Probabilistic load flow in systems with wind generation

By J. Usaola. 2009

159 citations recorded by the source corpus.

A method for solving a probabilistic power flow that deals with the uncertainties of (i) wind generation, (ii) load and (iii) generation availability in power systems is proposed. Dependence between random variables has been considered. The method is based on the properties of cumulants of random variables. Cornish-Fisher expansion series are used to obtain the cumulative distribution function (CDF) of the output variables. Multimodal CDF are obtained by convolutions, whose number has been minimised in order to decrease the computation requirements.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/37df2916eef08b6a8895c2cc274b4f002911fb4c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Chongqing Kang
2. Vijay Vittal
3. Qing Xia
4. Bin Zou
5. Qing Xiao
6. Jingwei Yang
7. Yi Wang
8. Qixin Chen

In Safety, Risk, Reliability and Quality

1. Bin Zou
2. Chongqing Kang
3. Qing Xia
4. Qing Xiao
5. Jingwei Yang
6. Yi Wang
7. Qixin Chen
8. Vijay Vittal

In Statistics and Probability

1. Bin Zou
2. Chongqing Kang
3. Qing Xia
4. Qing Xiao
5. Jingwei Yang
6. Yi Wang
7. Qixin Chen
8. Vijay Vittal

Citations in the corpus

• A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty (2015, methodology): “can be calculated using the stochastic load flow (SLF) technique [33].”
• A Novel Probabilistic Optimal Power Flow Model With Uncertain Wind Power Generation Described by Customized Gaussian Mixture Model (2016, unknown): “Indeed, this linearization method for probabilistic analysis has been adopted frequently in extant literatures [25], [26].”
• Dependent Discrete Convolution Based Probabilistic Load Flow for the Active Distribution System (2017, methodology): “PLF with correlation consideration can be computed by combining the transformation with the cumulant method and the Monte Carlo method [14].”
• Solving Probabilistic Optimal Power Flow Problem Using Quasi Monte Carlo Method and Ninth-Order Polynomial Normal Transformation (2014, background): “Combinedwith the normal transformation technique, this method has been used to solve the probabilistic power flow (PPF) problem with correlated inputs [9], [10].”
• Probabilistic Power Flow Studies for Transmission Systems With Photovoltaic Generation Using Cumulants (2012, methodology): “Also, [18] uses the combined cumulants and the Cornish-Fisher expansion method.”