Accurate solar cell modeling is essential for reliable performance evaluation and prediction, real-time control, and maximum power harvest of photovoltaic (PV) systems. Nevertheless, such a model cannot always achieve satisfactory performance based on conventional optimization strategies caused by its high-nonlinear characteristics. Moreover, inadequate measured output current-voltage (I-V) data make it difficult for conventional meta-heuristic algorithms to obtain a high-quality optimum for solar cell modeling without a reliable fitness function. To address these problems, a novel genetic neural network (GNN)-based parameter estimation strategy for solar cells is proposed. Based on measured I-V data, the GNN firstly accomplishes the training of the neural network via a genetic algorithm. Then it can predict more virtual I-V data, thus a reliable fitness function can be constructed using extended I-V data. Therefore, meta-heuristic algorithms can implement an efficient search based on the reliable fitness function. Finally, two different cell models, e.g., a single diode model (SDM) and double diode model (DDM) are employed to validate the feasibility of the GNN. Case studies verify that GNN-based meta-heuristic algorithms can efficiently improve modeling reliability and convergence rate compared against meta-heuristic algorithms using only original measured I-V data.

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In recent years, the conditions and environment of China's economic development have undergone or are about to undergo many major changes. At the same time, China's electricity consumption ranks the first in the world with a huge volume and a considerable annual net increment. It is necessary to dialectically understand the profound impact of the new normal of economic development on the growth of China's electricity demand. Faced with the ever-increasing power demand, the power industry is still heavy to ensure steady supply, and the proportion of power consumption will also gradually increase. The central position of power in the energy field is gradually promoted, and the power security guarantee has gradually become one of the core elements of the new energy security strategy: in the actual operation of the power grid, there will be some unstable operation, and the local power grid accident can easily expand into a large-scale blackout. This will not only threaten the daily consumption of electricity, but also affect the national economy to a certain extent. The proposed distributed generation system solves this problem, but it also brings new problems. The appearance of island effect brings more harm to power grid operation. Aiming at the harm of island effect, this paper puts forward the detection technology strategy of related island effect.