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Multi-region environmental economic load dispatch optimization method and device

An optimization method and multi-regional technology, applied in the field of smart grid, can solve problems such as uneven distribution, inability for decision-makers to make more reasonable decision-making judgments, and lack of diversity in solutions

Inactive Publication Date: 2016-12-21
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0005] In view of this, the present invention provides a multi-regional economic environment scheduling optimization method and device to overcome the shortcomings of the quantum particle swarm algorithm in the prior art that it is easy to fall into a local optimum in the optimization process. The quantum particle swarm algorithm finds out The distribution of the Pareto frontier is narrow and uneven, and the solutions obtained lack diversity, which cannot allow decision makers to make more reasonable decision-making judgments

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  • Multi-region environmental economic load dispatch optimization method and device
  • Multi-region environmental economic load dispatch optimization method and device
  • Multi-region environmental economic load dispatch optimization method and device

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Embodiment Construction

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0050] see figure 1 , is a schematic flowchart of a multi-regional economic environment scheduling optimization method based on a fast non-inferior solution sorting multi-objective variation quantum particle swarm algorithm provided by the embodiment of the present application. The method includes:

[0051] Step S1: Establish a multi-regional economic environment scheduling optimization model, the multi-regional economic environment scheduling optimization mod...

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Abstract

The embodiment of the present invention discloses a multi-regional economic environment scheduling optimization method and device based on a fast non-inferior solution sorting multi-objective variation quantum particle swarm algorithm. The method uses the first operation operator, the second operation operator and the third operation operator The children continue to iterate the first parent population, the second parent population and the third parent population, so that the population with many different types of particles, that is, the solution, can be obtained, thereby improving the quantum particle swarm in the prior art The disadvantage of the algorithm is easy to fall into local optimum, which improves the effect of multi-regional economic environment scheduling.

Description

technical field [0001] The embodiment of the present application relates to the technical field of smart grid, and more specifically relates to a multi-regional economic environment scheduling optimization method and device. Background technique [0002] Power system economic environment scheduling is the main content of energy management system. In some specific environments, power system economic environment scheduling is conceptually equivalent to power generation plan. Power generation plan includes generator combination, water and thermal power plan, exchange plan, maintenance plan and fuel Plans, etc.; according to the cycle, there are: ultra-short-term plans, that is, automatic power generation control, short-term power generation plans, that is, daily or weekly plans; medium-term power generation plans, that is, monthly to annual plans and corrections; long-term plans, that is, several years to decades plans, including power development planning and network developme...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06N3/00
CPCG06Q10/0631G06N3/006G06Q50/06
Inventor 孟安波林艺城殷豪李锦焙
Owner GUANGDONG UNIV OF TECH
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