Thesis
An efficient Non-iterative probabilistic load flow analysis method comparison and worked example
Masters by Coursework, Murdoch University
2016
Abstract
This paper presents an analytical assessment method for probabilistic power flow analysis using a Multivariate Complex Gaussian Distribution (MCGD) and a Direct Approach for the load flow equations.
To provide a reference for comparison and assessment, a standard Monte Carlo (MC) simulation and a Copula coefficient MC simulation were undertaken. Both use the Direct Approach for load flow equations.
Details and steps of all methods are provided along with background information deemed relevant to provide a self-contained body of knowledge. This improves accessibility to a less mathematically advanced audience.
It will be shown that the proposed technique is significantly quicker to compute and that the magnitude of mean voltages closely match those obtained using the MCSs.
Further, it will be shown that standard deviations observed varied up to 45% between methods, at specific load points, and it is concluded that further analysis is required to be able to determine that the proposed method is sufficiently accurate.
Details
- Title
- An efficient Non-iterative probabilistic load flow analysis method comparison and worked example
- Authors/Creators
- Richard Davis
- Contributors
- Ali Arefi (Supervisor)
- Awarding Institution
- Murdoch University; Masters by Coursework
- Identifiers
- 991005546030807891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Thesis
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