To efficiently extract the model parameters of photovoltaic (PV) modules, this paper proposed an identification method based on the Dynamic Elite-Leader Multi-Verse Optimizer (DLMVO) algorithm. An adaptive strategy was used to control parameters based on population evolution rate and aggregation rate to balance the exploitation and exploration to avoid the search falling into local optimization. In addition, this paper proposed a dynamic elite-leader-based variation strategy to enhance the probability of variation success and improve merit search speed. This proposed algorithm was applied to the parameter identification of two different PV modules and validated using six existing methods in the literature for comparison. The experimental results show that the DLMVO algorithm significantly reduced the standard deviation of the three models compared with the standard deviation of the MVO algorithm, the single diode decreased by nearly 40%, the single-component model decreased by about 28%, and the double diode exhibited the best effect, which decreased by 83%.

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Atmospheric Ar/NH3 dielectric barrier discharge (DBD) is a type of uniform dielectric barrier discharge that has potential applications in surface treatment, thin film surface deposition, hydrogen storage, etc. The characteristics and the application effects of Ar/NH3 DBD are strongly dependent on dielectric materials, electrode structures, and gas atmospheres. In this paper, a one-dimensional fluid numerical simulation model was established to investigate the effects of dielectric constant and secondary electron emission coefficient (SEEC) of the barrier dielectric material on the discharge characteristics and product distributions in Ar/NH3 gas mixture. The results show that increasing dielectric constant makes the discharge moment slightly earlier (discharge phase 17.5°–5°) and has a greater effect on the discharge intensity (discharge current), plasma parameters, and discharge products as well as their yields. While increasing SEEC makes the discharge moment significantly earlier (discharge phase 27.5° to −5°), it has less influence on the discharge intensity (discharge current), plasma parameters, and discharge products and their yields. On this basis, a possible strategy was proposed to describe the effect of the two dielectric parameters on the discharge characteristics and products.

The stable and reliable operation of microgrids requires the immediate communication and accurate measuring data of cyber systems. The cyber security of smart grids consists of detection and mitigation, where the latter mainly refers to resisting the attack and recovering the physical operation state through various means after cyber attacks. With the flexible electrical topology and the distributed control strategy based on the public communication network and end-to-end neighbor communication, the application and effect of cyber security technologies (firewall and encryption) in traditional cyber systems are limited. However, due to the fact that the cyber system and power system are coupled in microgrid cooperative control, countermeasures are added to the control to enhance the cyber security of microgrids, which has drawn more attention. Therefore, considering the control failure and even system results from the false data inject attack (FDIA) on the cooperative control of microgrids, this study investigates the synchronous mitigation framework based on local detection where the reactive power cooperative control targets of microgrids with and without FDIA are compatible by the resilient control method. The credibility is utilized to measure the reliability of local and neighbor data in the proposed method. The consensus communication coupling gain is weighted corrected by an adaptive update strategy of credibility to delete the attack signal. Moreover, the proposed method directly improves the conventional distributed secondary controller that reduces the complexity of controller design. Simulations investigate the effectiveness of the proposed distributed resilient mitigation strategy under conditions of deception and disruption attacks.