Recently, the capacities of on-board batteries and the outputs of quick chargers have been increasing. Increase in the battery capacity allows EV owners to charge more freely; however, charging may concentrate at a certain time such as on Friday afternoon, when EV owners charge in preparation for weekend's long trip. In the previous study, we evaluated the impact of quick charging on peak load at the system level and showed that a large peak occurs when charging behavior changes at a specific timing. To simulate the change in charging behavior, we set up the case that the charging threshold is raised to 60 percent on Friday afternoon. In this study, we assumed three patterns as trigger timing for charging shift: Tuesday, Wednesday, and Thursday, and two patterns as change in the charging threshold: 60 and 40 percent.

Through the analysis targeting Aichi Prefecture, we obtained following findings. (1) If the charging threshold is raised to 60 percent, the peak suppression effect remains for about two days. However, this measures cannot be used as a peak load suppression measures because the peak nearly equal to the reference case occurs when the charging threshold is raised to 60 percent. (2) If the charging threshold is raised to 40 percent, the peak suppression effect remains only about one day. Thus, only the case that the charging threshold is raised to 40 percent on Thursday afternoon shows a suppression effect on Friday's peak. (3) The economic value of the peak suppression effect of charging incentives is calculated as 31yen/kWh.

The increased adoption of renewable energy sources (RES) has resulted in various system instabilities. To comprehensively address these issues, we have developed a platform for analyzing future power systems. This platform takes into accounts the uncertainties associated with RES, allowing us to calculate power flow and evaluate grid stability under various realistic conditions. We describe a newly added functionality: clustering the multitude of generated conditions based on system stability and power flow. This enables us to extract representative conditions with distinct characteristics. And this report shows analysis results for the eastern Japanese grid in the future 2030.

Battery energy storage systems (BESS) are expected to be a key technology for achieving carbon neutrality by 2050. This paper presents the results and findings of a nearly 10-year field demonstration of a BESS with lithium-ion batteries starting in July 2013. During the first six years of the demonstration, the basic performance of the BESS was evaluated through normal operations such as load leveling. Subsequently, the BESS was intentionally reconfigured so that the degree of battery degradation in each part was partially different. The authors refer to this state of the BESS as “uneven degradation” in the paper. Since handling the uneven degradation would be an important issue for the BESS operation over long time or when reused batteries are used, the behavior of such unevenly degraded BESS was verified during the remaining demonstration period to understand its characteristics.

This paper proposes an algorithm for calculating currents and voltages during ground fault using the symmetric components, which has been conventionally used in power system fault analysis, with the equipment information constituting an independent micro grid system. The validity of the proposed algorithm is evaluated by PSCAD/EMTDC, and it was shown that the calculation accuracy of the proposed algorithm is sufficiently high. A method for calculating the ground compensation capacitor is also described.

This paper proposes a new method for unit commitment (UC) with Quantum Predator Prey Brain Storm Optimization (QPPBSO). The UC problems may be expressed as a mixed integer nonlinear programing problem in which binary variables mean on/off conditions of units and continuous ones imply their output. Recently, Evolutionary Computation (EC) has been applied to the UC problems due to the existence of indifferentiable cost functions such as large-scale steam turbine units, etc. However, there is still room for improvement in EC because the UC problems have high nonlinear features. This paper focuses on the integration of EC with Quantum Computing (QC) that is promising in power systems. Specifically, this paper combines QC with Predator Prey Brain Storm Optimization (PPBSO) of high performance EC. The effectiveness of the proposed method is demonstrated in the New England 39-node system.

