Research On Data Collection Technology For Regional Energy Internet

With the excessive consumption of non-renewable energy,renewable energy has received more and more attention,and has been widely used in the power industry in the form of distributed energy,which has promoted the development of regional energy Internet.At the same time,the massive data generated by the widespread deployment of intelligent electrical equipment supports the big data in the regional energy Internet application.As the first step in data applications,data collection is the cornerstone of data applications.Aiming at the characteristics of different data sources and different types of data on the power generation side and the power consumption side in the regional energy Internet,studying stable and effective data collection technologies could provide strong support for data applications.For the power generation side,due to the wide distribution of distributed energy sources and their remote location,it is not conducive for data collection,and the limited energy of the data collection sensors also makes it difficult for data collection on the power generation side.Based on this,the thesis studies the characteristics of wireless sensor network data collection,combined with the geographical distribution of distributed energy sources,and uses Kmeans++and Fuzzy Logic to dynamically cluster the wireless sensor network.The thesis conduct simulations on the proposed method,and the experimental data proved that the energy consumption of the data collection sensors was significantly reduced during the collection process.For the power consumption side,data collection using power technology can only obtain the electrical data of the device in real time,and could not obtain auxiliary data of other dimensions for the device,which is not conducive to feature extraction during data analysis and limits personalized intelligent monitoring of the device.Based on this,the thesis uses wireless communication technology to propose a power-side auxiliary data collection method.In particular,the thesis designs an application-level wireless communication protocol that supports data collection on the power side,and based on the matching theory,the proposed method achieves a good match between real-time electrical data and auxiliary data,and solves the problem of a single dimension of data collection on the power side.Finally,based on the proposed data collection method,a power-side auxiliary data collection system was actually built and verified the effectiveness of the proposed method.