In order to improve the algorithm of time-varying parameters and unknown parameters adaptability, avoid assuming the approximate part deviation caused by the algorithm, this paper proposes a adaptive control algorithm, the algorithm based on lyapunov direct method to predict the output voltage in the process of estimating each parameter in a reasonable manner to parameter estimation error with the actual output current and current automatic adjustment. The adaptive control of current tracking is realized and the error caused by assuming voltage or current and neglecting line resistance is avoided in the predictive current control algorithm. The simulation results show that the tracking current can track the target current with high precision from t = 0 in the presence of random noise, and the power factor is close to 1, showing a good steady-state performance. Frequency domain waveform, the calculated harmonic distortion rate is 2.2418%, waveform quality is good and each harmonic amplitude is small. Conclusion: adaptive control algorithm can quickly and accurately realize current tracking and greatly suppress the noise.

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In view of the current situation that it is difficult for the power control centre to take into account the multi-source information to conduct effective risk assessment on the dynamic process of the power grid, the challenges and opportunities faced by the power grid risk assessment under the background of the ubiquitous power Internet of Things are pointed out. The framework of the dynamic risk assessment system for the grid of the Internet of Things. At the same time, in view of the monitoring and fault diagnosis functions of sensor technology, especially gas sensor in transformer oil chromatographic monitoring, the application of ubiquitous power Internet of Things sensor technology in online monitoring of power equipment is discussed. First, the application of online monitoring of power equipment is analysed. The inevitable trend will then discuss in detail the monitoring and fault diagnosis functions of gas sensor technology in transformer oil chromatographic monitoring from sensor technology, gas sensor, transformer oil chromatographic device, and gas analysis method.

In recent years, with the increasing Power demand, new energy power has been continuously developed. As the main types of new energy power generation, wind power and photovoltaic power generation have strong randomness and correlation under the influence of natural conditions. The safe and efficient utilization of large-scale new energy power is the core content and basic goal of smart grid construction, while intermittent new energy is developing rapidly, there are also many problems. New energy resources and load centers show obvious reverse distribution characteristics. The fundamental reason that hinders the large-scale absorption of intermittent power in power grid lies in its randomness and volatility. It is necessary to study advanced prediction technology and control technology and make dynamic changes according to certain laws. The structure design of the new energy system of the large power grid can ensure that the power of wind, solar and other new energy can be connected to the grid to the maximum extent, the mathematical parameters and control strategies are correct and reliable, and the energy storage system can realize the dynamic tracking interaction with the power of the large power grid.