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Formulated the multi-microgrid (MMG) operation as a transaction commitment problem. • Designed a two-stage robust optimization based MMG coordinated operation approach. • Described discrete feature of energy interactive behaviour among multiple microgrids. • Mitigated the disturbances of uncertainties in renewable energy. • Reduced frequent energy exchange between the MMG and the grid.

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Oxygen migration is reported as key factors of resistive switching in graphene oxide (GO) based memories by different groups. A flexible nonvolatile resistive switching memory based on GO was fabricated through a spin-coating process. The speed of the SET and RESET operations of the GO memories was found to be significant asymmetric. The RESET speed is in the order of 100 ns under a −5 V voltage while the SET speed is three orders of magnitude slower (100 μs) under a 5 V bias. The behavior of resistive switching speed difference is elucidated by voltage modulated oxygen diffusion barrier change.

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The intermittency of renewable energy and load uncertainty in the combined cooling, heating, and power (CCHP) system operation is considered in this study. The authors propose a robust optimisation scheduling method to attenuate the disturbance of uncertainty, and derive the day-ahead scheduling decision under two strategies including electrical load tracking and thermal load tracking. Also, the budget of uncertainty is introduced to alleviate the conservatism of robust optimisation. Moreover, a minimax regret non-linear formulation is constructed to describe the performance of the system and different realisations of uncertainty. To solve the problem, the authors develop a hybrid solution method, which is composed of a two-stage Lagrangian relaxation iterative algorithm and an improved cross entropy algorithm. Simulation results demonstrate that the minimum of the maximum regret can be obtained, and the conservatism of robust optimisation is significantly reduced by properly setting the level of budget of uncertainty. As a result, the validity and effectiveness of the proposed robust optimisation model and algorithm are confirmed.

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