Issue |
E3S Web Conf.
Volume 252, 2021
2021 International Conference on Power Grid System and Green Energy (PGSGE 2021)
|
|
---|---|---|
Article Number | 01003 | |
Number of page(s) | 7 | |
Section | Power Control Technology and Smart Grid Application | |
DOI | https://doi.org/10.1051/e3sconf/202125201003 | |
Published online | 23 April 2021 |
A fuzzy inference based method for evaluating coordinated generation-grid-load-storage control ability in receiving-end power system
1 College of Electrical and Information Engineering, Hunan University, Changsha, Hunan 410082, China
2 State Grid Hunan Electric Power Company Limited, Changsha, Hunan 410004, China
3 Electric Power Research Institute, State Grid Hunan Electric Power Company Limited, Changsha, Hunan 410007, China
* Corresponding author’s e-mail: liaocf@hnu.edu.cn
With the rapid development of the flexible loads and energy storage, it is of great scientific and engineering value to improve safety and economy of the receiving-end power system with HVDC feed-in power by the coordinated generation-grid-load-storage control. In this paper, a fuzzy inference based method is proposed to assess the coordinated control ability of generation-grid-load-storage control for the receiving-end power system with HVDC feed-in power. First of all, the evaluation indexes are constructed with consideration of the coordination and interaction of power generation, power grid, power load and energy storage. Both subjective weight and objective weight are considered to calculate the comprehensive weight for each evaluation index. Furthermore, the Kmeans clustering based method is proposed to the grading in each evaluation index. Finally, the coordination control ability of the modified IEEE 57-bus system in different states is evaluated by the proposed method.
© The Authors, published by EDP Sciences, 2021
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.