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Source-load-storage scheduling method based on improved multi-objective particle swarm optimization algorithm

A multi-objective particle swarm and scheduling method technology, which is applied in the field of source-load-storage scheduling based on the improved multi-objective particle swarm algorithm, can solve the problem of slow convergence speed, easy to fall into local optimum, and solution efficiency and solution accuracy that cannot meet the scheduling requirements. To achieve the effect of increasing consumption, improving energy utilization efficiency, and increasing calculation speed

Pending Publication Date: 2019-08-23
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0004] In order to obtain the best dispatching scheme, in recent years, the multi-objective particle swarm optimization algorithm has been widely used in the research of multi-objective optimization problems in power systems due to its high solution efficiency. Trapped in a local optimal problem, its solution efficiency and solution accuracy can no longer meet the needs of modern power system dispatching

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  • Source-load-storage scheduling method based on improved multi-objective particle swarm optimization algorithm
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  • Source-load-storage scheduling method based on improved multi-objective particle swarm optimization algorithm

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[0046] The present invention will be further described below in conjunction with the accompanying drawings and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.

[0047] Such as figure 1 As shown, the embodiment of the present invention is based on the source-load-storage scheduling method based on the improved multi-objective particle swarm optimization algorithm, and the steps include:

[0048] S1. Aggregate thermal power plants and clean energy power plants, user loads, and energy storage equipment into a source-load-storage scheduling system, and determine the scheduling of the source-load-storage scheduling system with the minimum system operating cost and the largest amount of clean energy consumption Optimizing objective functions and constraints;

[0049] S2. Using the scheduling optimization objective function as the fitness function of the improved multi-objective particle swarm optimization algorithm, and usin...

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Abstract

The invention discloses a source-load-storage scheduling method based on an improved multi-objective particle swarm optimization algorithm. The method comprises the steps of: S1, integrating a thermalpower plant, a clean energy power plant, a user load and an energy storage device into a source-load-storage scheduling system, and determining the scheduling optimization objective function and theconstraint condition of the source-load-storage scheduling system to achieve the minimum system operating cost and the highest clean energy consumption; S2, using the scheduling optimization objectivefunction as the fitness function of the improved multi-objective particle swarm optimization algorithm, and using the constraint condition as a particle variable constraint section of the algorithm;and S3, by using the improved multi-objective particle swarm optimization algorithm, obtaining a minimum value of the fitness function and a particle variable that takes the minimum value of the fitness function according to the fitness function and the particle variable constraint section. The method is easy to implement and flexible to use, can improve the solution efficiency of a power scheduling scheme, and can obtain a reasonable power scheduling scheme with good economic benefit.

Description

technical field [0001] The invention relates to the technical field of power system control, in particular to a source-load-storage scheduling method based on an improved multi-objective particle swarm algorithm. Background technique [0002] In recent years, photovoltaic power generation and wind power generation in northern my country have developed rapidly, and the grid connection of a large amount of clean energy has alleviated the energy crisis to a certain extent. However, in the winter heating period, in order to meet the heat load demand, a large number of thermal power units work in the mode of "heating fixed power". Very restrictive. This thermoelectric coupling relationship makes the power system's peak-shaving capability insufficient, and the system usually needs to discard part of clean energy or cut off part of the load to ensure stable operation, resulting in a large amount of energy waste and reduced power supply reliability. [0003] The schedulable resour...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00H02J3/46G06Q10/06G06Q50/06
CPCH02J3/008H02J3/46G06Q10/06312G06Q50/06H02J2203/20Y04S10/50
Inventor 周任军彭院院许燕燕徐健张志遥殷旭锋
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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