Comparison of random sampling and heuristic optimization-based methods for determining the flexibility potential at vertical system interconnections

authored by: Johannes Gerster, Marcel Sarstedt, Eric Veith, Lutz Hofmann, Sebastian Lehnhoff
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 former 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 sides. 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.
Organisation(s): Electric Power Engineering Section
External Organisation(s): OFFIS - Institute for Information Technology
Type: Paper
Pages: 1-9
No. of pages: 9
Publication date: 2021
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Information Systems and Management, Artificial Intelligence, Energy Engineering and Power Technology, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Renewable Energy, Sustainability and the Environment
Sustainable Development Goals: SDG 7 - Affordable and Clean Energy
Electronic version(s): https://arxiv.org/abs/2106.01056 (Access: Open)
https://doi.org/10.1109/ISGTEurope52324.2021.9640108 (Access: Closed)