An OPF-based Control Framework for Hybrid AC-MTDC Power Systems under Uncertainty

TL;DR

This paper introduces an adaptive control framework for hybrid AC-HVDC systems that integrates wind power forecasts into an OPF-based control scheme, enhancing stability and robustness amid renewable energy uncertainties.

Contribution

It proposes a novel forecast-integrated, adaptive control framework combining OPF and droop control for hybrid AC-MTDC systems under renewable uncertainty.

Findings

Validated through hardware-in-the-loop simulations.

Demonstrated improved stability under high renewable penetration.

Effectively manages frequency and voltage deviations.

Abstract

The increasing integration of renewable energy, particularly offshore wind, introduces significant uncertainty into hybrid AC-HVDC systems due to forecast errors and power fluctuations. Conventional control strategies typically rely on fixed setpoints and neglect frequency deviations, which can compromise system stability under rapid renewable variations. To address this challenge, this paper presents a forecast-integrated, optimal power flow (OPF)-based adaptive control framework. Wind speed forecasts generated using a Random Forest model are incorporated into a time-coupled OPF to determine baseline converter setpoints in anticipation of wind fluctuations, which are further adjusted in real time based on actual operating conditions. An adaptive droop control scheme is developed that jointly considers DC voltage and AC frequency deviations. The effectiveness of the proposed control framework is validated through hardware-in-the-loop (HIL) simulations, demonstrating its capability to ensure stable and robust operation of hybrid AC-HVDC systems under high penetration of renewable energy.