The necessity to solve global warming problems by reducing CO2 emission in the electricity generation field had led to increasing interest in microgrids (MGs), particularly those containing the renewable sources such as solar and wind generation. Wind speed fluctuations cause high variations in the output power of a wind turbine which cause fluctuations in frequency and voltage of the MG during islanding mode and originate stability problems. In this paper, three techniques are proposed for solving and reducing the consequences of this problem. In the first technique, we develop a new fuzzy logic pitch angle controller. In the second technique, we design an energy-storage ultracapacitor which directly smoothes the output power of the wind turbine and enhances the performance of the MG during the islanding mode. In the third technique, storage batteries are used to support the MG in the islanding mode.

This paper presents an ECG compression algorithm based on the optimal selection of wavelet filters and threshold levels in different subbands that achieve maximum data volume reduction while guaranteeing reconstruction quality. The proposed algorithm starts by segmenting the ECG signal into frames; where each frame is decomposed into m subbands through optimized wavelet filters. The resulting wavelet coefficients are thresholded and those having absolute values below specified threshold levels in all subbands are deleted and the remaining coefficients are appropriately encoded with a modified version of the run-length coding scheme. The threshold levels to use, before encoding, are adjusted in an optimum manner, until predefined compression ratio and signal quality are achieved. Extensive experimental tests were made by applying the algorithm to ECG records from the MIT-BIH Arrhythmia Database. The compression ratio (CR), the root-mean-square difference (PRD) and the zero-mean percent rootmean- square difference (PRD1) measures are used for measuring the algorithm performance (high CR with excellent reconstruction quality). From the obtained results, it can be deduced that the performance of the optimized signal dependent wavelet outperforms that of Daubechies and Coiflet standard wavelets. However, the computational complexity of the proposed technique is the price paid for the improvement in the compression performance measures.

This paper presents an ECG compression algorithm based on the optimal selection of wavelet filters and threshold levels in different subbands that achieve maximum data volume reduction while guaranteeing reconstruction quality. The proposed algorithm starts by segmenting the ECG signal into frames; where each frame is decomposed into m subbands through optimized wavelet filters. The resulting wavelet coefficients are thresholded and those having absolute values below specified threshold levels in all subbands are deleted and the remaining coefficients are appropriately encoded with a modified version of the run-length coding scheme. The threshold levels to use, before encoding, are adjusted in an optimum manner, until predefined compression ratio and signal quality are achieved. Extensive experimental tests were made by applying the algorithm to ECG records from the MIT-BIH Arrhythmia Database. The compression ratio (CR), the root-mean-square difference (PRD) and the zero-mean percent rootmean- square difference (PRD1) measures are used for measuring the algorithm performance (high CR with excellent reconstruction quality). From the obtained results, it can be deduced that the performance of the optimized signal dependent wavelet outperforms that of Daubechies and Coiflet standard wavelets. However, the computational complexity of the proposed technique is the price paid for the improvement in the compression performance measures.

In this paper, a new wavelet-based copyright proving scheme is proposed. The original image is not required for watermark verification. Moreover, the proposed scheme does not introduce any visual quality degradation into the original image; however, a feature is extracted from the original image and mixed with the watermark to generate a secret key. This secret key is registered for verification. The feature of the image is extracted from the approximation subband in the t-level of the wavelet decomposition. A series of experiments are conducted to prove the robustness property. The results show that this proposed scheme has high robustness under heavy image signal processing attacks and geometric transformation attacks. Moreover, the experimental results show that our scheme outperforms recent works in most cases.

Damping of inter-area power system oscillation is detrimental to the goals of maximum power transfer and optimal power system security. In this paper, individual and coordinated optimization of parameters for both static series synchronous compensator (SSSC) based damping controller and power system stabilizer (PSS) to enhance the power system damping are presented. A lead-lag stabilizer is used to demonstrate this technique. An optimization method based on simulated annealing (SA) algorithm is used for optimal parameters design of the SSSC stabilizer and PSS to improve the dynamic stability of the power system. Eigenvalue analysis is carried out to assess the effectiveness of the proposed stabilizers on enhancing the electromechanical mode stability. The effect of SSSC based stabilizers on damping inter-area oscillations for a small disturbance are studied and compared with PSS. Obtained results include eigenvalue analysis and non-linear time simulation for two area multi-machine power systems.