Open AccessMulti‐objective programming optimization algorithm for large‐scale grid connection of new energy considering frequency stability
Author(s) -
Jin Panlong,
Gong Jianfeng,
Ge Pengjiang,
Guo Ning,
Qu Gaoqiang
Publication year - 2023
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/tje2.12210
Subject(s) - grid connection , limit (mathematics) , grid , computer science , electric power system , stability (learning theory) , frequency grid , energy (signal processing) , power (physics) , mathematical optimization , frequency deviation , scale (ratio) , automatic frequency control , mathematics , telecommunications , statistics , physics , geometry , quantum mechanics , machine learning , mathematical analysis
ABSTRACT In order to solve the problem of power supply frequency instability after large‐scale grid connection of new energy, a multi‐objective programming optimization algorithm for large‐scale grid connection of new energy considering frequency stability is proposed. Before planning, the limit evaluation method for grid connection of new energy considering the frequency stability of the power system is used to judge the frequency change limit of the power system to be connected to the grid. Through the real‐time measurement method of power system frequency under the large‐scale grid connection of new energy, the real‐time change value of power system frequency under the large‐scale grid connection of new energy is calculated. Combined with the mastered frequency change limit and real‐time frequency change value of power system, an optimization decision‐making model for multi‐objective planning of large‐scale grid connection of new energy is constructed, and the improved genetic algorithm is used to solve the grid connection strategy that the frequency control quantity does not exceed the limit and the auxiliary cost of multi‐objective planning for grid connection is the minimum. It is verified that the frequency of IEEE‐30 standard node system is stable and within the limit after the algorithm is used, and the auxiliary cost of multi‐objective planning for grid connection is significantly reduced.