Annual simulations of output curtailment to ensure fairness among wind farms

Daichi Sugawara, Hiroumi Saitoh, Wataru Wayama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, plenty of wind farms (WFs) have been introduced into power system throughout the world. If WFs are foreseen to cause excessive power generation in the entire power system, the WF output is curtailed as a last resort to maintain the integrity of the power system. Our previous work has developed a calculation method that minimizes the overall curtailed power of WFs and achieves fair allocation to WFs under the different rules that is applied in Japan regarding equipment and time, and the necessary and sufficient conditions for the fair allocation was proved. In this paper, in order to apply the calculation method to the actual system operation, annual simulations of WF output curtailment are performed with the developed method and actual data of northeast electric power system in Japan. It was found that the output curtailments are carried out frequently in the spring because demand in those season becomes lower than demand in the other season.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages470-475
Number of pages6
ISBN (Electronic)9781728185507
DOIs
Publication statusPublished - 2020 Nov
Event2020 International Conference on Smart Grids and Energy Systems, SGES 2020 - Virtual, Perth, Australia
Duration: 2020 Nov 232020 Nov 26

Publication series

NameProceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020

Conference

Conference2020 International Conference on Smart Grids and Energy Systems, SGES 2020
Country/TerritoryAustralia
CityVirtual, Perth
Period20/11/2320/11/26

Keywords

  • Curtailment
  • Linear programming
  • Optimization problem
  • Wind power

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Automotive Engineering
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Transportation

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