO algorithm, the IBWO algorithm, and the SCA algorithm, respectively. The results show that the IBWO algorithm can effectively improve the power generation of the hydro–solar complementary system and has a faster convergence speed than the BWO algorithm and the SCA algorithm, providing a new optimization tool for dealing with complex engineering optimization problems.