Fast frequency response with heterogeneous communication delay management under the SCION Internet architecture

TL;DR

This paper introduces a real-time reserve dispatch framework leveraging the SCION Internet architecture's low-latency paths to optimize frequency response services from distributed energy resources and controllable loads, addressing latency issues in traditional systems.

Contribution

It develops a cyber-physical co-optimization model and a heuristic algorithm for efficient, latency-aware frequency response reserve allocation using the SCION architecture.

Findings

The proposed algorithm approximates optimal reserve allocation.

SCION-based communication reduces latency for frequency response.

Numerical results show improved efficiency and near-optimal performance.

Abstract

System operators can increasingly exploit distributed energy resources (DERs) and controllable loads (CLs) to provide frequency response services. In conventional practice, communication between the system operator and flexible devices relies on the Border Gateway Protocol (BGP)-based Internet. However, existing BGP-based architectures face challenges in providing latency-guaranteed control, while direct private and proprietary communication networks lead to additional deployment and maintenance costs. In contrast, the SCION-based Internet architecture supports latency-minimum path selection, which makes it suitable for latency-sensitive frequency contingency services such as fast frequency response (FFR). Hence, this paper proposes a real-time reserve dispatch framework to optimally select a portfolio of flexible devices to deliver FFR services using the SCION-based Internet. First, an analytical expression of the system frequency dynamics with respect to heterogeneous communication latencies is derived. Next, a cyber-physical co-optimization model is formulated to jointly schedule communication paths and physical flexibility resources for real-time FFR provision. To improve the computation efficiency, we propose a heuristic FFR allocation algorithm to approximate the optimal response portfolio, integrating contributions from both DERs and CLs. Numerical case studies demonstrate the benefits of the proposed algorithm and its capability to approximate the optimality of the reserves allocation while significantly reducing the computation time.