Electricity Self-Sufficient Community Clustering for Energy Resilience

Yoshiki Yamagata, Daisuke Murakami, Kazuhiro Minami, Nana Arizumi, Sho Kuroda, Tomoya Tanjo, Hiroshi Maruyama

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Local electricity generation and sharing has been given considerable attention recently for its disaster resilience and other reasons. However, the process of designing local sharing communities (or local grids) is still unclear. Thus, this study empirically compares algorithms for electricity sharing community clustering in terms of self-sufficiency, sharing cost, and stability. The comparison is performed for all 12 months of a typical year in Yokohama, Japan. The analysis results indicate that, while each individual algorithm has some advantages, an exhaustive algorithm provides clusters that are highly self-sufficient. The exhaustive algorithm further demonstrates that a clustering result optimized for one month is available across many months without losing self-sufficiency. In fact, the clusters achieve complete self-sufficiency for five months in spring and autumn, when electricity demands are lower.

Original languageEnglish
Article number543
Issue number7
Publication statusPublished - 2016 Jul
Externally publishedYes


  • Community clustering
  • Electricity sharing
  • Graph partitioning
  • Simulated annealing
  • Vehicle to community system

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Building and Construction
  • Fuel Technology
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering


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