Multiple Time-Scale Optimization Scheduling for Microgrids

Abstract

In order to achieve the minimum operational cost of the microgrid and maximum environmental satisfaction, a multiple time-scale optimization scheduling for a grid-connected microgrid is presented, including day-ahead scheduling stage and daily scheduling stage. In this paper, the research on microgrid mainly including photovoltaics (PV), wind turbine (WT), energy storages, loads and tie line power. In the day-ahead scheduling stage takes into account the minimum operational cost as the objective function. In the daily scheduling stage, achieve the minimizing of the adjustment of the day-ahead scheduling and giving priority to the use of renewable energy. The improved algorithm of PSO (Particle Swarm Optimization) is used to solve the MINLP(Mixed Integer Nonlinear Programming) problems. In order to ensure that the microgrid system obtains the global optimal solution, the new migration strategy was proposed and displace the velocity update strategy. Simulation results shown that the proposed multiple time-scale optimization scheduling approach shown that minimum operational cost and maximize the use of renewable energies, making the microgrid operation more economical, cleaner and more efficient.