In the quest to integrate more renewable energy into power grids, researchers have developed a novel method to optimize the capacity configuration of multi-microgrid systems, potentially offering a more stable and cost-effective approach to managing power distribution. This breakthrough, published in *Power Technology*, addresses the growing challenges of balancing power flow and maintaining grid stability as renewable energy sources like wind and solar become more prevalent.
The study, led by Liu Zhong from the School of Energy and Power Engineering at Changsha University of Science and Technology, introduces a bi-level optimization model tailored for multi-microgrid distribution networks. The model aims to minimize life cycle costs while simultaneously reducing peak-valley differences, network losses, and voltage deviations. By leveraging the White Shark Optimizer (WSO) algorithm and the Cplex solver, the researchers were able to simulate and optimize the capacity configuration of a system incorporating wind power, photovoltaic energy, battery storage, and hydrogen energy storage.
“Our research demonstrates that the optimal configuration of wind-solar power generation systems and hybrid energy storage systems can significantly enhance both economic and stability outcomes,” said Liu Zhong. The findings reveal that the ideal ratio of wind-solar power generation to hybrid energy storage is approximately 1:0.27, a balance that outperforms systems relying on single energy storage solutions.
The implications for the energy sector are substantial. As grids increasingly incorporate renewable energy sources, the need for sophisticated management tools becomes paramount. This research provides a framework for optimizing the integration of diverse energy sources, potentially reducing operational costs and improving grid reliability. “The proposed method not only optimizes the joint cost of the system but also effectively reduces the load peak-valley difference and distribution network loss, thereby improving power quality,” added Liu Zhong.
The study’s application of the bi-level optimization model and advanced algorithms like WSO and Cplex sets a new standard for capacity configuration in multi-microgrid systems. By addressing the complexities of power balance and flow distribution, this research could pave the way for more resilient and efficient energy networks. As the energy sector continues to evolve, such innovations will be crucial in meeting the demands of a sustainable and stable power grid.
The research was published in *Power Technology*, a leading journal in the field of energy and power engineering, underscoring its relevance and potential impact on future energy systems.