An Interactive Multi-Dimensional Flexibility Scheduling in Low-carbon Low-inertia Power Systems

TL;DR

This paper evaluates the robustness, dependability, and resilience of low-inertia power systems with high renewable energy integration using case studies, simulations, and optimization to highlight the importance of a comprehensive multi-dimensional assessment.

Contribution

It introduces a combined analysis framework for assessing reliability, robustness, and resilience in low-inertia power systems, using innovative visualization and case studies.

Findings

Reliability, robustness, and resilience metrics vary significantly across scenarios.

The combined analysis provides a comprehensive view of system vulnerabilities.

Simulation results emphasize the need for integrated assessment approaches.

Abstract

Today, electrical energy plays a significant and conspicuous role in contemporary economies; as a result, governments should place a high priority on maintaining the supply of electrical energy. In order to assess various topologies and enhance the security of power systems, it may be useful to evaluate robustness, dependability, and resilience all at once. This is particularly true when there is a significant amount of renewable energy present. The R3 concept, which consists of these three interrelated characteristics, describes the likelihood that a power system would fail, the potential severity of the repercussions, and the speed at which the system will recover from a failure. This paper uses eight case studies created from the IEEE 24-bus RTS and thoroughly assesses the properties of reliability, robustness, and resilience to highlight the significance of the issue. The sequential Monte Carlo method is used to evaluate reliability, cascade failure simulations are used to evaluate robustness, and a mixed-integer optimization problem is used to study resilience. Different indicators related to each of the three assessments are computed. The significance of the combined analysis is emphasized as the simulation findings are described visually and statistically in a unique three-dimensional manner eventually.