This paper introduces the integration method of system dynamics into unit commitment (UC) by defining constraints of the Rate of Change of Frequency (RoCoF), Nadir, and quasi-steady state based on the swing equations. It also suggests that forecasting errors are directly related to the required reserve power and advocates for the advancement of error estimation techniques.

Recently, with the growing problem of global warming and the depletion of fossil resources, government's attention has been focused on renewable energy sources. Wind power, a major renewable energy source, is underutilized in Japan due to its unstable output. So high accurate short-term wind speed prediction methods are the key to the promotion and popularization of wind power generation. Improving the accuracy of wind speed prediction can effectively improve the stability and economy of wind turbines. In this paper, the authors propose a wind speed prediction method by using neural network called LSTM (Long Short-Term Memory) and carry out the accuracy verification by case study. In addition, the authors propose two improved prediction methods to solve the problems of insufficient learning data, poor prediction accuracy due to the wide range of data dispersion, and poor prediction accuracy at the peak. The effectiveness of the improved methods is verified by case study. And the accuracy of all the methods was verified by using meteorological data from Akita and Hokkaido in Japan.

Electric buses are introduced toward achieving carbon neutrality by 2050, and there is a movement to utilize their storage batteries. On the other hand, the electric power system, where distributed energy resources are rapidly spreading, is becoming increasingly complex, and the impact of charging by electric buses on power system is an issue. In this study, we propose an optimization method for electric bus charge/discharge schedule that considers sector coupling between transportation system and power system. Then, we evaluate the effectiveness of the proposed method from the viewpoints of both the distribution system operator and the electric bus operator by performing power flow calculations using a distribution system model. The results show that the proposed method can contribute to power demand shifting and smoothing power flow in distribution network by charging and discharging, and that multiple evaluation indices, e.g. peak-cutting of power flow, line occupation rate, distribution loss, reverse power flow utilization rate, renewable energy rate and CO₂ emissions, are improved compared to the conventional charging scheduling method.

One of the models for rotating machines such as synchronous machines and induction machines is the phase-domain model, which is characterized by formulating the circuit equations of the rotating machine in the phase domain and solving them simultaneously with the external system to which the rotating machine is connected. Although this model has excellent numerical stability and calculation accuracy, it requires refactorization of the subcircuit including the rotating machine at each calculation time step, which degrades the calculation speed. This paper describes the results of an attempt to improve the calculation speed when using the phase-domain model by using partial refactorization, which makes the refactorization process more efficient.

The paper presents a new fault location method with travelling waves (surge) on distribution line to restore power supply as soon as possible. Proposed method builds a diagram which describes transmission and reflection of travelling waves over the lines and generates pseudo waves based on the diagram. The least error condition including fault point is estimated by numerical analysis comparing measured waves and pseudo waves. The method is robust and accurate without line parameters such as the speed of travelling wave. And the method can be applicable for multiple faults and branch line faults without any additional modification.

Hybrid CPV/PV modules can achieve higher conversion efficiency than conventional concentrator photovoltaic (CPV) modules by utilizing the diffuse solar irradiance component. We fabricated a hybrid CPV/PV module consisting of a crystalline silicon (c-Si) solar cell stacked with LCPV with a geometric concentration factor of 16x and analyzed its power generation characteristics based on a 4-year long-term field test. The results showed that our hybrid CPV/PV module achieved a conversion efficiency of 17-35%, surpassing that of tracking-type flat-plate c-Si solar cells. The reason for this is that the Si cell can assist under conditions with a small fraction of direct solar irradiation. Under clear sky conditions, the CPV component provided about 80% of the power generated by the hybrid CPV/PV module. Although the conversion efficiency decreased as diffuse solar irradiance became dominant, the rate of decrease was smaller than that of the conventional CPV modules. The field tests were conducted under a variety of weather conditions except rainy weather, and the results obtained suggest the possibility of deploying hybrid CPV/PV modules.