Enhanced Control Strategy of Multi-terminal HVDC System to Facilitate Renewable Integration

Abstract

Integration of Renewable Power Sources or renewables in electric power systems is of paramount importance to reduce carbon emissions and ensure a sustainable future for mankind. Being highly variable and intermittent, these inverter-interfaced energy sources degrade power system inertia and create supply-demand balance problems. Multi-terminal HVDC transmission offers solution to this predicament owing to highly controllable voltage-source converter (VSC) stations. Droop control is commonly employed to enable autonomous controllability in reaction to frequency variations beyond a minimum threshold and DC voltage deviations. Adaptively adjusting the droop gains enables the controller to adapt its response to ever-changing grid and VSC conditions. Frequency support and DC voltage regulation are primary objectives in any hybrid AC/DC system like an MTDC transmission system. Satisfaction of these objectives requires conflicting power changes at VSC stations. The goal of an effective adaptive droop control strategy is to reach a compromise between these objectives given the grid conditions. Existing droop schemes accomplish this goal but vary the droop gains in a linear fashion given the operating conditions of a highly non-linear power system. These techniques are also vulnerable to system parameter variations and need special consideration, in an already complicated mathematical modeling process, to introduce robustness to parameter variations. Fuzzy decision systems offer an ideal solution as they do not require mathematical modeling in controller design while also introducing robustness to parameter variations via proper tuning of their membership functions and their soft decision boundaries. The aim of the research works presented in this dissertation is to employ fuzzy decision systems for robust control of VSC stations in MTDC transmission system. The proposed solutions do not require complex mathematical models, are robust to system parameter variations, rely on local measurements, and are able to consider multiple control inputs when selecting droop gains for active power control of VSC stations. The fuzzy inference systems designed for droop gain selection in the active power controller of VSC station demonstrate enhanced frequency support, DC voltage regulation, and adequate power sharing among VSC stations of an MTDC transmission system compared to the existing state-of-the-art techniques. This proves the ability of such inference systems to reach an effective compromise between conflicting control objectives based on local conditions at VSC stations.

Date of Award	2025
Original language	American English
Supervisor	Mohamed El Moursi (Supervisor)