A deterministic sampling strategy for failure identification in uniform linear arrays using compressed sensing/sparse recovery technique is proposed. Numerical results confirm the good performance of the technique described in this paper compared to the mean performance of the method based on random sampling strategy.

The use of ${\ell }_p$ ( $0<p<1$ ) norm minimization will improve array diagnosis performance provided that the issue of local minima associated to its non-convex nature is properly handled. In order to overcome this deficiency, a hybrid method using random perturbation and non-convex optimization is investigated in this paper. Although it acquires a higher computational time, the trade-off between an accurate diagnosis and the computational burden appears to be acceptable. Theoretical analysis and simulation results demonstrate that the proposed method overcomes this disadvantage effectively and achieves better performance compared to the standard ${\ell }_1$ norm minimization with a smaller number of far-field measurements, suggesting that the proposed method can be used to improve the performance of array diagnosis.

The AC fault of receiving end power grid can cause HVDC continuous commutation failure, bring very high power impact on both of the sending and receiving end power grid, which will threaten the safe and stable operation of the AC-DC interconnected system. The voltage drop of converter station caused by AC faults is an important reason for HVDC continuous commutation failure. By preventing the transmission of AC fault, that is, enhancing reactive power support capability of AC power grid is an important measure to suppress HVDC continuous commutation failure. So after analyzing the dynamic characteristics and mechanism of HVDC commutation failure caused by AC faults, an emergency control method of the reactive compensation devices near the inverter stations is proposed in this paper to decrease the voltage drop under faults and reduce power impact of HVDC commutation failure on the whole system. Firstly, based on the characteristics of the actual power grid and the distribution of the reactive compensation devices, the devices which are involved in the emergency control measures inside the inverter station and nearby are determined. Secondly, the sensitivity of each device switching to the bus voltage of converter station are calculated. Then according to the sensitivity index and the drop or rise condition of transient voltage of converter station, the emergency control amount of the compensation devices is calculated. At last, the effectiveness of the proposed method is verified by the simulation of actual power grid.

Due to the apparent drawbacks of Crude Monte Carlo method (CMC)-including requiring a large number of samples, comparatively lower sampling efficiency, an improved sampling technique based on Variance Minimization (VM) strategy is proposed. The VM strategy is a versatile and widely-applied adaptive importance sampling technique. In this paper, the VM strategy is applied to find an importance probability density function (IPDF) before sampling. And then the obtained IPDF is sampled by Latin Hypercube Sampling (LHS). Besides, the variance of test function can be further reduced through Antithetic Random Variables (ARV) technique. The simulation results of two examples show that this new combined sampling method based on VM strategy (CSMVMS) can effectively reduce sample size and enhance efficiency under certain level of precision.