The invention discloses a
cascade reservoir
optimal scheduling method based on a self-adaptive improved
particle swarm optimization algorithm, and belongs to the field of water conservancy and
hydropower. The
cascade reservoir
optimal scheduling method comprises the steps: obtaining basic information of a
cascade reservoir system; constructing a cascade reservoir
optimal scheduling model taking the
water level of each time period in the reservoir scheduling period as a decision variable and the maximum
generating capacity as an objective function, and determining constraint conditions; initializing particle swarm parameters according to basic information and constraint conditions of the cascade
reservoir system; calculating the relative progress of each particle, updating the
inertia weight,
cognitive learning factor and social
learning factor of each particle according to the relative progress, and further updating the speed and position of each particle; and calculating the optimal
adaptive value after the particle swarm updating is completed, and obtaining the power generation capacity, the month end
water level and the reservoir outlet flow of the cascade
reservoir system in each month. According to the cascade reservoir optimal scheduling method, the particle swarm parameters are adaptively adjusted by using the particle relative progress, and the defect that the traditional
particle swarm algorithm is easy to fall into
local optimum is overcome, and the power generation benefit of the cascade reservoir is improved.