Optimal corrective dispatch of uncertain virtual energy storage systems

TL;DR

This paper develops a risk-aware optimization strategy for dispatching uncertain virtual energy storage systems (VESSs) to enhance grid balancing with high renewable penetration, accounting for energy state and capacity uncertainties.

Contribution

It introduces a novel risk-based chance-constrained control approach for optimally dispatching energy-constrained VESSs under uncertainty, improving grid balancing performance.

Findings

The proposed method effectively manages VESS uncertainties in simulations.

It reduces reliance on ramp-rate limited generators.

The approach improves grid stability with high renewable variability.

Abstract

High penetrations of intermittent renewable energy resources in the power system require large balancing reserves for reliable operations. Aggregated and coordinated behind-the-meter loads can provide these fast reserves, but represent energy-constrained and uncertain reserves (in their energy state and capacity). To optimally dispatch uncertain, energy-constrained reserves, optimization-based techniques allow one to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. Therefore, this paper investigates the uncertainty associated with energy-constrained aggregations of flexible, behind-the-meter distributed energy resources (DERs). The uncertainty studied herein is associated with estimating the state of charge and the capacity of an aggregation of DERs (i.e., a virtual energy storage system or VESS). To that effect, a risk-based chance-constrained control strategy is developed that optimizes the operational risk of unexpectedly saturating the VESS against deviating generators from their scheduled set-points. The controller coordinates energy-constrained VESSs to minimize unscheduled participation of and overcome ramp-rate limited generators for balancing variability from renewable generation, while taking into account grid conditions. To illustrate the effectiveness of the proposed method, simulation-based analysis is carried out on an augmented IEEE RTS-96 network with uncertain energy resources and temperature-based dynamic line ratings.