To realize a stable and economical supply of electric power, meteorological information is actively utilized in the operation and planning of electric power systems. This paper introduces the current status of meteorological information and how it is utilized in the planning and operation of power systems. Meteorological information is being utilized at a higher temporal and spatial granularity due to the massive introduction of renewable energy, and there are high expectations for future advanced utilization, such as the use of ensemble forecasting.

For improving the profitability of electricity retailers, it is important to reduce the penalty cost for the imbalance between a day-ahead planned electricity demand and the actual electricity demand on the day. To reduce the imbalance, a Battery Energy Storage System (BESS) installed in customers of electricity retailer can be used, because BESS may not be used so frequently for primary purposes of installation. In consideration that the available BESS capacity is smaller than the imbalance, simply predicting whether the imbalance is positive or negative instead of the amount of imbalance can be useful for using BESS of such a limited capacity. The forecast error of Photovoltaic (PV) power output can be major reason of the imbalance when a certain amount of PV is included in power supply plan of retailer. Therefore, this study investigates the relation between the actual error of PV power output forecast and the change from a day-ahead forecasted value to the forecasted value of later initial time. Then, this study evaluates the usefulness of BESS operation based on the direction of change in forecasted value for reducing the imbalance.

The photovoltaic (PV) power output might be frequently curtailed to maintain electricity supply-demand balance in future power systems. In our previous study, we proposed a new method for updating the battery energy storage system (BESS) charge/discharge and the generator unit commitment (UC) schedules based on the forecasted and actual PV power outputs. The forecast dataset was updated every three hours (8 times a day). Although the simulation results showed that the proposed method could reduce the supply-demand imbalances, it was not clear whether the forecasted or actual values made contributions. Therefore, in this study, we propose and evaluate a real-time scheduling and operation method using the forecasted and actual PV power outputs assuming that the forecasted dataset is updated only once a day. Numerical simulations of supply-demand operations are conducted on the power system model of the Kanto area of Japan for one year. The results show that the previous study method has a slight advantage over proposed method in terms of curtailed PV energy and operational cost of thermal generators reduction, but the difference is very small, indicating that the contribution of the actual PV power outputs is greater than that of the forecasted PV power outputs.

For the carbon neutral society, installation of renewable energies is increasing. In particular, expectations for Wind Turbine Generator Systems (WTGSs) have raised in Japan. However, since output of the WTGSs fluctuates, it may cause difficulty in the operation of the electric power system, such as reduction of frequency stability by the imbalance of power supply-demand. As a measure, transmission and distribution companies introduced grid codes for WTGSs. Therefore, Energy Storage System (ESS) is usually used to satisfy the grid code. However, because the ESS is expensive, kW and kWh capacity should be small. Therefore, this study proposes the constant control during the designated time by using forecast to reduce the ESS capacity requirement while satisfying the grid code. In addition, as measures for the forecast error, kW and kWh adjustment considering renewal are proposed too. The result by simulation showed that the proposed method can reduce 36% of ESS capacity compared to the conventional method.

Recently, there is a movement aimed at realizing distributed energy systems, especially photovoltaic power generation (PV) is expected in Japan, and it is expected that the number of interconnections of PV will increase in the future. Insolation is easily affected by the weather and the supply of electricity becomes unstable. Therefore, it is important to forecast the amount of insolation. In this study, the main purpose of this research is to develop a highly accurate and practical method for insolation forecasting, based on satellite image data provided by the Himawari-8 satellite and past actual measurement data released by the Japan Meteorological Agency. In this paper, the authors propose an amount of insolation forecasting method by using neural network and carry out the accuracy verification by case study. In addition, the authors also use the ConvLSTM (Convolutional Long Short-Term Memory) model to forecast the cloud imageries for the insolation forecasting. In order to verify the usefulness of the proposed method, the forecast results by the proposed method were compared with the forecast results without using satellite image data and the forecast results with latest satellite image data. In conclusion, by using the satellite image data and forecasting the cloud imageries, it was possible to grasp the characteristics of the insolation, prevent erroneous prediction, and improve the prediction accuracy.

A review of photovoltaic (PV) power output forecasting technology is presented based on the latest information in the literature. In addition to short-term ahead prediction and day ahead prediction techniques using numerical weather prediction models, the challenges of forecasting techniques caused by factors other than weather forecasting (dust and snow) are discussed. Uncertainties in forecasts using ensemble forecasting are also discussed. Case studies are presented on the impact assessment of various solar power forecasts. It also introduces the available data for climate change adaptation in anticipation of future climate change. In addition, the trends of related projects to improve forecasting technology in Japan and abroad are described. The challenges of PV output forecasting technology are itemized.

As the introduction of renewable energy sources (RESs) increases, there is a concern that the inertia and synchronizing power of power systems will decrease and the system stability will deteriorate. In particular, if a large-scale wind farm is disconnected from the grid in compliance with the grid code due to a grid fault, the entire grid may become unstable. Under such a background, this paper proposes a storage battery system which has the functions of reactive power control and virtual synchronous generator (VSG) control as well as control of system frequency fluctuations due to fluctuating output from the wind farm. In addition, a new control method is also implemented in the battery control system in order to improve the total charge/discharge efficiency of the battery by suppressing unnecessary charging and discharging. The proposed battery system is composed of multiple batteries installed at different locations and they are controlled coordinately. Effectiveness of the battery system for system stabilization is verified by simulation analyses.

Microgrid (MG) would be a promising option to improve energy efficiency and resiliency against disasters. However, one of the biggest motivations for deploying MGs on a commercial scale is to bring stable economic benefits to MG operators and end users by reducing operating costs. This paper shows that shared electric vehicles (EVs) in the MaaS society can bring economic benefits to MGs by using them as mobile storage batteries. First, this paper proposes an “EV and Energy” Management system (E²MS), which realizes efficient energy supply with using shared EVs as mobile storage batteries while satisfying EV-sharing requests. Numerical case studies show that the proposed E²MS enables wide-area coordination among MGs and EVs and mobile energy storage function of EVs would have a superior economical potential over stationary storage batteries in MG application.

Liquid insulators have excellent cooling and insulation performance, but impurities and contaminants in the liquid or dissolved gases and moisture are known to have a significant influence on insulation performance. In this paper, using the Super High Frequency-wideband Partial Discharge (PD) current Pulse Waveform measurement system, “SHF_PDPW system”, that the authors have developed and applied to PD measurement in SF₆ gas so far, PD current waveforms in mineral oil were investigated in detail. Differences in PD current waveforms due to degassing treatment condition of the mineral oil and polarity effect of applied voltage could be clearly clarified. These differences cannot be observed by ordinary oscilloscopes with analog bandwidths around 1GHz, and are important findings to understand PD phenomena, which were first observed by the super-wideband measurements.

DC magnetic fields under the Hida-Shinano 200kV DC overhead transmission line were assessed by measurements. The DC magnetic fields observed under the DC overhead transmission line are a superposition of the geomagnetic field and that generated by the DC line current. In this study, the DC magnetic fields generated by the transmission line were obtained by a vector subtraction of the geomagnetic field from the total DC magnetic field. The measured geomagnetic field was 47.1μT and the assessed magnetic fields from the line with a current of 2250A were from 3.8μT to 8.3μT depending on the operating condition of the DC transmission line.