Improving power distribution system reliability via optimized Microgrid integration and storage management

Modern power distribution systems are increasingly incorporating volatile renewable energy sources and distribution system operators need to develop suitable measures to ensure power system reliability and stability under all circumstances. The objective of the work is to develop an optimization methodology to improve the efficiency and reliability of power distribution systems by integrating microgrids and auxiliary services. The approach utilizes a genetic algorithm to optimize energy exchanges between microgrids and the grid, aiming to reduce congestion, alleviate line overloads, minimize penalty costs for the distribution system operator, and enhance the integration of renewable energy sources. The results show how optimized energy exchange and the strategic use of auxiliary services can improve grid stability and reliability while creating economic benefits for both the distribution system operator and the microgrid owners. Specifically, the optimized system reduced the number of time steps during which one or more lines were overloaded from 10,172 to 2793, improving the reliability coefficient from 0.05788 to 0.08215. Penalties incurred by DSO due to network congestion were reduced by over 75 %, resulting in substantial financial savings. Furthermore, the results highlight the broader potential of such methods to support the transition to more resilient, efficient, and cooperative power distribution systems.