Abstract
Interconnection planning involving bi-directional converters (BdCs) is crucial for enhancing the reliability and robustness of hybrid alternating current (AC)/direct current (DC) microgrid clusters with high penetrations of renewable energy resources (RESs). However, challenges such as the non-convex nature of BdC efficiency and renewable energy uncertainty complicate the planning process. To address these issues, this paper proposes 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 to linearize BdC efficiency and constructs the DcUS to balance computational efficiency and solution robustness. Additionally, a fully parallel column and constraint generation algorithm is developed to solve the model efficiently. Numerical simulations on a practical hybrid AC/DC microgrid system demonstrate 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. These results highlight the computational efficiency, robustness, and practicality of the proposed approach, making it a promising solution for modern power systems.
| Original language | English |
|---|---|
| Pages (from-to) | 130-143 |
| Number of pages | 14 |
| Journal | Engineering |
| Volume | 51 |
| DOIs | |
| Publication status | Published - Aug 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Bi-directional converter
- Hybrid alternating current/direct current microgrid
- Interconnection planning
- Solar power uncertainty
ASJC Scopus subject areas
- General Computer Science
- Environmental Engineering
- General Chemical Engineering
- Materials Science (miscellaneous)
- Energy Engineering and Power Technology
- General Engineering
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