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An intelligent microgrid optimal scheduling method for improving a particle swarm algorithm

A technology for improving particle swarm and optimizing scheduling, applied in computing, computing models, data processing applications, etc., to reduce operating costs and maximize economic benefits

Active Publication Date: 2019-05-03
XIAMEN GREAT POWER GEO INFORMATION TECH
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AI Technical Summary

Problems solved by technology

[0003] In the past, the research on microgrid operation mainly focused on the microgrid system composed of wind, solar and other power generation units, without considering the impact of electric vehicles. With the large-scale use of electric vehicles, the irregular use behavior of users leads to the optimization of microgrids. Scheduling has undergone great changes. Therefore, in view of the uncertainty of renewable energy in the current micro-grid, providing a micro-grid optimal scheduling method for safe and economical operation of the micro-grid has become an urgent problem to be solved in the application and development of the micro-grid. important question

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  • An intelligent microgrid optimal scheduling method for improving a particle swarm algorithm
  • An intelligent microgrid optimal scheduling method for improving a particle swarm algorithm
  • An intelligent microgrid optimal scheduling method for improving a particle swarm algorithm

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Embodiment Construction

[0018] The present invention will be further described below in conjunction with accompanying drawing.

[0019] Such as figure 1 and figure 2 Shown, the inventive method has is:

[0020] Step 1: Set the basic parameters of the annealing mutation algorithm, including the population size N, the maximum number of iterations it, and the initial value C of the two learning factors 1s 、C 2s and the termination value C 1e 、C 2e , the initial value ω of the inertia weight s and the termination value ω e , the mutation probability P m Wait.

[0021] Step 2: Initialize the individuals in the population according to the upper and lower limits of the output of each distributed power source in the microgrid.

[0022] Step 3: Calculate the fitness value of each particle according to the established microgrid operation objective function, and record the individual optimal and global optimal values.

[0023] Step 3: Introduce the simulated annealing algorithm. In each iteration, a ...

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Abstract

The invention relates to an intelligent micro-grid optimization scheduling method of an improved particle swarm optimization algorithm. The problem of system energy uncertainty caused by renewable energy in a microgrid is solved. According to the method, annealing and variation ideas are introduced into the PSO algorithm, the global search capability of the particle swarm algorithm is improved byutilizing the probability kick characteristic of the simulated annealing algorithm, and meanwhile, the fine search capability of the particle swarm algorithm is improved by utilizing the characteristic of carrying out key search on a local area near an individual area by utilizing the Gaussian variation algorithm. According to the invention, economical efficiency and reliability of microgrid operation can be effectively improved.

Description

technical field [0001] The invention belongs to the field of optimal scheduling of micro-grids, and relates to an optimal scheduling method of intelligent micro-grids with an improved particle swarm algorithm. Background technique [0002] With the improvement of social environmental awareness and energy security awareness, people gradually realize the inherent shortcomings of traditional power grids. The smart microgrid technology provides a new solution for countries to build green, safe and sustainable power supply systems. Since the microgrid contains uncontrollable renewable energy, the energy in the microgrid system has serious uncertainty. Therefore, it is critical to carry out research on the optimal scheduling of the smart microgrid system to promote the application and development of smart microgrid projects. supporting role. [0003] In the past, the research on microgrid operation mainly focused on the microgrid system composed of wind, solar and other power ge...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/00
Inventor 葛泉波宁士远姜淏予
Owner XIAMEN GREAT POWER GEO INFORMATION TECH
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