Open AccessRisk‐based many‐objective configuration of power system fault current limiters utilising NSGA‐III
Author(s) -
Guo Chao,
Ye Chengjin,
Ding Yi,
Lin Zhenzhi,
Wang Peng
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2020.0482
Subject(s) - transient (computer programming) , limiter , electric power system , fault (geology) , reliability engineering , fault current limiter , hazard , computer science , control theory (sociology) , range (aeronautics) , voltage , process (computing) , pareto principle , power (physics) , engineering , mathematical optimization , mathematics , electrical engineering , physics , telecommunications , chemistry , control (management) , organic chemistry , quantum mechanics , artificial intelligence , aerospace engineering , seismology , geology , operating system
The fault current limiter (FCL) has been envisaged as a feasible solution to defend against out‐of‐range short‐circuit currents (SCCs) in power systems. However, the existing studies mainly sited and sized FCLs under deterministic fault scenarios. Moreover, the influences of FCLs on power systems are complex including dynamic aspects, which makes it extremely difficult to configure FCLs optimally. This paper proposes a risk‐based many‐objective FCL configuration framework. Specifically, a data‐driven Proportional Hazard Model (PHM) is developed to evaluate the nodal long‐term short‐circuit probability considering equipment aging, weather statistics, and surrounding conditions. The risks in terms of out‐of‐range SCC, abnormal voltage sag, and transient instability are formulated as the objective functions of the FCL configuration model, as well as the overall FCL investment. The time‐domain dynamic response process of FCLs is considered in both the SCC limiting and the transient stability simulation process, mainly in the form of a time‐varying resistance. The state‐of‐the‐art NSGA‐III is deployed to search the Pareto‐optimal FCL configuration solutions of the established many‐objective FCL configuration problem. The numerical results verify that the risk‐based model configures FCLs more economically with a 7.5% decrease of average FCL investment compared with the deterministic model.