Stochastic Analysis (MCS) for Mitigation of Reliability Indicators of the Power Distribution System
Abstract
The study aims to indicate the methodology of an algorithm to mitigate the supply reliability indicators through small-scale simulations with the IEEE 34 model through deterministic analysis of the Monte Carlo Method through Matlab, to calculate the SAIDI and SAIFI indicators independent of the problem caused in the distribution. The algorithm consists of analyzing the data and selecting the recloser and/or DG to serve the most consumers. The results show that the best results are with the activation of the DG at bar 890 of the model, where the SAIDI obtained a reduction of 57.88% and the SAIFI a reduction of 57.63%. Thus, the implementation of smart grid and DG systems by distribution system operators will improve the reliability of the power system. Thus, with the methodology applied on a large scale, to exemplify, in the reliability indicators of some South American countries, there are reductions, SAIFI from 17.6 to 7 events/year and SAIDI from 21.6 to 9.18 hours/year. © 2022 IEEE.
- Energy Integration
- SAIDI
- SAIFI
- Smart-grid
- South American
- Electric power distribution
- MATLAB
- Monte Carlo methods
- Reclosing circuit breakers
- Reliability analysis
- Stochastic systems
- % reductions
- Energy-integration
- Power-distribution system
- Reliability indicators
- SAIDI
- SAIFI
- Smart grid
- South american
- Stochastic analysis
- Supply reliability
- Smart power grids
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149180146&doi=10.1109%2fIEEEPESGTDLatinAmeri53482.2022.10038302&partnerID=40&md5=20396cefcc0746469ebe956924cf895fhttps://repositorio.maua.br/handle/MAUA/620