Comparison of Random Sampling and Heuristic Optimization-Based Methods for Determining the Flexibility Potential at Vertical System Interconnections

TL;DR

This paper compares random sampling and heuristic optimization methods for identifying the feasible operation region of distribution grids, aiming to improve coordination between grid operators and enhance flexibility potential assessment.

Contribution

It introduces a novel Dirichlet-based random sampling method and a hybrid approach using stochastic evolutionary optimization for better FOR coverage.

Findings

Dirichlet sampling improves edge coverage of the FOR

Hybrid method reduces power flow calculations needed

Comparison shows trade-offs between methods in coverage and efficiency

Abstract

In order to prevent conflicting or counteracting use of flexibility options, the coordination between distribution system operator and transmission system operator has to be strengthened. For this purpose, methods for the standardized description and identification of the aggregated flexibility potential of distribution grids are developed. Approaches for identifying the feasible operation region (FOR) of distribution grids can be categorized into two main classes: Random sampling/stochastic approaches and optimization-based approaches. While the latter have the advantage of working in real-world scenarios where no full grid models exist, when relying on naive sampling strategies, they suffer from poor coverage of the edges of the FOR due to convoluted distributions. In this paper, we tackle the problem from two different angles. First, we present a random sampling approach which mitigates the convolution problem by drawing sample values from a multivariate Dirichlet distribution. Second, we come up with a hybrid approach which solves the underlying optimal power flow problems of the optimization-based approach by means of a stochastic evolutionary optimization algorithm codenamed REvol. By means of synthetic feeders, we compare the two proposed FOR identification methods with regard to how well the FOR is covered and number of power flow calculations required.