The introduction of photovoltaic (hereafter referred to as PV) systems is increasing. In winter, snow on PV reduces output in snowy regions. This paper reports on national and international research and development trends on the issue of snow cover on PV systems. Products of the Japan Meteorological Agency for short-time-ahead forecasting of snow cover will also be presented.

This paper proposes a local/remote control authority switching method in IEC 61850-based telecontrol systems. The proposed method enables control authority switching at arbitrary levels such as substations, substation sections, and individual transmission lines (individual bays). The testing results obtained from a prototype telecontrol system demonstrate the practicality of the control authority switching implemented based on the proposed method.

Inrush current phenomenon of a three-phase transformer is caused by mismatching polarities and absolute values of the initial magnetic flux induced by residual flux remnants in each phase core before the transformer is energized. Because the residual flux is the final value of magnetic flux transients that occur immediately after disconnection, the inrush current can be suppressed by considering the residual flux and controlling the timing of a circuit breaker. However, when a transformer is first energized in the field, the residual flux is unknown.

In this study, we apply lower frequency and lower voltage to a transformer system simulating a three-phase transformer and then integrates the transformer voltage by time to digitally calculate and capture the true residual flux. Next, when the transformers are energized, a phase angle control is applied to the timing of a switch to effectively suppress inrush current. As a result, the usefulness of the lower frequency and lower voltage application to suppress inrush current is indicated.

In japan, AC 100V class wiring system, electrical fires might be brought about by the tracking phenomena in the power plug. With the aim of establishing a method to protect the entire wiring system, the tracking phenomena that might occur between socket and power plug have been experimentally reproduced and the electrical aspects have been observed at the beginning of the tracking phenomena. In the early stage of the tracking phenomena, a spark discharge occurs at tiny gap between the blades of the power plug and moisture-absorbed dust. This spark discharge brings out a high frequency spike current near the crest of the source voltage. By continuously monitoring the current, it might be possible to detect the beginning of the tracking phenomena.

Solar photovoltaic (PV) systems are vital technology for producing sustainable and clean energy since they transform solar radiation into electricity without causing harm to the environment. However, despite the wide adoption of solar PV in electricity production, this system is still faced with efficiency problems due to the changing environmental conditions. Thus, the “Maximum Power Point Tracking (MPPT)” control problem stems from the need for a solar PV to always transmit the maximum available power to the load, irrespective of weather conditions. This paper comprehensively reviews various reinforcement learning (RL) techniques applied to solve the MPPT control problem of solar PV systems, especially under partial shading conditions. In addition, mathematical formulation and Markov Decision Process models for solving solar PV MPPT control problems are presented. Furthermore, the limitations of traditional RL methods and how function approximation methods are used to solve them are discussed. Finally, the challenges associated with applying the RL approach to solar PV MPPT control and the future research directions for solving these challenges are presented.