In recent years, attention has been focused on technologies and efforts to reduce global warming and environmental impact, as well as sustainability. There is also a growing need for environmentally friendly, renewable electrical insulating oils, which are used to fill static equipment such as transformers. This article focuses on the characteristics of biodegradable electrical insulating oils and their application to equipment, and introduces industry trends and regulations, particularly regarding vegetable oils (natural esters).

Natural disasters such as earthquakes and typhoons can cause prolonged power outages, threatening social infrastructure. As climate risks grow, Distributed Energy Resources (DERs) are gaining attention as a resilience measure, particularly for Business Continuity Management (BCM). This study proposes a method to quantify the resilience value of DERs through four steps: condition setting, risk assessment, curve analysis, and value calculation. Case studies on single and multiple buildings show that reducing failure probabilities improves overall resilience. Quantifying DER resilience value can support decision-making and promote DER deployment as a disaster risk mitigation strategy.

HVDC with modular multilevel converters (MMC) is being considered for the point-to-point transmission system. RMS analysis is used for efficient analysis of the impact of HVDC on the existing AC system. However, conventional MMC models are not suitable for RMS analysis because they represent complex circuits and controls of MMC in detail. We have developed a simplified MMC model suitable for RMS analysis by extracting the features of MMC. This model reduces the cell capacitors of the MMC to a single capacitor, and only the DC modulation function is added to the conventional 2-level converter model. To verify the developed model, we compared the results between XTAP and CPAT. The waveforms of the RMS and instantaneous value analyses are in good agreement. The accuracy of the developed model was verified by comparing the behavior during change of active power order and system disturbance.