Building a reliable forecasting system can quantify future fluctuations in short-term photovoltaic output power, which is essential for optimizing grid configuration and reducing operating costs. However, most of the existing studies only use denoising technology to preprocess data, which results in the elimination of some key information. And the traditional optimizer cannot meet the parameter optimization requirements of the prediction system because of its limited search capacity and search space. Based on the above problems, a combined system based on multi-stage data processing strategy and improved optimizer is proposed, which solves the tradeoff problem between prediction accuracy and stability. Firstly, the multi-stage processing strategy effectively improves the signal-to-noise ratio and preserves more implicit information. Then, the optimal sub-model determination strategy extends the structural framework of model selection and improves the flexibility of the prediction system. Finally, three improved strategies are introduced to improve the optimization ability and convergence speed of the optimizer, which magnifies the advantages of the prediction system. An empirical study using Safi-Morocco data shows that the symmetric mean absolute percentage errors of three photovoltaic modules are 4.777%, 4.755% and 6.033%, respectively, which implies that the system can not only achieve accurate prediction of photovoltaic output power, but also help to balance supply and demand and improve the overall sustainability and stability of the grid-connected power system.

中文翻译：

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基于多级数据处理策略和改进优化器的光伏功率预测系统

建立可靠的预测系统可以量化未来短期光伏输出功率的波动，这对于优化电网配置和降低运营成本至关重要。然而现有研究大多仅采用去噪技术对数据进行预处理，导致一些关键信息被剔除。而传统的优化器由于搜索容量和搜索空间有限，无法满足预测系统的参数优化要求。基于上述问题，提出了一种基于多阶段数据处理策略和改进优化器的组合系统，解决了预测精度和稳定性之间的权衡问题。首先，多级处理策略有效提高了信噪比并保留了更多的隐含信息。然后，最优子模型确定策略扩展了模型选择的结构框架，提高了预测系统的灵活性。最后，引入了三种改进策略来提高优化器的优化能力和收敛速度，放大了预测系统的优势。利用Safi-Morocco数据进行实证研究表明，三种光伏组件的对称平均绝对百分比误差分别为4.777%、4.755%和6.033%，这意味着该系统不仅可以实现光伏输出功率的准确预测，而且还可以实现光伏输出功率的准确预测。有利于平衡供需，提高并网电力系统的整体可持续性和稳定性。