To enhance frequency and active power control performance, this research proposes a decentralized approach for power grid frequency regulation support using grid-forming (GFM) converters. The proposed approach employs the Kharitonov method to design a robust proportional-integral (PI) controller in the outer control loop of a grid-connected GFM converter. The PI controller is made expressly to deal with the uncertainties and disruptions that are common in power grid operations. The PI controller successfully mitigates system risks by demonstrating strong stability through the application of the Kharitonov approach. Additionally, depending on the expected system performance, this work uses Bayesian optimization to choose the optimal parameters from the robust Kharitonov solutions family. In decentralized frequency regulation, the Kharitonov approach combined with Bayesian optimization presents a viable framework for robust-optimal control system parameters tuning. The efficacy of the proposed method in attaining robust optimal frequency regulation support in a power grid with a grid-connected GFM converter is demonstrated and the result is examined in the simulation environment.

In recent years, many supply-demand control or operation methods have been proposed considering large integration of renewable energy. AGC30 model is a standard model for supply-demand and frequency analysis developed by IEEJ and expected to be used to evaluate such supply-demand control or operation methods. Our research group has been enhancing the functions of the AGC30 model for long-term simulation, inputting external data, and accommodating the number and types of generators. The improved AGC30 model is proposed and the system frequency analysis simulation is conducted on the proposed model. The control command values for economic load dispatching control and those for load frequency control are dispatched based on the trade results of the electricity spot and balancing markets, respectively, in the model, although they were based on the fuel cost and the ramp rate in the original AGC30 model and other previous studies.

Increasing integration of inverter power sources into the electrical power system has raised concerns about a lack of system inertia, leading to potential disturbances in system frequency and speed during grid disruptions. Virtual synchronous generator (VSG) control is a promising solution for inertia support of the electrical power system. VSG's inertia enhances system stability by eliminating small and occasional disturbances. Also, the power variation in power electronic interface inverters caused by VSG control increases the stress on power semiconductor devices. This study focuses on the ability of VSG employing three-level topology to ensure system stability and the impact on the lifetime power semiconductors. The result shows that while VSG contributes more to system stability with lager inertia, it also reduces the lifetime of power semiconductors. However, the application of three-level topology was found to mitigate the reduction in the lifetime of power semiconductors.

The amount of electricity generated by photovoltaic (PV) systems can traditionally be calculated from solar radiation, but predictions can be significantly off due to snow accumulation on PV panels. Additionally, the output of wind farms (WF) varies with meteorological conditions, making predictions challenging. We have previously assumed the year 2040 and, focusing on days where PV output predictions were inaccurate, provided deterministic scenarios. By solving the Unit Commitment (UC) problem, we evaluated the impact of PV output prediction errors due to snow accumulation on power supply operation. In this study, we conducted Monte Carlo simulations considering the uncertainty of PV output and WF output for both 2021 and 2040. We analyzed the impact of PV output prediction errors due to snow accumulation on power supply operation. The simulation results revealed that improving the accuracy of PV output predictions is effective in reducing the risk of supply disruptions.

Microgrids (MGs) are emerging as a promising option to improve energy efficiency and resiliency against disasters. A MG usually supplies to a small area, in which supply-demand mismatches tend to be larger. In this paper, we propose an “EV and Energy” management system (E²MS) targeted for vanpool-type ridesharing MaaS. The proposed E2MS aims to integrate ridesharing EVs as mobile storage batteries with energy management in MG, addressing both the ridesharing vehicle routing problem and MGs' EMS. Numerical case studies demonstrate that EVs can transport ridesharing users while also performing energy time-shift and energy transfer between MGs.

The potential inside the winding rises due to potential oscillation when a lightning surge enters a transformer winding. In particular, depending on the surge waveform and the winding system, the potential distribution inside the winding varies. In this study, the insulating properties of three ester-based insulation oils, which are expected to be alternative mineral oils, when a standard lightning surge voltage with negative polarity is applied were investigated using the insulating constitution models (interturn and inter-section) that simplifies the insulating components of transformer winding. It was found that the PDIV and BDV differed slightly among the esters, although the discharge phenomena did not differ significantly among the esters.

When operating a Grid-Forming inverter under voltage control, overcurrent is likely to occur in the event of a short circuit at the near end, so an overcurrent suppression function is required. However, this function causes a problem of reduced stability. Therefore, a control method to improve transient stability while suppressing overcurrent was investigated. The control principle was explained, and the validity of the proposed control method was confirmed by simulation.

