Decentralized control approach to power curtailment instruction problem for PV generation plants with storage

Hikaru Akutsu, Kenji Hirata*, Akihiro Ohori, Nobuyuki Hattori, Yoshito Ohta

*Corresponding author for this work

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

5 Scopus citations

Abstract

PV (photovoltaic) generation has experienced the most growth among the renewable energy sources in the last few years, and the interconnection capacity of PV generations may continue to increase. However, more recently special problem in Japan, the capacity of qualified PV generation facilities exceeds the allowable interconnection capacity determined by each power grid company. This fact is recognized as a critical issue for reliable operations of power grids, and it will be enforced by law that the power grid company can announce the output curtailment instruction signal to the PV generation plants. An output curtailment essentially means wasting potential solar energy. Operating methodologies for the PV generation plant that can reduce the amount of wasted energy are needed to be developed. This paper considers the PV generation plant equipped with the energy storage and investigates decentralized management of power conditioning systems which are used to interconnect the PV system into the grid. The effectiveness of the proposed methodology is evaluated through the numerical and real physical experiments.

Original languageEnglish
Title of host publication2017 Asian Control Conference, ASCC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2825-2830
Number of pages6
ISBN (Electronic)9781509015733
DOIs
StatePublished - 2018/02/07
Event2017 11th Asian Control Conference, ASCC 2017 - Gold Coast, Australia
Duration: 2017/12/172017/12/20

Publication series

Name2017 Asian Control Conference, ASCC 2017
Volume2018-January

Conference

Conference2017 11th Asian Control Conference, ASCC 2017
Country/TerritoryAustralia
CityGold Coast
Period2017/12/172017/12/20

ASJC Scopus subject areas

  • Control and Optimization

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