Complementarity-constrained predictive control for efficient gas-balanced hybrid power systems

TL;DR

This paper introduces two novel predictive control methods that incorporate complementarity constraints to efficiently manage gas turbines in hybrid power systems with renewable energy and storage.

Contribution

It presents new approaches for handling semi-continuous operating regions of gas turbines in predictive control, improving efficiency over traditional continuous formulations.

Findings

Proposed methods outperform baseline controllers in fuel efficiency.

Complementarity constraints effectively model semi-continuous turbine operation.

Case study demonstrates improved system performance with the new approaches.

Abstract

Controlling gas turbines (GTs) efficiently is vital as GTs are used to balance power in onshore/offshore hybrid power systems with variable renewable energy and energy storage. However, predictive control of GTs is non-trivial when formulated as a dynamic optimisation problem due to the semi-continuous operating regions of GTs, which must be included to ensure complete combustion and high fuel efficiency. This paper studies two approaches for handling the semi-continuous operating regions of GTs in hybrid power systems through predictive control, dynamic optimisation, and complementarity constraints. The proposed solutions are qualitatively investigated and compared with baseline controllers in a case study involving GTs, offshore wind, and batteries. While one of the baseline controllers considers fuel efficiency, it employs a continuous formulation, which results in lower efficiency than the two proposed approaches as it does not account for the semi-continuous operating regions of each GT.