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Operation optimization method of segmented integrated energy system based on multi-population genetic algorithm

A technology of integrated energy system and genetic algorithm, which is applied in the field of segmented integrated energy system operation optimization, can solve the problems of a large number of constraint conditions, and the model solution is easy to fall into local optimum, so as to improve the stability of convergence and good global optimization ability , the effect of great economic benefits

Active Publication Date: 2022-04-01
NARI TECH CO LTD
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Problems solved by technology

For the optimization of comprehensive energy operation, due to the need to consider multiple types of power sources, main grid interaction, energy storage and other factors at the same time, the direct use of global modeling requires a large number of constraints to be dealt with, and the model is prone to fall into local optimum when solving

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  • Operation optimization method of segmented integrated energy system based on multi-population genetic algorithm
  • Operation optimization method of segmented integrated energy system based on multi-population genetic algorithm
  • Operation optimization method of segmented integrated energy system based on multi-population genetic algorithm

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Embodiment Construction

[0098] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application will be described in detail below in conjunction with the accompanying drawings;

[0099] refer to figure 1 , a flow chart of the operation optimization method for the segmented integrated energy system, figure 2 , multi-population genetic algorithm flow chart:

[0100] Step 1: Divide 24 hours into five time periods according to the segmented electricity price of "trough-peak-flat period-peak-flat period", including: period one (from moment 1 to moment T 1 ), period two (from time (T 1 +1) to time T 2 ), period three (from time (T 2 +1) to time T 3 ), period four (from time (T 3 +1) to time T 4 ), period five (from moment (T 4 +1) to time 24);

[0101] Step 2: Construct a five-period running optimization objective function f 1 ,as follows:

[0102]

[0103] Amo...

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Abstract

The invention discloses a segmented comprehensive energy system operation optimization method based on multi-population genetic algorithm. First, divide 24 hours into five time periods according to the segmented electricity price of “low valley-peak-flat period-peak-flat period”, and calculate the optimal optimization variable matrix for five periods through multi-population genetic algorithm, and then construct each The objective function and constraint conditions of the time period, and finally, the optimization results of each time period are refined and calculated sequentially through the multi-population genetic algorithm. This method can reduce the number of model constraints as much as possible, realize the optimal allocation of multiple energy sources in the integrated energy system, and achieve the greatest economic benefits.

Description

technical field [0001] The invention relates to a segmented comprehensive energy system operation optimization method based on multi-population genetic algorithm. Background technique [0002] In order to better cope with a series of challenges such as the gradual depletion of fossil energy and the increasingly prominent environmental pollution problems, it is necessary to integrate multiple energy resources to achieve optimal operation among multiple energy sources, thereby improving energy utilization efficiency. However, compared with the power system, the integrated energy system has the characteristics of high system coupling and rich energy supply methods, which makes it face greater technical challenges in terms of operation optimization. [0003] At present, although there are many related studies on system operation optimization theory, the research on the construction of comprehensive energy operation optimization solution model is still in the exploratory stage. U...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/12
CPCG06Q10/04G06Q50/06G06N3/126
Inventor 张筱辰朱金大杨冬梅陈永华杜炜刘刚傅金洲何国鑫陈卉
Owner NARI TECH CO LTD
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