Power Transfer Capability Improvement to HVDC Transmission System using Artificial Neural Network and Inference System (ANFIS) Controller
نویسندگان
چکیده
High Voltage Direct Current (HVDC) Transmission systems traditionally employ PI controllers with fixed proportional (P) and integral (I) gains Kp and Ki respectively. Although such controllers are robust and simple, they are not easily optimized to obtain the best performance under all conditions. In the field of intelligent control systems, fuzzy logic control and artificial neural network based control are the two most popular control methodologies being used. Neuro-fuzzy systems, as the name suggests combine ANNs and fuzzy logic into one system. The aim of such a combination is to inherit advantages of both the intelligent control techniques and shunt out their individual disadvantages. The CIGRÉ model as one of the conventional methods has been studied and new complementary characteristics have been added to improve its stability and damping rate of voltage and current oscillations during the disturbance in the AC Systems and to increase the efficiency of the proposed model. Keywords–HVDC transmission, CIGRÉ Benchmark model, faults in HVDC system, proportional integral (PI) Controller,
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