The crisis of climate change aroused international needs to reduce the greenhouse gas emission in energy sector. Government of South Korea formulated an agenda of carbon neutrality through announcing 2050 Net-Zero Carbon Scenario A and B in October 2021. As the power supply from renewable energy increases, it becomes a core element to take into account the daily intermittency of renewable energy in analyzing the upcoming energy plans. However, the existing yearly Load Duration Curve is insufficient for applying day and night power change in daily scale into energy mix analysis, since it derives the energy mix for whole year on the basis of classifying annual base load and peak load. Therefore, a new energy mix simulation model based on the daily power load and supply simulation is needed for the future energy analysis. In this study we developed a new model which simulates the average power supply and demand daily (over a 24 hour period) for each season. The model calculates the excess and shortage power during day and night by integrating each energy’s daily power pattern. The 2050 Net-Zero Carbon Scenario A was used for the model verification, during which the same amounts of power production from each energy source were applied: nuclear, renewable, carbon-free gas turbine, fuel cell and byproduct gas. Total power demand pattern and renewable energy production pattern were drawn from the data of 2017 power production, and Pumped-storage Hydroelectricity and Energy Storage System were used as day-to-night conversion. Detailed assumptions for each energy were based on the Basis of Calculation for Net-Zero Carbon Scenario from Government. The model was verified with three cases which were divided depending on the method of hydrogen production and whether the Curtailment and Conversion Loss (CCL) of renewable energy were considered or not. Case 1 assumed production of hydrogen occurred for 24 hours while not considering CCL, had 0% relative error in comparison of total annual power production, and case 2, considering CCL, had a 1.741% relative error. Case 3 assumed production of hydrogen occurred only during daytime with excess power and CCL consideration, yielded 0.493% relative error in total amount of hydrogen production, confirming that the model sufficiently describes the Government’s Scenario A with the input of total power production. This model is expected to be used for analyzing further energy mix with different ratios of each energy source, with special focus on nuclear and renewable energy sources.

This study is about the control method of smart skin applying SPD(Suspended Particles Display). Smart skin is a self-developed composite window system for the purpose of reducing the cooling load and lighting load. The simulation by TRNSYS18 was modeled in detail based on an actual office located in Jeonju. The previously studied smart skin control method (case1) is a time-dependent control method, and a new control method (case2) was devised based on the data that consideration of daily insolation is important in an actual environment. As a result of simulation by case1, it was found that the amount of cooling energy and lighting energy saved was reduced by 15.1% and 39.2%, respectively, compared to the general model. As a result of the simulation by case2, it was found that the amount of cooling energy and lighting energy saved was reduced to 17.6% and 57.5%, respectively, compared to the general model. Therefore, the newly proposed control method considering the amount of insolation and time was found to be effective in reducing cooling energy and lighting energy.

In this study, an algorithm for control of SPD(Suspended Particles Display) on Smart Skin was proposed. The office with SPD located in Jeonju, Jeollabuk-do was modeled and simulated using TRNSYS18. Through simulation, the energy and lighting consumption of building were analyzed The two kinds of control algorithm(SPD and dimming control method for cool energy and lighting energy saving(CASE 1) and improved control method(CASE 2)) were compared. For this research, Two models(with and without SPD and dimming control) were analyzed by comparing the cooling energy and the light energy consumption was reduced 15.1%, and the lightind energy consumption was reduced by 39.2% more than the model without SPD and dimming control. But, at the improved control method(CASE 2) the cooling energy consumption was reduced of more 2.5% and lighting energy consumptions was reduced of more 18.3% than CASE 1. When using SPD and dimming control, lighting energy consumptions showed more sensitive to solar radiation than cooling energy consumptions. As the improved control method(CASE 2) showed more advantageous saving tate than SPD and dimming control metrhod for cool energy and lighting energy saving(CASE 1), it was found that the improved control method (CASE 2) must be utilized in practice for SPD and dimming control.