A Novel Multi-Verse optimization for Optimal Configuration of Wind/Photovoltaic/Storage GridConnected Microgrid

For the problem of optimizing energy configuration in grid-connected wind/photovoltaic/storage microgrid, the microgrid optimization model with the levelized cost of energy (LCOE) and the renewable energy efficiency (R) was established. At the same time, an efficient hybrid algorithm, Levy flight and differential evolution-based multi-objective hybridized with multi-verse optimization (LDEMVO) is developed to find feasible solutions. The introduction of differential evolution enriches the diversity of the groups, and the combination of Levy flights has a beneficial effect on avoiding local optimum and accelerating convergence speed. Then, the performance of the proposed LDEMVO is evaluated by comparing with four others intelligent optimization algorithms, the multi-verse optimization (MVO), the particle swarm optimization (PSO), the whale optimization algorithm (WOA) and the gray wolf optimization algorithm (GWO). Finally, the simulation results prove that the proposed LDEMVO is superior to MVO and PSO both in solutions' quality and convergence rate when realizing the capacity configuration of the distributed power supply.