Issue |
E3S Web Conf.
Volume 236, 2021
3rd International Conference on Energy Resources and Sustainable Development (ICERSD 2020)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 6 | |
Section | Development, Utilization and Protection of Traditional Energy Resources | |
DOI | https://doi.org/10.1051/e3sconf/202123601004 | |
Published online | 09 February 2021 |
IGDT-based Robust Power Dispatch for Active Distribution Network Considering Demand Response
1 Locomotive and rolling stock Department, Kunming Railway Vocational and Technical College Kunming, China
2 Department of Control Engineering, Chengdu University of Information Technology, Chengdu, China
* Huimin Zhuang: huimin@cuit.edu.cn
Considering increasing uncertain renewable energy sources (RES) and flexible loads in active distribution network (ADN), this study proposes a novel optimal model for robust hourly energy scheduling of ADN. Firstly, a deterministic optimal dispatching model is formulated, which aims at minimizing the total operation cost of distribution network; Secondly, the information gap decision theory (IGDT) is employed to handle uncertainties of RES generation. One of the features of the proposed model is to take into account the impact of demand response of flexible loads and energy storage system (ESS) as the effective tools to reduce unintended costs due to uncertainty of RESs. Also, the uncertainty of RESs is handled in a way that maximum tolerable uncertainty is achieved for a given worsening of total operation cost. The model is formulated as a mixed integer nonlinear optimization problem and solved in the genetic algorithm. Numerical simulation on the IEEE 33-bus system has been performed. Comparisons with two types of probabilistic techniques demonstrate the effectiveness and benefits of the proposal.
© 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.