The Risk Assessment of Transmission and Transformation Joint Systems Considering Large Scale Wind Power and Photovoltaic Integration

Renewable energy sources often exhibit intermittency and volatility, and their large-scale integration into the grid can have a major influence on the safe and stable operation of transmission and transformation joint systems. However, existing research has not considered the effects of the unpredictability of renewable energy output on the operational risk of transmission and transformation joint systems. Therefore, this paper comprehensively considers the probabilistic characteristics and correlations of wind power and photovoltaic output, and constructs a joint wind-photovoltaic probabilistic density model based on Copula theory. Subsequently, a state reduction method and a double-layer Monte Carlo sampling method are proposed to perform inner and outer layer sampling for transmission and transformation joint systems with renewable energy integration. Finally, the proposed method has been proven to be effective using an improved IEEE-RBTS 6-bus system. Simulation results show that considering renewable energy integration in the risk assessment of transmission and transformation joint systems has a significant impact on risk indicators.