Accurate short-term electric load forecasting is significant for the smart grid. It can reduce electric power consumption and ensure the balance between power supply and demand. In this paper, the Stacked Denoising Auto-Encoder (SDAE) is adopted for short-term load forecasting using four factors: historical loads, somatosensory temperature, relative humidity, and daily average loads. The daily average loads act as the baseline in final forecasting tasks. Firstly, the Denoising Auto-Encoder (DAE) is pre-trained. In the symmetric DAE, there are three layers: the input layer, the hidden layer, and the output layer where the hidden layer is the symmetric axis. The input layer and the hidden layer construct the encoding part while the hidden layer and the output layer construct the decoding part. After that, all DAEs are stacked together for fine-tuning. In addition, in the encoding part of each DAE, the weight values and hidden layer values are combined with the original input layer values to establish an SDAE network for load forecasting. Compared with the traditional Back Propagation (BP) neural network and Auto-Encoder, the prediction error decreases from 3.66% and 6.16% to 2.88%. Therefore, the SDAE-based model performs well compared with traditional methods as a new method for short-term electric load forecasting in Chinese cities.

Chemical compounds dissolved in insulating oil, as indicators can excellently monitor the paper aging condition, which has attracted increasing interest in areas of transformer condition monitoring and fault diagnosis. Because of their outstanding features, such as good correlation with the degree of polymerization of cellulose paper and the aid of non-destructive online monitoring, chemical indicators have been effectively used for transformer condition assessment. In this study, a comprehensive, in-depth insight into the indicators of the aging of insulating paper from aging characteristics, physico-chemical characteristics, shortcomings of various compounds, generation pathways and mechanisms, and monitoring technologies are provided. It is expected that these chemical indicators can provide better guidance for the evaluation of paper insulation performance and transformer aging. In addition, the latest research progress, as well as current challenges and future prospects are also outlined. This study provides a theoretical basis and reference for chemical indicators in the fields of microscopic formation mechanism, diffusion equilibrium phenomenon, and insulation aging state assessment.

With the increasing application of CHP and an industry transition to distributed energy, it is necessary to make a comprehensive economic analysis and comparison of the entire lifetime of CHP from the net present value (NPV), payback period, and cost-saving ratio (CSR). Five systems, including micro-CHP, gas boiler (GB), air-source heat pump (ASHP), domestic gas-fired heater and domestic electric hot water-heater, are simulated. First, this paper takes annual heat use efficiency (AHUE) into account to compare the economy of each domestic hot water (DHW) system. The results show that a domestic gas-fired heater system is the most economical option in the AHUE of 31.28%. The economic influence of CHP and gas-fired heater under different AHUE are then analyzed. The results show that the DHW system based on CHP is the best when the AHUE is more than 55.35%. Finally, three different operation strategies of CHP are considered in this paper. From the perspective of annual energy cost and payback, the internal combustion-based CHP with thermal energy system (TES) is superior to the other two strategies being studied. Considering the optimal economic benefits, the CSR of the three different operation strategies is 41.3%, 69.69% and 69.77%, respectively.

In this paper, RGB image sensors based on visible light communication system are designed and researched. In our study, the spatial inter-symbol interference is considered and the formation mechanism of the stray light, the influence of the spatial inter-symbol interference, and the influence of RGB image sensors are analyzed. The mathematics expression of the system signal-to-noise ratio (SNR) and bit error ratio (BER) is given. The simulation result indicates that there is a critical communication distance in the system. Once the communication distance exceeds the critical value, the system BER performance increases sharply. In addition, an adaptive threshold detection method is introduced and the performance is simulated. By means of estimating the spatial inter-symbol interference noise power, the optimal detection threshold can be obtained and the system BER performance increases significantly.