Transmission planning considering spatial correlation of wind power

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Due to similar meteorological conditions, neighboring wind farm outputs are correlated, which usually results in amplified uncertainty. However, wind power is assumed to be independent in traditional transmission planning, causing potential risks in wind integration and power system security. This paper initially proposes a transmission planning approach considering correlation of wind power. The spatial dependence of neighboring wind farm outputs is modeled by Copula theory. Then, a transmission planning method is established based on multi-scenario model of correlated wind power and is further solved by generic algorithm. Validity of the proposed method is tested on Garver 6-bus system. Numerical results show that transmission extension plan is affected by wind correlation. The transmission line between wind connection sites is avoided to prevent amplified negative effects of dependent wind power. Compared with traditional planning, the proposed method shows similar economic performance in total cost, with increasing transmission investment and reducing operation cost.

Original languageEnglish
Title of host publication2016 IEEE PES 13th International Conference on Transmission and Distribution Construction, Operation and Live-Line Maintenance, ESMO 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509051656
DOIs
StatePublished - 2 Jul 2016
Event13th IEEE PES International Conference on Transmission and Distribution Construction, Operation and Live-Line Maintenance, ESMO 2016 - Columbus, United States
Duration: 12 Sep 201615 Sep 2016

Publication series

NameProceedings of the IEEE International Conference on Transmission and Distribution Construction and Live Line Maintenance, ESMO
Volume0

Conference

Conference13th IEEE PES International Conference on Transmission and Distribution Construction, Operation and Live-Line Maintenance, ESMO 2016
Country/TerritoryUnited States
CityColumbus
Period12/09/1615/09/16

Keywords

  • Correlation
  • Genetic algorithm
  • Probabilistic method
  • Transmission planning
  • Wind energy

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