Accelerating Chance-constrained SCED via Scenario Compression

TL;DR

This paper introduces scenario compression techniques, including convex hull vertex compression and box compression with risk validation, to speed up chance-constrained SCED solutions while controlling solution risk.

Contribution

It presents novel compression methods and a risk validation scheme that enable faster SCED solutions with quantifiable risk management.

Findings

Vertices-based compression yields equivalent solutions to full scenario sets.

Box compression introduces risk that can be quantified and managed.

Compression methods significantly improve problem-solving efficiency.

Abstract

This paper studies some compression methods to accelerate the scenario-based chance-constrained security-constrained economic dispatch (SCED) problem. In particular, we show that by exclusively employing the vertices after convex hull compression, an equivalent solution can be obtained compared to utilizing the entire scenario set. For other compression methods that might relax the original solution, such as box compression, this paper presents the compression risk validation scheme to assess the risk arising from the sample space. By quantifying the risk associated with compression, decision-makers are empowered to select either solution risk or compression risk as the risk metric, depending on the complexity of specific problems. Numerical examples based on the 118-bus system and synthetic Texas grids compare these two risk metrics. The results also demonstrate the efficiency of compression methods in both problem formulation and solving processes.