A Quantitative Assessment Method for Power System Flexibility based on Probabilistic Optimal Power Flow

Given its fluctuation and stochasticity, renewable energy generation’s high proportion to connect poses challenges to the flexibility of the power system. For that reason, a quantitative assessment method of power system flexibility based on probabilistic optimal power flow was proposed. Firstly, the flexible resource models of the power system were constructed. Historical data was processed to generate scenarios by using the k-means method, and the probabilistic models of wind power, photovoltaic power, and load fluctuation were constructed considering the time correlation based on the Markov chain model and the Copula function. Secondly, associating economic costs with system flexibility, quantitative assessment indicators that take into account the operational economy were established considering system flexibility margin expectations, vacancy expectations, and probability of deficiencies. Thirdly, the probabilistic optimal power flow model with flexibility resources was constructed, and the system state and index were estimated by the Monte Carlo simulation method and tracking center trajectory interior point method. Finally, analyzing the case of the IEEE RTS-24 system show that the appropriate allocation of renewable energy and energy storage systems could improve system flexibility and operating economy.