LAPSE:2019.0051
Published Article
LAPSE:2019.0051
Electricity Self-Sufficient Community Clustering for Energy Resilience
January 7, 2019
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.
Record ID
Keywords
community clustering, electricity sharing, graph partitioning, simulated annealing, vehicle to community system
Subject
Suggested Citation
Yamagata Y, Murakami D, Minami K, Arizumi N, Kuroda S, Tanjo T, Maruyama H. Electricity Self-Sufficient Community Clustering for Energy Resilience. (2019). LAPSE:2019.0051
Author Affiliations
Yamagata Y: Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan; Department of Statistical Modeling, Institute of Statistical Mathematics, Tachikawa, Tokyo 190-8562, Japan
Murakami D: Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
Minami K: Department of Statistical Modeling, Institute of Statistical Mathematics, Tachikawa, Tokyo 190-8562, Japan
Arizumi N: Center for Semiconductor Research and Development, Toshiba Corporation, Kawasaki, Kanagawa 212-8520, Japan
Kuroda S: Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan [ORCID]
Tanjo T: Center for Cloud Research and Development, National Institute of Informatics, Chiyoda, Tokyo 100-0003, Japan
Maruyama H: Chief Strategy Officer, Preferred Networks, Inc., Chiyoda, Tokyo 100-0004, Japan
[Login] to see author email addresses.
Murakami D: Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
Minami K: Department of Statistical Modeling, Institute of Statistical Mathematics, Tachikawa, Tokyo 190-8562, Japan
Arizumi N: Center for Semiconductor Research and Development, Toshiba Corporation, Kawasaki, Kanagawa 212-8520, Japan
Kuroda S: Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan [ORCID]
Tanjo T: Center for Cloud Research and Development, National Institute of Informatics, Chiyoda, Tokyo 100-0003, Japan
Maruyama H: Chief Strategy Officer, Preferred Networks, Inc., Chiyoda, Tokyo 100-0004, Japan
[Login] to see author email addresses.
Journal Name
Energies
Volume
9
Issue
7
Article Number
E543
Year
2016
Publication Date
2016-07-14
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en9070543, Publication Type: Journal Article
Record Map
Published Article
LAPSE:2019.0051
This Record
External Link
doi:10.3390/en9070543
Publisher Version
Download
Meta
Record Statistics
Record Views
402
Version History
[v1] (Original Submission)
Jan 7, 2019
Verified by curator on
Jan 7, 2019
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2019.0051
Original Submitter
Calvin Tsay
Links to Related Works