Open AccessResearch on the Application of Artificial Intelligence Technology in Power System Intelligent Dispatching Automation
Author(s) -
Hongying Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2083/4/042047
Subject(s) - particle swarm optimization , ac power , scada , computer science , automation , crossover , voltage , grid , electric power system , power (physics) , control engineering , engineering , control theory (sociology) , real time computing , control (management) , algorithm , electrical engineering , artificial intelligence , mechanical engineering , physics , geometry , mathematics , quantum mechanics
From the perspective of meeting the power quality requirements of users, the article analyses the characteristics of traditional voltage and reactive power control mode and the regional power grid reactive voltage optimization centralized closed-loop control mode (AVC system) based on the dispatch automation system (SCADA/EMS) from the perspective of technical management. Combining the reactive power/voltage real-time optimization control model, a real-time optimization control method of the regional power grid based on the improved differential evolution algorithm is proposed. The particle swarm algorithm is combined with the characteristics of reactive power/voltage control to improve the initial particle quality, reduce the optimization space, and introduce a crossover operator to improve the calculation speed and efficiency of the algorithm. Taking an actual regional power grid as an example, the simulation calculation of reactive power/voltage real-time optimization is carried out. The results show that the proposed algorithm and control strategy are feasible and effective.