With the continuous advancement in the renewable power system construction process, the uncertainty of system operating conditions has significantly increased, resulting in a lower antidisturbance ability, higher cascading failure occurrence rate, and shorter evolution time. The traditional power-flow calculation method relies on the enumeration of scenarios to consider random factors, making it difficult to cope with the complex operating conditions experienced with a high percentage of new energy grids in terms of timeliness and accuracy. Therefore, a multi-scale feature-set-based data-driven method for identifying cascading faults under conditions of having a high percentage of new energy grids is proposed by mining historical data patterns and fully considering the stochastic information contained in historical operation data. Indexes that can describe the topological characteristics of a complex network and the operation state of the system are extracted from the macro-, meso-, and micro-levels to form the index set. Based on a bidirectional long-term and short-term memory neural network, the mapping relationship between the index set and the system operation state is studied using the historical cascading failure dataset. This enables a cascading fault prediction model of a high-proportion renewable power system to be constructed. The effectiveness of the proposed model is verified using the topology of the Xinjiang power-grid system.

With the increasing proportion of new energy in power system, the safety and stability of large-scale new energy has become a common concern. Taking the 1 000 kV Zhangbei—Xiong’an UHVAC transmission line from the 10 million kilowatt new energy base in Zhangbei area as an example, this paper builds a PSASP electromechanical transient simulation model, which includes new energy model and distributed condenser model with low voltage crossing function. The paper analyzes the constraints of the new energy transmission capacity. And then the influence of different configuration schemes on short-circuit ratio of new energy and the suppression effect of transient overvoltage are studied. Finally, the optimization effect of transient overvoltage problem is verified by ADPSS all electromagnetic transient simulation. The results show that transient overvoltage and steady-state low voltage are the main factors restricting the transmission capacity of UHVAC line from new energy base. The distributed small-scale condenser is installed at the generator end with low short-circuit ratio of new energy, which can effectively restrain the transient overvoltage problem and improve the overall output capacity of new energy. The results of the study are of great reference value for planning, operation and design of the same kind of new energy delivery project in China.

In order to reduce the sensitivity of AC line differential protection in flexible DC transmission system of inverter new energy station, an optimization scheme of differential protection based on improved criterion is proposed. Firstly, according to the AC line fault characteristics of the flexible DC transmission system of the inverter new energy station, the adaptability of the AC line differential protection is analyzed. In case of fault in the normal area, the braking component is set to 0 to improve the sensitivity of the protection. When the phase angle difference on both sides exceeds 90°, the current phase angle difference on both sides is added to the criterion to reduce the reduction of sensitivity. Then, compared with the method of directly reducing the braking coefficient, the optimization scheme can take into account the reliability of differential protection by changing parameters, and the optimization scheme is not affected by the strength of the external system of the inverter new energy station. Finally, the 4-terminal flexible DC system model of inverter new energy station connected to Zhangbei is built in PSCAD simulation software, and the simulation verifies the effectiveness of the optimization scheme.