Back to Search
Start Over
Resilience-Oriented DG Siting and Sizing Considering Stochastic Scenario Reduction.
- Source :
-
IEEE Transactions on Power Systems . Jul2021, Vol. 36 Issue 4, p3715-3727. 13p. - Publication Year :
- 2021
-
Abstract
- In this paper, a fuel-based distributed generator (DG) allocation strategy is proposed to enhance the distribution system resilience against extreme weather. The long-term planning problem is formulated as a two-stage stochastic mixed-integer programming (SMIP). The first stage is to make decisions of DG siting and sizing under the given budget constraint. In the second stage, a post-extreme-event-restoration (PEER) is employed to minimize the operating cost in an uncertain fault scenario. In particular, this study proposes a method to select the most representative scenarios for the SMIP. First, a Monte Carlo Simulation (MCS) is introduced to generate sufficient scenarios considering random fault locations and load profiles. Then, the number of scenarios is reduced by the K-means clustering algorithm. The advantage of scenario reduction is to make a trade-off between accuracy and computational efficiency. Finally, the SMIP is solved by the progressive hedging algorithm. The case studies of the IEEE 33-bus and 123-bus test systems demonstrate the effectiveness of the proposed algorithm in reducing the expected energy not served (EENS), which is a critical criterion of resilience. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08858950
- Volume :
- 36
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Power Systems
- Publication Type :
- Academic Journal
- Accession number :
- 151250305
- Full Text :
- https://doi.org/10.1109/TPWRS.2020.3043874