Altintasi, Cagri

Detecting potential power quality (PQ) events that may occur in the network is an important issue to provide safe electricity to customers. In this study, a new hybrid algorithm named adaptive fitness distance balance hybrid artificial hummingbird algorithm-artificial rabbit optimization (AFDB-AHAARO) algorithm is introduced for the detection and classification of PQ events. A hybrid algorithm is developed to improve the early convergence of the AHA algorithm by expanding the search to avoid local minima. The proposed method, unlike the optimization algorithms used in the literature, is directly applied to the detection and classification of PQ events. The performance of the proposed algorithm is investigated by 6000 different single and multiple PQ events in the Matlab in noisy and noiseless environments, considering the IEEE-1159 standards. The obtained results are compared with the AHA algorithm and the methods proposed in the literature, and it is shown that the proposed method outperforms in noisy environments. It also provides information about the time interval of PQ events. The validity of the proposed algorithm in real systems is demonstrated by testing it on the voltage signal with flicker disturbance obtained from the electrical network and on experimentally generated sag and swell events.

Babacan, Y.; Uzunoğlu, C.P.; Cekli, S.; Kaçar, F.; Uğur, M.

Compact fluorescent lamps (CFLs) are widely employed in lighting systems thanks to their energy efficient characteristics. In contrast to incandescent lamps, CFLs have highly non-linear current–voltage characteristics and exhibit harmonic distortions during their operation. Although nonlinearity and accelerated harmonic effects may cause disturbance in power networks, CFLs are frequently preferred due to their low energy consumption. In this study a test set-up is operated for investigating non-linear characteristics of commercially available CFLs. During these tests non-linear current and voltage waveforms of CFLs are analyzed via oscilloscope and compared with the proposed memristor emulator circuit output waveforms. The non-linear characteristics of CFLs are accurately modelled by proposed memristor emulator circuit, which has a tunable threshold property. To obtain proper comparison wavelet analysis is conducted for current waveforms of CFLs and memristor emulator circuit. The wavelet analysis is an efficient tool for processing non-linear signals, which are prone to display high frequency distortions. In addition to wavelet analysis, the Fourier Transform (FFT) characteristics and total harmonic distortion (THD) levels are also analyzed for correlation of CFLs and proposed memristor.