Economical Operation of Microgrid With Various Devices Via Distributed Optimization

This paper aims at minimizing economical cost of a microgrid by jointly scheduling various devices, e.g., appliances, batteries, thermal generators, and wind turbines. To properly model the system, the characteristics of all devices is fully investigated; in particular, the chance constraint is introduced to capture the randomness of power generation of wind turbines. Then, this problem is formulated as a large-scale mixed-integer program with coupling constraints. In order to solve this problem efficiently, it is decoupled via dual decomposition into a set of sub-problems to be solved distributedly on each appliance, battery, and generator. While the scheduling of generator is well studied in literature, this paper specially proposes an efficient method for appliance scheduling, and then employs Benders' decomposition for battery scheduling. The performance of the proposed approach is verified by numerical simulations.