Technical Papers
Apr 25, 2016

Optimal Integration of Variable Renewables in Electric Power Systems of Japan

Publication: Journal of Energy Engineering
Volume 143, Issue 3

Abstract

After the Fukushima nuclear accident, nuclear policy has become uncertain in Japan, and alternatively, variable renewable (VR) energy, such as wind and photovoltaic (PV), is highlighted for addressing climate change and energy security issues. This paper attempts to assess the massive integration of VR into Japan’s long-term power-generation mix, employing the dynamic multiregional optimal power-generation mix model, which is a large-scale linear programming model including 200 million constraints. The feature of the model enables explicit consideration of the actual variability of wind and PV outputs in a 10-min temporal resolution and to analyze the impact of those variabilities on long-term expansion planning of power plants. Simulation results show that both nuclear decommission and carbon regulation policies make VR economically justified and encourage its expansion in Japan’s long-term power-generation mix. When nuclear is totally decommissioned and CO2 is mitigated by 50% from 2010 levels by 2050, the power-generation cost in 2050 shows a doubling compared with that in the scenario where nuclear power is not decommissioned and carbon regulation is not assigned.

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Acknowledgments

This work was supported by JSPS KAKENHI Grant Number 25870176.

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Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 143Issue 3June 2017

History

Received: Jun 30, 2015
Accepted: Feb 1, 2016
Published online: Apr 25, 2016
Discussion open until: Sep 25, 2016
Published in print: Jun 1, 2017

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Authors

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Ryoichi Komiyama [email protected]
Associate Professor, Resilience Engineering Research Center, Univ. of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113 8656, Japan (corresponding author). E-mail: [email protected]
Yasumasa Fujii
Professor, Dept. of Nuclear Engineering and Management, Univ. of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113 8656, Japan.

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