Implementation Of Particle Swarm Optimization To Optimize Parameters Of VSC- HVDC In The Aim Of Improving The Frequency Stability

The use of Renewable Energy Sources (RES) and High Voltage Direct Current (HVDC) technology is becoming increasingly common due to their advantages. However, RES have inherent characteristics such as low inertia and intermittency, which can negatively impact the stability of grids. In contrast, HVDC technology has been shown to improve grid stability. This paper demonstrates this improvement using simulation results from the 39-bus New England grid under different scenarios. Additionally, to enhance system reliability, the Particle Swarm Optimization (PSO) technique has been proven effective in determining parameters of the Voltage Source Converter (VSC) of an HVDC system. By comparing simulation results of the grid under various circumstances, the authors gained a comprehensive and accurate understanding of the system's operation. The PSO algorithm was implemented using Python and the DigSilent PowerFactory simulation software, making it easily applicable in practical settings.

I. Introduction

The issue of greenhouse gas emissions is a significant global concern, and renewable energy sources (RES) are viewed as one of the most effective solutions to address this problem. However, most wind turbines (WTs) and photovoltaic (PV) systems produce direct current (DC) that must be converted to alternating current (AC) through inverters, which removes the inertia of the energy source and reduces the stability of connected systems [1]. Additionally, the output power of WTs and PV systems is intermittent and reliant on various weather conditions, such as wind speed, temperature, and irradiance, among others. These two fundamental characteristics of RES are one of the primary causes of system instability, particularly with respect to frequency stability during system malfunctions [2] [3].