System LCOE of variable renewable energies: a case study of Japan’s decarbonized power sector in 2050

• DOI: 10.1007/s11625-021-00914-1
• Publication Date: 2021-02-05T15:19:59Z
• Authors: Yuhji Matsuo; Ryoichi Komiyama
• Keywords: Variable renewable energy; Dispatchable generation

Decarbonization of the power sector is an important milestone for the achievement of ambitious GHG reduction targets. Given the intrinsic shortcomings of nuclear power and zero-emission thermal power generation, such as large investment costs and public acceptance, along with the locational limits of dispatchable renewables such as hydro and geothermal, variable renewable energies (VRE) should play an important role to decarbonize the power sector. Very high penetration of VRE, however, would require additional “integration” costs related to grid expansion, power curtailment, and power storage. In this article, focusing on a decarbonized power system in Japan in 2050, we calculated two metrics that capture the non-linear nature of the integration cost related to high VRE penetration: Average system LCOE (levelized cost of electricity) and relative marginal system LCOE. The former metric allocates the integration cost to each power source, which is divided by the adjusted power output, while the latter measures the changes in the total system cost with the substitution of two types of power sources. The results show that both the average and the relative marginal system LCOE of VRE will rise when the share of VRE rises, but the latter will rise much more sharply than the former. This suggests that the anticipated challenges for achieving very high shares of VRE may still exist even if the cost of VRE may decline rapidly in the future. As the relative marginal system LCOE of VRE can be heavily dependent on meteorological conditions, it is essential to use multi-annual data to estimate it. The metric relative marginal system LCOE can be used for the soft-linking of a detailed power sector model to an integrated assessment model, which can contribute to a better quantitative analysis of climate policies.