Options
A generalized framework for chance-constrained optimal power flow
Publikationstyp
Journal Article
Date Issued
2018-12-01
Sprache
English
Author(s)
Volume
16
Start Page
231
End Page
242
Citation
Sustainable Energy, Grids and Networks 16: 231-242 (2018)
Publisher DOI
Scopus ID
Publisher
Elsevier
Deregulated energy markets, demand forecasting, and the continuously increasing share of renewable energy sources call – among others – fora structured consideration of uncertainties in optimal power flow problems. The main challenge is to guarantee power balance while maintaining economic and secure operation. In the presence of Gaussian uncertainties affine feedback policies are known to be viable options for this task. The present paper advocates a general framework for chance-constrained OPF problems in terms of continuous random variables. It is shown that, irrespective of the type of distribution, the random-variable minimizers lead to affine feedback policies. Introducing a three-step methodology that exploits polynomial chaos expansion, the present paper provides a constructive approach to chance-constrained optimal power flow problems that does not assume a specific distribution, e.g. Gaussian, for the uncertainties. We illustrate our findings by means of a tutorial example and a 300-bus test case.
Subjects
Affine policies
Chance-constrained optimal power flow
Polynomial chaos
Uncertainties
DDC Class
333.7: Natural Resources, Energy and Environment
004: Computer Sciences
510: Mathematics