Open AccessReactive power optimization of AC and DC system based on improved genetic algorithm
Author(s) -
Lingyun Ren,
Jian Zhang
Publication year - 2020
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 - 10.1088/1742-6596/1549/5/052028
Subject(s) - ac power , computer science , genetic algorithm , electric power system , node (physics) , voltage , power (physics) , electronic engineering , algorithm , engineering , electrical engineering , physics , structural engineering , quantum mechanics , machine learning
In the context of the rapid development of DC transmission, this paper studies the multi-objective reactive power optimization of AC and DC transmission systems. By studying the relevant basic knowledge, it provides a theoretical basis for studying reactive power optimization of AC-DC distribution networks. This paper provides an improved genetic algorithm that uses node voltage offset and total active network loss as two objective functions. A fast non-dominated sequencing genetic algorithm with elite strategy NSGAII is applied to the multi-target reactive power of AC and DC systems. During the optimization, a corresponding reactive power optimization program was written, and the feasibility of the proposed method was verified by an example of the IEEE 9-node system.