Cascade reservoir optimal operation method based on adaptive particle swarm optimization algorithm

A particle swarm optimization, cascade reservoir technology, applied in the direction of calculation, calculation model, data processing application, etc., can solve the problem of loss of population diversity, affecting the stability of the algorithm, affecting the speed and efficiency of convergence, etc.

Inactive Publication Date: 2014-07-23
HOHAI UNIV
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Problems solved by technology

However, there are still some shortcomings in the PSO algorithm: random initialization affects the stability of the algorithm and the speed a...

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  • Cascade reservoir optimal operation method based on adaptive particle swarm optimization algorithm
  • Cascade reservoir optimal operation method based on adaptive particle swarm optimization algorithm
  • Cascade reservoir optimal operation method based on adaptive particle swarm optimization algorithm

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Embodiment Construction

[0042] Such as figure 1 As shown, the specific steps of the application of dynamic grouping adaptive particle swarm optimization algorithm in cascade reservoir optimization scheduling are as follows:

[0043] (1) Fixed initialization of particles in the search area

[0044] Specify the size of the population, set the upper and lower limits of position and speed, and set the learning factor c 1 、c 2 、c 3 、c 4 , the maximum number of iterations and convergence accuracy of the algorithm.

[0045] (2) Evaluate the initialized particles

[0046] Calculate the fitness value of the particle according to the fitness function (set according to the specific situation), and then arrange the calculated fitness value in ascending order. The fitness value of is denoted as f min , and the largest one is denoted as f max , while calculating f avg , f' avg and f″ avg , divide the entire population into dynamic subgroups, greater than f min less than f" avg is inferior group, great...

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Abstract

The invention discloses a cascade reservoir optimal operation method based on the adaptive particle swarm optimization algorithm. According to the method, aiming at the defect of the particle swarm method in cascade reservoir optimal operation, fixed initialization improvement is conducted firstly on particle random initialization to enable the algorithm to have the possibility of approaching the optimal value at the beginning, large-scale dead zones do not exist, convergence speed is increased, and the stability of the algorithm is improved; then according to the group cooperation idea and the cluster ecological niche idea, an initialized group is dynamically divided into three subgroups, optimization and parameter selection are conducted on each subgroup in an adaptive mode according to the difference of particles, and in this way, the particle diversity is improved, the information exchange model is changed, and local optimum of the algorithm is avoided. According to the improved algorithm, the function problems of nonlinearity and multiple local minima can be well solved, and an effective and feasible solution is provided for cascade reservoir optimal operation.

Description

technical field [0001] The invention relates to a cascade reservoir optimization scheduling method based on an adaptive particle swarm optimization algorithm. Under the condition of a known cascade reservoir model, solving the model provides a new way to solve this problem. Background technique [0002] Reservoir scheduling is based on the primary and secondary of the water conservancy and hydropower tasks undertaken by the reservoir and the prescribed operating principles, relying on the storage capacity of the reservoir, through various buildings and equipment of the water conservancy hub, in accordance with the design requirements, in ensuring the safety of the dam and downstream flood control Under the premise of safety, it is a reservoir operation control technology that regulates the process of entering the reservoir to realize more power generation and improve comprehensive utilization efficiency. [0003] Reservoir scheduling is generally divided into two categories:...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/00
Inventor 高红民徐立中李臣明吴学文马贞立王逢州
Owner HOHAI UNIV
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