베이지안 모형 평균화를 통해 재구축된 기후변화 시나리오에 따른 다목적댐 수력발전량의 변화 분석

초록

The ongoing increase in the global population and rapid technological advancements have led to rising electricity demand, resulting in greater uncertainty in energy supply. Although hydroelectric power generation is an important component of renewable energy, it is greatly affected by changing precipitation and runoff patterns due to global warming. To investigate the impact of climate change on the future hydroelectric power generation (HPG) of Soyanggang Dam and Chungju Dam, we integrated climate projections from four global climate models (CanESM5, ACCESS-ESM1-5, INM-CM4-8, IPSL-CM6A) using Bayesian Model Averaging (BMA), and predicted future HPG using Support Vector Regression (SVR) and Long Short-Term Memory (LSTM) models. Changes in HPG according to different scenarios and time periods were investigated based on the analysis of variance (ANOVA). We calculated the Standardized PrecipitationEvapotranspiration Index (SPEI) for the future period, identified drought events using run theory, and estimated the amount of increase or decrease in HPG according to drought. Overall results show that changes in HPG are most significant during the flood(Jul-Sep) season in drought years. Specifically, in drought years, the HPG of Soyanggang Dam during the flood season decreased by 10.8 % under the SSP2-4.5 scenario, whereas under the SSP5-8.5 scenario, the HPG during the annual(Jan-Dec), drought(Jan-Jun, Oct-Dec), and flood(Jul-Sep) season decreased by 30 %, 33.3 %, and 23.6 %, respectively. For Chungju Dam, The HPG during flood season decreased by 42.5 % under the SSP2-4.5, while under the SSP5-8.5, the HPG during the annual and flood season decreased by 12.4 % and 63.8 %, respectively. This is because precipitation and runoff patterns change seasonally according to climate change scenarios, and multipurpose dam managers need to ensure the stability of hydroelectric power considering these pattern changes.

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