Power quality prediction of low voltage grid connected photovoltaic power system using mathematical model / Faranadia Abdul Haris

With the rapid growth of Grid Connected Photovoltaic (GCPV) System interconnection brings new challenges that linked to the solar irradiance intermittency as well as limited on the behaviour predictability towards utility grid. Hence, the power quality assessment becoming increasingly important as the impact of this interconnection increased significantly. This occurrence might lead to power quality parameter could be out of acceptable limits. However, there is a lack of literature on power quality prediction associated with GCPV system and a method of prediction in identifying the relationship between power quality parameters and solar irradiance variation. In this study, the prediction of power quality of GCPV system is executed under Malaysia climate variation. Three objectives have been identified which are a development of Mathematical model GCPV system on power quality parameters mainly on the total harmonic current distortion, short term flicker, long term flicker, power factor and AC voltage. Then, verification of accuracy proposed model empirically and prediction of power quality on utility grid by comparing the proposed model with actual data. In this study, the proposed Mathematical model is developed to predict the total harmonic current distortion, flicker, power factor as well as AC voltage based on the fundamental equation that utilizes the solar irradiance as it input meanwhile the power quality parameters as it output. The process of model verification is based on the real data measurement on the GCPV system that involved in this study as well as on the utility grid which follows the IEC Standards requirement. Based on the analytical analysis between power quality parameters with environmental under different brands of the inverter, it revealed that the solar irradiance and the features of inverter give a significant influence on these power quality parameters that involved. Based on the comparative study and statistical approach, it shows a good agreement between simulation results of actual and prediction data. It shows that the proposed model provides an effective method for prediction mainly on the power quality parameters of GCPV system and feasible in time under the same accuracy. Furthermore, by developing a model for power quality prediction as well as exploring this relationship will illustrate an outline of their interconnection for power quality improvement schemes. By conducting a proper analysis and prediction also allow their use in any amount while maintaining the required standards of power quality.