A binary adaptive differential evolution algorithm for dynamic economic dispatch considering significant wind power

Dynamic economic dispatch (DED) is a high-dimensional, non-convex, multi-constrained optimization problem. With the increase of wind power penetration into power systems, the DED problem becomes more difficult. In the mathematical model, the constraints of wind farm output and spinning reserve are proposed to deal with the random and unpredictable nature of wind power. In the power system with large-scale wind farm, wind power should be adjusted according to available spinning reserve capacity. To improve the searching capability of binary differential evolution (BDE) algorithm, an adaptive adjusting strategy for control parameters is adopted. At the same time, the constraints are solved by some new strategies, which can make all the particles feasible, then searching efficiency is greatly improved. The presented method is proved effective by some numerical examples.