Load Recovery Optimization with Wind Farms Based on Uncertain Bi-level Programming

In the process of power system res toration after a large power outage, the power support of wind farms is taken into account that it can speed up the restoration of the system. However, the uncertainty of wind farm output also increases the risk of secondary power outages. To solve this problem, this paper adopts the uncertain bi-level programming theory to establish a load recovery optimization model that takes into account the uncertainties of wind power and load, and the model converts it into load power and wind power forecasting errors for processing. Furthermore, the traditional deterministic power grid safe operation constraint is changed to a chance constraint in the form of confidence. In order to meet the requirements of online rapid decision-making, the normal distribution theory is used to transform the uncertainty model into its definite equivalence model, and CPLEX is used to solve it. Finally, an IEEE39-bus system with wind farms is taken as an example to verify the effectiveness of the proposed method.