With the escalating frequency and severity of natural disasters due to global warming, ensuring stable power supply critical infrastructure like fire stations, hospitals, communication facilities becomes imperative for urban recovery social safety. Previous studies have focused on various approaches continuously operating grids, often employing optimisation models. However, these models suffer from high computation times, necessitating a prompt approach handling unexpected events. Machine...

Photovoltaic power generation must be predicted to counter the system instability caused by an increasing number of photovoltaic power-plant connections. In this study, a method for predicting cloud volume and using satellite images is proposed. Generally, solar irradiance cover have high correlation. However, because not provided Meteorological Administration or weather site, can used instead radiation. A lot information, such as direction speed movement contained in image. Therefore,...

A power transformer is an essential device for stable and reliable transfer to customers. Therefore, accurate modeling of transformers required simulation-based analysis with the model. The paper proposes efficient straightforward parameter estimation based on sweep frequency response (SFRA) test data. method first develops a model consisting repetitive RLC sections mutual inductances then aligns simulated SFRA curve measured one by adjusting parameters. Note that this adjustment individual...

The complexity and uncertainty of the distribution system are increasing as connection distributed power sources using solar or wind energy is rapidly increasing, digital loads expanding. As these keep investment cost for facilities, optimal planning becomes a matter greater focus. This paper analyzed existing mid-to-long-term load forecasting method KEPCO’s proposed mid- to long-term based on ensemble learning. After selecting input variables required model through correlation analysis,...

The prosumer market allows prosumers to sell their energy surplus consumers. should offer the amount of and its unit price contracted consumers while economically operating system. This paper presents optimal operations business strategies maximize prosumer's benefit by utilizing an storage system ensuring a contract with residential under progressive pricing policy, where electricity increases monthly consumption. By proposed method, time-of-use scheme stores abundant renewable or utility...

The rapid integration of renewable energy sources and the increasing complexity modern power systems urge development advanced methods for ensuring system stability. This paper presents a novel continuation flow (CPF) method that combines two well-known parameterization techniques: natural arc-length parameterization. proposed hybrid approach significantly improves computational efficiency, reducing processing time by 32.76% compared to conventional while maintaining high accuracy. enables...

Distribution systems have become more complex because of the increasing penetration renewable energy resources. Moreover, unbalanced voltages are one voltage quality issues in distribution systems. Conventional optimization methods time-consuming solving each scenario. Deep reinforcement learning (DRL) is an effective technique for real-time operations to overcome time-consumption problem. This paper proposes a safe deep (SDRL)-based system operation method mitigate voltage. The SDRL...

Traditionally, the distribution system is operated to improve revenue, reliability, and power quality. Extensive optimal operation strategies are researched solve model-based problems. However, penetration of distributed generations (DGs) renewable energy resources (RESs) such as photovoltaic wind generation has increased recently. The RES uncertainties variability, which cause complexity operation. In this sense, time-consuming complex formulation becoming a challenge an Furthermore,...

Examining power transformer faults is crucial for maintaining the reliability of system. The most popular methods detecting fault include thermal analysis, vibration partial discharge dissolved gas analysis(DGA), and sweep frequency response analysis(SFRA). Especially, SFRA test examined to detect internal such as winding fault. Simulation-level analysis enables inspection before connecting grid. This paper proposes a parameter estimation method using machine learning equivalent model.

This paper explained a mid-long term load forecasting that can reflect the pattern of increasing loads when is planning installation lines and facilities in terms distribution system. In case models, unlike short-term additional social economic variables are needed, so input should be selected through data analysis on output relationships. Then, this investigated existing used models analyzed strengths weaknesses them. Finally, proposed method mode for planning.