The current conventional high-voltage transmission line monitoring method mainly obtains line parameters through fiber optic sensing equipment, and analyzes the parameters to grasp the actual load situation of the line, which leads to poor monitoring effect due to the lack of design of load flow threshold. In this regard, a monitoring method for high-voltage transmission lines based on self-assembled MAC access is proposed. By constructing the reward function, the routing monitoring algorithm is designed and the image monitoring module structure is designed. Combined with the heat balance equation, the line load flow value is calculated and the judgment of the line load condition is realized by setting the flow threshold. In the experiments, the monitoring performance of the proposed method is verified. The experimental results show that when the proposed method is used for transmission line monitoring, the system data loss rate is low and has a more desirable monitoring effect.
The power industry has achieved rapid development with the strong support of national policies, which makes the relevant data information show geometric growth. With the further promotion of the power market reform, the market transaction subjects are gradually diversified. In this progress, a good trading strategy is particularly important in order to get more generous profits in the market trading progress. The application of power big data technology can provide security guarantee for electric power production and electric power transaction. Through data mining, data analysis, data extraction and data storage, it can provide a data basis for the development of various transactions in the electric power market. Based on the mining and processing of power big data, this paper builds a two-stage decision-making framework for the power market to study the trading strategies of market participants. The model established in this paper considers the uncertainty in the two-stage decision-making process, which can reflect the risks associated with the decision-making process.
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