The massive deployment of PV and wind, which provides decarbonized energy supply, bring about various additional challenges in operation of a power system. The congestion of transmission lines is an emerging issue which has been constraining new connections of renewable generation such as photovoltaic and wind. In Japan, the rules to connect and operate generation have been recently revised to accept new connection by managing the congestion by redispatch new renewable generation as well as existing thermal generation. Under this situation, production cost simulation including transmission constraints is a mandatory for planning and operation of a power system and for decision making of each renewable energy project. In this study, the authors modeled demand and supply condition and transmission to reproduce a power system operation of the Tohoku Area in FY2019 using power demand and supply analysis with DC-power flow and to review a system operation of the future system in 2030s.

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Converting fixed speed pumped hydro plants into variable speed plants contributes to keep power system frequency while storing extra variable renewable energy (VRE). This paper quantitatively evaluates impacts of such conversion on the decrease of curtailed VRE energy and CO₂ emission. The simulation model minimizes annual power system costs in 2030, considering accurate constraints of adjusting power and tie-line capacities across 9 areas in Japan. The results show that the variable speed conversion is effective in decreasing VRE curtailment particularly in an area where the capacity of storage battery is insufficient. The CO₂ emission decrease is offset, to some extent, by the increase of capacity factor of coal-fired plants that is brought by the power demand leveling effects of the variable speed conversion. When a carbon pricing of \10,000/CO₂-ton is introduced, the CO₂ emission significantly decreases though annual total cost rises. However, the variable speed conversion with carbon pricing reduces both CO₂ emission and the annual fuel cost.

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This study analyzed the reduction in electricity consumption due to home energy management systems (HEMS) using micro data from the fiscal year 2020 statistics of the Japanese government. Based on issues arising from previous studies on HEMS, we pointed out the need to correct for biases in household characteristics. From this perspective, a propensity score corresponding to the probability of adopting HEMS was calculated and a doubly robust estimator, which is considered to be one of the most accurate causal inference methods, was applied. As a result, it was estimated that the adoption of HEMS would reduce annual electricity consumption by 5.7%. On the other hand, the results were not statistically significant, suggesting problems related to the highly skewed characteristics of the households that adopted HEMS. Finally, we discussed expectations and challenges related to the analysis method, implications for the global warming mitigation approaches, and the significance of the statistics data.

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The study was conducted to assess quantitative clarification of energy-saving behaviors of high school students in China. To clarify mechanisms underlying the behaviors we applied statistical analysis to responses from questionnaires with 45 multiple-choice questions administered to over 500 students. Survey questions assessed eight factors based on two-phase model. Three personal attributes included environmental education, environmental knowledge, and future behavior. Respondents were then divided into two groups based on their scores. We proposed three hypotheses. Our model explains energy-saving behavior. The path of factorial linkages affects behaviors significantly. Individual attributes significantly affect energy-saving behavior. As a result, students’ energy-saving behaviors were explained using the model. Path analysis also yielded significant positive correlation results. These results suggested that goal intention, feasibility evaluation, and coping effectiveness perception affected behavioral intentions. The t-test results indicated higher mean values for the good group than for the normal group in the three individual attribute. These results can enable teachers to incorporate information for effective energy education.

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This paper provides the study including multi-regional modeling of energy systems of Japan for optimization to find solutions for both climate change issue and financial incentives. For that, the modeling with OSeMOSYS and its interface MoManI, OSS-based applications, and open data of electric power supply and demand are provided, which allows to share results and solutions beyond companies. In the study, parameters to define rate of ramp-up/down of electric power production by technology, constraints to set upper limit thereof, parameters to define lower limit of production by technology and constraints to limit electric power production thereunder are additionally implemented in the model of Japan to fit actual power-grid trend. This paper also provides multi-regional modeling of energy systems of Japan including additional model feature to define energy trading among regions. By setting these parameters on MoManI to represent characteristics calculated from past actual power supply data, the output of cost-minimizing optimization shows similar trend to actual one. This result shows that it is possible to build a multi-regional model of energy systems of Japan using OSeMOSYS and MoManI, which are basically European-oriented tool.

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