2030년 저탄소 전력 공급 정책 시뮬레이터 및 실험

Abstract

This study introduces the structure and operation principles of a policy simulator designed for the 2030 low-carbon power supply plan in the South Korean power grid and, as a utilization example, conducts an experiment on the changes in generation mix, power generation cost, and carbon emissions due to fuel price fluctuations. The simulator developed in this study includes 370 power plants that exist or are planned to be constructed by 2030 and uses the cost-minimizing Mixed Integer Linear Programming (MILP) approach for the hourly power plant operation problem. As inputs for the simulation, it provides an input window where policy alternatives can be used, including various costs, power plant technical characteristics, demand, choice of the 9th or 10th basic plan, methane leakage rate, methane's climate impact model, ammonia-carbon mixing ratio, natural gas-hydrogen mixing ratio, carbon tax, health damage cost of greenhouse gases, net spinning reserve (SR) accumulation effect of renewable energy, the status of a 24-hour energy storage system (ESS), and simulation period. The simulator developed in this study can output information on the levelized generation cost, carbon emissions, power plant operation rate, and power generation volume per power plant by analyzing the determined power plant operation and shutdown information. It can be used as a visual tool to derive the effects of policy alternatives instantly. © 2024 Korean Institute of Electrical Engineers. All rights reserved.

This study introduces the structure and operation principles of a policy simulator designed for the 2030 low-carbon power supply plan in the South Korean power grid and, as a utilization example, conducts an experiment on the changes in generation mix, power generation cost, and carbon emissions due to fuel price fluctuations. The simulator developed in this study includes 370 power plants that exist or are planned to be constructed by 2030 and uses the cost-minimizing Mixed Integer Linear Programming (MILP) approach for the hourly power plant operation problem. As inputs for the simulation, it provides an input window where policy alternatives can be used, including various costs, power plant technical characteristics, demand, choice of the 9th or 10th basic plan, methane leakage rate, methane's climate impact model, ammonia-carbon mixing ratio, natural gas-hydrogen mixing ratio, carbon tax, health damage cost of greenhouse gases, net spinning reserve (SR) accumulation effect of renewable energy, the status of a 24-hour energy storage system (ESS), and simulation period. The simulator developed in this study can output information on the levelized generation cost, carbon emissions, power plant operation rate, and power generation volume per power plant by analyzing the determined power plant operation and shutdown information. It can be used as a visual tool to derive the effects of policy alternatives instantly.