Grid Inadequacy Assessment against Power Injection Diversity from Intermittent Generation, Dynamic Loads, and Energy Storage

TL;DR

This paper introduces new metrics to assess grid inadequacy in accommodating diverse power injections from intermittent sources, dynamic loads, and energy storage, aiding future grid planning and resilience analysis.

Contribution

The paper proposes novel grid inadequacy metrics based on the size of infeasible power flow sets relative to injection sets, using sampling and projection methods.

Findings

Metrics reveal grid vulnerabilities to power injection diversity.

Illustrative examples demonstrate the metrics' usefulness.

Metrics provide a new quantification approach for grid inadequacy.

Abstract

The integration of more intermittent generation, energy storage, and dynamic loads on top of a competitive market environment requires future grids to handle increasing diversity of power injection states. Grid planners need new tools and metrics that can assess how vulnerable grids are against this future. To this end, we propose grid inadequacy metrics that expose grid inability to accommodate power injection diversity from such sources. We define the metrics based on a previously unexplored characterization of grid inadequacy, that is, the size of the DC power flow infeasible set relative to the size of the power injection set is indicative of inherent grid inadequacy to accommodate power injection diversity without intervention. We circumvent the difficulty of characterizing the high-dimensional sets involved using three approaches: one sampling-based approach and two approaches that project the sets in lower dimensions. Illustrative examples show how the metrics can reveal useful insights about a grid. As with other metrics, the proposed metrics are only valid relative to the assumptions used and cannot capture all intricacies of assessing grid inadequacy. Nevertheless, the metrics provide a new way of quantifying grid inadequacy that is potentially useful in future research and practice. We present possible use-cases where the proposed metrics can be used.