Abstract
In 2017, the Mistry of Health, Labor, and Welfare in Japan added a requirement for domestic disaster base hospitals to install electric power generation equipment with a generation capacity at least 60% of usual demand for securing business continuity. In this study, we developed a multi-objective optimization tool for assisting the determination of the capacity of distributed generation equipment and contract plans considering energy-resiliency after a disaster. The selected objective functions are a total cost representing economy and environment, and an expected value of power shortage ratio after the catastrophe representing energy-resiliency. As a result, our developed tool could obtain the Pareto-optimal solutions for various size hospitals on the parameter plane of the two objective functions. As well as total costs, for all optimal solutions, the expected value of power shortage ratio under disaster situation resulted in less than 40% suggesting that the national requirement standard is satisfied. Then, the cluster analysis was carried out to grasp the tendency of optimal solutions. From the analysis of average value for each cluster, it is shown that the optimal introductory capacities of gas engine generators and storage batteries couple through the outage probabilities of gas supply. Furthermore, the optimal capacity of photovoltaic is much larger than the one assumed to install on the estimated rooftop area of the hospital building, which suggests that hospital can take an option to introduce more photovoltaics to an adjacent area if possible.
| Original language | English |
|---|---|
| Pages (from-to) | 6538-6543 |
| Number of pages | 6 |
| Journal | Energy Procedia |
| Volume | 158 |
| DOIs | |
| Publication status | Published - 2019 Jan 1 |
| Externally published | Yes |
| Event | 10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China Duration: 2018 Aug 22 → 2018 Aug 25 |
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Keywords
- Business continuity
- Distributed power generation
- Energy resiliency
- Multi-objective optimization
ASJC Scopus subject areas
- Energy(all)
Cite this
Multi-objective optimization to determine installation capacity of distributed power generation equipment considering energy-resilience against disasters. / Uemichi, Akane; Yagi, Masaaki; Oikawa, Ryo; Yamasaki, Yudai; Kaneko, Shigehiko.
In: Energy Procedia, Vol. 158, 01.01.2019, p. 6538-6543.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - Multi-objective optimization to determine installation capacity of distributed power generation equipment considering energy-resilience against disasters
AU - Uemichi, Akane
AU - Yagi, Masaaki
AU - Oikawa, Ryo
AU - Yamasaki, Yudai
AU - Kaneko, Shigehiko
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In 2017, the Mistry of Health, Labor, and Welfare in Japan added a requirement for domestic disaster base hospitals to install electric power generation equipment with a generation capacity at least 60% of usual demand for securing business continuity. In this study, we developed a multi-objective optimization tool for assisting the determination of the capacity of distributed generation equipment and contract plans considering energy-resiliency after a disaster. The selected objective functions are a total cost representing economy and environment, and an expected value of power shortage ratio after the catastrophe representing energy-resiliency. As a result, our developed tool could obtain the Pareto-optimal solutions for various size hospitals on the parameter plane of the two objective functions. As well as total costs, for all optimal solutions, the expected value of power shortage ratio under disaster situation resulted in less than 40% suggesting that the national requirement standard is satisfied. Then, the cluster analysis was carried out to grasp the tendency of optimal solutions. From the analysis of average value for each cluster, it is shown that the optimal introductory capacities of gas engine generators and storage batteries couple through the outage probabilities of gas supply. Furthermore, the optimal capacity of photovoltaic is much larger than the one assumed to install on the estimated rooftop area of the hospital building, which suggests that hospital can take an option to introduce more photovoltaics to an adjacent area if possible.
AB - In 2017, the Mistry of Health, Labor, and Welfare in Japan added a requirement for domestic disaster base hospitals to install electric power generation equipment with a generation capacity at least 60% of usual demand for securing business continuity. In this study, we developed a multi-objective optimization tool for assisting the determination of the capacity of distributed generation equipment and contract plans considering energy-resiliency after a disaster. The selected objective functions are a total cost representing economy and environment, and an expected value of power shortage ratio after the catastrophe representing energy-resiliency. As a result, our developed tool could obtain the Pareto-optimal solutions for various size hospitals on the parameter plane of the two objective functions. As well as total costs, for all optimal solutions, the expected value of power shortage ratio under disaster situation resulted in less than 40% suggesting that the national requirement standard is satisfied. Then, the cluster analysis was carried out to grasp the tendency of optimal solutions. From the analysis of average value for each cluster, it is shown that the optimal introductory capacities of gas engine generators and storage batteries couple through the outage probabilities of gas supply. Furthermore, the optimal capacity of photovoltaic is much larger than the one assumed to install on the estimated rooftop area of the hospital building, which suggests that hospital can take an option to introduce more photovoltaics to an adjacent area if possible.
KW - Business continuity
KW - Distributed power generation
KW - Energy resiliency
KW - Multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=85063905529&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063905529&partnerID=8YFLogxK
U2 - 10.1016/j.egypro.2019.01.104
DO - 10.1016/j.egypro.2019.01.104
M3 - Conference article
VL - 158
SP - 6538
EP - 6543
JO - Energy Procedia
JF - Energy Procedia
SN - 1876-6102
ER -