This paper provides an overview of the current status and challenges of agrivoltaic systems in Japan. With limited land available for photovoltaic installation, agrivoltaic systems—which integrate solar power generation with agriculture by utilizing farmland—are expected to play a crucial role in achieving the 2030 renewable energy expansion target. The report discusses installation methods and strategies for optimizing light conditions for both crops and solar panels. It also explores next-generation solar technologies, such as perovskite and organic solar cells. Additionally, it highlights expectations for AI-driven smart agriculture, local energy management, and technological advancements to enhance the economic feasibility and sustainability of agrivoltaic systems.

The increase in integration of renewable energy sources and electricity system reform in Japan will increase generation uncertainty in power system. To handle the uncertainty and increase operation efficiency, the systems that optimize voltage profiles, such as the Optimized Performance Enabling Network for Volt/var(Q) (OPENVQ) proposed by the authors, are used. In this paper, an operation adjustment framework based on the look-ahead grid snapshot is proposed as an mechanism to adjust operations for the promotion of utilization the systems. As a specific application of the framework, we proposed a method to reduce bus line voltage deviations due to forecast errors. The evaluation was performed using data with errors between forecast demand and actual demand, and it was shown that the deviation avoidance rate was improved while maintaining the transmission loss reduction performance compared to the case where a uniform bus voltage margin was set for deviation avoidance. As another example of application of the framework, we proposed a method to reduce the amount of equipment operated for optimization. Compared to the method of periodically thinning out the equipment operation targets, it is shown that the equipment operation reduction rate is improved while maintaining the transmission loss reduction performance.

When a constraint violation occurs due to adding a new load to distribution systems, it can be resolved by reconfiguring the distribution systems by changing the states of switches and/or by minimum necessary investment. However, it is difficult to reconfigure the distribution system while satisfying the constraints made more severe by the new load installation. To find distribution system candidates that satisfy the severe constraints, this paper propose a multi-stage constrained multiobjective evolutionary algorithm (CMOEA). The proposed CMOEA dynamically changes the selection pressure at each search stage for constraints in normal and fault states, and it efficiently finds distribution system candidates that satisfy the severe constraints. Furthermore, the proposed CMOEA equals the number of sections and minimizes the number of remote/manual switch replacements as much as possible. The effectiveness of the proposed CMOEA is verified by case studies using a large-scale distribution system model equipped with many manual and remote switches.

To further promote renewable energy, the Feed-in-Premium (FIP) system was launched in April 2022 in Japan. Under the FIP scheme, renewable energy power producers and aggregators have faced new issues, which are imbalance risk due to the responsibility for planned amounts of power and market risk due to fluctuating power market prices. In order to address these issues, highly accurate renewable energy generation forecasting, imbalance reduction, and profitability enhancement technologies are required. However, comprehensive studies on the effectiveness of these necessary technologies through empirical evaluations using actual energy resources under the real environments have not been sufficiently conducted. In this paper, we conduct large-scale demonstration evaluation of the renewable energy generation forecasting technologies, the power market trading strategy technologies, and the battery control technologies using actual energy resources across the country, such as photovoltaic (PV) generators, wind power generators and storage batteries. Through the empirical evaluations, it is clarified that the evaluated technologies contribute to reducing imbalance risk and improving profitability with respect to imbalance risk and market risk, respectively.