Optimization of Self-Sufficient Microgrid Design with Integration of Renewable Energy Resources
Abstract
The increasing penetration of renewable energy sources and storage technologies is driving the transformation of conventional power distribution systems toward decentralized microgrid-based architectures. A major challenge lies in jointly determining the optimal segmentation of existing networks into microgrids and the strategic allocation of distributed energy resources, while balancing investment, operational efficiency, and reliability. This paper proposes a novel single-stage optimization methodology that simultaneously determines microgrid segmentation and the optimal placement of batteries, solar, and wind generators. The formulation minimizes annual operating costs by considering investment and operational expenses, energy losses, and the cost of energy not supplied due to service interruptions. Starting from a conventional radial topology, the optimization is performed using simulated annealing to explore a large combinatorial solution space efficiently. The methodology is applied to the IEEE 69-node distribution system, achieving a 15% reduction in total annual costs and enhanced reliability, with System Average Interruption Frequency Index and System Average Interruption Duration Index reduced by 35% and 47%, respectively. These results highlight the effectiveness and flexibility of the proposed approach as a medium-term planning tool for the design of self-sufficient and resilient distribution networks.