Electricity Self-Sufficient Community Clustering for Energy Resilience

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

doi:10.3390/en9070543

Abstract

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.

Highlights

While electricity is a fundamental requirement for sustainable urban development, electricity supply can be interrupted by natural or man-made disasters, including earthquakes and cyber-attacks
Implementation of decentralized systems would be important in Asian countries, where populations are increasing rapidly, while natural disasters are simultaneously increasing in frequency and intensity owing to climate change
The paper is organized as follows: Section 2 describes situations relating to electric vehicle (EV) and PV in Japan; Section 3 explains the clustering algorithms used; Section 4 empirically compares these algorithms, and clarifies advantages and disadvantages of each algorithm in terms of the sharing community clustering; and, Section 5 contains discussions on the analysis results, and our conclusions

Summary

Introduction

While electricity is a fundamental requirement for sustainable urban development, electricity supply can be interrupted by natural or man-made disasters, including earthquakes and cyber-attacks. On the other hand, regarding electricity storage, use of electric vehicle (EV) batteries has extensively been discussed (e.g., [7,8,9]) and reviewed by [10]. Yamagata and Seya [12] demonstrated that a V2C system provides sufficient electricity for households in many of the local communities in Yokohama, Japan. They showed a significant regional imbalance, with the storage capacity (i.e., the number of EVs) being insufficient in some regions and excessive in others. The paper is organized as follows: Section 2 describes situations relating to EV and PV in Japan; Section 3 explains the clustering algorithms used; Section 4 empirically compares these algorithms, and clarifies advantages and disadvantages of each algorithm in terms of the sharing community clustering; and, Section 5 contains discussions on the analysis results, and our conclusions

EV and PV in Japan

Meta-Heuristic Optimization

Calculation of the Storage Capacity

Calculation of the Potential PV Electricity Supply in Month m

Calculation of the Electricity Demand in Month m