Bi-Layer Decentralized Optimization Algorithm for Peer-to-Peer Energy Trading in Multimicrogrids

The growth of distributed renewable energy in microgrids (MGs) raises challenges in energy management and consumption. As an innovative approach, peer-to-peer (P2P) energy trading offers a promising solution to address these problems. In this article, we propose a bi-layer decentralized (BLD) optimization algorithm for P2P energy trading in multimicrogrids (MMG). Compared with traditional optimization algorithms that are single-layer decentralized (i.e., decentralizing solely at inter-MG trading and typically centralizing prosumers within the MG), the proposed algorithm achieves bi-layer decentralization (i.e., decentralization extends to both inter-MG and intra-MG trading). In this way, the BLD algorithm can significantly preserve the information privacy and decision independence of prosumers. In addition, the proposed algorithm can efficiently manage power flow in a decentralized manner at both layers, whereas existing decentralized algorithms frequently neglect this critical feature. Furthermore, an accelerated BLD (ABLD) algorithm is proposed to address time-consuming issues in this nested P2P trading for MMG. Numerical simulations on various test systems demonstrate the effectiveness of the proposed algorithm. The results indicate that the error of the proposed algorithm is below 0.1%. In addition, BLD requires 15602.03 s to converge with 560 prosumers, while ABLD only requires 228.05 s.