Coordinated Supervisory Control of Multi-Terminal HVDC Grids: A Model Predictive Control Approach

Abstract

A coordinated supervisory control scheme for future multi-terminal High-Voltage Direct-Current (HVDC) grids is proposed. The purpose is to supervise the grid and take appropriate actions to ensure power balance and prevent or remove voltage or current limit violations. First, using DC current and voltage measurements, the power references of the various Voltage Sources Converters (VSC) are updated according to participation factors. Next, the setpoints of the converters are smoothly adjusted to track those power references, while avoiding or correcting limit violations. The latter function resorts to Model Predictive Control and a sensitivity model of the system.

Existing System

Monte-Carlo simulation.

Proposed System

This paper proposes a scheme for MTDC grid supervisory control. It is coordinated, i.e. it receives measurements from the MTDC system and sends back setpoints to the AC/DC converters. Furthermore, it satisfies the following requirements: accommodate the varying power injections by renewable sources; be robust with respect to model inaccuracies as well as disturbances, such as outages of AC/DC converters or DC cables/lines; prevent or correct DC voltage and current violations; smoothly drive the system from the current to a desired operating point; avoid excessive impact on the adjacent AC systems and provide additional services (such as frequency support). Avoid extensive communication between controllers. Optimization-based approaches are the most appealing owing to their ability to handle constraints. However, most optimization methods proposed in the literature have been devised to operate in open loop. Hence, they cannot account for model inaccuracies, component failures, etc. The controller relies on the MPC concept and involves solving a constrained optimization problem at each discrete time. The MPC formulation was chosen for its ability to accommodate model simplifications and uncertainties while incorporating constraints. This allows predicting the system evolution with a static, sensitivity-based model.

Architecture

Overall Control Structure