where effective decision making is done even under extreme situations, and
effective decontamination actions. The value of MTBD can be assessed more
precisely by geologically-based study. Price elasticity, which determines the
resourcefulness of the system, will be lowered aggressive introduction of emergency power source although cost-effectiveness of their installation should be
considered, of course. Assessment on these policies through energy model analysis
will give the potential contributions and benefits of them. Concerning scenarios
planning and model refinement, the design of systems has a key role. Social
activities in today’s world are supported by highly complex and interdependent
system, and so, risks surrounding us are very systemic. Fukushima nuclear power
plant accident is such a kind of risk. Therefore, targeted system should be comprehensive enough to consider their inter-relations although the system considered
in this paper is limited within electricity supply system. In addition, more kinds of
risks should be considered because our challenges to be dealt with now in this
world are not only nuclear usage.
Finally, to address above requirements, the most important seems to learn
effectively from accidents and update our social scientific knowledge base. The
implement of what we have learned into energy model makes it more sophisticated
and the model will tell us how to design resilient systems.
Acknowledgements This work was supported by JST Strategic Basic Research
Programs RISTEX, Resilience Analysis for Social Safety Policy.
References
1. M. Bruneau et al., A framework to quantitatively assess and enhance the seismic resilience of
communities. Earthquake Spectra 19, 733–752 (2003)
2. R. Komiyama, Y. Fujii, Long-term scenario analysis of nuclear energy and variable renewables
in Japan’s power generation mix considering flexible power resources. Energy Policy 83,
169–184 (2015)
3. International Energy Agency (IEA), World Energy Outlook 2013 (OECD, Paris, France, 2013)
4. H. Matsuzawa, R. Komiyama, Y. Fujii, Analysis of energy system resilience to disaster in
Kanto Region using stochastic programming. Proc. Conf. Energy Econ. Environ. 34, 223–226
(2015)
5. Y. Uchiyama, Y. Hatano, K. Okajima, Social Risk in Energy System (CORONA Publishing
Co., Ltd., 2012), pp. 70–74
6. Z.L. Chen, W.B. Powell, Convergent cutting plane and partial-sampling algorithm for
multistage stochastic linear programs with recourse. J. Optim. Theory Appl. 102, 497–524
(1999)
Evaluation of Optimal Power Generation Mix …
301
effective decontamination actions. The value of MTBD can be assessed more
precisely by geologically-based study. Price elasticity, which determines the
resourcefulness of the system, will be lowered aggressive introduction of emergency power source although cost-effectiveness of their installation should be
considered, of course. Assessment on these policies through energy model analysis
will give the potential contributions and benefits of them. Concerning scenarios
planning and model refinement, the design of systems has a key role. Social
activities in today’s world are supported by highly complex and interdependent
system, and so, risks surrounding us are very systemic. Fukushima nuclear power
plant accident is such a kind of risk. Therefore, targeted system should be comprehensive enough to consider their inter-relations although the system considered
in this paper is limited within electricity supply system. In addition, more kinds of
risks should be considered because our challenges to be dealt with now in this
world are not only nuclear usage.
Finally, to address above requirements, the most important seems to learn
effectively from accidents and update our social scientific knowledge base. The
implement of what we have learned into energy model makes it more sophisticated
and the model will tell us how to design resilient systems.
Acknowledgements This work was supported by JST Strategic Basic Research
Programs RISTEX, Resilience Analysis for Social Safety Policy.
References
1. M. Bruneau et al., A framework to quantitatively assess and enhance the seismic resilience of
communities. Earthquake Spectra 19, 733–752 (2003)
2. R. Komiyama, Y. Fujii, Long-term scenario analysis of nuclear energy and variable renewables
in Japan’s power generation mix considering flexible power resources. Energy Policy 83,
169–184 (2015)
3. International Energy Agency (IEA), World Energy Outlook 2013 (OECD, Paris, France, 2013)
4. H. Matsuzawa, R. Komiyama, Y. Fujii, Analysis of energy system resilience to disaster in
Kanto Region using stochastic programming. Proc. Conf. Energy Econ. Environ. 34, 223–226
(2015)
5. Y. Uchiyama, Y. Hatano, K. Okajima, Social Risk in Energy System (CORONA Publishing
Co., Ltd., 2012), pp. 70–74
6. Z.L. Chen, W.B. Powell, Convergent cutting plane and partial-sampling algorithm for
multistage stochastic linear programs with recourse. J. Optim. Theory Appl. 102, 497–524
(1999)
Evaluation of Optimal Power Generation Mix …
301