An economic dispatch model in an industrial microgrid with wind power based on robust optimization

Wind power is a kind of new, clean, renewable and widely used energy. Utilizing wind power in an industrial microgrid is of great significance in energy conservation and emission reduction. This paper researches on an industrial microgrid with wind power, establishes a multi-stage model with self-generation scheduling optimation for an industrial microgrid, which aims at minimizing the energy costs through adjusting the production and power generation schedule properly based on robust optimization, and then utilizes Benders decomposition algorithm to solve the model. Numerical tests on the model are given with data of an industrial microgrid, and it is confirmed that the fluctuation of wind power and load is smoothed by the model effectively and the electric energy costs are decreased. Additionally, the model is proved to perform better than the deterministic optimal model under the worst condition, and the balance of conservatism and optimality can be adjusted by different uncertainty prices according to the requirement.