Open AccessRegression‐based control of thyristor‐controlled series compensators for optimal usage of transmission capacity
Author(s) -
Yang Rui,
HugGlanzmann Gabriela
Publication year - 2014
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.2013.0080
Subject(s) - thyristor , transmission (telecommunications) , computer science , control theory (sociology) , electric power system , key (lock) , transmission system , voltage , engineering , control engineering , power (physics) , control (management) , telecommunications , physics , computer security , quantum mechanics , artificial intelligence , electrical engineering
Flexible AC transmission system devices provide the opportunity to improve the usage of the current transmission facilities by controlling network flows and nodal voltages. The optimal steady‐state settings of these devices can be determined using optimal power flow calculations. However, this requires knowledge of the system parameters, generation settings and loads. A two‐stage regression‐based control scheme is proposed to determine the optimal settings of thyristor‐controlled series compensators (TCSCs) with the objective to optimally utilise the current transmission system in the presence of renewable energy resources. A regression function describing the relationship between a set of key measurements and the optimal device settings is determined in the offline simulation. This function is then used to calculate the optimal device settings by only receiving the information from a limited number of key measurements without solving the OPF problem in the online operation. Studies are carried out with TCSCs in three‐test systems, the IEEE 14‐bus system, a 28‐bus system and the IEEE 118‐bus system. The simulation results with one, two and four TCSCs are presented, illustrating the performance of the proposed regression‐based control scheme.