Open AccessResearch on Site Selection Method of Battery Energy Storage System Based on Critical CutSet Identification
Author(s) -
Zeng Jing,
Peiqiang Li,
Z. Zhang,
Xinke 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 - 10.1088/1742-6596/2087/1/012012
Subject(s) - identification (biology) , battery (electricity) , computer science , set (abstract data type) , reliability engineering , electric power system , transient (computer programming) , energy storage , selection (genetic algorithm) , domain (mathematical analysis) , energy (signal processing) , power grid , power (physics) , stability (learning theory) , grid , engineering , artificial intelligence , mathematics , machine learning , mathematical analysis , statistics , physics , botany , geometry , quantum mechanics , biology , programming language , operating system
Under different operating conditions, the influence of energy storage battery on the power grid is different, and the location and capacity determination methods are also different. Therefore, how to scientifically and reasonably select the location is of great significance. This paper proposes a candidate set identification method for the most vulnerable branch and critical cut set of power system transient stability based on branch potential energy, and uses the improved comprehensive index to identify the critical cut set. This method does not need to wait for the end of time domain simulation to determine the most vulnerable lines and critical cut sets, thus providing the basis for the location of battery energy storage system (BESS). Through the power system comprehensive analysis program (PSASP) simulation, the accuracy of theoretical analysis and engineering practicability are verified.