Most transmission towers are constructed of galvanized steel for corrosion protection. After corrosion of galvanized steel progresses over time, the surface is repaired by painting. Once transmission towers are painted, they are repainted after a certain period due to paint deterioration. To give the order of priority to inspections and repairs, it is necessary to evaluate corrosion and paint deterioration, and to appropriately determine when to apply the first paint and when to repaint. In this article, the inspection and diagnosis technologies for transmission towers are introduced. In addition, the problems with evaluation methods of corrosion and paint deterioration through inspection and diagnosis are explained. For example, visual inspection of the painted surface is influenced by the subjectivity of the inspector, which may lead to variation in judgment. Considering these problems, improved evaluation methods have been developed. The paint deterioration evaluation methods using impedance measurement that can be used on-site for transmission towers as a quantitative method are also introduced in this article.

In recent years, a large scale of renewable energy (RE) such as photovoltaic (PV) power generation has been introduced to the power grid. As the output of RE fluctuates due to weather conditions, various difficulties occur in the operation of the power grid. One of them is grid congestion, in which transmission lines and transformers become overloaded. Thus the operation must be planned to avoid grid congestion based on the forecasted values of the RE output. However, the prediction of the RE output is usually accompanied by errors. Therefore, it is also important to operate the grid taking into account the uncertainty of the forecasted values. In addition, PV output has a strong correlation with solar radiation and it fluctuates depending on the amount of clouds in the atmosphere. Therefore, it is necessary to utilize meteorological forecast information. Recently, the Japan Meteorological Agency (JMA) has started to distribute the Meso-scale Ensemble Prediction System (MEPS) as weather forecast information that takes uncertainty into account. In this paper, we utilize the MEPS information to evaluate the diversity of grid operation by using optimal power flow considering the uncertainty.

With the accelerated introduction of renewable energy into the grid, the problem of power oscillations has emerged among inverter-based resources (IBRs). In conventional eigenvalue analysis, systems with constant grid frequency are assumed, and line dynamics are often omitted to avoid higher-order systems. In this study, however, a microgrid (MG) consisting of grid-forming (GFM) and grid-following (GFL) inverters is assumed. A comprehensive mathematical model, including transmission lines and inverter controls, is constructed, where the frequency of the MG varies from the nominal value due to the frequency droop characteristic of the GFM. Sensitivity analyses were conducted to identify parameters with high sensitivities to eigenvalues and to determine control parameters contributing to power oscillations. Additionally, the mechanisms by which these parameters are mutually interfered with were investigated. The effect of suppressing power fluctuations by preferentially adjusting these parameters was confirmed through both numerical analysis and experiments. These results are based on the assumption that the system consists of typical GFM and GFL. In other words, the preferential adjustment method of the identified parameters can be applied to general IBRs even if their controls are confidential, leading to improved grid stability.

Protection relays are used to ensure stable and efficient operation of the transformer. Protection relays detects the transformer fault and remove the fault point rapidly. However, there is a possibility that the transformer inrush current causes the maloperation of protection relay. Therefore, it is necessary to detect the inrush current instantaneously. This paper proposes a method for detecting transformer inrush current based on equivalent circuit parameter of transformer. This method estimates transformer equivalent circuit parameters from voltage and current waveforms using z-transform. The proposed method has the ability to detect inrush current faster and less computational complexity than conventional methods. To evaluate the theoretical principles of the proposed method, numerical simulation using MATLAB are performed. In addition, the proposed method is verified experimentally for a single-phase transformer.

In Japanese distribution lines, insulation-covered conductor is generally used. Flashover characteristics of an insulator with the insulation-covered conductor are different from that with a bare conductor. However, flashover characteristics of an insulator with the insulation-covered conductor have not been well studied. To improve the accuracy of a lightning outage rate calculation method of medium-voltage distribution lines, it is important to develop an accurate flashover model of an insulator with insulation-covered conductor. In this paper, first, we experimentally examine the flashover characteristic of an insulator with a insulation-covered conductor against a short-wave-tail lightning impulse voltage. Next, we propose a flashover model of the insulator taking into account the influence of the insulation-covered conductor. Finally, we evaluate the influence of the insulation-covered conductor on the flashover rate of the insulator using the proposed flashover model. As a results, we clarify that the flashover rate on distribution lines can be up to 50% lower by taking into account the influence of the insulation-covered conductor.