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Based on the characteristics of the whale optimization algorithm (WOA) and perturbation observation (P&O) method, this paper proposes a novel hybrid approach called the improved chaotic whale optimization combined with perturb and observe (ICWOA-P&O) method for maximum power point tracking (MPPT) control to solve the challenge of low efficiency in photovoltaic (PV) power generation under local shadows. First, the ICWOA is used for a global search to quickly locate the position of the maximum power point (MPP). Then, the P&O method is used for a fine-grained local search to quickly track the position of the global maximum power point (GMPP) with low oscillation. To ensure accuracy, the tracking performance of the ICWOA-P&O method is comprehensively compared with the WOA-P&O, WOA, and PSO models under four conditions: uniform irradiance, static local shading, dynamic shading, and sudden changes in irradiance and temperature. The simulation results verify that under the above four conditions, the ICWOA-P&O method can track the MPP continuously and stably and greatly improves the convergence time and accuracy. Compared with the other three methods, the ICWOA-P&O method can effectively obtain the fastest tracking speed (less than 0.1 s), the highest tracking accuracy (more than 99.97%), the smallest relative error (less than 0.03%), and the smallest oscillation fluctuation. Finally, this study integrated the ICWOA-P&O algorithm into the designed MPPT controller hardware and established a practical PV experimental platform based on the ICWOA-P&O control algorithm for practical tests. [ABSTRACT FROM AUTHOR]

Mn2+ activated glass‐ceramic (GC) has received tremendous attention in the exploration of luminescent materials for solid‐state lighting due to the high stability, broad red emission, and low toxicity. However, the doped Mn2+ ions still suffer from the oxidation and uncontrollable ions migration during the melting process of conventional preparation techniques, which is detrimental to the luminescence performance. Herein, transparent Mn2+‐doped mullite GCs have been prepared at low temperature (∼850°C) via the spark plasma sintering of EMT‐type zeolite. The GC samples show typical red emission peaking at 620 nm that can be assigned to spin‐forbidden 4T1(G)→6A1(S) transition of Mn2+ located in the octahedral coordination site of the host. Owing to the charge compensation mechanism and produced oxygen vacancies, the self‐reduction of Mn3+ to Mn2+ ions is realized and the oxidization is inhibited. The mullite nanocrystals acted as additional scattering centers introduce Rayleigh scattering to enhance the emission intensity. Moreover, benefitted from the established mullite nanocrystals network, the Mn2+‐doped GCs exhibit improved thermal conductivity up to 1.79 W K−1 m−1 and more excellent mechanical properties than conventional GCs, simultaneously. [ABSTRACT FROM AUTHOR]

Gradient-based non-dominated sorting genetic algorithm II (G-NSGA-II) is successful for solving multi-objective optimization problems. However, the effectiveness of gradient-based hybrid operator is influenced by the distribution of individuals in the population. In order to solve the problem, based on the framework of G-NSGA-II, we propose an improved gradient-based NSGA-II algorithm by introducing a new chaotic map model named IG-NSGA-II. In this algorithm, a new hybrid chaotic map model is first established to initialize population for keeping the diversity of the initial population. Then, the substitution operation of chaotic population candidate is introduced to maintain the diversity and uniformity of the Pareto optimal solution set. Finally, the proposed algorithm is tested on several standard test problems and compared with other algorithms. The experimental results indicate that the proposed algorithm leads to better performance results in terms of the convergence to Pareto front or the diversity of the obtained non-dominated solutions. [ABSTRACT FROM AUTHOR]