Genetic algorithm-based three-phase load imbalance adjustment method for power distribution area
A technology of unbalanced load and distribution station area, applied in the computer field, can solve the problems of poor similarity, frequent decoding of code randomness, poor adjustment effect, etc., achieve good adjustment effect and overcome the effect of code randomness
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2020-12-29
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Abstract
Description
technical field
[0001] The invention relates to the field of computer technology, in particular to a genetic algorithm-based three-phase load unbalance adjustment method in a distribution station area. Background technique
[0002] The three-phase unbalance problem, one of the important indicators of power quality, still restricts the safety, stability and economy of power grid operation. Especially in my country's low-voltage distribution network, the problem of three-phase imbalance has existed for a long time, and has become the most common and difficult problem at the end of my country's low-voltage distribution network. The three-phase imbalance in the distribution station area will increase the loss of distribution transformers and lines, reduce the power quality and distribution output, and in serious cases will endanger the safety of equipment, and have a serious impact on grid safety, economic operation and reliable power supply. Therefore, it is one of the main re...
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Embodiment Construction
[0020] The present invention will be specifically introduced below in conjunction with specific embodiments.
[0021] An embodiment of the present invention provides a genetic algorithm-based three-phase load unbalance adjustment method in a distribution station area, the method includes the following steps:
[0022] S101, using the improved quantum genetic algorithm to obtain the phase sequence scheme of the three-phase load in the distribution station area;
[0023] S102. According to the phase sequence scheme, adjust the three-phase load unbalance problem in the distribution station area.
[0024] Optionally, the improved quantum genetic algorithm includes the following steps:
[0025] (1) Create a population Q(t) and randomly generate multiple chromosomes;
[0026] (2) Perform a measurement on each chromosome in the population Q(t), and obtain the corresponding definite solution p(t);
[0027] (3) Evaluate the fitness of each determined solution p(t) respectively;
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