Multi-layer optimization for grid-connected micro-grid power planning considering metabolic capacity

Optimizing the energy structure, ensuring the reliability of power supply and improving the utilization of renewable energy sources are the primary objectives of micro-grid power planning This paper takes wind/light/storage micro-grid as an example, defines the concept of metabolic capacity to describe the ability of renewable utilization in a micro-grid, presents a new multi-layer optimization method to study the life-cycle cost of a micro-grid planning. The upper layer optimizes thc type, thc capacity, and allocation combinations of micro-grid power sources; The middle layer optimizes the system operation considering the network subsidy policy which State Grid newly carried out and the real-time electricity prices synthetically; The lower layer calculates the cost of micro-grid reliability cost based on reliability cost-benefit analysis. A modified Immune Particle Swarm Algorithm is designed to optimize the proposed three layer goals. As examples results shown, the proposed multi-layer optimization strategy and the Immune Particle Swarm Algorithm are very effective to coordinate the relationship in depth among the factors of economy, reliability and economic dispatch during micro-grid planning, it reduces thc redundant investment micro-grid power supply efficiently, meanwhile,increases the use of renewable energy and guarantees the system reliability