AUTHOR=Ding Xiaohua , Chen Xingying , Yu Kun , Cao Feifan , Wang Bo 

TITLE=Multi-time-scale voltage control of the distribution network with energy storage equipped soft open points

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1374704

DOI=10.3389/fenrg.2024.1374704

ISSN=2296-598X

ABSTRACT=The integration of distributed generation units into distribution networks (DNs) has brought about several operational challenges, including voltage issues and increased power loss. Energy storage equipped soft open points (E-SOPs) can accurately and flexibly control active and reactive power flows to address these problems. Additionally, the photovoltaic (PV) inverter as well as the network reconfiguration (NR) play a significant role in the voltage control by adjusting the reactive power and the topology of DN respectively. However, due to differences in response times, there is a lack of systematic coordination between NR and the inverters of E-SOP and PV. This paper proposes a multi-time-scale voltage control model that includes day-ahead NR scheduling, inter-day droop control optimization of PV and E-SOP, and real-time local droop control. Considering the uncertainties of renewable DG outputs and loads, a robust optimization method is employed in the day-ahead stage to obtain a reliable network structure. Then, with more accurate intraday predictions, a stochastic optimization method is utilized to obtain the optimal state of charge interval, aiming to provide a flexible regulation range for battery energy storage to cope with the power fluctuations during the real-time stage. Besides, to address the intra-day voltage control model with bilinear constraints of the droop control function, a particle swarm optimization method is utilized. The results are verified on a 33-bus DN system through comparative analyses, showing effective performance.