Issue |
E3S Web Conf.
Volume 143, 2020
2nd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2019)
|
|
---|---|---|
Article Number | 02039 | |
Number of page(s) | 8 | |
Section | Environmental Science and Energy Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202014302039 | |
Published online | 24 January 2020 |
Dynamic Robust Reconfiguration of Distribution Network with Low-wind-speed Wind Turbine Integrated
1 School of Electrical Engineering and Automation, HeFei University of Technology, Anhui, China
2 State Grid Chaohu Municipal Electric Power Company, Anhui, China
3 State Grid Shanghai Maintenance Company, Shanghai, China
* Corresponding author: 13905690716@163.com
For distribution systems where wind sources are poor, low-wind-speed wind turbines (LWTG) plays an important role in improving the security, economy and reliability of the system. However, the stochastic volatility of LWTG output and loads poses a challenge to the technology of distribution network reconfiguration. Considering the uncertainty of LWTG output, photovoltaic output and changes of load in multiple continuous periods, a dynamic robust reconfiguration model is established. The optimization target is to minimize the three-phase current unbalance and network loss. The model solving process combines the Latin hypercube sampling-based Monte Carlo method, the Semi-invariant method and the compound differential evolution algorithm. The influence of LWTG on the reconfiguration results is explored based on the modified IEEE34-node simulation system, and the performance of the proposed dynamic robust reconfiguration method is then verified.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.