System design to reduce disaster risks by installing distributed power resources

Akane Uemichi*, Masaaki Yagi, Ryo Oikawa, Yudai Yamasaki, Shigehiko Kaneko

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Subsidy and social systems should be designed to effectively promote, for example, the introduction of a mechanical system. For an effective subsidy distribution, developing evidence-based decision-making methodologies is essential. We developed a tool that minimizes an objective function includes economic costs, environmental cost, and disaster risk to determine the amount of energy distributed by the equipment when installing in hospitals against disasters. Open data available on the Internet are used as simulation values herein. This simulation model optimizes six design values using a genetic algorithm based on the values (business site area, demand for heat and electricity, and maximum allowable loss) input by customers for their construction and visualizes the total cost. The tool allows to quantitatively assess the changes in the initial and running costs owing to equipment installation and the avoidable losses related to CO 2 emission reductions and disaster risks. In addition, the net present value (NPV) can be calculated using the obtained values for initial and running costs, thereby allowing to clearly estimate the return on investments after equipment installation. The opportunity profit can be calculated based on the difference between the NPV after 15 years assuming no risk and with disaster risks. A method to set this opportunity profit as a calculated subsidy amount is proposed herein. Decision support can be provided via these simulations to the customers and government subsidy system design engineers.

Original languageEnglish
Pages (from-to)49-56
Number of pages8
JournalMultiscale and Multidisciplinary Modeling, Experiments and Design
Issue number1
Publication statusPublished - 2018 Mar 1
Externally publishedYes


  • Disaster risks
  • Distributed power generation
  • Energy system
  • Evidenced-based decision-making
  • Optimization

ASJC Scopus subject areas

  • Materials Science(all)
  • Mechanics of Materials
  • Applied Mathematics


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