Electrolyzer connected by a self-commutation type converter that can regulate active power has been identified as alternative regulating resources to stabilize the power system which has a high penetration of renewable energy generation. The authors have been proposed frequency-watt control by a self-commutation type converter connected to a controllable load and have proposed a system for regulating active power. The parallelization system to decrease hydrogen supply cost and encourage higher penetration of electrolyzer requires efficiency control because of variation in cell degradation caused due to equipment operation and individual difference. This paper proposed control method considering variation of cell degradation between multiple electrolyzers participating in reserve market. Moreover, the daily simulation using actual data in two electrolyzers system which differs degree of cell degradation is perfomed to reveal controllability and economically effect of the system participating in reserve market.

For drones to fly autonomously or fly beyond visual line of sight, it is necessary to prepare coordinates for latitude, longitude, and altitude. However, current route design based on equipment drawings and measured one point at a time in manual flight has problems with accuracy and having high workload. In this research, we developed a technology to segment the aerial point cloud obtained by LiDAR into each element using deep learning, extract skeletal coordinates, and skeletal estimation.

In developed countries, the maintenance of ageing electrical power equipment is an important issue, and rational measures are being taken using asset management techniques. Rational maintenance and renewal planning based on risk analysis is required, and it is necessary to accurately estimate the failure rate according to the age of the equipment to be evaluated. One of the methods for understanding ageing characteristics is statistical analysis of equipment operating data such as failures and operating records. However, there are some points to consider when applying this method to equipment that can be operated for a long period of time, has a wide age distribution and is expected to have high reliability through preventive maintenance. Generally, failure statistical analysis involves linear regression, which assumes errors of equal variance in the observed data. However, this approach may have some problem when non-negligible errors are present. It is required regression analysis with appropriate weights and the estimation of appropriate prediction intervals. In this paper, the utilization of variance in binomial distributions and prediction interval estimation by failure occurrence simulation have been proposed, and the safety side estimation method for the failure rate is realized.

The bending test was conducted to establish a guideline for a transformer life, which uses the thermally upgraded Kraft paper (TUK) wrapped copper windings. Test samples were prepared with different degrees of deterioration by heat treatment. The breaking strength of the insulation paper shows that the average degree of polymerization, which corresponds to a load capacity of 1200kgf/cm² was approximately 300. However, it was shown that the TUK windings had a smaller load capacity than the regular Kraft windings in the DP range of 500 to 900. The tensile properties of the insulating paper were tested and considered that the decrease in breaking elongation not the strength causes the difference in load capacity between the two.

Electric power systems with increasing photovoltaic (PV) systems face concerns regarding degradation in frequency stability due to heightened output forecast errors. As a countermeasure, given the dynamic factors like demand, PV output, and meteorological elements, calculating the optimal reserve margin (ORM) becomes crucial for economic efficiency and resilience reinforcement. To ensure an efficient ORM, Artificial Intelligence (AI) is one of useful strategies used to analyze the combination of all the elements. However, AI is characterized by a black box problem, and to achieve transparency, AI needs to be transformed into explainable AI. To begin with, this paper analyzed all features importance using SHAP adopting a Gaussian process regression model. Then, relevant explanatory variables were selected to improve the prediction accuracy of the ORM. Finally, to verify the effectiveness, this paper planned day-ahead scheduling while securing the ORM determined by the proposed method. It executed detailed demand/supply and system frequency simulations as an operation. The proposed method decreased the risk posed by PV output forecast errors and shortage of reserve margin. Also, the maximum PV capacity increased from 96.2% to 166.2% while maintaining frequency stability.

