Combined MV-LV Power Grid Operation: Comparing Sequential, Integrated, and Decentralized Control Architectures

The increasing connection of distributed energy resources (DERs) to low-voltage (LV) power grids challenges the operation of both connected LV grids and upstream medium-voltage (MV) grids, through power flow via the MVLV transformers. Handling the coupling between MV and LV grids calls for combined...

Full description

Saved in:
Bibliographic Details
Published in2022 International Conference on Smart Energy Systems and Technologies (SEST) pp. 1 - 6
Main Authors Zhan, Sen, Morren, Johan, van Den Akker, Wouter, van der Molen, Anne, Paterakis, Nikolaos G., Slootweg, J. G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 05.09.2022
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The increasing connection of distributed energy resources (DERs) to low-voltage (LV) power grids challenges the operation of both connected LV grids and upstream medium-voltage (MV) grids, through power flow via the MVLV transformers. Handling the coupling between MV and LV grids calls for combined MV-LV network operation models. This study develops various optimization-based models, built respectively on sequential, integrated, and decentralized control architectures. A new objective function is also designed to attain fairer DER curtailment strategies. For the decentralized architecture, this study explores the generalized Benders decomposition (GBD) and two augmented Lagrangian relaxation (ALR)-based approaches: the alternating direction method of multipliers (ADMM) and the auxiliary problem principle (APP). Computational results based on open-source Simbench networks show reduced power curtailment from the integrated architecture compared to the sequential one. For decentralization, GBD already shows superior convergence performance compared to ADMM and APP under moderate accuracy requirements. Under higher accuracy requirements, GBD maintains fast convergence, while ADMM and APP fail to converge in a reasonable number of iterations.
DOI:10.1109/SEST53650.2022.9898456