Narrowing Frequency Probability Density Function For Achieving Minimized Uncertainties In Power Systems Operation - A Stochastic Distribution Control Perspective
Keywords
frequency response; Power systems; probability density function shaping; stochastic distribution control; swing equation
Abstract
In this paper, the summary of the stochastic swing equation will be firstly given taking into account of DERs. This will then be followed by the development of stochastic distribution control model that links the power sources and the loads with the PDF of the frequency using Fokker Planck Kolmogorov (FPK) equations. A generic constrained optimization problem will be formulated, where the cost function is composed of a kind of 'functional distance' between the actual and the desired PDFs of the frequency. A feasible solution using B-spine Neural Networks based stochastic distribution control model will be described. Using the obtained stochastic distribution control model, a feedback type control algorithm will be described that uses controllable power sources and the loads to shape the PDF of the frequency or to minimize the randomness of the frequency via minimized entropy approach. Future directions will be briefly discussed in the later part of the paper.
Publication Date
10-26-2018
Publication Title
2018 IEEE Conference on Control Technology and Applications, CCTA 2018
Number of Pages
211-216
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CCTA.2018.8511533
Copyright Status
Unknown
Socpus ID
85056864996 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85056864996
STARS Citation
Wang, Hong and Qu, Zhihua, "Narrowing Frequency Probability Density Function For Achieving Minimized Uncertainties In Power Systems Operation - A Stochastic Distribution Control Perspective" (2018). Scopus Export 2015-2019. 9499.
https://stars.library.ucf.edu/scopus2015/9499