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Achieving the economical and stable operation of Multi-microgrids (MMG) systems is vital. However, there are still some challenging problems to be solved. Firstly, from the perspective of stable operation, it is necessary to minimize the energy fluctuation of the main grid. Secondly, the characteristics of energy conversion equipment need to be considered. Finally, privacy protection while reducing the operating cost of an MMG system is crucial. To address these challenges, a Data-driven strategy for MMG systems with Shared Energy Storage (SES) is proposed. In this paper, the Mixed-Attention is applied to fit the conditions of the equipment, and Multi-Agent Soft Actor-Critic(MA-SAC) , Multi-Agent Win or Learn Fast Policy Hill-Climbing (MA-WoLF-PHC) are proposed to solve the partially observable dynamic stochastic game problem. By testing the operation data of the MMG system in Northwest China, following conclusions are drawn: the R-Square (R2) values of results reach 0.999, indicating the neural network effectively models the nonlinear conditions. The proposed MMG system framework can reduce energy fluctuations in the main grid by 1746.5 kW in 24 h and achieve a cost reduction of 16.21% in the test. Finally, the superiority of the proposed algorithms is verified through their fast convergence speed and excellent optimization performance. • A data-driven method to describe the nonlinear conditions of energy conversion equipment was proposed. • A novel energy management-energy auction strategy based on MMG system framework with SES was designed. • SAC algorithm and WoLF-PHC algorithm were improved. • Privacy protection of MGs by nonlinear and non-convex constraints is realized. • The effect of different hyperparameters on the MA-SAC algorithm was analyzed. [ABSTRACT FROM AUTHOR]

Proton ceramic fuel cells (PCFCs) are gaining attention due to their high energy conversion efficiency. However, the development of PCFCs is hindered by the lack of efficient and robust cathode materials. This article proposes a solution by introducing certain cationic deficiency into the Ba 0.9 La 0.1 Co 0.7 Fe 0.2 Nb 0.1 O 3-δ (BLCFN) cathode matrix, which results in abundance of oxygen vacancies as well as enhanced proton defects. Consequently, the catalytic activity and hydration activity of the BLCFN oxygen electrode are improved during the reduction reaction process. Specifically, the polarization impedance (R p) of the (Ba 0.9 La 0.1) 0.95 Co 0.7 Fe 0.2 Nb 0.1 O 3-δ (BL95CFN) decreases by 20% compared to the pristine BLCFN, reaching 0.12 Ω·cm2 at 700 °C in air. The R p of BL95CFN decreases by 12% in a steam environment of 20 vol%. This enhancement is attributed to the higher concentration of oxygen vacancies, which leads to an improved proton diffusion rate and hydration performance. The peak power density of the anode-supported BL95CFN | BZCYYb | BZCYYb-NiO single cell reaches 641 mW cm−2 at 700 °C, and the performance of this single cell remains stable for nearly 100 h. These findings highlight the vital role of adjusting oxygen vacancy and proton diffusion, providing a feasible strategy for improving the performance and stability of PCFC cathode materials. • An A-site deficiency engineered Ba 0.9 La 0.1 Co 0.7 Fe 0.2 Nb 0.1 O 3-δ cathode is proposed. • A-site deficiency greatly enhanced ORR activity of Ba 0.9 La 0.1 Co 0.7 Fe 0.2 Nb 0.1 O 3-δ. • Oxygen vacancy by introducing cationic defects, enhances catalytic activity and hydration reaction activity. • (Ba 0.9 La 0.1) 0.95 Co 0.7 Fe 0.2 Nb 0.1 O 3-δ cathode showed good long-term stability. [ABSTRACT FROM AUTHOR]