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Photovoltaic power output forecast error exists objectively and inevitably, and it can provide a guarantee for safe and stable operation of the power system through analyzing its characteristics. In this paper, the influence of predicted output fluctuation characteristics (predicted output amplitude and power variation) on prediction error was studied based on the analysis of variance (ANOVA) method. The prediction error conditions were classified into six types based on the clustering of numerical characteristics of predicted output. Then, a Generalized Gaussian Mixture Model (GGMM) was proposed to fit the prediction error distribution of each type of photovoltaic output. The mean absolute error (MAE), coefficient of determination (R2), and root mean square error (RMSE) were used as accuracy evaluation indexes. The example analysis showed that the GGMM can satisfy the asymmetry and kurtosis diversity of the error distribution after division by conditions, and the fitting result is better than that of the normal distribution, improved Laplace distribution and t Location-Scale distribution model.

The feasibility of battery energy storage system (BESS) in ameliorating power system transient stability has been proved. However, the required BESS capacity is large, which leads to high price. Meanwhile, the improving effect is significantly affected by fault location and BESS location. To address the problem, a distributed configuration of BESS, with a coordinated control method, is proposed in this paper. Firstly, an independent double-closed loop decoupling controller is designed for each BESS, so that the BESS unit can realize decentralized control according to its local correlation information. Secondly, particle swarm optimization is applied to optimize the control parameters of the distributed controllers to achieve coordinated control. Simulation results show that the distributed BESS controllers optimized by particle swarm optimization can better coordinate with each other, and the transient stability of the system is significantly improved.

Commutation failure is a key issue that affects the safe operation of HVDC transmission systems. Scholars at home and abroad have conducted research on the mechanism, evaluation indicators, and control strategies of commutation failure. However, most of the researches are aimed at the working conditions of commutation failure caused by a short-circuit fault on the AC side. There are few studies on the commutation failure caused by the harmonic injection on the AC side and the distortion of the AC bus voltage waveform. This paper clarifies the mechanism of commutation failure caused by waveform distortion, and proposes an index of harmonic commutation margin. On this basis, an evaluation method for commutation failure caused by waveform distortion is proposed. By predicting the commutation voltage-time area and optimization methods to assess whether the current voltage conditions have the risk of commutation failure. Finally, an electromagnetic transient simulation model is established on PSCAD/EMTDC, and the evaluation method in this chapter is verified by simulating the working conditions of the inverter side bus voltage waveform distortion. The results show its effectiveness in evaluating the commutation failure. The research provides a theoretical basis to the implementation of the control function and has broad engineering application prospects.