A team of researchers from The Hong Kong Polytechnic University, the US Electric Power Research Institute, South China University of Technology, and The Chinese University of Hong Kong (Shenzhen), has proposed a novel bi-directional converter (BdC) based interconnection planning approach for hybrid alternating current (AC)/direct current (DC) microgrids (HMGs) with high penetrations of renewable energy resources (RESs). The study, titled “Fortifying Renewable-Dominant Hybrid Microgrids: A Bi-Directional Converter Based Interconnection Planning Approach,” was recently published in Engineering.

The increasing deployment of DC sources and loads, such as solar power generation and electric vehicles, has driven the evolution of conventional AC microgrids into HMGs. This transition leverages the strengths of both AC and DC microgrids, reducing conversion losses and enhancing overall system efficiency. BdCs play a crucial role in this setup by facilitating power transfer between AC and DC sub-microgrids. However, planning interconnections for HMGs faces significant challenges due to the non-convex nature of BdC efficiency and the uncertainty associated with renewable energy outputs.

To address these challenges, the researchers developed a tri-level BdC-based planning framework that incorporates dynamic BdC efficiency and a data-correlated uncertainty set (DcUS) derived from historical data patterns. The proposed framework employs a least-squares approximation (LSA) to linearize BdC efficiency, balancing computational efficiency and solution robustness. Additionally, a fully parallel column and constraint generation (FPC&CG) algorithm was developed to solve the model efficiently.

The study’s key contributions include the convexification of the BdC efficiency model using the LSA method, the development of a computationally efficient DcUS that balances conservativeness and robustness, and the creation of a fully parallelizable solution algorithm. The LSA method provides a more accurate approximation of BdC efficiency compared to previous methods, with an average error of 9.1% versus 33.4%. The DcUS reduces the conservativeness of planning solutions while maintaining robustness against worst-case scenarios, offering a significant improvement over existing uncertainty sets like the box-based uncertainty set (BbUS) and the convex-hull-based uncertainty set (CHUS).

Numerical simulations on a practical HMG system demonstrated that the proposed method reduces interconnection costs by up to 21.8% compared to conventional uncertainty sets while ensuring robust operation under all considered scenarios. The results highlight the computational efficiency, robustness, and practicality of the proposed approach, making it a promising solution for modern power systems.

The researchers concluded that their approach provides a practical and scalable solution for interconnecting HMGs, balancing economic considerations, solution robustness, and computational efficiency. Future work may incorporate dynamic stability considerations and explore the implementation of multi-terminal energy routers in microgrid interconnection planning.

The paper “Fortifying Renewable-Dominant Hybrid Microgrids: A Bi-Directional Converter Based Interconnection Planning Approach,” is authored by Zipeng Liang, C.Y. Chung, Qin Wang, Haoyong Chen, Haosen Yang, Chenye Wu. Full text of the open access paper: https://doi.org/10.1016/j.eng.2025.02.020. For more information about Engineering, visit the website at https://www.sciencedirect.com/journal/engineering.