Estimating the uncertainty of net load of 2030 Renewable Generation

Autor: 조상민 ( Sang-min Cho ), 조일현 ( Ilhyun Cho ), 전우영 ( Wooyoung Jeon )
Rok vydání: 2019
Předmět:
Zdroj: New & Renewable Energy. 15:28-38
ISSN: 1738-3935
DOI: 10.7849/ksnre.2019.12.15.4.028
Popis: Under mounting pressure to reduce carbon emission and fine dust, South Korea set a challenging 2030 target for renewable generation. However, the rapid deployment of variable renewable generation undermines the reliability of the power system and causes problems for stable electricity supply. In this study, we analyzed uncertainty and variability of a net load in 2030, which is a key factor for a system operator to run a power system reliably. Two methodologies are applied to estimate the net load: the 2-stage ARMAX model and Monte Carlo simulation. The analysis showed that while spring and fall seasons have a serious duck curve problem that significantly affects the base load, the duck curve problem was not significant in summer or winter due to high peak demand. The duck curve problem, which is mainly caused by the variability of solar PV generation, creates a distinct problem by generating a net load plunge of approximately 44% compared to the peak of net load. The uncertainty of renewable generation was a relatively minor problem by having approximately 5% level of forecasting error compared to peak demand. In conclusion, policy implications for the duck curve problem in 2030 are proposed.
Databáze: OpenAIRE