Stochastic programming for energy plant operation

Tomoki Fukuba, Takayuki Shiina, Ken ichi Tokoro

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

1 Citation (Scopus)

Abstract

A stochastic programming model of the operation of energy plants with the introduction of photovoltaic generation and a storage battery is developed. The uncertainty of the output of the photovoltaic generation is represented by a set of discrete scenarios, and the expected value of the operation cost is minimized. The effectiveness of the stochastic programming model by comparing it with the deterministic model is shown. As an economic evaluation, the recovery period for the initial investment of photovoltaic generation and storage battery is also shown.

Original languageEnglish
Title of host publicationTheory and Applications of Models of Computation - 15th Annual Conference, TAMC 2019, Proceedings
EditorsT. V. Gopal, Junzo Watada
PublisherSpringer-Verlag
Pages208-221
Number of pages14
ISBN (Print)9783030148119
DOIs
Publication statusPublished - 2019 Jan 1
Event15th Annual Conference on Theory and Applications of Models of Computation, TAMC 2019 - Kitakyushu, Japan
Duration: 2019 Apr 132019 Apr 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11436 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Annual Conference on Theory and Applications of Models of Computation, TAMC 2019
CountryJapan
CityKitakyushu
Period19/4/1319/4/16

Keywords

  • Energy plant
  • Operational planning
  • Optimization
  • Photovoltaic generation
  • Stochastic programming
  • Unit commitment problem

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Fukuba, T., Shiina, T., & Tokoro, K. I. (2019). Stochastic programming for energy plant operation. In T. V. Gopal, & J. Watada (Eds.), Theory and Applications of Models of Computation - 15th Annual Conference, TAMC 2019, Proceedings (pp. 208-221). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11436 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-030-14812-6_13