TLBO Algorithm for Multi-Level Inverter-Based Multi-Terminal HVDC System in Grid-Tied Photovoltaic Power Plant

Abstract

The main objective of this paper is to overcome the problems with conventionally tuned proportional-plus-integral (PI) controller by using TLBO-PI technique, which enhances the dynamic performance. The significant problem is that it is not able to provide optimal parameters, which is overcome by new teaching-learning-based optimization (TLBO) algorithm. This research work develops a new TLBO for multi-level inverter (MLI)-based multi-terminal HVDC (MLI-MT-HVDC) in grid-tied photovoltaic power plants (GTPVPPs). In this, 7-level inverter is replaced by a conventional 3-level, due to its advantage of less number of switching components, less dc source requirement, low total harmonic distortion (THD) and due to main effective reason of application in HVDC transmission. Here two terminals with individual grid integration are interconnected to a common terminal of solar distributed generation (DG). Among those terminals with grid integration, one is faulty and other is healthy terminal, in which the healthy terminal is not affected due to the fault on a faulty terminal. A teacher and students in a class are employed in step-by-step manner to generate an optimal result. The test system is also controlled with a fuzzy logic controller (FLC), adaptive neuro-fuzzy inference system (ANFIS), but due to its simple structure and its application in industries, a PI controller with new optimization method is implemented. Additionally, it is clear that TLBO-PI can reduce the THD to the level as per IEEE 519-2014 standards, improve fault-ride-through (FRT) capability and enhance the dynamic performance better during abnormalities and dynamic load.