In the book Modeling, Operation, and Analysis of DC Grids: From High Power DC Transmission to DC Microgrids
Academic Press, London, United Kingdom
Summary
In this chapter, we present several approaches to analyze probabilistic power flow problems over DC grids. On one hand, we discuss the classical probabilistic methods Monte Carlo simulation and point estimation. To avoid the dependence of computing partial derivatives in power DC systems and inversions of Jacobian matrixes, we introduce data-driven approaches to approximate the power flow calculations in these grids. On the other hand, we present two Bayesian methods to consider the probabilistic state over DC grids. Numerical results in a 21-bus DC microgrid and a five-terminal HVDC grid show the accuracy and computational efficiency of the proposed methodologies.
ISBN: 978-0-12-822101-3
DOI: 
https://doi.org/10.1016/B978-0-12-822101-3.00012-5
DOI of the book:
https://doi.org/10.1016/C2019-0-02801-4
Published: 2021
Citation:
C.D. Zuluaga-Ríos, Probabilistic analysis in DC grids, in Modeling, Operation, and Analysis of DC Grids: From High Power DC Transmission to DC Microgrids. Ed. Academic Press. London, United Kingdom, 2021.
IIT-21-321L
