Multi-timescale coordinated optimization of hybrid three-phase/single-phase multimicrogrids

Abstract

With the increasing amount and type of connected microgrids in the near-term future power networks, how to optimize the operation of multimicrogrids efficiently and reliably has become essential for taking full advantage of the complex systems. In this paper, a multitimescale coordinated optimization strategy for hybrid three-phase/single-phase multimicrogrids is proposed. The multitimescale strategy is implemented for day-ahead economic optimization on a long-time scale and real-time tracking optimization on a short-time scale. With the consideration of the economy of microgrids and three-phase unbalance constraints in multimicrogrids, a strategy of collecting-distributing fuzzy modified adaptive particle swarm economic optimization is introduced. In this day-ahead strategy, a bilayer rolling optimizing structure is designed, where the lower layer conducts economic optimization at all time slots and the upper layer balances the tie-line power at each time slot based on the results obtained from the lower layer. On this basis, by taking a day-ahead optimized tie-line power as baseline values, the real-time power of energy storage systems is obtained by adopting an improved nondominated sorting genetic algorithm, which achieves distributed real-time optimization for the multimicrogrid. Simulation results verify that the proposed strategy is feasible.