A Reliable Quadratic Programming Algorithm for Convex Economic Dispatch with Renewable Power Uncertainty

In the stochastic economic dispatch with renewable power, the renewable power uncertainty cost is usually considered based on the overestimation and underestimation penalty cost, which is formulated as an integral of renewable power distribution. However, although the model could be convex, iteration algorithms such as sequential linear programming are needed to solve the economic dispatch model due to the integral item. Iteration methods bring some new problems such as step size setup and sometimes lead to a bad convergence. To address this issue, this paper proposes a reliable algorithm for convex economic dispatch with renewable power uncertainty. The integral form of renewable power uncertainty cost is converted into a linear form, which can be reliably solved based on off-the-shell commercial solvers. Numerical studies in the IEEE 118-bus system are presented to demonstrate the merits of the proposed method. The results show that, compared with iteration algorithms, the proposed model is much more efficient.