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Set combination optimization method based on BPSO and Lagrange multiplier algorithm

A discrete particle swarm and unit combination technology, applied in computing, data processing applications, instruments, etc., can solve the problems of dynamic programming method, such as large amount of calculation, difficult to deal with large-scale systems, and affecting algorithm convergence.

Active Publication Date: 2014-11-26
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The priority order method is simple and fast, but it is not easy to obtain the optimal solution; the dynamic programming method is difficult to deal with large-scale systems due to the large amount of calculation; the operator selection of the Lagrangian relaxation method will affect the convergence of the algorithm

Method used

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  • Set combination optimization method based on BPSO and Lagrange multiplier algorithm
  • Set combination optimization method based on BPSO and Lagrange multiplier algorithm
  • Set combination optimization method based on BPSO and Lagrange multiplier algorithm

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Embodiment Construction

[0043] The following is an application case of the present invention, which is used to optimize the unit combination of 10 units and 24 hours. This calculation example is widely used in the verification of unit combination to compare the advantages and disadvantages of different algorithms.

[0044] The parameters of the 10 units are shown in Table 1, and the estimated 24-hour power load is shown in Table 2, and the spinning reserve is required to be at least 5% of the power load. At any time, the total output power of the unit must be equal to the electrical load, and the sum of the maximum power of the starting unit is not less than the sum of the electrical load and the spinning reserve.

[0045] Table 1

[0046]

[0047] Table 2

[0048] time

[0049] This method comprises the following steps:

[0050] (1) Initialize parameters to determine the cycle of unit combination optimization, the number of units, the power load (predicted value) of each time ...

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Abstract

The invention, which belongs to the power system scheduling automation technology field, aims at providing a set combination optimization method based on a BPSO and a Lagrange multiplier algorithm. An operation cost of a generator set is used as an optimized object and the BPSO and the Lagrange multiplier algorithm are combined. And the method comprises the following steps that: initial starting up and stopping matrixes are generated randomly; a matrix that does not satisfy a minimum starting up and stopping constraint condition is transformed; with regard to a starting up and stopping matrix that can satisfy a power constraint condition, the Lagrange multiplier algorithm is used to solve a power distribution scheme; a matrix adaptive value is calculated; an individual optimal value and a global optimal value are updated; a particle speed and a matrix element are updated; and an optimal power distribution matrix and an adaptive value are output after the iteration number is reached. According to the method provided in the invention, resource configuration capability of a power system can be effectively improved and set operation costs are reduced.

Description

technical field [0001] The invention belongs to the technical field of power system scheduling automation, and in particular relates to a unit combination optimization method based on discrete particle swarm and Lagrangian multiplier algorithm. Background technique [0002] With the increasing scale of the power system and the improvement of social awareness of "energy saving and emission reduction", the requirements for rational allocation of power grid resources and ensuring the economic operation of the power system are getting higher and higher. Unit combination optimization is to determine the units participating in the operation and the active power output of each unit during the operation period in a dispatch cycle (generally 24 hours) under the condition of satisfying the system load, spinning reserve requirements and technical conditions of unit operation. The total operating cost of the system is minimized. [0003] At present, the optimization methods to solve th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q50/06
Inventor 金磊杨欢赵荣祥
Owner ZHEJIANG UNIV