A Bayesian Approach to the Reliability Analysis of Renewables-Dominated Islanded DC Microgrids

The DC microgrid (DC MG) concept enables the hosting of DC-type renewable energy resources. However, their intermittent nature means that a high penetration of renewables can jeopardize supply adequacy and voltage provision during islanding. The work presented in this paper was therefore directed at...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on power systems 2021-09, Vol.36 (5), p.4296-4309
Main Authors: Eajal, Abdelsalam A., El-Awady, Ahmed, El-Saadany, Ehab F., Ponnambalam, Kumaraswamy, Al-Durra, Ahmed, Al-Sumaiti, Ameena S., Salama, Magdy M. A.
Format: Article
Language:English
Subjects:
Adequacy
Algorithms
Alternative energy sources
Bayes methods
Bayesian analysis
Bayesian network
DC microgrid
Distributed generation
distributed generator
droop control
Electric potential
Electric power supplies
Electric power systems
Energy sources
Islanding
Microgrids
Monte Carlo simulation
Network reliability
Penetration
Power flow
Power system reliability
Probabilistic logic
Reliability
Reliability analysis
renewable power
Statistical analysis
Voltage
Voltage control
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The DC microgrid (DC MG) concept enables the hosting of DC-type renewable energy resources. However, their intermittent nature means that a high penetration of renewables can jeopardize supply adequacy and voltage provision during islanding. The work presented in this paper was therefore directed at developing a probabilistic graphical approach based on Bayesian networks (BNs) for the reliability analysis of renewables-dominated DC MGs. The proposed BN model incorporates a family of novel reliability indices for quantifying the impact of a high penetration of renewables on MG reliability, including loss of renewable power supply, rise in voltage, and reversal of power flow. The model is supported by a newly formulated fast and accurate linearized power flow algorithm for probability calculations. The accuracy of the BN model has been verified against a Monte-Carlo simulation (MCS). The effective application of the new BN model for reasoning and impact assessment reveals that a high penetration of renewables affects reliability indices differently. Case study results suggest that the proposed BN model shows promise as a valuable tool for the reliability analysis of renewables-dominated MGs that feature islanding capability.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2021.3056314