In the context of the “Carbon peak, Carbon neutral” target, the introduction of carbon trading and the connection of new energy generation such as wind power and photovoltaics to the power grid have become important means to achieve a reduction to low carbon emissions. To this end, a virtual optimization model is established to take into account both low-carbon and economic aspects. Firstly, based on the basic concept of a virtual power plant, a virtual power plant model containing wind power, photovoltaic power, a gas turbine, and energy storage is established. Then, considering the uncertainty factors of wind power and PV power generation, Latin hypercube sampling (LHS) is used to simulate wind power and PV output scenarios, combined with the improved CLARA clustering algorithm to reduce the scenarios to form a classical scenario set to reduce the influence of wind power and PV output volatility. Finally, a carbon-trading mechanism and time-sharing tariff are introduced, and the model is solved with the objective function of maximizing the net benefit and minimizing the carbon emission of the Virtual Power Plant. Using arithmetic examples for verification, the results show that the introduction of carbon-trading mechanism can improve the net benefits of the Virtual Power Plant while promoting energy saving and emission reduction.

A new fault location method based on the three-terminal travelling wave method is proposed for the fault location problem of multi-branch overhead line–cable transmission lines. Firstly, the process of fault travelling wave propagation in overhead transmission lines and the phenomenon of refraction are analysed, and an improved phase-mode transformation is introduced to decouple the electromagnetic coupling and perform fault phase selection. Secondly, the Pearson correlation coefficient is introduced to compare the similarity of the current travelling waveforms at different measurement points in order to implement fault segmentation. To solve the problems of the complexity of the fault travelling wave propagation process and the difficulty of identifying the travelling wavehead, the Hilbert–Huang transform is used to extract the fault signal characteristics, and the travelling wave arrival moment is accurately calculated by the sampling error correction method to determine the fault location. Finally, the accuracy and stability of the method are verified via a simulation test on the MATLAB/Simulink platform. The results show that the proposed positioning method combining the three-terminal travelling wave method with HHT and sampling error correction can locate the fault location more accurately, and it has good potential for application in the engineering field. It provides a new technical means for fault location in overhead transmission lines, which is expected to become one of the most important technologies in the future power system.

Aiming at the problem of low positioning accuracy caused by modal aliasing and noise interference in DC cable fault location analysis of a VSC-HVDC system, a double-ended fault location method for flexible DC cables based on improved local mean decomposition is proposed. Firstly, the local mean decomposition (LMD) is used to decompose the six-mode voltage signal to obtain the product function (PF) component; then, to overcome the problem that the instantaneous frequency function of the LMD is limited by the extreme value, the Hilbert transform is performed on the PF1 to obtain the instantaneous frequency curve, and the arrival time of the voltage traveling wave head is determined from the mutation information. Finally, the fault distance is obtained by using the principle of double-ended traveling wave fault location. Different fault conditions are simulated, analyzed, and compared with wavelet transform and Hilbert–Huang transform. The results show that the proposed method has a positioning error within 1%, and it is less affected by interference noise and transition resistance.