Privacy-Preserving Cooperative Optimal Operation for Reconfigurable Multimicrogrid Distribution Systems: A Noniterative Distributed Optimization Approach

作者：Rufeng Zhang, Y. Zhang, Yunyang Zou, Tao Jiang, Xue Li · 发表于：IEEE Transactions on Industrial Informatics · 年份：2025 · DOI：10.1109/tii.2025.3558346 · 被引用次数：9 · 研究领域：Smart Grid Energy Management、Distributed and Parallel Computing Systems、Microgrid Control and Optimization

With the proliferation of distributed generators (DGs), multimicrogrid distribution systems (MMDSs) have emerged, where cooperative optimal operation plays a crucial role in improving operational flexibility and economy. On the other hand, when considering distribution network reconfiguration (DNR), traditional iterative distributed algorithms can protect privacy but face challenges, such as high computational complexity and poor convergence. To address these issues, this article proposes a cooperative operation method for MMDSs based on an equivalent projection (EP) theory. Specifically, a bi-level cooperative method for MMDSs is first proposed. Therein, the flexible resources within the MMDS are identified, while DNR and soft open point (SOP) technologies are considered. Second, to protect privacy of the lower-level microgrids (MGs), the improved Fourier–Motzkin elimination (IFME) and Gaussian elimination methods are used to derive the low-dimensional projection feasible region (PFR) of the lower-level MGs. Third, a noniterative solution method based on the EP theory is developed to efficiently solve the bilevel cooperation model, while addressing the privacy concerns from participants. Numerical results show that the third-order approximate PFR model can achieve a lossless transformation of the bilevel model, effectively balancing computational efficiency and accuracy. Compared to traditional distributed algorithms, the developed noniterative solution method exhibits super...