A two-stage chance constrained volt/VAr control scheme for active distribution networks with nodal power uncertainties

Firdous Ul Nazir, Bikash C. Pal*, Rabih A. Jabr

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

97 Citations (Scopus)

Abstract

Volt/var control (VVC) is one of the primary functions of the distribution management system aiming at optimum operation of power distribution networks while respecting all of their operational and security constraints. However, the recent huge integration of highly stochastic distributed generation (DG) sources with the grid presents a significant challenge to the traditional VVC schemes, which assume the future to be perfectly known. This paper presents a two-stage chance constrained optimization scheme to handle these nodal power uncertainties and guarantees that the operational and security constraints are respected for almost all realizations of the uncertainty. The chance constrained model is solved by collecting enough randomly chosen samples from the probability spaces of the uncertain parameters so that the class of the problem, a mixed integer second-order cone program, is not elevated. The algorithm not only dispatches the optimum schedule for discrete controlling devices like transformers and shunt capacitors but also optimizes the predefined decision rules for reactive power control of DG sources, thus falling in line with the requirement laid down in the revised IEEE 1547 Standard. Numerical simulations on three different test systems show the superiority of the proposed algorithm over the traditional deterministic methods.

Original languageEnglish
Article number8419280
Pages (from-to)314-325
Number of pages12
JournalIEEE Transactions on Power Systems
Volume34
Issue number1
DOIs
Publication statusPublished - 25 Jul 2018
Externally publishedYes

Keywords

  • Chance constrained optimization
  • distributed generation (DG)
  • radial distribution systems
  • volt/var control (VVC)

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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