Best–Worst Scaling (BWS) was applied to assess Japanese consumer preferences for battery electric vehicles (BEVs). Although BEVs are still unfamiliar to most of the Japanese consumers, BWS has advantages in obtaining rich information on preferences by identifying “best” and “worst” options. An online questionnaire survey was conducted and 448 samples of Japanese consumers who drove regularly were collected. BWS object case and multi-profile case were both applied in this study. Results of BWS object case revealed that purchase price was the most important factor. In addition, operation cost and driving range were important factors. Conversely, the reduction of carbon dioxide and air pollutants were less important factors. BWS multi-profile case revealed that different scenarios for operation cost, yen/100 km and annual saving, were both valued properly by respondents. Random parameter logit estimates of multi-profile case demonstrated the preference heterogeneity of every attributes of BEVs. The results suggest that consumer preferences and purchasing behaviors are much diverse. More public programs and companies’ efforts to reduce the vehicle price and to inform the environmental advantages adequately are necessary to promote the diffusion of BEVs in Japan.
Operation scheduling problem is one of the most important issues to efficiently manage the electric power supply and demand in power grids, especially in microgrids. This problem is formulated as a complicated optimization problem having multiple optimization variables. In the problem framework, we need to set an appropriate reserve power against the uncertainty in forecasted values of the electric power demand and the output of variable renewable energy-based generation systems. This paper presents a problem framework and its solution method to make an aggregated schedule of operation of controllable components in microgrids and electricity trade with electricity market. Traditionally, the reserve power in the operation scheduling problems is set to compensate a certain variation of net loads, which are calculated by the sum of forecasted values of the demand and the output of variable renewable energy-based generation systems. However, it is desirable to set the reserve power flexibly considering distribution characteristics of forecast errors of the net load. In the proposed problem framework, the necessary operating reserve is automatically calculated by reflecting the uncertainty-originated risk to the objective function. Through numerical simulations and discussions on their results, usefulness of the authors’ proposal is verified.
We propose a method for personalizing neighborhood comparisons towards improving energy efficiency services. The method uses a regression model considering attributes of households, whose prediction can be regarded as electricity consumption for similar neighborhoods. The method is implemented in a field experiment based on a smartphone-based service. By evaluating the validity of the method, it is implied that the proposed method can personalize the neighborhood comparison to provide information in a manner that improves satisfaction in the households. This paper also demonstrates the practical utility of the proposed method.
The massive deployment of PV and wind, which provides decarbonized energy supply, bring about various additional
challenges. Among the challenges, the reduction of operational capacity of synchronous machines in a power system induce
reduced inertial of a power system. With the reduced system inertia, the system frequency deviates faster and more largely
and the deviation sometimes results in instability of a power system operation. In this paper, based on the various scenarios
including PV penetration, load dispatch operation types, we analyze the system inertia of the future Japanese power system
by identifying operational capacity of synchronous generator machines through a demand and supply simulation of the
Japanese power system, to find the characteristics of the reduction of the system inertial under different scenarios and
The Government of Japan and many other governments seek achieving carbon neutrality to avoid dangerous climate change.
Hydrogen and synthetic gas (methanation) are focused as zero-emission options in gaseous fuel. Methanation is a process for
synthesizing methane produced by zero emission hydrogen and CO2 captured from flue gases, but particularly methanation has
not been analyzed enough in terms of the conditions of economic feasibility and economical potentials. This study evaluated
contributions of methanation as well as hydrogen for global carbon neutrality, using a global energy systems model. According
to the analysis, methanation is one of the important roles for the deep emission reductions toward carbon neutrality in the world.
Amounts of global exports and imports of the synthetic gas (methanation) will be almost same as those of hydrogen in 2050.
Particularly in Japan, the role of methanation option will be big among the world nations. Without the methanation option, the
global emission reduction costs for achieving 2 ℃ target will increase by about 14 billion US$/yr in 2050.