Search

The safety and reliability of power system have a direct impact on People’s Daily electricity quality. With the continuous development of information technology, society puts forward new requirements on the operation mode of power system. Based on this, this article is based on the energy of the Internet under the background of the operation mode of the new energy power system and key technology, firstly analysis the energy Internet applications on the necessity of new energy power system operation mode [1], and then analysis the energy of the Internet under the background of new energy power system operating mode, finally discusses the energy Internet under the background of the key technology of new energy power system.

Single image super-resolution (SISR) aims to reconstruct a high-resolution image from a degraded low-resolution image. In recent years, the super-resolution methods based on convolutional neural network (CNN) have achieved promising performance on SISR task, indicating that CNN is a viable approach to image super-resolution reconstruction. The one limitation of the current SISR methods is that many methods use the pixel-wise loss. It is well known that the pixel-wise loss cannot well recover high-frequency details even if the high peak signal-to-noise ratio (PSNR) can be obtained. Some other methods purely focus on restoring more details, which resulted in poor PSNR score and high-frequency noise. In this paper, we proposed a multi-component loss function based on pixel-wise loss, perceptual loss and adversarial loss for a multi-scale feature mapping generator network for SISR image reconstruction model. We evaluated our method on commonly used benchmarks and compared it with other SISR methods. The results showed that our method could achieve the better balance between the high-frequency detail and stable spatial structure generation.