Scenario Generation of Renewable Energy power Considering Identification of Meteorological Risk Factors

Conventional scenario generation for renewable energy power systems primarily relies on historical output data, often neglecting critical meteorological factors. This oversight can result in an underestimation of risks in power system analysis. Key meteorological risks—such as extreme temperature fluctuations, prolonged periods of low wind or solar irradiance, and severe storms—directly impact the availability and stability of renewable energy sources. As renewable energy, characterized by its inherent volatility and intermittency, increasingly contributes to the energy mix, these factors become vital. To address this gap, this paper proposes a novel scenario generation method that integrates meteorological risk factors into the modeling process. By utilizing historical data on meteorological characteristics, including wind speed, solar irradiance, and precipitation, the proposed approach constructs probability models to simulate potential output scenarios. Incorporating these risk factors offers a more comprehensive framework for managing uncertainties in power system operations. Case studies validate the effectiveness of this approach, demonstrating improved scenario accuracy and enhanced support for reliable power system planning under varying weather conditions.