By using the data collected by the cluster intelligent and complex optimization of the power system equipment, the cluster intelligent and complex optimization algorithms are introduced into the CAD-aided intelligent operation and maintenance of power system equipment (CAD-IOMPSE). Based on this, the CAD-aided intelligent operation and maintenance graph of power system equipment is used to apply the cluster intelligent complex data contained in the quality inspection of the different types of data obtained to restrict the relationship between different entities for the value of knowledge contained in the collected power data in the operation process and control stage of the power system. According to the types of equipment with problems in the operation of power system, the defects and problems are quickly diagnosed to quickly locate the problems and give solutions. Finally, the results of example analysis show that compared with the traditional naming entity recognition algorithm, BiLSTM-softmax and Seq2Seq-Attention model, the algorithm in this study is better than the traditional algorithm in the three evaluation index values of accuracy, recall, and F1 value.

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The purposes are to find the techniques suitable for the safety relay protection of intelligent substations and discuss the applicability of edge computing in relay protection. Regarding relay protection in intelligent substations, edge computing and optimized simulated annealing algorithm (OSAA) are combined innovatively to form an edge computing strategy. On this basis, an edge computing model is proposed based on relay fault traveling waves. Under different computing shunt tasks, OSAA can converge after about 1,100 iterations, and its computing time is relatively short. As the global optimal time delay reaches 0.5295, the corresponding computing time is 456.27s, apparently better than the linear search method. The proposed model can reduce the computing time significantly, playing an active role in the safe shunting of power relays. The simulation also finds that the voltage and current waveforms corresponding to the fault state of Phase A are consistent with the actual situations. To sum up, this model provides a reference for improving and optimizing intelligent substation relay protection.

With the further development of harmonic pollution in the power system, scientists have carried out research on harmonics. Among them, harmonic detection is the first step in harmonic research. In this paper, a harmonic detection method based on an observer is proposed. This method first uses the cascaded Second-Order Generalized Integration (SOGI) algorithm, which can filter the Direct Current (DC) component of the input signal to extract the fundamental frequency, and then uses a time-varying observer to extract the harmonics. This can be used to extract harmonics from a distorted online grid signal. The effectiveness of the proposed method was evaluated on the Speedgoat Rapid Control Prototype (RCP) platform. The results show that it can complete the convergence within 0.05 s, and the standard deviation after stability will not exceed 1%.

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