LI Xianshan, ZOU Fang, LI Xinyan, et al. Multi-objective Hierarchical Optimal Configuration Method for Microsources of Stand-alone Microgrid[J]. High voltageapparatus, 2018, 54(10): 170-178.
LI Xianshan, ZOU Fang, LI Xinyan, et al. Multi-objective Hierarchical Optimal Configuration Method for Microsources of Stand-alone Microgrid[J]. High voltageapparatus, 2018, 54(10): 170-178. DOI: 10.13296/j.1001-1609.hva.2018.10.028.
Multi-objective Hierarchical Optimal Configuration Method for Microsources of Stand-alone Microgrid
The optimal sizing of microsources is the focus point at the planning stage of microgrid
and it is the basisfor the entire life cycle of microgrid operating economically
safely and reliably. In this paper
a multi-objective mi-crosources optimal configuration method of stand-alone microgrid considering the maximum load support and the low-est total system cost is proposed. To ensure power supply reliability and quality in a stand-alone microgrid system
the corresponding microgrid networking rules is put forward
and then verified that networking rules is one of the mi-crosources configuration rules which must be followed;in order to achieve complementary effects of uncontrollablemicrosources
energy storage is proposed as a system balance of the bridge;the impact of the system reserve degreeto microsources configuration is analyzed
which laid the foundation for future expansion of microgrid. In this paper
two types of micro-power are analyzed
using a hierarchical optimization method to improve the optimize speed andcertainty of the results. The first layer is formed using HOMER software system to obtain the lowest lifecycle cost ofdifferent types of microsources configuration
and screened out combination which meets networking rules
the firstlayer results which as the initial solution is involved the second stage
using particle swarm algorithm to obtain theoptimal configuration in which load power shortage the lowest as the target. Compared with pure particle swarm opti-mization
the method proposed in this paper can achieve the optimal economic supply capability and high reliabilitywith a faster convergence rate.