Formulation and evaluation of long-term allocation problem for renewable distributed generations

Ikki Tanaka, Hirokana Yuge, Hiromitsu Ohmori

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The penetration rate of renewable energy into the power systems has been increasing in many countries. The governments and international energy organisations have announced the long-term visions such as power generation and penetration rate of renewable energy. However, the specific installation plans and scenarios have not been discussed and determined. Although plenty of researches related to optimal allocation problem of renewable energy-based distributed generations (DGs) have been proposed in past decade, most of the studies have considered only 1 year's allocation and daily annual system operation. Therefore, this study proposes a novel scenario-based two-stage stochastic programming problem for long-term allocation of DGs. Also, a scenario generation procedure is presented for solving the problem. Furthermore, few studies have focused on the evaluations and analyses of the optimal solutions in various aspects. Thus, this study shows the optimal allocation results on 34-bus distribution network, considering the different scenario generation methods and number of scenarios. The authors finally discuss the important points and indicate that decision makers have to consider several important issues. In addition, they developed and released a general-purpose framework for optimal allocation of DGs as an open source.

Original languageEnglish
Pages (from-to)1584-1596
Number of pages13
JournalIET Renewable Power Generation
Volume11
Issue number12
DOIs
Publication statusPublished - 2017 Oct 18

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Distributed power generation
Stochastic programming
Electric power distribution
Power generation

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

Cite this

Formulation and evaluation of long-term allocation problem for renewable distributed generations. / Tanaka, Ikki; Yuge, Hirokana; Ohmori, Hiromitsu.

In: IET Renewable Power Generation, Vol. 11, No. 12, 18.10.2017, p. 1584-1596.

Research output: Contribution to journalArticle

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