Heterogeneous Large-Scale Data Fusion Mechanism of Energy Storage Power Station Based on Neural Network
Yimin Deng, Zhoubo Weng, Tianlong Zhang · Journal of Multimedia Information System · 2023
To solve the problems of many automation systems, diverse data standards, and duplication of information content in the current energy storage power station system, and to further improve the freshness, current situation and accuracy of the energy storage power station big data, the heterogeneous large energy storage power station. The fusion of large-scale data has become a general trend. The usual data fusion algorithm is to fuse the features of sensor data in different spaces at the same time. Among them, the deep convolutional neural network (DCNN) has outstanding fusion performance, and realizes the integration of feature extraction, information association, and decision-making judgment by utilizing multiple convolutional layers, pooling layers, and fully connected layers. This paper proposes a data fusion algorithm based on convolutional neural network (AbDCNN-DAE). The algorithm introduces a denoising autoencoder and an attention mechanism, which can fuse data from various aspects to realize the arrangement of disorganized power grid data. The experimental results compared with other methods show that the algorithm proposed in this paper has better performance.