Application of Improved Particle Swarm Optimization Algorithm in Reservoir Optimal Scheduling

The reservoir optimization and dispatch are hounded by the problems of large scale and complex structure, the involvement of a large number of decision variables, and complex constraints, as well as the high-dimensional, nonlinear, and strong constraints. In view of this, the traditional optimization method is difficult to solve directly or has low calculation efficiency, and there are problems such as premature maturity. In this study, the particle swarm optimization (PSO) algorithm based on the inertia weight of the decaying cosine curve overcomes the shortcomings of the existing PSO algorithm, which is easy to fall into the local optimum, enhances the global and local search capabilities, and offers an improved PSO algorithm. By applying the above optimization algorithm to the reservoir optimization dispatch model, it is found that the method is easy to implement, and the efficiency is high, which provides a new way for the solution of the reservoir optimization dispatch model.