Cascade reservoir optimal scheduling method based on self-adaptive improved particle swarm optimization algorithm

Abstract

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.

Description

technical field [0001] The invention belongs to the technical field of water conservancy and hydropower, and more specifically relates to a cascade reservoir optimization scheduling method based on an adaptive improved particle swarm algorithm. Background technique [0002] The optimal dispatching of cascade reservoirs in the basin is to coordinate the relationship between water head, flow and output among reservoirs at all levels under the premise of meeting the market, power grid load demand and hydropower system constraints, upstream and downstream flood control safety, ecological safety, and shipping safety, so as to improve the quality of cascade reservoirs in the basin. Therefore, the optimal dispatching of cascade reservoirs is essentially a multi-dimensional, multi-local extremum, complex nonlinear multi-constraint optimization problem. [0003] At present, the methods used to solve the optimal dispatching model of cascade reservoir groups are roughly divided into tw...

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Problems solved by technology

[0005] Aiming at the defects of the prior art, the object of the present invention is an adaptive improved particle swarm optimization algorithm cascade reservoir optimization dispatching method, aiming at solving the problem that the traditional particle swarm optimization algorithm is easy to fall into a local optimal solution when solving the cascade reservoir optimization dispatching model, so that The population loses its diversity, resulting in the problem of low power generation efficiency of cascade reservoirs

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