
Non-linear devices draw non-sinusoidal currents from the source; hence, they cause harmonic distortions in power systems. The shunt active power filter (SAPF) is a well-known method for alleviating current harmonics, compensating the reactive power and improving the power factor; however, the effective design of an SAPF is quite challenging and a thrust area of research. The current controlling technique, switching pulse generation technique and parameter selection are cumbersome tasks in SAPF design. SAPF performance depends on the proper selection of many parameters, such as filter interfacing impedance, DC-link capacitor and PI-controller gains. The effect of these parameters on the performance of SAPF has been studied and optimum values have been obtained by using the Taguchi method. This paper also indicates the benefits of using the Taguchi method compared with existing genetic algorithm (GA) for optimizing the parameters of the SAPF. An instantaneous reactive power theory (IRPT)-based SAPF has been modeled and simulated in MATLAB/Simulink. The SAPF’s parameters have been optimized by using the both proposed Taguchi SNR and the existing GA method. With optimized values of parameters results have been obtained, analyzed and the superiority of the proposed Taguchi method over the existing GA method is discussed. The simulation results were also validated with experimental results.
total harmonic distortion (THD), Taguchi method, signal-to-noise ratio (SNR), power quality, optimization, shunt active power filter (SAPF)
total harmonic distortion (THD), Taguchi method, signal-to-noise ratio (SNR), power quality, optimization, shunt active power filter (SAPF)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
