Sampled-data control under time-varying delays: a robust approach for high-renewable smart grids

TL;DR

This paper introduces a robust control method for smart grids with renewable energy that adapts to communication issues like delays and packet loss.

Contribution

A novel adaptive sampled-data control framework that links communication quality to real-time control adjustments with stability guarantees.

Findings

The adaptive controller reduces settling time by up to 33% under communication impairments.

It also decreases overshoot by 52% and control-related energy cost by 40% compared to traditional methods.

Operational reliability is maintained even with 10% packet loss and high jitter.

Abstract

The increasing reliance on inverter-based renewable energy sources in smart grids makes closed-loop stability highly sensitive to communication-induced uncertainties, including time-varying delays, sampling jitter, and packet loss. Conventional sampled-data and delay-dependent controllers typically address these impairments in isolation or rely on conservative worst-case designs, limiting their effectiveness under dynamically changing communication quality. This paper proposes a robust adaptive sampled-data control framework that explicitly links communication degradation to control-layer adaptation while preserving tractable stability guarantees. A bounded delay–jitter intensity index, \documentclass[12pt]{minimal}
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\begin{document}$$\theta _k \in [0,1]$$\end{document}, is introduced as an online-measurable proxy for communication quality and is used to schedule the feedback gain in real time. Stability is rigorously certified using a delay-weighted Lyapunov–Krasovskii functional and affine Linear Matrix Inequality (LMI) conditions verified at the admissible uncertainty endpoints, ensuring exponential stability under the combined effects of delay, jitter, and packet loss. The proposed approach is validated on a hybrid renewable microgrid with inverter-based distributed energy resources under stochastic communication impairments. Across multiple scenarios—including bounded delay, high jitter, and 10% packet loss–the adaptive controller reduces settling time by up to 33%, overshoot by 52%, and control-related energy cost by 40% compared to fixed-gain and worst-case robust baselines. In addition, cyber-aware operational reliability metrics confirm consistent preservation of admissible operating margins under degraded communication conditions. These results position the proposed method as a stability-certified control-layer complement to cyber-resilient and data-driven smart grid architectures, enabling reliable operation of high-renewable grids under realistic communication constraints.

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