Open AccessOperation and control of HVDC stations using continuous mixed p ‐norm‐based adaptive fuzzy technique
Author(s) -
Muyeen S.M.,
Hasanien Hany M.
Publication year - 2017
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.2016.1690
Subject(s) - control theory (sociology) , high voltage direct current , fuzzy logic , transmission system , electric power system , computer science , fuzzy control system , controller (irrigation) , grid , voltage source , offshore wind power , voltage , control engineering , engineering , transmission (telecommunications) , power (physics) , wind power , direct current , mathematics , control (management) , electrical engineering , telecommunications , agronomy , physics , geometry , quantum mechanics , artificial intelligence , biology
The power system is purely non‐linear and there exist a lot of uncertainties in generation, transmission, and distribution sectors. This study focuses on the operation and control of a voltage source converter (VSC)‐based high voltage direct current (HVDC) transmission system, which can cope up with system non‐linearity and parameter uncertainties. The HVDC system connects an offshore wind farm to the onshore power grid. A new adaptive fuzzy logic controller is proposed for both onshore and offshore HVDC stations to control the real and reactive power flow in normal and undertrain parameter conditions. The adaptive technique is based on the continuous mixed p‐norm algorithm, which updates the fuzzy inference system automatically at a high convergence speed. The performance of the proposed adaptive controller is tested under different parameter uncertainties and the results are compared with Taguchi optimisation‐based proportional‐integral controllers.