Source-Load Uncertainty and Correlation Scenarios Generation Considering Typical Climate Risks

With the increasing penetration of wind energy and the associated uncertainty in wind output, as well as the rising peak demand for electricity, addressing climate risks has become a pressing concern. The strong correlation between meteorological conditions, wind and photovoltaic output, and electricity load has heightened the sensitivity and vulnerability of the power system to climate variations. Therefore, it is imperative to incorporate climate risks into scenario generation for studying power system flexibility and reliability. This paper focuses on modeling the correlation between meteorology and uncertainty factors in “source load,” classifying typical climate types, and elucidating their relationship. Building upon this, the probability distribution of typical climate types is derived using Monte Carlo sampling, and a climate-risk-inclusive “source-charge” scenario is generated in a time series format. Finally, the impact of climate risks on the power system is analyzed through a case study in a specific region.