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This paper proposes a reactive power coordination control scheme between voltage source converter based HVDC (VSC-HVDC) system and filter switching of line commutated converter based HVDC (LCC-HVDC) system for a hybrid multi-infeed VSC/LCC HVDC system. The conventional reactive power control strategies of filter switching of LCC-HVDC system and VSC-HVDC system are analyzed, and the limitations of them are pointed out. To reduce the filter switching, a control module is designed for the coordination control scheme. A hybrid multi-infeed system model was built in PSCAD/EMTDC for simulation verification. The simulation results showed that the performance of the reactive power coordinated control is better than that of the reactive power independent control between VSC-HVDC system and LCC-HVDC system.

Intelligent recognition of switch state based on computer vision is one of the important research contents of power intelligence. For solving the problem of low recognition rate under poor imaging environment, this paper presents an improved VGG19 network. There are 3 improved aspects: 1) in the first convolutional layer, the convolution features are extracted from the RGB image and the LBP image of the switch, and then the two convolution features are averaged as the output result of the first convolution layer, in order to enhance the adaptability of features to illumination changes and the ability to extract detailed features; 2) in the subsequent 15 convolution layers, the convolution feature output of each layer is averaged with the original input, and then convolved again, so as to extract detail features by secondary convolution; 3) we selects CReLU instead of ReLU as activation function for reducing the redundancy of the convolution kernel. Experiments show that the new method can greatly improve the performance of switch state recognition.

The secondary system of smart substation has high characteristics of network and integration. The secondary circuit and its safety measures are characterized by strong concealment and poor visualization. There is a great safety risk in the implementation of secondary equipment safety measures. In this paper, a joint verification system of secondary equipment safety measures for smart substation is proposed. The joint verification system uses the monitoring system and the third-party safety measure monitoring equipment to jointly arrange defence, carry out the whole process verification of the implementation process of the secondary equipment safety measure ticket, and carry out visual display, effectively ensuring the correctness of the implementation of the secondary equipment safety measure.

This paper analyses the current status of the intelligent substation industrial control system network and the main problems of security protection methods. Based on the analysis of the characteristics of intelligent substation industrial control network, a vulnerability scanning system based on OpenVAS is designed. The vulnerability scanning system is superior to the original vulnerability scanning system in performance and functionality, which effectively improves the security performance of the entire system and reduces system risk.

With the increasing number of UHV transmission lines crossing projects, suspension type spans are widely used in cross-construction. Among them, under the condition of construction accidents, the dynamic impact of the bearing cables and towers on the wires has received extensive attention. Based on this problem, this paper studies the impact of dynamic impact loads on transmission towers under construction accident conditions, and proposes reinforcement measures for transmission towers.

A laboratory-scale oxy-fuel combustion experimental apparatus was built up to simulate the real oxy-fuel combustion. Under conditions with three kinds of recycles (no-RFG, de-ash and ash), combustion experiments of DT bituminous coal (rich in Si and Al) and SH bituminous coal (rich in Ca) were conducted to investigate the influence of recycled ash on formation of ultrafine particle matters. The results show that, compared with the no-RFG condition, under condition with de-ash flue gas recycle, the yields of ultrafine particle matters of the DT and SH coal were both basically invariant, while that under condition with ash recycle decreased by about 12.03% (DT coal) and 7.73% (SH coal), respectively. Under condition with ash recycle, the silicon aluminate, which was rich in the ash of DT coal, would absorb the Na and K vapor released during the combustion, and the rich CaO in the SH coal may also absorb the S element during the combustion to restrain the S from migrating to the ultrafine particles, both of the reactions decreased the formation of the ultrafine particles.

The construction of transmission line in Tibet high altitude area has the characteristics of low pressure, low oxygen and low temperature. In the special environmental condition, the transmission line construction equipment with engine as the power source is highly effective, which affects the efficiency and safety of construction[1].The experimental study on engineering mechanical industry plateau transmission line is still in the blank stage,thus relying on the Tibet networking project selects 5 different high altitude test points to plateau 500kV transmission line construction commonly used types of pullers, tensioners and powered winch as an object of study to carry out the typical construction equipment energy efficiency test of field measurements effective output power equipment in different altitude environment from the perspective of practical application and analysis of law and effect mechanism of falling equipment.

Compared with traditional substation, smart substations has process layer network, which functions as the secondary circuit of traditional substation protection an d is actually equivalent to relay protection and automatic safety devices. Once an exception occurs in the network traffic of process layer, the reliability, rapidity and agility of relay protection action will be affected instantly. According to the characteristics of network traffic of smart substations, a network traffic prediction model, which is based on improved particle swarm wavelet neural network, is proposed in this paper to assist decision-making for the network performance analysis and prediction, network failures and virus invasion warning of smart substations. Experiments have been carried out and validated the high accuracy and fast convergence of the prediction model, which could improve the accuracy and rapidity of smart substation network traffic prediction and ensure the safe operation of grid.