Off-grid systems are an effective approach to power supply for areas that are distant from urban areas and away from major power sources. Many countries and regions have adopted off-grid systems for off-grid areas. On the other hand, there are not many studies that consider off-grid systems for existing grids in order to improve costs. For regions where the scale of electricity demand is becoming smaller in relation to the scale of transmission facilities, and cost-effectiveness is deteriorating, going off-grid is expected to have a significant impact on reducing the overall cost of the electricity system. The facilities to be introduced for off-grid operation are expected to be small renewable energy power sources and storage batteries, which can be added or removed in a short period of time, and thus the facility configuration is expected to be more flexible than the conventional transmission facilities. In this paper, a decision tree analysis method is used to evaluate the cost of the off-grid system considering the uncertainty of electricity demand, and a comparison with the conventional system is made. By giving multiple options for capital investment against the uncertainty of long-term fluctuations in electricity demand, the optimal type and capacity of facilities can be selected at each investment timing. The estimation results show that OG is more effective in dealing with fluctuations in electricity demand, especially in situations where electricity demand is expected to decrease.

In recent years, various control modes of grid-forming inverter (GFM) have been studied for transient stability and short-term frequency stability in power systems with large amount of renewable energy sources (RES). In this paper, we investigate the trade-off between the two stabilities caused by GFM to get a better knowledge of RES's effective control mode for each interconnection area. Numerical simulations newly reveal that applying GFM to receiving area deteriorates both stabilities in some fault scenarios due to its reactive power output when the terminal voltage drops slightly. Based on the results, a reactive power control strategy of GFM to address the trade-off issues is proposed and RES's effective control mode for each interconnection area is summarized.

This paper proposes a grid-islanding planning method for real-time optimization of grid configuration. Recently, the number of natural disasters and the needs for resilience enhancement technologies have been increasing. As one of these solutions, grid-islanding technology is attracting attention. For grid-islanding, it is desirable to expand the power supply area to reduce the outage damage as much as possible. However, if we expand the area too large, it is difficult to maintain its stability and there is a risk of re-outage. Therefore, we need to propose an appropriate grid-islanding planning method that minimizes the outage damage with maintaining the grid stability. In addition, if the optimal plan is searched by a brute force approach with its huge planning time, fast start of the first restoration and replanning according to dynamic situation changes can't be done. To realize the method, we combined mathematical planning and stability analysis and added a stability estimation function to efficiently search for the optimal plan avoiding the brute force approach. The method was tested with an outage scenario based on the typhoon case and its planning time was about 10 minutes.

This paper proposes implementing and remotely setting any protection control logical nodes for fault clearance and fault cascading prevention applications that require high speed, high accuracy, and noise immunity using the IEC 61850 process bus. The validity of the proposed method is verified through reference implementation and evaluation tests of a domestic protection and control function. The evaluation test results show that the protection control function implemented by the proposed method can perform remote setting changeover and switching based on IEC 61850 and that the required performance in terms of protection relay execution time and accuracy can be obtained. The study also provides key findings on the processing time needed to control on/blocked the trip signal outputs and protection control functions, as well as the amount of communication transmission. This study is expected to contribute to establishing technologies for maintaining power system stability and interconnection of systems in the future.

Most of the conventional technologies for open fault detection of bypass circuit have difficulty in detecting the open fault position of the bypass circuit of the PV module. The purpose of this research is to develop the detection technology of the open fault position in a string. Since an IR camera is used to detect faults, the reflection on the surface of PV modules have a significant effect on detection. Though the proposed detection technology is useful in a fine day. As for the reflection of fixed objects such as building or utility pole, the reflection effect can be removed. However, detection accuracy of fault position decreases by reflection of a lot of moving small clouds. In this paper, we show the technology to increase the detection accuracy by removing the disturbance caused by moving objects such as small clouds.

The Power and Energy Society Annual Conference was held at Osaka Metropolitan University on September 4-6, 2024. Total number of 383 papers were presented in 47 sessions. In addition to oral presentations and poster sessions, new events such as organized sessions and a joint symposium between Divisions B and C were introduced, contributing to the success of the conference. This report summarizes the conference.